Academic literature on the topic 'Interference fit estimation'

Interference fit is widely used in many industrial fields for its high ability to transmit an axial force or torque between a shaft and hub. But the performance of interference fits during their life in service is limited by stress concentrations and surface wear. Nowadays, theoretical methods based on thick-walled cylinder theory become increasingly abundant. However, the prediction results of stress distribution in press-fit process are not accurate for ignoring the stress concentrations. Since the stress distribution is significant for analysis of surface wear and assembly quality, especially for precision assembly of small parts, the purpose of this study is to build a new theoretical model to predict the stress distribution. The stress distribution equation was deduced based on a simplified model that a nonuniform linear load acts on a portion of semi-infinite plane. Finally, the stress distribution in the press-fit process was analyzed by the theoretical model, as well as the stress distribution of different material pairs (Ni36CrTiAl–50Ni-50Fe, AISI 1045–AISI 1045) under full contact condition. The comparison between theoretical and numerical results shows that the new theoretical model has high accuracy in predicting stress distribution and maximum stress, and the relative error is less than 17%. Therefore, the new theoretical model can give more reasonable results and provide a more reliable approach for design of interference fits. Furthermore, the model provides a method for the optimization of interference analysis under different structures and working conditions, and gives a theoretical basis for real-time estimation of assembly quality.

Shattercane interference in irrigated soybean was evaluated during 1987, 1988, and 1989 at Clay Center, NE, using ‘Rox’ forage sorghum to simulate shattercane. Soybean yield reduction did not occur if shattercane was removed by 2 wk after emergence in 1987 and 6 wk after emergence in 1988 and 1989. Shattercane interference with soybean began when shattercane height exceeded soybean height. Soybean yield was reduced up to 25% before the height differential reached 30 cm, the minimum difference required for selectively applying glyphosate with a wiper applicator. Soybean nodes per stem, pods per stem, and beans per pod decreased as duration of interference increased. A direct relationship between soybean yield loss and shattercane density fit a rectangular hyperbolic function. Yield loss per shattercane plant was highest at low shattercane densities. Soybean plant height, biomass, nodes per stem, pods per stem, pods per node, and beans per pod decreased as shattercane density increased. An interference model for estimation of soybean yield and economic loss based on shattercane density was developed.

Estimating [Formula: see text] using downgoing waves in zero-offset vertical seismic profiles (VSPs) can be challenging when scattered waves from near-borehole heterogeneities interfere with direct arrivals. In any [Formula: see text] estimation method that assumes a downgoing plane wave, constructive and destructive wave-mode interference can cause errors in the estimate. For example, in the spectral-ratio method, such interference modulates the amplitude spectra introducing significant variations and even nonphysical negative [Formula: see text] (amplification) estimates. We have investigated this phenomenon using synthetic and field data sets from offshore Australia and developed a two-step waveform-based method to characterize scattering anomalies and improve [Formula: see text] estimates. Waveform information is key to deal with closely spaced band-limited seismic events. First, we solve an inverse problem to locate and characterize scatterers by minimizing the traveltime and waveform misfits. Then, using the estimated parameters, we model the scatterers’ contribution to the VSP data and remove it from the observed waveforms. The resulting spectra resemble those that would have been acquired in the absence of the scatterers and are much more suitable for the spectral-ratio method. By assuming a 1D medium and a simple scatterer shape (i.e., circular), we parameterize a scattering heterogeneity using five parameters (depth, distance, size, velocity, and density) and seek a solution using a grid search to handle the nonuniqueness of the VSP inversion. Instead, adaptive subtraction is required to fine-tune the modeled interference to better fit the observation. We successfully use this method to characterize and mitigate the strongest wave interference in the field data. The final [Formula: see text] estimates contain milder variations and much less nonphysical negative [Formula: see text]. Our results demonstrate that the proposed method, readily extendible to multiple scatterer cases, can locate discrete scatterers, remove the effects of their interference, and thus significantly improve the [Formula: see text] estimates from VSP data.

In the atom gravimeter, three Raman pulses are utilized to realize the interference of atom matter waves, and atom interference fringes are obtained by scanning the chirp rate of the Raman laser during the interference time. Previously, fringe data analysis methods used LS (Least Squares) to fit the cosine function of each interference fringe data to minimize the standard deviation between the estimated value and the observed value of each group of fringe data or the EKF (Extended Kalman Filter) method to obtain the estimation of the gravity value. In this paper, we propose a new method applied to the interference fringe fitting of the atom gravimeter, namely, through the FPSO (Fitness Particle Swarm Optimization) method to estimate the parameters of the interference fringe atom and then estimate the gravity value. First, the theoretical analysis and proof are carried out by using simulation data. On this basis, we carried out a gravity measurement experiment in the ship-mounted mooring state, which further verified the feasibility and effectiveness of the algorithm. The simulation and experimental results show that, compared with LS and EKF methods, the FPSO method can search the relatively optimal fitting parameters of atom interference fringes quickly and accurately and improve the accuracy and stability of the atom gravimeter measurement. It is feasible and effective to apply the FPSO method to fitting atom interference fringes. The FPSO method proposed in this paper can be used as a new method for fitting atom interference fringes, which provides a new idea and choice for accurate gravity measurement in a dynamic environment.

An estimation of the critical period of weed control is helpful in formulating appropriate weed-control strategies. A regression approach is presented to estimate the thresholds of critical period of weed control and time of equal interference (or time of onset of competition). In this approach, yields were either a linear or logistic function of the duration of weed-free and weed-infested periods. Confidence intervals of the thresholds of critical period and time of equal interference were determined for the linear model. An approximation to the standard error of critical period and associated confidence interval were given for any general form of the model. The method was applied to estimate the critical period of weed control in rainfed lentil using data from four field experiments conducted in Jordan. The relationship of yield with the duration of weed-free period was described by a linear function, whereas the relationship with the duration of weed-infested period showed a better fit with a logistic function. To maintain 90% of maximum seed yield, the maximum time allowed to let weeds grow after the crop emergence varied over locations from 4.8 to 5.8 wk. The same level could be achieved if the crop is kept free of weeds from its emergence until 12.1 to 14.1 wk; while the time when the same amount of yield would be achieved under both approaches varied from 7.7 to 9.3 wk after crop emergence. For straw yield, the time to get 90% of the maximum yield could vary over location from a maximum of 4.5 to 8.0 wk under weed-infestation and from at least 11.5 to 13.5 wk when weed-free. The time to achieve the same amount of straw under two systems of competition varied from 6.5 to 9.9 wk after crop emergence. One of the four experiments showed a longer critical period than the others for seed and straw yields.

In this work, we adopt the analysis of a heterogeneous cellular network by means of stochastic geometry, to estimate energy and spectral network efficiency. More specifically, it has been the widely spread experience that practical field assessment of the Signal-to-Noise and Interference Ratio (SINR), being the key physical-layer performance indicator, involves quite sophisticated test instrumentation that is not always available outside the lab environment. So, in this regard, we present here a simpler test model coming out of the much easier-to-measure Bit Error Rate (BER), as the latter can deteriorate due to various impairments regarded here as equivalent with additive white Gaussian noise (AWGN) abstracting (in terms of equal BER degradation) any actual non-AWGN impairment. We validated the derived analytical model for heterogeneous two-tier networks by means of an ns3 simulator, as it provided the test results that fit well to the analytically estimated corresponding ones, both indicating that small cells enable better energy and spectral efficiencies than the larger-cell networks.

Abstract Background Identification and monitoring of chronic kidney disease (CKD) requires accurate quantification of serum creatinine. The poor specificity of Jaffe creatinine methods is well documented, and guidelines recommend enzymatic methodology. We describe our experience of moving from Jaffe to enzymatic creatinine methodology. We present comparison of >5000 paired Jaffe and enzymatic creatinine results, examine interferences, and attempt to assess clinical consequences of changing methodology. Methods Overall, 5303 serum samples received for routine creatinine measurement were analyzed using Jaffe and enzymatic methods with an Abbott Architect autoanalyzer. Associated results for glucose, total bilirubin, triglycerides, total protein, and hemolytic, icteric, and lipemic indexes were extracted from the laboratory database. CKD staging was estimated for each sample to assess potential clinical effects. Results The methods correlated well (r = 0.996) and showed good agreement (Passing-Bablok fit, y = 0.935x + 0.074). Paired analysis, however, showed significant differences (P < 0.001), and approximately 20% of results differed by more than ±10%. Multivariate analysis demonstrated independent associations between difference in creatinine results, glucose (P < 0.0001), and hemolytic index (P = 0.009). Glucose demonstrated positive interference in the Jaffe method, and hemolysis produced negative interference in the enzymatic method. Little or no association was observed with other analytes. CKD staging differed in 4% of samples. Conclusions Differences between Jaffe and enzymatic serum creatinine results exceed the recommended 5% target for a significant proportion of samples, particularly at concentrations <1.13 mg/dL (100 µmol/L). Both glucose and hemolysis contribute to the variance in results. Although the clinical impact of these differences seems small, laboratories should continue moving toward enzymatic creatinine estimation to ensure the best estimate of renal function.

Abstract Steel wire rope (SWR) defects plagued its application in many important fields, such as cranes, ports, etc. However, the accuracy of SWRs’ local flaws detection based on magnetic flux leakage (MFL) method is susceptible to the lift-off distance. This paper proposes an instantaneous lift-off distance estimation method to study the effect of lift-off distance on MFL detection for SWR. We firstly derive the relation between the lift-off distance and the MFL field strength based on the magnetic dipole model. After obtaining the time-frequency representation of the MFL signal by using multi-synchrosqueezing transform, we extract the instantaneous amplitude (IA) of the strand signal without other noise interference. Finally, the nonlinear least-squares method is used to fit the relation between the IAs of the strand signals and the lift-off distances to achieve the estimation of the instantaneous lift-off distance. A SWR with three local flaws is tested to validate the proposed method. This work provides instantaneous monitoring of lift-off distances, and it can be used in future noise suppressing methods development or quantitative analysis of local flaws.

The detailed structure information under the forest canopy is important for forestry surveying. As a high-precision environmental sensing and measurement method, terrestrial laser scanning (TLS) is widely used in high-precision forestry surveying. In TLS-based forestry surveys, stem-mapping, which is focused on detecting and extracting trunks, is one of the core data processing tasks and the basis for the subsequent calculation of tree attributes; one of the most basic attributes is the diameter at breast height (DBH). This article explores and improves the methods for stem mapping and DBH estimation from TLS data. Firstly, an improved 3D stem mapping algorithm considering the growth direction in random sample consistency (RANSAC) cylinder fitting is proposed to extract and fit the individual tree point cloud section. It constructs the hierarchical optimum cylinder of the trunk and introduces the growth direction into the establishment of the backbone buffer in the next layer. Experimental results show that it can effectively remove most of the branches and reduce the interference of the branches to the discrimination of trunks and improve the integrity of stem extraction by about 36%. Secondly, a robust least squares ellipse fitting method based on the elliptic hypothesis is proposed for DBH estimation. Experimental results show that the DBH estimation accuracy of the proposed estimation method is improved compared with other methods. The mean root mean squared error (RMSE) of the proposed estimation method is 1.14 cm, compared with other methods with a mean RMSE of 1.70, 2.03, and 2.14 cm. The mean relative accuracy of the proposed estimation method is 95.2%, compared with other methods with a mean relative accuracy of 92.9%, 91.9%, and 90.9%.

Ce mémoire traite du développement de récepteurs et de techniques d'estimation de canal pour les systèmes mobiles sans fil de type DS-CDMA multi-porteuse. Deux problèmes principaux doivent être pris en compte dans ce cas. Premièrement, l'Interférence d'Accès Multiple (IAM) causée par d'autres utilisateurs. Deuxièmement, les propriétés des canaux de propagation dans les systèmes radio mobiles. Ainsi, dans la première partie du manuscrit, nous proposons deux structures adaptatives (dites détection séparée et détection jointe) pour la mise en oeuvre de récepteurs minimisant l'erreur quadratique moyenne (MMSE), fondés sur un Algorithme de Projection Affine (APA). Ces récepteurs permettent de supprimer les IAM, notamment lorsque le canal d'évanouissement est invariant dans le temps. Cependant, comme ces récepteurs nécessitent les séquences d'apprentissage de chaque utilisateur actif, nous développons ensuite deux récepteurs adaptatifs dits aveugles, fondés sur un algorithme de type projection affine. Dans ce cas, seule la séquence d'étalement de l'utilisateur désiré est nécessaire. Quand les séquences d'étalement de tous les utilisateurs sont disponibles, un récepteur reposant sur le décorrélateur est aussi proposé et permet d'éliminer les IAM, sans qu'une période pour l'adaptation soit nécessaire. Dans la seconde partie, comme la mise en oeuvre de récepteurs exige l'estimation du canal, nous proposons plusieurs algorithmes pour l'estimation des canaux d'évanouissement de Rayleigh, variables dans le temps et produits dans les systèmes multi-porteuses. A cette fin, les canaux sont approximés par des processus autorégressifs (AR) d'ordre supérieur à deux. Le premier algorithme repose sur deux filtres de Kalman interactifs pour l'estimation conjointe du canal et de ses paramètres AR. Puis, pour nous affranchir des hypothèses de Gaussianité nécessaires à la mise en oeuvre d'un filtre optimal de Kalman, nous étudions la pertinence d'une structure fondée sur deux filtres H_inf interactifs. Enfin, l'estimation de canal peut être vue telle un problème d'estimation fondée sur un modèle à erreur-sur-les-variables (EIV). Les paramètres AR du canal et les variances de processus générateur et du bruit d'observation dans la représentation de l'espace d'état du système sont dans ce cas estimés conjointement à partir du noyau des matrices d'autocorrélation appropriées
This dissertation deals with the development of receivers and channel estimation techniques for multi-carrier DS-CDMA mobile wireless systems. Two major problems should be taken into account in that case. Firstly, the Multiple Access Interference (MAI) caused by other users. Secondly, the multi-path fading of mobile wireless channels. In the first part of the dissertation, we propose two adaptive structures (called separate and joint detection) to design Minimum Mean Square Error (MMSE) receivers, based on the Affine Projection Algorithm (APA). These receivers are able to suppress the MAI, particularly when the fading channel is time-invariant. However, as they require a training sequence for every active user, we then propose two blind adaptive multiuser receiver structures based on a blind APA-like multiuser detector. In that case, only the knowledge of the spreading code of the desired user is required. When the spreading codes of all users are available, a decorrelating detector based receiver is proposed and is able to completely eliminate the MAI without any training. In the second part, as receiver design usually requires the estimation of the channel, we propose several training-based algorithms for the estimation of time-varying Rayleigh fading channels in multi-carrier systems. For this purpose, the fading channels are approximated by autoregressive (AR) processes whose order is higher than two. The first algorithm makes it possible to jointly estimate the channel and its AR parameters based on two-cross-coupled Kalman filters. Nevertheless, this filtering is based on restrictive Gaussian assumptions. To relax them, we investigate the relevance of a structure based on two-cross-coupled H_inf filters. This method consists in minimizing the influence of the disturbances such as the additive noise on the estimation error. Finally, we propose to view the channel estimation as an Errors-In-Variables (EIV) issue. In that case, the channel AR parameters and the variances of both the driving process and the measurement noise in the state-space representation of the system are estimated from the null space of suitable correlation matrices

This paper presents the spin sensitivity and magnetic response analysis of the nano-superconducting-quantum-interference devices (SQUIDs). We employed the computational study to understand the schemes of a nano-SQUID’s detection capability according to the device’s geometry and fabrication process. We find that the performance of the nano-device increased by decreasing the loop size of the SQUIDs, and it reached the maximum value at the corners of the loop. We then estimated the flux noise SΦ of the SQUIDs in the thermal white noise regime and discussed the field amplification factor around the cross-section area. Furthermore, we fabricated YBa2Cu3O7 (YBCO) based nano-SQUIDs with Josephson junctions at MgO biocrystal grain boundaries using the Pulsed Laser Deposition (PLD) and Focused Ion Beam (FIB) technique. By comparison with the estimated value of our calculation, the spin sensitivity evaluated by the experimentally fabricated devices coincides nicely with our estimation.

In HVACR equipment, internally enhanced round tube (microfin) designs such as axial, cross-grooved, helical, and herringbone are commonly used to enhance the boiling and condensing performance of evaporators, condensers, and heat pumps. Typically, such tubes are mechanically expanded by a mandrel into a fin pack to create an interference fit between the tube outside surface and the fin collar to minimize the thermal contact resistance between tube and fin. However, during this expansion process, the internal enhancements undergo varying amounts of deformation, which degrades the in-tube thermal performance. Extensive data on condensing heat transfer coefficients in microfin tubes have been reported in the open literature. However, researchers have seldom used expanded tubes to acquire and report such data. Hence, it is always questionable to use such pristine tube data for designing heat exchangers and HVACR systems. Furthermore, the HVACR industry has been experiencing steeply rising copper costs, and this trend is expected to continue in coming years. So, many equipment manufacturers and suppliers are actively converting tubes from copper to aluminum. However, because of appreciable differences between the material properties of aluminum and copper, as well as other manufacturing variables, such as mandrel dimensions, lubricant used, etc., tube expansion typically deforms aluminum fins more than copper fins. Based on an analysis of the surface area changes arising from tube expansion, and an assessment of the best extant in-tube condensation heat transfer correlations, this work proposes a method of estimating the impact of tube expansion on in-tube condensation heat transfer. The analysis leads to certain interesting and useful findings correlating fin geometry and in-tube condensation thermal resistance. This method can then be applied to more realistically design HVACR heat exchangers and systems.