Статті в журналах: "Damage Diagnosi"

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D'Agostin, Martina, Arianna Traunero, Chiara Zanchi, Matteo Bramuzzo, Sara Lega, and JERNEJ DOLINŠEK. "La diagnosi di celiachia attraverso casi clinici interattivi." Medico e Bambino 41, no. 1 (January 25, 2022): 29–32. http://dx.doi.org/10.53126/meb41029.

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Coeliac disease is an immune-mediated systemic disease that affects 1% of the population and it is caused by the ingestion of gluten in genetically predisposed subjects. Clinical manifestations and intestinal damage completely resolve once gluten is excluded from the diet, therefore the precocity of diagnosis is of primary relevance. Although considerable progress has been made in recent years, the wide spectrum of clinical manifestations still causes diagnostic delay. The European Society for Paediatric Gastroenterology, Hepatology and Nutrition (ESPGHAN) has recently published an update of the guidelines providing tools to optimize diagnostic skills. This work aims to summarize the main topics of the new guidelines through illustrative clinical cases.

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Ai, Demi, Hui Luo, and Hongping Zhu. "Diagnosis and validation of damaged piezoelectric sensor in electromechanical impedance technique." Journal of Intelligent Material Systems and Structures 28, no. 7 (July 28, 2016): 837–50. http://dx.doi.org/10.1177/1045389x16657427.

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Piezoelectric sensor diagnosis and validity assessment as a prior component of structural health monitoring system are necessary in the practical application of electromechanical impedance technique. This article proposed an innovative sensor self-diagnosis process based on extracting the characterization of the real admittance (inverse of impedance) signature within a high-frequency range, which covered both diagnosis on damaged sensor after its installation and discrimination of sensor and structural damages during structural health monitoring process. Theoretical analysis was derived from the impedance model of piezoelectric-bonding layer-structure dynamic interaction system. Experimental investigations on piezoelectric sensor-bonded steel beam involved with structural damages of mass addition and notch damage were conducted to verify the process. It was found that the real admittance was reliable and critical in sensor diagnosis, and sensor faults of debonding, scratch, and breakage can be identified and differentiated from structural damage. Validity assessment of the diagnosed damaged sensor was addressed through resonant frequency shift method. The results showed that the validity of damaged sensor for structural health monitoring was inordinately depreciated by sensor damage. This article is expected to be useful for structural health monitoring application especially when damaged piezoelectric sensors existed.

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Xu, Qian. "Investigation of Damage Diagnosis of Retaining Wall Structures Based on the Hilbert Damage Feature Vector Spectrum." Shock and Vibration 2019 (October 7, 2019): 1–22. http://dx.doi.org/10.1155/2019/3509470.

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To diagnose damages within the retaining wall structure, the Hilbert marginal energy spectrum was acquired via the Hilbert–Huang transformation of virtual impulse response functions of responses to the retaining wall under ambient excitations. Based on the Hilbert marginal energy spectrum, the Hilbert damage feature vector spectrum was created. On the basis of the damage feature vector spectrum, a damage identification index was proposed. Based on the damage feature vector spectrum and damage index, the damage state of the retaining wall was detected by the damage feature vector spectrum, damage locations of the wall were diagnosed by the damage index trend surface, and the damage intensity of the wall was identified by the quantitative relationship between the damage index and damage intensity. Based on this, a damage diagnosis method for retaining wall structures was proposed. To verify the feasibility and validity of the damage diagnosis method, both model tests and field tests on a pile plate retaining wall are performed under ambient excitations. Test results show that the damage state of the wall can be detected sensitively, damage locations can be diagnosed validly, and damage intensity can be identified quantitatively via this damage diagnosis method.

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Wang, Sheng Chun, Rong Sheng Shen, Tong Hong Jin, and Shi Jun Song. "Dynamic Behavior Analysis and its Application in Tower Crane Structure Damage Identification." Advanced Materials Research 368-373 (October 2011): 2478–82. http://dx.doi.org/10.4028/www.scientific.net/amr.368-373.2478.

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First establish a dynamic model of tower crane in the load lifting process, the lifting load is solved.Then establish the FEM model of the tower crane under the normal and the damage condition. Get the dynamic displacement of the normal and the damage status under the lifting dynamic load. Propose a damaged diagnosis method by the displacement rate. The results of the study show that this method can not only diagnose the structural damage status, but also determine the positions of structural damage. This will be a new search on tower crane structural health diagnosis.

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Yuan, Xiaoqing, Naqash Azeem, Azka Khalid, and Jahanzeb Jabbar. "Vibration Energy at Damage-Based Statistical Approach to Detect Multiple Damages in Roller Bearings." Applied Sciences 12, no. 17 (August 26, 2022): 8541. http://dx.doi.org/10.3390/app12178541.

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This study proposes a statistical approach based on vibration energy at damage to detect multiple damages occurring in roller bearings. The analysis was performed at four different rotating speeds—1002, 1500, 2400, and 3000 RPM—following four different damages—inner race, outer race, ball, and combination damage—and under two types of loading conditions. These experiments were performed on a SpectraQuest Machinery Fault Simulator™ by acquiring the vibration data through accelerometers under two operating conditions: with the bearing loader on the rotor shaft and without the bearing loader on the rotor shaft. The histograms showed diversity in the defected bearing as compared to the intact bearing. There was a marked increase in the kurtosis values of each damaged roller bearing. This research article proposes that histograms, along with kurtosis values, represent changes in vibration energy at damage that can easily detect a damaged bearing. This study concluded that the vibration energy at damage-based statistical technique is an outstanding approach to detect damages in roller bearings, assisting Industry 4.0 to diagnose faults automatically.

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An, Yonghui, Yue Zhong, Yanbin Tan, and Jinping Ou. "Experimental and numerical studies on a test method for damage diagnosis of stay cables." Advances in Structural Engineering 20, no. 2 (July 28, 2016): 245–56. http://dx.doi.org/10.1177/1369433216659927.

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To diagnose the state of stay cables, a vibration-based model-free damage diagnosis method of stay cables using the changes in natural frequencies is further proposed and validated. The structural frequency is rapidly and easily acquired; moreover, it is simple and reliable for damage diagnosis. The frequency would change after the stay cable is damaged, so the frequency change could be used as the damage index. However, the stay cables are very long in long-span cable-stayed bridges, and their frequencies are very small; the frequency change due to small damage of the stay cable would be submerged by the surrounding noise and error of parameter identification process. A temporary diagonal steel bar–based method is used to solve this issue. The steel bar is installed with one end on the stay cable close to the bottom anchor head and the other end on the bridge deck; thus, the stay cable is divided into a short part and a long part by the steel bar. The frequency of a stay cable with a given tension force increases with the decrease in its length; according to the qualitative analysis, the frequency of the short part increases dramatically, and the local frequency change of the short part due to the same damage in the whole stay cable is amplified dramatically; thus, the small damage of a stay cable can be diagnosed easily. Numerical simulations of a stay cable selected from a cable-stayed bridge and a laboratorial stay cable are used to validate the method and also give a recommended rule for design of the temporary diagonal steel bar; experimental validation has also been conducted. All the results indicate that the proposed method works very well in damage diagnosis of stay cables. The proposed method is an output-only, model-free, fast and economical damage diagnosis method for stay cables.

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Bhargav Sai, Cherukuri, and D. Mallikarjuna Reddy. "Dynamic Analysis of Faulty Rotors through Signal Processing." Applied Mechanics and Materials 852 (September 2016): 602–6. http://dx.doi.org/10.4028/www.scientific.net/amm.852.602.

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In this study, an effective method based on wavelet transform, for identification of damage on rotating shafts is proposed. The nodal displacement data of damaged rotor is processed to obtain wavelet coefficients to detect, localise and quantify damage severity. Because the wavelet coefficients are calculated with various scaled indices, local disturbances in the mode shape data can be found out in the finer scales that are positioned at local disturbances. In the present work the displacement data are extracted from the MATLAB model at a particular speed. Damage is represented as reduction in diameter of the shaft. The difference vectors between damaged and undamaged shafts are used as input vectors for wavelet analysis. The measure of damage severity is estimated using a parameter formulated from the distribution of wavelet coefficients with respect to the scales. Diagnosis results for different damage cases such as single and multiple damages are presented.

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Kim, Ju-Won, Kassahun Demissie Tola, Dai Quoc Tran, and Seunghee Park. "MFL-Based Local Damage Diagnosis and SVM-Based Damage Type Classification for Wire Rope NDE." Materials 12, no. 18 (September 7, 2019): 2894. http://dx.doi.org/10.3390/ma12182894.

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Wire ropes used in various applications such as elevators and cranes to safely carry heavy weights are vulnerable to breakage or cross-sectional loss caused by the external environment. Such damage can pose a serious risk to the safety of the entire structure because damage under tensile force rapidly expands due to concentration of stress. In this study, the magnetic flux leakage (MFL) method was applied to diagnose cuts, corrosion, and compression damage in wire ropes. Magnetic flux signals were measured by scanning damaged wire rope specimens using a multi-channel sensor head and a compact data acquisition system. A series of signal-processing procedures, including the Hilbert transform-based enveloping process, was applied to reduce noise and improve the resolution of signals. The possibility of diagnosing several types of damage was verified using enveloped magnetic flux signals. The characteristics of the MFL signals according to each damage type were then analyzed by comparing the extracted damage indices for each damage type. For automated damage type classification, a support vector machine (SVM)-based classifier was trained using the extracted damage indices. Finally, damage types were automatically classified as cutting and other damages using the trained SVM classifier.

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9

Zhang, Jian Wei, Yi Na Zhang, and Sheng Zhao Cheng. "Damage Diagnosis of Radial Gate Based on Modal Strain Energy." Applied Mechanics and Materials 71-78 (July 2011): 4240–43. http://dx.doi.org/10.4028/www.scientific.net/amm.71-78.4240.

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Non-destructive testing and safety monitoring of structure has been a hot and difficult engineering research problems, and an effective extraction of damage characteristic factor is a critical and theoretical research on structural damage detection and monitoring technology. The basic theory of modal strain energy and the steps to damage diagnosis are discussed in the paper.A a radial gate with different damaged locations and damaged degree is studied,and the results show that modal strain energy can be used as structural damage location sensitive factor,and that the indicator can be a very good identification of the location and extent of structural damage,and that the results of damage diagnosis are clear and reliable.

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Gao, Feng, Xiaojiang Wu, Qiang Liu, Juncheng Liu, and Xiyun Yang. "Fault Simulation and Online Diagnosis of Blade Damage of Large-Scale Wind Turbines." Energies 12, no. 3 (February 7, 2019): 522. http://dx.doi.org/10.3390/en12030522.

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Damaged wind turbine (WT) blades have an imbalanced load and abnormal vibration, which affects their safe and stable operation or even results in blade rupture. To solve this problem, this study proposes a new method to detect damage in WT blades using wavelet packet energy spectrum analysis and operational modal analysis. First, a wavelet packet transform is used to analyze the tip displacement of the blades to obtain the energy spectrum. The damage is detected preliminarily based on the energy change in different frequency bands. Subsequently, an operational modal analysis method is used to obtain the modal parameters of the blade sections and the damage is located based on the modal strain energy change ratio (MSECR). Finally, the professional WT simulation software GH (Garrad Hassan) Bladed is used to simulate the blade damage and the results are verified by developing an online fault diagnosis platform integrated with MATLAB. The results show that the proposed method is able to diagnose and locate the damage accurately and provide a basis for further research of online damage diagnosis for WT blades.

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Gotoh, Jin'ichiro, Shinya Imano, Hidetoshi Kuroki, and Yasushi Hayasaka. "OS12W0356 Remote damage-diagnosis of hot-gas-path components of gas turbines." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2003.2 (2003): _OS12W0356. http://dx.doi.org/10.1299/jsmeatem.2003.2._os12w0356.

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12

Xu, Jie, Zhengyang Zhao, Qian Ma, Ming Liu, and Giuseppe Lacidogna. "Damage Diagnosis of Single-Layer Latticed Shell Based on Temperature-Induced Strain under Bayesian Framework." Sensors 22, no. 11 (June 2, 2022): 4251. http://dx.doi.org/10.3390/s22114251.

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Under the framework of Bayesian theory, a probabilistic method for damage diagnosis of latticed shell structures based on temperature-induced strain is proposed. First, a new damage diagnosis index is proposed based on the correlation between temperature-induced strain and structural parameters. Then, Markov Chain Monte Carlo is adopted to analyze the newly proposed diagnosis index, based on which the frequency distribution histogram for the posterior probability of the diagnosis index is obtained. Finally, the confidence interval of the damage diagnosis is determined by the posterior distribution of the initial state (baseline condition). The damage probability of the unknown state is also calculated. The proposed method was validated by applying it to a latticed shell structure with finite element developed, where the rod damage and bearing failure were diagnosed based on importance analysis and temperature sensitivity analysis of the rod. The analysis results show that the proposed method can successfully consider uncertainties in the strain response monitoring process and effectively diagnose the failure of important rods in radial and annular directions, as well as horizontal (x- and y-direction) bearings of the latticed shell structure.

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13

Lotsch, J., N. Reither, V. Bogdanov, A. Hahner, A. Ultsch, K. Hill, and T. Hummel. "A brain-lesion pattern based algorithm for the diagnosis of posttraumatic olfactory loss." Rhinology journal 53, no. 4 (December 1, 2015): 365–70. http://dx.doi.org/10.4193/rhino15.010.

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Background: Brain areas processing olfactory information exhibit functionally relevant morphological dynamics. This suggests the exploitation of anatomical information in the diagnosis of an olfactory dysfunction. Following previous identifications of olfactory eloquent areas such as the olfactory bulbs and tracts, we focused at a brain-morphology based algorithm for establishing the diagnosis of olfactory loss following brain injury. Methodology: Forty-one patients with a history of head trauma dated back 40 ± 39 months, and additional 23 patients without head trauma, were assessed for damages in 11 olfaction-relevant brain areas using magnetic resonance imaging (MRI). Olfactory function was derived from the use of a standardized, reliable and validated olfactory test. An olfactory diagnostic algorithm was derived following classification and regression tree analysis of the brain lesion pattern. Results: Subjects were assigned to olfactory diagnoses of anosmia, hyposmia or normosmia. These diagnoses were predictable at an accuracy of 62.3 % from the degree of damage in the olfactory bulb and in the left temporal lobe pole. The main diagnosis algorithm addressed the presence of anosmia, which could be predicted from the degree of damage in these brain areas at an accuracy of 81.3 %. Conclusions: We independently reproduced previously identified brain regions in which morphological damage is associated with olfactory loss. Based on this reproduction, an algorithm was developed for the diagnosis of anosmia from central-nervous damage. Thus, we introduce a morphological component to the olfactory diagnosis that specifically addresses clinical cases of olfactory loss following head trauma.

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Kong Qiongying, 孔琼英, 叶波 Ye Bo, 邓为权 Deng Weiquan, 陈宸 Chen Chen та 王丹宏 Wang Danhong. "基于ToF损伤因子的碳纤维复合材料疲劳损伤概率成像方法". Laser & Optoelectronics Progress 58, № 16 (2021): 1610002. http://dx.doi.org/10.3788/lop202158.1610002.

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Fitri Naryanto, Rizqi, Mera Kartika Delimayanti, Kriswanto Kriswanto, Ari Dwi Nur Indriawan Musyono, Imam Sukoco, and Mohamad Naufal Aditya. "Development of a mobile expert system for the diagnosis on motorcycle damage using forward chaining algorithm." Indonesian Journal of Electrical Engineering and Computer Science 27, no. 3 (September 1, 2022): 1601. http://dx.doi.org/10.11591/ijeecs.v27.i3.pp1601-1609.

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Indonesia is an <span>ASEAN country with the most motorcycle users, where one-third of its population own motorcycles. The automatic motorcycle is the most widely used type due to its agility and fuel-efficient abilities. Sudden motorcycle damage could hamper the users' activities. However, most of these users do not know the reason for the damage. This paper presents the development of expert system for diagnosing the damage of motorcycle using forward chaining method. This system was implemented in mobile application. Through a mobile application, a solution for these users can be obtained. This application immediately discovers the damaged location and repair process. Furthermore, it acts as the first solution before motorcycle repair is carried out in a shop. In this study, the forward chaining method was implemented. It is based on a pattern-matching algorithm whose primary objective is to match facts (input data) with appropriate rules from the rule base. Various test results showed that the diagnostic application used for automatic motorcycle damages 100% worked.</span>

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Chen, Xiang Yu, Sha Sha Dong, and Fu Shun Liu. "A Multi-Hierarchical Damage Identification Method for Jacket Platform Using BP Neural Network." Applied Mechanics and Materials 166-169 (May 2012): 1170–75. http://dx.doi.org/10.4028/www.scientific.net/amm.166-169.1170.

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Jacket-type platforms may be the most common type of offshore structures, and damage localization and severity estimation is important for these structures. This paper employs a multi-hierarchical damage identification method based on BP neural network to detect damages in jacket platforms. Firstly, the damaged storey of the jacket is detected, and the numbers of the elements among the detected storey are then detected. According to this method, the learning samples can be more targeted and the number can be reduced largely. In the end, a jacket model is used to investigate the performance of this method, and the results indicate that this approach is more effective and has higher accuracy than direct diagnosis method.

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Ayu*, Fitri, Dwi Sapta Aryatiningsih, Ambiyar, Fahmi Rizal, and Anita Febriani. "Design and Application of Detection Damage Hardware to Your Computer with Certainty Factor." International Journal of Management and Humanities 5, no. 10 (June 30, 2021): 28–31. http://dx.doi.org/10.35940/ijmh.j1328.0651021.

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In this study, an expert system is used to detect symptoms of damage to computer hardware. With the application of certainty factor models, it is expected to be able to detect symptoms of damage to computer hardware starting with the symptoms of damage from the computer along with solutions for handling the damage. This study aims to produce a fault diagnosis application on web-based computer hardware. This application is expected to make it easier for users to find solutions regarding experienced hardware problems. This expert system application is made using the certainty factor method so that the resulting diagnosis will display symptoms that have more certainty factors. This application was designed using UML and the PHP programming language with black-box testing. The study was conducted by collecting data through literature study, browsing, and interviews. The research method used is the waterfall method. The time of the research is from September 2019 to February 2020. This research is in an application to diagnose damage to computer hardware. Computer Hardware Damage Detection Application can be a guide for computer users in overcoming the damage to hardware with certainty factor methods and can help users in caring for computer hardware so it is not easily damaged.

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Wang, Guang Yan. "Variables Sequence Calculating Method in the Process of Bayesian Network Constructing for Battlefield Damage Diagnosis." Applied Mechanics and Materials 701-702 (December 2014): 98–105. http://dx.doi.org/10.4028/www.scientific.net/amm.701-702.98.

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In order to improve damage diagnosis ability of maintenance personnel, constructing method of Bayesian network applied to weapon battlefield damage diagnosis is researched. Battlefield damage correlations among damaged parts of weapon are analyzed if one weapon is attacked by bombshells, and is the basis of damage diagnosis with the use of Bayesian network. Bayesian network for damage diagnosis is constructed based on K2 arithmetic. Variables sequence is the key factor of Bayesian network constructing, a statistical method of ascertaining variables sequence is presented with the use of weapon battlefield simulation technology.

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Iwasaki, Atsushi, Akira Todoroki, and Tsuneya Sugiya. "OS09W0317 Unsupervised damage detection of CFRP structure with statistical diagnostic method." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2003.2 (2003): _OS09W0317. http://dx.doi.org/10.1299/jsmeatem.2003.2._os09w0317.

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20

Sukhonosenko, V. M., and A. A. Міan. "Combined damage to the knee ligaments and the coxofemoral nerve." N.N. Priorov Journal of Traumatology and Orthopedics 1, no. 3 (September 15, 1994): 22–25. http://dx.doi.org/10.17816/vto105069.

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The examination and treatment of 25 patients with chronic combined damage to the knee ligaments and the coxofemoral nerve have led the authors to the conclusion that many patients are not diagnosed as having nerve injury in the early period. Early diagnosis of combined damages makes it possible to perform treatment in time in recovering the ligaments and nerve function and to rule out intricate reconst motive operations in the late period of injury. In chronic combined damages to the ligaments and the nerve, the most justifiable therapeutical method is surgery: plastic recovery of the ligaments and revision of the nerve, which is expedient to make simultaneously, the scope of an operation on the nerve is determined by the nature of a damage. Positive clinical results seen among most patients confirmed the efficiency of the therapeutical method.

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21

Lin, Tzu-Kang, Dong-You Lee, Yu-Chung Hsu, and Kai-Wei Kuo. "Damage Detection of Regular Civil Buildings Using Modified Multi-Scale Symbolic Dynamic Entropy." Entropy 24, no. 7 (July 17, 2022): 987. http://dx.doi.org/10.3390/e24070987.

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Based on the examination of the fundamental characteristics of structures, structural health monitoring (SHM) has received increased attention in recent years. Studies have shown that the SHM method using entropy analysis can precisely identify the damaged location of the structure, which is very helpful for the daily inspection or maintenance of civil structures. Although entropy analysis has shown excellent accuracy, it still consumes too much time and too many resources in terms of data processing. To improve the dilemma, in this study, modified multi-scale symbolic dynamic entropy (MMSDE) is adopted to identify the damaged location of the civil structure. A damage index (DI) based on the entropy diagram is also proposed to clearly indicate the damage location. A seven-story numerical model was created to verify the efficiency of the proposed SHM system. The results of the analysis of each case of damage show that the MMSDE curve for the damaged floor is lower than that for the healthy floor, and the structural damage can be correctly diagnosed by the damage index. Subsequently, a scaled-down steel benchmark experiment, including 15 damage cases, was conducted to verify the practical performance of the SHM system. The confusion matrix was used to further evaluate the SHM system. The results demonstrated that the MMSD-based system can quickly diagnose structural safety with reliability and accuracy. It can be used in the field of long-term structural health monitoring in the near future.

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Natsuaki, M. "238 Diagnosis of perioperative myocardial damage by early measurement of CK isoenzyme." Japanese Journal of Cardiovascular Surgery 15, no. 5 (1986): 477–78. http://dx.doi.org/10.4326/jjcvs.15.477.

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Roy, Rinto, and Marco Gherlone. "Delamination and Skin-Spar Debond Detection in Composite Structures Using the Inverse Finite Element Method." Materials 16, no. 5 (February 28, 2023): 1969. http://dx.doi.org/10.3390/ma16051969.

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This work presents a novel strategy for detecting and localizing intra- or inter-laminar damages in composite structures using surface-instrumented strain sensors. It is based on the real-time reconstruction of structural displacements using the inverse Finite Element Method (iFEM). The iFEM reconstructed displacements or strains are post-processed or ‘smoothed’ to establish a real-time healthy structural baseline. As damage diagnosis is based on comparing damaged and healthy data obtained using the iFEM, no prior data or information regarding the healthy state of the structure is required. The approach is applied numerically on two carbon fiber-reinforced epoxy composite structures: for delamination detection in a thin plate, and skin-spar debond detection in a wing box. The influence of measurement noise and sensor locations on damage detection is also investigated. The results demonstrate that the proposed approach is reliable and robust but requires strain sensors proximal to the damage site to ensure accurate predictions.

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Kourehli, S. S. "LS-SVM Regression for Structural Damage Diagnosis Using the Iterated Improved Reduction System." International Journal of Structural Stability and Dynamics 16, no. 06 (June 2016): 1550018. http://dx.doi.org/10.1142/s0219455415500182.

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A damage detection and estimation method is proposed for structural health monitoring using incomplete modal data and least squares support vector machine (LS-SVM). To accommodate the use of incomplete modal data, the iterated improved reduction system (IIRS) method has been used to condense the mass and stiffness matrices of the structure. The first two incomplete mode shapes and natural frequencies of a damaged structure are used as input data to the LS-SVM. The coupled simulated annealing (CSA) and standard simplex method using 10-fold cross-validation techniques are adopted to determine the optimal tuning parameters in the LS-SVM model. Three illustrative examples with and without noise in modal data are prepared to evaluate the performance of the proposed method. The results indicated that this method can be reliably used to identify the damages of structures with good accuracy.

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Fu, Wenmei, Zhiqiang Liu, Chaozhi Cai, Yingfang Xue, and Jianhua Ren. "Damage Diagnosis of Frame Structure Based on Convolutional Neural Network with SE-Res2Net Module." Applied Sciences 13, no. 4 (February 16, 2023): 2545. http://dx.doi.org/10.3390/app13042545.

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The complex application environments of frame structures and the similar vibration signals between different locations make it difficult to accurately diagnose damage using traditional methods. Based on modifying the parameters and configuration of the convolution neural network with training interference (TICNN), this paper proposes a new model for damage diagnosis of frame structures by implanting a squeeze-and-excitation neural network (SENet) and Res2Net modules. Taking the frame structure model from the University of British Columbia as the research object, the proposed damage diagnosis model was used to diagnose its damage type. The proposed new model was compared with other models in terms of accuracy and anti-noise ability. The experimental results show that the accuracy of the proposed model was 99.44% when the training epoch was 30 and 99.78% when training epoch was 100. It is superior to other similar models in terms of convergence speed and accuracy. At the same time, the proposed model also has an excellent advantage in anti-noise ability. Therefore, the proposed damage diagnosis model has the advantages of fast convergence and higher damage diagnosis accuracy under a strong noise environment. It can realize the accurate damage diagnosis of structural frames.

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Gong, Zhi Guo, Run Dong Gao, and Peng Zhao. "Application of Modal Analysis in Local Damage Diagnosis of Steel Beam." Applied Mechanics and Materials 138-139 (November 2011): 592–97. http://dx.doi.org/10.4028/www.scientific.net/amm.138-139.592.

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For one cantilever steel beam, according to the stress concentration principle resulted from the small hole, four small holes were drilled at different positions to form the local damage of the steel beam. The modal tests including the displacement modal and the strain modal were conducted before and after the steel beam was damaged. The test results indicated: from the decreased frequency, one could only judge on the whole that the steel beam had been damaged, but could not determine the detailed damaged positions; the detailed damaged positions of the steel beam were also difficult to be determined by the displacement modal test whether by ripple technique or by hammering technique, but could be determined by the strain modal test by hammering technique, especially under the first order of modal. The research achievements can offer some references for the diagnosis of local damage of engineering structures by the strain modal analysis method.

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de Paula Monteiro, Ronant, Amanda Lucatto Marra, Renato Vidoni, Claudio Garcia, and Franco Concli. "A Hybrid Finite Element Method–Analytical Model for Classifying the Effects of Cracks on Gear Train Systems Using Artificial Neural Networks." Applied Sciences 12, no. 15 (August 4, 2022): 7814. http://dx.doi.org/10.3390/app12157814.

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Rotating machinery is fundamental in industry, gearboxes especially. However, failures may occur in their transmission components due to regular usage over long periods of time, even when operations are not intense. To avoid such failures, Structural Health Monitoring (SHM) techniques for damage prediction and in-advance detection can be applied. In this regard, correlations between measured signal variations and damage can be inspected using Artificial Intelligence (AI), which demands large numbers of data for training. Since obtaining signal samples of damaged components experimentally is currently unviable for complex systems due to destructive test costs, model-based numerical approaches are to be explored to solve this problem. To address this issue, this work applied an innovative hybrid Finite Element Method (FEM)–analytical approach, reducing computational effort and increasing performance with respect to traditional FEM. With this methodology, a system can be simulated with accuracy and without geometrical simplifications for healthy and damaged cases. Indeed, considering different positions and dimensions of damages (e.g., cracks) on the tooth roots of gears can offer new ways of damage investigation. As a reference to validate healthy systems and damage cases in terms of eigenfrequencies, a back-to-back test rig was used. Numerical simulations were performed for different cases, resulting in vibrational spectra for systems with no damage, with damage, and with damage of different intensities. The vibration spectra were used as data to train an Artificial Neural Network (ANN) to predict the machine state by Condition Monitoring (CM) and Fault Diagnosis (FD). For predicting the health and the intensity of damage to a system, classification and multi-class classification methods were implemented, respectively. Both sets of classification results presented good prediction agreement.

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Guan, De Qing, Xiao Lin Zhong, and Hong Wei Ying. "Damage Identification of Arch Bridge Based on Curvature Mode Wavelet Analysis." Applied Mechanics and Materials 166-169 (May 2012): 1176–79. http://dx.doi.org/10.4028/www.scientific.net/amm.166-169.1176.

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Based on the curvature modal damage identification of wavelet analysis principle, the finite element method was applied to analyze the vibration characteristics of the damaged deck arch bridge. Take Haar wavelet as the mother wavelet, through the continuous wavelet transform of curvature mode and then identified the damaged position by the maximum of wavelet coefficients. analyze the damage identification problem under three different damaged conditions (condition 1: only the arch 1 contained one damaged location; condition 2: the arch 1 and the arch 2 contained one damaged location respectively; condition 3: the arch 1 contained two damaged locations and the arch 2 contained one damaged location).This paper provided a valuable reference of damage identification and diagnosis for arch bridge.

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Hadi Nugroho, Donny, M. Fairuzabadi, Meilany Nonsi Tentua, and Mohamed Nor Azhari Azman. "System Expert Diagnosis Iphone Cellphone Damage Web-Based." APPLIED SCIENCE AND TECHNOLOGY REASERCH JOURNAL 1, no. 2 (February 20, 2023): 10–19. http://dx.doi.org/10.31316/astro.v1i2.4641.

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Mobile phones (HP) or smartphones are the most popular communication tools used by the public. Based on interviews with several mobile phone users and technicians, the iPhone is currently one of the best-selling and most prestigious brands. But in reality, the iPhone user community, in general, does not understand the damage that often occurs to HP. This leads users to bring the damaged HP to the service point without knowing in advance what kind of damage occurred to the HP. The study aims to build an app to diagnose damage to web-based iPhone phones. In collecting the data needed for the study, the authors used methods of literature study, interviews, and observation. This web-based iPhone mobile damage diagnostic system application is made using the PHP programming language. The game development stage includes analysis, system design, implementation, and testing. The expert system application to diagnose damage to the web-based iPhone phone that is made can be used to find out the damage to the iPhone phone, before being taken to the service so that users know what damage is repaired. The results of system testing showed that this application is feasible and can be used as a web-based iPhone mobile damage diagnostic system application.

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Hrubar, Y. O., M. Y. Hrubar, I. Y. Kuziv, and O. V. Kuziv. "Study of reliability of meniscus damage signs using high intensity 1,5 tesla mri compared to the results of arthroscopic interventions in acute and obsolete knee injury." Reports of Vinnytsia National Medical University 24, no. 3 (October 12, 2020): 425–32. http://dx.doi.org/10.31393/reports-vnmedical-2020-24(3)-10.

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Annotation. Among the large joints, the knee joint is most often injured, which is due to the peculiarities of its structure and functional loads in the process of human life. The most common injuries are meniscus damages of the knee joint, that is the evidence of steady increase in the number of partial arthroscopic meniscectomies, which have become the most common orthopedic procedure. Diagnosis of meniscus damage is based on the results of clinical examination, sonography and MRI. Increasing the resolution of MRI machines, improving the technique of their implementation allows to improve the quality of diagnosis of meniscus ruptures and improve the results of surgical arthroscopic interventions on the knee joint. The aim of the study – to demonstrate the capabilities of high-intensity 1.5 Tesla MRI and to study the reliability of MRI signs of meniscus damage in comparison with the results of arthroscopic interventions in acute and chronic knee joint injury. The work is based on the results of MRI examinations and arthroscopic interventions of 247 patients with acute and chronic knee joint injuries aged 14 to 59 years. Medial meniscus damage was diagnosed in 206 (83.41%) patients. Lateral meniscus ruptures were diagnosed in 34 patients (13.76%). Simultaneous damage of both menisci was found in 7 (2.83%) patients. It was found that ruptures of the medial meniscus by location were: the root of the posterior horn of the medial meniscus in 4 (1.94%) patients, ruptures of the posterior horn in 82 (39.81%) patients. Injury of the posterior horn with the transition to the body of the meniscus was diagnosed in 117 (56.79%) patients. Anterior horn ruptures were detected in 3 (1.46%) patients. With ruptures of the lateral meniscus: damage of the root of the posterior horn of the lateral meniscus was found in 2 (5.88%) patients, damage of the posterior horn in 9 (26.47%) patients. Posterior horn rupture with transition to the body of the meniscus was diagnosed in 19 (55.89%) patients. Isolated ruptures of the anterior horn were found in 4 (11.76%) patients. Simultaneous damage to both menisci was found in 7 (2.83%) patients. 206 (83.40%) partial meniscectomies were performed during arthroscopic interventions and meniscus suturings were performed over 41 (16.60%) patients. In order to identify meniscus damage and their location during MRI knee joint investigations 21 pseudo-positive and 18 pseudo-negative cases of diagnosis were revealed. The sensitivity of MRI for defining damage and localization of meniscus rupture was 91,7%, specificity 92,6%, diagnostic accuracy 94,8%. Discrepancies in the evaluation of meniscal damage most often occurred in cases of their combined ruptures and degenerative changes in the menisci.

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Martell Martínez, Moraima. "Microalbuminuria as a marker of kidney damage in patients with diabetes mellitus." Journal of Clinical and Medical Reviews 1, no. 1 (December 22, 2022): 01–04. http://dx.doi.org/10.58489/2836-2330/001.

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Background: diabetes mellitus has increased its incidence and prevalence gradually in recent years throughout the world. Currently, diabetes mellitus and high blood pressure are the main causes of chronic kidney failure in its different stages. Nephropathy is one of the most serious complications affecting diabetics. Its onset is usually insidious, progresses without symptoms, and generally becomes clinically evident after 5 to 10 years of diabetes progression. This complication in early stages (incipient nephropathy) can be diagnosed through microalbuminuria, which is currently the first marker that exists to detect the existence of the condition. This review aims to summarize the importance of the determination of microalbuminuria in diabetic patients with the aim of making an early diagnosis of the disease and the control of risk factors.

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Ju, F. D., and M. E. Mimovich. "Experimental Diagnosis of Fracture Damage in Structures by the Modal Frequency Method." Journal of Vibration and Acoustics 110, no. 4 (October 1, 1988): 456–63. http://dx.doi.org/10.1115/1.3269550.

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The present paper used the modal frequency method to diagnose the fracture damage experimentally in simple structures, based on the analytical theory of the spring-loaded “fracture-hinge.” It is illustrated that the damage geometry uniquely defines the spring constant of the “fracture hinge,” which is therefore independent of the loading strength, the frequency of vibration, and the damage location. The experiment also measures the change in modal frequencies to locate the damage on the beam. With an accurate analytical model for the experimental samples, the locations of the damages can be predicted to within an accuracy of one percent of the length. The damage intensity is around four percent in accuracy.

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Heinrichs, Kurt, and Bernd Fitzner. "Stone monuments of the Nemrud Dag sanctuary/Turkey petrographical investigation and diagnosis of weathering damage." Zeitschrift der Deutschen Gesellschaft für Geowissenschaften 158, no. 3 (September 1, 2007): 519–48. http://dx.doi.org/10.1127/1860-1804/2007/0158-0519.

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Jiang, Xie, Xin Zhang, and Yuxiang Zhang. "Piezoelectric Active Sensor Self-Diagnosis for Electromechanical Impedance Monitoring Using K-Means Clustering Analysis and Artificial Neural Network." Shock and Vibration 2021 (July 1, 2021): 1–13. http://dx.doi.org/10.1155/2021/5574898.

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Piezoelectric sensor is a crucial part of electromechanical impedance technology whose state will directly affect the effectiveness and accuracy of structural health monitoring (SHM). So carrying out sensor self-diagnosis is important and necessary. However, it is still difficult to distinguish sensor faults from structural damage as well as identify the cases and degrees of sensor faults. In the study, three characteristic indexes of admittance which have different indication intervals for damages of structure and sensors were selected from six indexes after comparison. To improve the discrimination effect, three principal components (PC) were extracted by principal component analysis (PCA). And the damage information represented by PCs was clustered by the K-means algorithm to identify the cases of damage. Then, the degrees of sensor damages were classified with the artificial neural network (ANN). The results show that the K-means clustering analysis based on admittance characteristics can accurately distinguish and identify the structural damage and four kinds of sensor damages, namely, pseudosoldering, debonding, wear, and breakage. The trained ANN model has a good recognition effect on the damage degrees and the accuracy of recognition reaches 100%. This study has a certain reference value for piezoelectric sensor self-fault identification.

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35

Su, Wei Chih, Chiung Shiann Huang, and Liane Jye Chen. "Damage Diagnosis of a Structure in Time-Frequency Domain." Applied Mechanics and Materials 764-765 (May 2015): 1051–57. http://dx.doi.org/10.4028/www.scientific.net/amm.764-765.1051.

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This work proposes a simple and efficient approach to locating the storeys whose stiffness change in the life cycle of a structure. The storeys that may be damaged are determined by comparing the unitary stiffness matrix in different stages in the life cycle of a building. An appropriate ARX (autoregressive with exogenous input) model of structure in established from the structural dynamic responses in terms of acceleration or velocity. The parameters in an ARX model are identified through the short time Fourier transform, and the natural frequency and damping ratio of structure are estimated directly through these identified parameters. The effectiveness of the proposed procedure is verified using the numerically simulated earthquake acceleration responses of a six-storey structure that is damaged at one or two storeys. The proposed scheme is compared to the DLV approach (flexibility-based damage locating vector approach) in identifying damage storeys.

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Bahlous, S. El-Ouafi, M. Neifar, S. El-Borgi, and H. Smaoui. "Ambient Vibration Based Damage Diagnosis Using Statistical Modal Filtering and Genetic Algorithm: A Bridge Case Study." Shock and Vibration 20, no. 1 (2013): 181–88. http://dx.doi.org/10.1155/2013/756912.

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The authors recently developed a damage identification method which combines ambient vibration measurements and a Statistical Modal Filtering approach to predict the location and degree of damage. The method was then validated experimentally via ambient vibration tests conducted on full-scale reinforced concrete laboratory specimens. The main purpose of this paper is to demonstrate the feasibility of the identification method for a real bridge. An important challenge in this case is to overcome the absence of vibration measurements for the structure in its undamaged state which corresponds ideally to the reference state of the structure. The damage identification method is, therefore, modified to adapt it to the present situation where the intact state was not subjected to measurements. An additional refinement of the method consists of using a genetic algorithm to improve the computational efficiency of the damage localization method. This is particularly suited for a real case study where the number of damage parameters becomes significant. The damage diagnosis predictions suggest that the diagnosed bridge is damaged in four elements among a total of 168 elements with degrees of damage varying from 6% to 18%.

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Du, Guang Qian, Chang Zhi Zhu, Li Juan Long, and Meng Zhang. "Structural Damage Detection Based on Curvature Mode Shapes and Neural Network Technique." Applied Mechanics and Materials 204-208 (October 2012): 2907–12. http://dx.doi.org/10.4028/www.scientific.net/amm.204-208.2907.

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On the basis of the theory that natural frequency changes and curvature mode shapes can be employed to determine the locations and degrees of damage of structures, a BP neural network technique with an improved input structure was developed. The two networks were used for diagnosis of structural damage, and structural damages were predicted using gray theory. The results showed that the gray theory to predict the structural damage neural network was applicable to irregular objects such injury problem diagnosis.

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Zhang, Rui, Zhen Fu Chen, Yuan Chu Gan, and Qiu Wang Tao. "Damage Diagnosis in Self-Compacting Concrete Beams Base on Eigenfrequencies and Mode Shape Derivatives." Applied Mechanics and Materials 160 (March 2012): 307–12. http://dx.doi.org/10.4028/www.scientific.net/amm.160.307.

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In this paper, modal characteristics of self-compacting concrete (SCC) beams were studied through experiment. 3 self-compacting concrete beams were gradually damaged and then subjected to vibration test in free-free boundary conditions after each load step. From analysis, eigenfrequencies could indicate the existence of damage but it could not represent the damage locations. Modal Assurance Criterion (MAC) is lesser reliable to indicate crack damage compare to eigenfrequencies. Next to these, capacity for damage detection and localization of Coordinate Modal Assurance Criterion (COMAC) and the flexibility matrix method are also examined and compared. This paper introduces in detail the dynamic properties and damage localization methods in SCC, which provide basal databases of damage diagnosis for SCC structures and promote the popularization of SCC in civil infrastructures.

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Kumar, Kundan, Prabir Kumar Biswas, and Nirjhar Dhang. "Damage Diagnosis of Steel Truss Bridges under Varying Environmental And Loading Conditions." March 24, No 1 (March 2019): 56–67. http://dx.doi.org/10.20855/ijav.2019.24.11255.

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In this paper, we propose a damage detection and localization algorithm for steel truss bridges using a data-driven approach under varying environmental and loading conditions. A typical steel truss bridge is simulated in ANSYS for data generation. Damage is introduced by reducing the stiffness of one or more members of the truss bridge. The simulated acceleration time-history signals are used for the purpose of damage diagnosis purpose. Vibration data collected from healthy bridges are processed through principal component analysis (PCA) to find the reduced size weighted feature vectors in model space. Unknown test vibration data (healthy or damaged) finds the closest match of its reduced size model from the training database containing only healthy vibration data. The residual error between the spread of closest healthy vibration data and unknown test vibration data is processed to determine damage location and severity of the damage to the structure. A comparative study between a proper orthogonal decomposition (POD) based damage detection algorithm and proposed algorithm is presented. The results show that the proposed algorithm is efficient to identify the damage location and assess the severity of damage, called as the Damage Index (DI), under varying environmental and moving load conditions.

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Sendy, Feras. "Laparoscopic Diagnosis and Treatment of Stage 4 Endometriosis after Traumatic Agni karma with Abdominal Scars: a Case Report." Obstetrics Gynecology and Reproductive Sciences 4, no. 2 (August 10, 2020): 01–02. http://dx.doi.org/10.31579/2578-8965/040.

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Agni karma refers to the use of heated metals by traditional physicians. Endometriosis is defined as implantation of endometrial cells outside the endometrial cavity. Presenting symptoms are dyspareunia and dysmenorrhea. Recognition and awareness of such disorder are vital to avoid skin damage. A 31 years old nulliparous presented with dysmenorrhea and dyspareunia after unsuccessful attempts to alleviate symptoms by heated metals. Stage 4 endometrioses was diagnosed via laparoscopy and bilateral ovarian cystectomy was done for endometriomas. Agni karma is an unacceptable treatment for endometriosis as it results in avoidable body damage. Using heated rods is contraindicated in endometriosis, as it does neither alleviate symptoms nor treat the condition. It is used due to its lower cost, rapidity to treat the illness and non-complex equipment. To prevent unnecessary body damages, awareness is crucial along with consulting legal healthcare centers where medical and surgical treatment from qualified healthcare professionals is provided.

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Guan, De Qing, Qi Tang, and Hong Wei Ying. "Research on Damage Identification of Suspension Bridge by Wavelet Analysis of the Strain Mode." Applied Mechanics and Materials 193-194 (August 2012): 976–79. http://dx.doi.org/10.4028/www.scientific.net/amm.193-194.976.

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The suspension bridge contained damage was made as the object of study. Three different damage conditions for suspension bridge were calculated(conditions 1, the left midspan contains a damaged zone, condition 2, the left end bay contains two damaged zone, condition 3, both sides midspan contains a damaged zone). Using the wavelet analysis theory, solving strain modal parameters of the suspension bridge with cracks by means of Lanczos method. Then the cracks location of the suspension bridges could be identified by the maximum of wavelet coefficients. It can be concluded that the method using wavelet analysis of strain mode is more accurate and more effective through the calculation and analysis of the suspension bridge damage identification. The method can be useful in the suspension bridge damage identification and diagnosis.

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FAN, Qingrong, Kazuteru NAGAMURA, Kiyotaka IKEJO, Masato KAWADA, and Mitsuo HASHIMOTO. "1209 A Diagnosis Method for Gear Damage Based on Empirical Mode Decomposition and Support Vector Machines." Proceedings of the Machine Design and Tribology Division meeting in JSME 2014.14 (2014): 67–70. http://dx.doi.org/10.1299/jsmemdt.2014.14.67.

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43

Ji, Jiangtao, Kaikang Chen, Xin Jin, Jing Pang, Xing Chen, Zhaoyang Wang, and Jingyuan Fan. "Research on the Beam Damage Diagnosis Method for a High-Speed Transplanter Based on the Strain Mode." Applied Engineering in Agriculture 37, no. 1 (2021): 25–32. http://dx.doi.org/10.13031/aea.13186.

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Abstract. The vibration of agricultural machinery significantly influences driving comfort and operation reliability. In recent years, research on the vibrational characteristics of agricultural machinery has gradually expanded. To solve the problem of the obvious vibration of a high-speed transplanter under operating conditions, this article examines the method of beam damage diagnosis for high-speed transplanters based on the strain mode. Based on the modal theory, the displacement and strain modal analysis of the beam of the high-speed transplanter is performed. The analysis shows that the relative deviation of the modal frequencies of the same order before and after the beam is damaged is small. There is no obvious abrupt change in the displacement mode shape, while the strain mode shape has a sudden change peak after the beam is damaged. Thus, the strain mode change rate is constructed as a diagnostic index for beam damage. The analysis results show that the strain mode change rate increases with the increase in beam damage degree. Finally, the least squares method is used to fit the corresponding relationship between the two quantities. The results show that the strain mode change rate is sensitive and reliable as an index of damage diagnosis, which can better determine the location and degree of damage to the beam. Keywords: Beam, Damage, Diagnosis, Rice transplanter, Strain mode.

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Iwasaki, Atsushi, Yoshinobu Shimamura, and Akira Todoroki. "OS17-3-6 Optimization of the statistical model for the statistical damage diagnostic method." Abstracts of ATEM : International Conference on Advanced Technology in Experimental Mechanics : Asian Conference on Experimental Mechanics 2007.6 (2007): _OS17–3–6——_OS17–3–6—. http://dx.doi.org/10.1299/jsmeatem.2007.6._os17-3-6-.

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45

Kosulin, S. V., Ju O. Vinnik, and Ju V. Ivanova. "Tactical approaxhes to diagnosis and treatment of hepatorenal syndrome in patients with blastomatous obstructive jaundice." PROBLEMS OF UNINTERRUPTED MEDICAL TRAINING AND SCIENCE 42, no. 2 (July 2021): 28–31. http://dx.doi.org/10.31071/promedosvity2021.02.028.

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The article discusses problems of early diagnosis and, accordingly, treatment of hepatorenal syndrome (HRS) in case of obstructive jaundice of blastomatous origin. The results of a comprehensive examination of 37 patients with blastomatous obstructive jaundice (OJ) with clinical and laboratory signs of HRS were analyzed. Patients were evaluated for clinical and biochemical parameters of blood and urine, blood electrolytes, indicators of the blood coagulation system according to unified methods. The main work is devoted to the determination of the biomarker of renal tubular damage, neutrophil-gelatinase-associated lipocaine (s-NGAL) as a marker and indicator of HRS severity, careful and detailed analysis, monitoring of levels (s-NGAL) and other bioactive substances as an indicator of treatment efficacy. Introduction of active ultrasound as a replacement for contrast computer tomography to reduce the load on precompromised kidneys. It has been proven that the level of renal tubular damage, neutrophil-gelatinase-associated lipocaine s-NGAL is an early marker of renal damage whose function is to reduce the severity of damage to the proximal tubules of the kidneys, normalize damaged tissue by participating in apoptosis, increase survival of damaged restoration of damaged epithelium, stimulation of differentiation and structural reorganization of renal epithelial cells. The fact that s-NGAL was not significantly reduced in the stage of recovery of diuresis, confirms the presence of patients with blastomatous MF severe and persistent toxic tubulointerstitial disorders. Based on this determination of the biomarker (s-NGAL) in the serum of patients with blastomatous mechanical jaundice and performing in them at primary ultrasound color Doppler mapping and pulsed wave Doppler imaging of the kidneys with the calculation of the resistance index may serve as early signs of damage.

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Dubey, Anurag, Vivien Denis, and Roger Serra. "A Novel VBSHM Strategy to Identify Geometrical Damage Properties Using Only Frequency Changes and Damage Library." Applied Sciences 10, no. 23 (December 5, 2020): 8717. http://dx.doi.org/10.3390/app10238717.

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Vibration-based structural health monitoring is an efficient way to diagnose damage and structural integrity at the earliest stage. In this paper, a new strategy is developed for damage localization and estimation, as well as damage properties identification for a rectangular geometry damage using only eigenfrequencies of the healthy and damaged structure. This strategy is applied to a cantilever beam. In this framework, a damage library is built by correlating 2D and 3D finite element models. The correlation is done by minimizing a so-called frequency shift coefficient. The proposed strategy also uses the frequency shift coefficient to correlate a 2D damaged model with an unknown beam case. The 2D damage, represented by a bending stiffness reduction, is then associated to a 3D damage by employing the damage library. Numerical cases with single and double damage of varying position and severity are tested and used to validate the approach. Finally, experimental results are proposed that show the relevance of the strategy.

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47

Gautier, G., R. Serra, and J. M. Mencik. "Roller Bearing Monitoring by New Subspace-Based Damage Indicator." Shock and Vibration 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/828093.

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A frequency-band subspace-based damage identification method for fault diagnosis in roller bearings is presented. Subspace-based damage indicators are obtained by filtering the vibration data in the frequency range where damage is likely to occur, that is, around the bearing characteristic frequencies. The proposed method is validated by considering simulated data of a damaged bearing. Also, an experimental case is considered which focuses on collecting the vibration data issued from a run-to-failure test. It is shown that the proposed method can detect bearing defects and, as such, it appears to be an efficient tool for diagnosis purpose.

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Li, Shun Guo, and Hui Li. "The Fractional Diagnosis of Multi-Span Continuous Bridge’s Structural Damage Based on Neural Network and Genetic Algorithm." Applied Mechanics and Materials 71-78 (July 2011): 1298–304. http://dx.doi.org/10.4028/www.scientific.net/amm.71-78.1298.

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The natural environmental erosion and human factors such as the impact of traffic accidents, crack propagation, concrete carbonation and etc, make the bridge’s damage more serious. Therefore, the bridge damage diagnosis has become a hot field of bridge engineering issues. This paper put forward the fractional diagnosis method of multi-span bridge structure reflecting the structural cracks and carbonation damage. In this paper, adopting the optimization equivalent method, the finite element model of damaged structure is set up according to the damaging characteristic of multi-span continuous bridge structure. A damage index of strain mode with practical meanings is adopted which can reflect local damage. Basing on this index, fractional-step detection method of structural damage is presented. The first step is to identify the damage region, then locate the detailed damage location and degree; Performance of the proposed damage detection approach is demonstrated with analysis of a multi-span continuous bridge. The result turns up trumps.

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49

Nakhaee Amroodi, Morteza, Abolfazl Bagherifard, Mahmoud Jabalameli, Mostafa Salehpour, and Shoeib Majdi. "Alkaptonuric Ochronosis Superimposed With Septic Arthritis in a Middle-aged Man." Journal of Research in Orthopedic Science 7, no. 1 (February 1, 2020): 41–46. http://dx.doi.org/10.32598/jrosj.7.1.41.

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Alkaptonuria is a rare inborn metabolic disease, in which an enzymatic deficiency accumulates alkapton in different tissues, causing darkness and injury, especially in spine and large cartilages, called ochronosis. The urine darkness can be a key to early diagnosis in childhood, but some cases are missed until adulthood and gradual damage to cartilages causes disability and impairs the patients’ quality of life. Here, a 49-year old male patient is presented with a 2 week history of left knee pain and swelling, who underwent arthrotomy, and the macro- and microscopic evaluation revealed ochronosis, superimposed by septic arthritis. Diagnosis of this rare disease should be considered in differential diagnoses of common joint disorders, like septic arthritis and osteoarthritis, so that appropriate management of the disease can prevent further damages.

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Bazzi, Claudio, Teresa M. Seccia, Pietro Napodano, Cristina Campi, Brasilina Caroccia, Leda Cattarin, and Lorenzo A. Calò. "High Blood Pressure Is Associated with Tubulointerstitial Damage along with Glomerular Damage in Glomerulonephritis. A large Cohort Study." Journal of Clinical Medicine 9, no. 6 (June 1, 2020): 1656. http://dx.doi.org/10.3390/jcm9061656.

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The key role of arterial hypertension in chonic kidney disease (CKD) progression is widely recognized, but its contribution to tubulointerstitial damage (TID) in glomerulonephritis (GN) remains uncertain. Hence, the objective of this study is to clarify whether TID is associated with glomerular damage, and whether the damage at the tubulointerstitial compartment is more severe in hypertensive patients. The study included retrospectively consecutive patients referred to the Nephrology Unit with diagnoses of primary glomerulonephritis, lupus nephritis (LN), and nephroangiosclerosis (NAS) at biopsy. At least six glomeruli per biopsy were analysed through light and immunofluorescence microscopy. Global glomerulosclerosis (GGS%), TID, and arteriolar hyalinosis (AH) were used as markers of CKD severity. Of the 448 patients of the cohort, 403 received a diagnosis of GN, with the remaining being diagnosed with NAS. Hypertension was found in 52% of the overall patients, with no significant differences among those with GN, and reaching 88.9% prevalence rate in NAS. The hypertensive patients with GN had more marked damage in glomerular and tubular compartments than normotensives independently of the amount of proteinuria. Moreover, hypertension and GGS% were found to be strongly associated with TID in GN. In GN patients, not only the severity of glomerular damage but also the extent of TID was associated with high blood pressure.

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