Статті в журналах з теми "Signal processing digital techniques; electricity"

Many areas of activity face the problem of electricity quality. At the same time, diagnosing the quality of the energy provided makes it possible to identify and remedy problems that have arisen in the system. Advanced signal processing techniques and the use of advanced systems allow for a complex analysis of the phenomenon. The paper presents an electricity meter equipped with an electricity quality analysis system. It was developed based on the Xilinx Artix-7 programmable logic matrix. A Digilent Arty A7 development board was used due to its design and experimentation facilities. The developed system determines the power consumed and the main elements that define the quality of electricity: harmonics and other deviations from the frequency of nominal power supply, flicker, voltage gaps, voltage variations, transient surge, temporary surge, etc. The possibility of using an embedded system equipped with the Microblaze soft microprocessor, the existence of a 12-bit analog-digital converter and the maximum sampling frequency of 1 MSPS and the possibility of assisted design allows to obtain a measurement system with superior characteristics. The results obtained and the experiments carried out confirm the expected performance for the electricity meter.

In recent years, there has been a desire to improve electricity generation and consumption, to reach sustainability. Technological solutions today allow a rational use of electricity with good overall performance. Traditionally, from production to distribution, electrical energy is AC-supported for compatibility reasons and easy voltage level transformation. However, nowadays most electric loads need DC power to work properly. A single high-efficiency central AC-DC power converter may be advantageous in eliminating several less efficient AC-DC embedded converters, distributed all over a residential area. This paper presents a new single-phase AC-DC converter using one active bridge (most isolated topologies are based on the dual active bridge concept) and a high-frequency isolation transformer with low-value non-electrolytic capacitors, together with its control system design. The converter can be introduced into future low-voltage DC microgrids for residential buildings, as an alternative to several embedded AC-DC converters. Non-linear control techniques (sliding mode control and the Lyapunov direct method) are employed to guarantee stability in the output DC low voltage with near unity power factor compensation in the AC grid. The designed converter and controllers were simulated using Matlab/Simulink and tested in a lab experimental prototype using digital signal processing (DSP) to evaluate system performance.

In the industrial application, the induction motors (IMs) and the digital signal processing (ZQ28335) combination are very important in the scientific field. Two thirds of consumption of electricity is due to motor driven equipment. The direct torque control (DTC) is the standard of the industry and it has fast response control system applications. The drawback of DTC is the flux and torque ripples in the measurements. The scalar control can be considered as a solution to this drawback but with poor response. Torque and speed of IM are controlling individually, the variable speed drive (VSDs) is used. This occurs with variation of the voltage and frequency of IM supply. To decrease the levels of flux and torque ripples, 3-level inverters represent an attractive technique. The compromise of a huge flux and torque at the beginning level and low values at steady state of operation is crucial to ensure better stability with feedback linearization of the nonlinear behavior. In this paper, VSD with DTC IM with multilevel inverter with the newest version of ZQ28335 digital signal processor (DSP) is proposed. Emulation and the results of experiment through DSP ZQ28335 make certain correct dynamic response to the operations of torque and flux.

The feasibility of power transfer enhancement, through simultaneous AC–DC power transmission in a two-terminal transmission network, has been proposed earlier by the authors, and the concept is well established. To meet the increase in demand for electricity, a new technique is proposed in this article to increase the use of existing transmission lines in addition to independent control of AC and DC power flow. This paper extends the concept to a three-terminal transmission network by considering a power tapping from the middle of the line. DC is also superimposed in the already existing three-terminal AC transmission system. In the proposed topology, a multi-terminal simultaneous AC–DC system is used, which is integrated with a zig-zag transformer and more than two voltage source converter (VSC) stations. Each terminal may represent an area of the power system. Anyone/two-terminal(s) may act as sending end, whereas the remaining two/one terminal(s) may act as receiving end. Power can flow in either direction through each segment of the transmission system. At sending end, VSC converts a part of AC to DC and injects it into the neutral of the zig-zag transformer. On receiving terminal, DC power is tapped from neutral of zig-zag transformer and fed to VSC for conversion back to AC. The concept is verified in the digital simulation software PSCAD/EMTDC.

PurposeA recent innovative technology used in wireless communication is recognized as multiple input multiple output (MIMO) communication system and became popular for quicker data transmission speed. This technology is being examined and implemented for the latest broadband wireless connectivity networks. Though high-capacity wireless channel is identified, there is still requirement of better techniques to get increased data transmission speed with acceptable reliability. There are two types of systems comprising of multi-antennas placed at transmitting and receiving sides, of which first is diversity technique and another is spatial multiplexing method. By making use of these diversity techniques, the reliability of transmitting signal can be improved. The fundamental method of the diversity is to transform wireless channel such as Rayleigh fading into steady additive white Gaussian noise (AWGN) channel which is devoid of any disastrous fading of the signal. The maximum transmission speed that can be achieved by spatial multiplexing methods is nearly equal to channel capacity of MIMO. Conversely, for diversity methods, the maximum speed of broadcasting is much lower than channel capacity of MIMO. With the advent of space–time block coding (STBC) antenna diversity technique, higher-speed data transmission is achievable for spatially multiplexed multiple input multiple output (SM-MIMO) system. At the receiving end, detection of the signal is a complex task for system which exhibits SM-MIMO. Additionally, a link modification method is implemented to decide appropriate coding and modulation scheme such as space diversity technique STBC to use two-way radio resources efficiently. The proposed work attempts to improve detection of signal at receiving end by employing STBC diversity technique for linear detection methods such as zero forcing (ZF), minimum mean square error (MMSE), ordered successive interference cancellation (OSIC) and maximum likelihood detection (MLD). The performance of MLD has been found to be better than other detection techniques.Design/methodology/approachAlamouti's STBC uses two transmit antennas regardless of the number of receiver antennas. The encoding and decoding operation of STBC is shown in the earlier cited diagram. In the following matrix, the rows of each coding scheme represent a different time instant, while the columns represent the transmitted symbols through each different antenna. In this case, the first and second rows represent the transmission at the first and second time instant, respectively. At a time t, the symbol s1 and symbol s2 are transmitted from antenna 1 and antenna 2, respectively. Assuming that each symbol has duration T, then at time t + T, the symbols –s2* and s1*, where (.)* denotes the complex conjugate, are transmitted from antenna 1 and antenna 2, respectively. Case of one receiver antenna: The reception and decoding of the signal depend on the number of receiver antennas available. For the case of one receiver antenna, the received signals are received at antenna 1 , hij is the channel transfer function from the jth transmit antenna and the ith receiver antenna, n1 is a complex random variable representing noise at antenna 1 and x (k) denotes x at time instant k ( at time t + (k – 1)T.FindingsThe results obtained for maximal ratio combining (MRC) with 1 × 4 scheme show that the BER curve drops to 10–4 for signal-to-noise (SNR) ratio of 10 dB, whereas for MRC 1 × 2 scheme, the BER drops down to 10–5 for SNR of 20 dB. Results obtained in Table 1 show that when STBC is employed for MRC with 1 × 2 scheme (one antenna at transmitter node and two antennas at receiver node), BER curve comes down to 0.0076 for Eb/N0 of 12. Similarly, when MRC with 1 × 4 antenna scheme is implemented, BER drops down to 0 for Eb/N0 of 12. Thus, it can be concluded from the obtained graph that the performance of MRC with STBC gives improved results. When STBC technique is used with 3 × 4 scheme, at SNR of 10 dB, BER comes nearer to 10–6 (figure 7.3). It can be concluded from the analytics observed between AWGN and Rayleigh fading channel that for AWGN channel, BER is found to be equal to 0 for SNR value of 13.5 dB, whereas for Rayleigh fading channel, BER is observed nearer to 10–3 for Eb/N0 = 15. Simulation results (in figure 7.2) from the analytics show BER drops to 0 for SNR value of 12 dB.Research limitations/implicationsOptimal design and successful deployment of high-performance wireless networks present a number of technical challenges. These include regulatory limits on useable radio-frequency spectrum and a complex time-varying propagation environment affected by fading and multipath. The effect of multipath fading in wireless systems can be reduced by using antenna diversity. Previous studies show the performance of transmit diversity with narrowband signals using linear equalization, decision feedback equalization, maximum likelihood sequence estimation (MLSE) and spread spectrum signals using a RAKE receiver. The available IC techniques compatible with STBC schemes at transmission require multiple antennas at the receiver. However, if this not a strong constraint at the base station level, it remains a challenge at the handset level due to cost and size limitation. For this reason, SAIC technique, alternative to complex ML multiuser demodulation technique, is still of interest for 4G wireless networks using the MIMO technology and STBC in particular. In a system with characteristics similar to the North American Digital mobile radio standard IS-54 (24.3 K symbols per sec. with an 81 Hz fading rate), adaptive retransmission with time deviation is not practical.Practical implicationsThe evaluation of performance in terms of bit error rate and convergence time which estimates that MLD technique outperforms in terms of received SNR and low decoding complexity. MLD technique performs well but when higher number of antennas are used, it requires more computational time and thereby resulting in increased hardware complexity. When MRC scheme is implemented for singe input single output (SISO) system, BER drops down to 10–2 for SNR of 20 dB. Therefore, when MIMO systems are employed for MRC scheme, improved results based on BER versus SNR are obtained and are used for detecting the signal; comparative study based on different techniques is done. Initially ZF detection method is utilized which was then modified to ZF with successive interference cancellation (ZFSIC). When successive interference cancellation scheme is employed for ZFSIC, better performance is observed as compared to the estimation of ML and MMSE. For 2 × 2 scheme with QPSK modulation method, ZFSIC requires more computational time as compared to ZF, MMSE and ML technique. From the obtained results, the conclusion is that ZFSIC gives the improved results as compared to ZF in terms of BER ratio. ZF-based decision statistics can be produced by the detection algorithm for a desired sub-stream from the received vector whichs consist of an interference which occurred from previous transmitted sub-streams. Consequently, a decision on the secondary stream is made and contribution of the noise is regenerated and subtracted from the vector received. With no involvement of interference cancellation, system performance gets reduced but computational cost is saved. While using cancellation, as H is deflated, coefficients of MMSE are recalculated at each iteration. When cancellation is not involved, the computation of MMSE coefficients is done only once, because of H remaining unchanged. For MMSE 4 × 4 BPSK scheme, bit error rate of 10–2 at 30 dB is observed. In general, the most thorough procedure of the detection algorithm is the computation of the MMSE coefficients. Complexity arises in the calculation of the MMSE coefficients, when the antennas at the transmitting side are increased. However, while implementing adaptive MMSE receivers on slow channel fading, it is probable to recover the signal with the complications being linear in the antennas of transmitter node. The performance of MMSE and successive interference cancellation of MMSE are observed for 2 × 2 and 4 × 4 BPSK and QPSK modulation schemes. The drawback of MMSE SIC scheme is that the first detected signal observes the noise interference from (NT-1) signals, while signals processed from every antenna later observe less noisy interference as the process of cancellation progresses. This difficulty could be overcome by using OSIC detection method which uses successive ordering of the processed layers in the decreasing power of the signal or by power allocation to the signal transmitted depending on the order of the processing. By using successive scheme, a computation of NT delay stages is desired to bring out the abandoned process. The work also includes comparison of BER with various modulation schemes and number of antennas involved while evaluating the performance. MLD determines the Euclidean distance among the vector signal received and result of all probable transmitted vector signals with the specified channel H and finds the one with the minimum distance. Estimated results show that higher order of the diversity is observed by employing more antennas at both the receiving and transmitting ends. MLD with 8 × 8 binary phase shift keying (BPSK) scheme offers bit error rate near to 10–4 for SNR (16 dB). By using Altamonti space ti.Social implicationsIt should come as no surprise that companies everywhere are pushing to get products to market faster. Missing a market window or a design cycle can be a major setback in a competitive environment. It should be equally clear that this pressure is coming at the same time that companies are pushing towards “leaner” organizations that can do more with less. The trends mentioned earlier are not well supported by current test and measurement equipment, given this increasingly high-pressure design environment: in order to measure signals across multiple domains, multiple pieces of measurement equipment are needed, increasing capital or rental expenses. The methods available for making cross-domain, time-correlated measurements are inefficient, reducing engineering efficiency. When only used on occasion, the learning curve to understand how to use equipment for logic analysis, time domain and RF spectrum measurements often requires an operator to re-learn each piece of separate equipment. The equipment needed to measure wide bandwidth, time-varying spectral signals is expensive, again increasing capital or rental expenses. What is needed is a measurement instrument with a common user interface that integrates multiple measurement capabilities into a single cost-effective tool that can efficiently measure signals in the current wide-bandwidth, time-correlated, cross-domain environments. The market of wireless communication using STBCs has large scope of expansion in India. Therefore, the proposed work has techno-commercial potential and the product can be patented. This project shall in turn be helpful for remote areas of the nearby region particularly in Gadchiroli district and Melghat Tiger reserve project of Amravati district, Nagjira and so on where electricity is not available and there is an all the time problem of coverage in getting the network. In some regions where electricity is available, the shortage is such that they cannot use it for peak hours. In such cases, stand-alone space diversity technique, STBC shall help them to meet their requirements in making connection during coverage problem, thereby giving higher data transmission rates with better QOS (quality of service) with least dropped connections. This trend towards wireless everywhere is causing a profound change in the responsibilities of embedded designers as they struggle to incorporate unfamiliar RF technology into their designs. Embedded designers frequently find themselves needing to solve problems without the proper equipment needed to perform the tasks.Originality/valueWork is original.

Terahertz signal transmission in DNA is simulated and analyzed using molecular dynamics and digital signal processing techniques to demonstrate that signals encoded in vibrational movements of hydrogen bonds can travel along the backbone of DNA and eventually be recovered and analyzed using digital signal processing techniques.

This paper presents the discussion on efficiency of different implementation methodologies of DSP algorithms targeted for modern FPGA architectures. Modern programmable structures are equipped with specialized DSP embedded blocks that allow implementing digital signal processing algorithms with use of the methodology known from digital signal processors. On the first place however, programmable architectures give the designer the possibility to increase efficiency of designed system by exploitation of parallelism of implemented algorithms. Moreover, it is possible to apply special techniques such as distributed arithmetic (DA) that will boost the performance of designed processing systems. Additionally, application of the functional decomposition based methods, known to be best suited for FPGA structures allows utilizing possibilities of programmable technology in very high degree. The paper presents results of comparison of different design approaches in this area.

Image processing is method of performing some operations on an image, for enhancing the image or for getting some information from that image, or for some other applications is nothing but Image Processing [1]. Image processing is one sort of signal processing, where input is an image and output may be an image, characteristics of that image or some features that image [1]. Image will be taken as a two dimensional signal and signal processing techniques will be applied to that two dimensional image. Image processing is one of the growing technologies [1]. In many real time applications image processing is widely used. In the field of bio technology, computer science, in medical field, envi-ronmental areas etc., image processing is being used for mankind benefits. The following steps are the basics of image processing:Image is taken as an inputImage will be processed (manipulation, analyzing the image, or as per requirement)Altered image will be the outputImage processing is of two typesAnalog Image Processing:As the name implies, analog image processing is applied on analog signals. Television image is best example of analog signal processing [1].(DIP) Digital Image Processing:DIP techniques are used on images, which are in the format of digital for processing them, and get the required output as per the application. Operations were applied on the digital images for processing [1].In this paper, we will discuss about the technologies or tools for image processing especially by using Open CV. With the help of Open CV image processing will be very easy and efficient. When Open CV is collaborated or integrated with python the results are mind blowing. We will discuss about the process of using python and Open CV.

With the exponential growth of big data and data warehousing, the amount of data collected from various stock markets around the world has increased significantly. It is now impossible to process and analyze data using mathematical techniques and basic statistical calculations to forecast trends such as closing and opening prices, as well as daily stock market lows and highs. The development of smart and automated stock market forecasting systems has made significant progress in recent years. Digital signal processing is required for analysis and preprocessing because of the accuracy and speed with which these large amounts of data must be processed and analyzed. In this paper, we evaluate some of these predictive algorithms based on three parameters such as speed, accuracy and complexity, we analyze the data using the dataset from kaggle.com and we implement these algorithms using pythons. The results of our analysis in this paper shows a significant correlation between the yearly prices until the year 2018 where there is a significant increase in stock price.

Silicon drift detector (SDD) is a kind of high performance X-ray detector, which is widely used. The ray detection system based on SDD is composed of SDD device, preamplifier and pulse processing system. The now available pulse processing system has the problems of poor pulse pile-up rejection performance and being vulnerable to the parameter fluctuations of front-end system, which degrades the performance of detection system. A digital pulse processing system is proposed. In this system, analog-to-digital converter (ADC) directly samples the output signal of preamplifier, and transmits the data to the digital pulse processing platform for processing. According to the signal characteristics of SDD device and preamplifier, the influence of ADC sampling bits and sampling frequency on system performance is analyzed. Two optimized ADC sampling circuits are proposed to reduce energy resolution degradation induced by insufficient ADC sampling bits. The pulse shaping algorithm in the digital pulse processing system is studied. The results show that the shaping signal will not be distorted due to the parameter fluctuations of the front-end system, which proves the robustness of the digital pulse processing system. The digital pulse processing system is implemented and tested, and the correctness of the system is verified.

Digital sounds and images are used everywhere today, and they are all generated originally by analogue signals. On the other hand, in digital signal processing, the storage or transmission of digital data, such as music, videos or image files, necessitates converting such analogue signals into digital signals via sampling. When these data are sampled, the values from the discrete, sampled points are kept while the information between the sampled points is lost. Various techniques have been developed over the years to recover this lost data, but the results remain incomplete. Professor Yutaka Yamamoto's research is focused on improving how we can recover or reconstruct the original analogue data.

This paper aims at elaborating on the digital signal processing techniques used in data manipulation in the radioSolariz solar radio-telescope project. Focus is drawn on the implementation of different digital signal processing algorithms through the use of streaming single instruction – multiple data extensions 2. This complementary instruction set to general purpose personal computer microprocessors offers increased computational power by realizing parallel processing. The benefit is a higher data throughput while lowering the electrical power consumption of the digital signal processing computer. Optimized code fragments are shown along with original code snippets and these are discussed and analyzed. Future work and implementation of other modern parallel processing technologies are envisaged.

The field of advanced digital signal processing methods is one of the fastest developing scientific and technical disciplines, and is important in the field of Shunt Active Power Filter control methods. Shunt active power filters are highly desirable to minimize losses due to the increase in the number of nonlinear loads (deformed power). Currently, there is rapid development in new adaptive, non-adaptive, and especially hybrid methods of digital signal processing. Nowadays, modern methods of digital signal processing maintain a key role in research and industrial applications. Many of the best practices that have been used to control shunt active power in industrial practice for decades are now being surpassed in favor of new progressive approaches. This systematic research review classifies the importance of using advanced signal processing methods in the field of shunt active power filter control methods and summarizes the extant harmonic extraction methods, from the conventional approach to new progressive methods using genetic algorithms, artificial intelligence, and machine learning. Synchronization techniques are described and compared as well.

For improving the generality, expandability and accuracy, the general embedded intelligent monitoring system of tower crane is developed. The system can be applied to different kinds of tower cranes running at any lifting ratio, can be initialized using U disk with the information of tower crane, and fit the lifting torque curve automatically. In dangerous state, the system can sent out alarm signals with sounds and lights, and cut off power by sending signals to PLC through communication interface RS485. When electricity goes off suddenly, the system can record the real-time operating information automatically, and store them in a black box, which can be taken as the basis for confirming the accident responsibility.In recent years, tower cranes play a more and more important role in the construction of tall buildings, in other construction fields are also more widely used. For the safety of tower cranes, various monitors have been developed for monitoring the running information of crane tower [1-8]. These monitors can’t eliminate the errors caused by temperature variations automatically. The specific tower crane’s parameters such as geometric parameters, alarming parameters, lifting ratio, lifting torque should be embedded into the core program, so a monitor can only be applied to a specific type of tower crane, lack of generality and expansibility.For improving the defects of the existing monitors, a general intelligent monitoring modular system of tower crane with high precision is developed, which can initialize the system automatically, eliminate the temperature drift and creep effect of sensor, and store power-off data, which is the function of black box.Hardware design of the monitoring systemThe system uses modularized design mode. These modules include embedded motherboard module, sensor module, signal processing module, data acquisition module, power module, output control module, display and touch screen module. The hardware structure is shown in figure 1. Figure 1 Hardware structure of the monitoring systemEmbedded motherboard module is the core of the system. The motherboard uses the embedded microprocessor ARM 9 as MCU, onboard SDRAM and NAND Flash. Memory size can be chosen according to users’ needs. SDRAM is used for running procedure and cache data. NAND Flash is used to store embedded Linux operating system, applications and operating data of tower crane. Onboard clock with rechargeable batteries provides the information of year, month, day, hour, minute and second. This module provides time tag for real-time operating data. Most interfaces are taken out by the plugs on the embedded motherboard. They include I/O interface, RS232 interface, RS485 interface, USB interface, LCD interface, Audio interface, Touch Screen interface. Pull and plug structure is used between all interfaces and peripheral equipments, which not only makes the system to be aseismatic, but also makes its configuration flexible. Watch-dog circuit is designed on the embedded motherboard, which makes the system reset to normal state automatically after its crash because of interference, program fleet, or getting stuck in an infinite loop, so the system stability is improved greatly. In order to store operating data when power is down suddenly, the power-down protection circuit is designed. The saved data will be helpful to repeat the accident process later, confirm the accident responsibility, and provide the basis for structure optimization of tower crane.Sensor module is confirmed by the main parameters related to tower crane’s security, such as lifting weight, lifting torque, trolley luffing, lifting height, rotary angle and wind speed. Axle pin shear load cell is chosen to acquire lifting weight signals. Potentiometer accompanied with multi-stopper or incremental encoder is chosen to acquire trolley luffing and lifting height signals. Potentiometer accompanied with multi-stopper or absolute photoelectric encoder is chosen to acquire rotary angle signals. Photoelectric sensor is chosen to acquire wind speed signals. The output signals of these sensors can be 0~5V or 4~20mA analog signals, or digital signal from RS485 bus. The system can choose corresponding signal processing method according to the type of sensor signal, which increases the flexibility on the selection of sensors, and is helpful for the users to expand monitoring objects. If the acquired signal is analog signal, it will be processed with filtering, isolation, anti-interference processing by signal isolate module, and sent to A/D module for converting into digital signals, then transformed into RS485 signal by the communication protocol conversion device according to Modbus protocol. If the acquired signal is digital signal with RS485 interface, it can be linked to RS485 bus directly. All the acquired signals are sent to embedded motherboard for data processing through RS485 bus.The data acquisition module is linked to the data acquisition control module on embedded motherboard through RS485 interface. Under the control of program, the system inquires the sensors at regular intervals, and acquires the operating data of crane tower. Median filter technology is used to eliminate interferences from singularity signals. After analysis and processing, the data are stored in the database on ARM platform.Switch signal can be output to relay module or PLC from output control module through RS485 bus, then each actuator will be power on or power off according to demand, so the motion of tower crane will be under control.Video module is connected with motherboard through TFT interface. After being processed, real-time operating parameters are displayed on LCD. The working time, work cycle times, alarm, overweight and ultar-torque information will be stored into database automatically. For meeting the needs of different users, the video module is compatible with 5.7, 8.4 or 10.4 inches of color display.Touch screen is connected with embedded motherboard by touch screen interface, so human machine interaction is realized. Initialization, data download, alarm information inquire, parameter modification can be finished through touch screen.Speaker is linked with audio interface, thus alarm signals is human voice signal, not harsh buzz.USB interface can be linked to conventional U disk directly. Using U disk, users can upload basic parameters of tower crane, initialize system, download operating data, which provides the basis for the structural optimization and accident analysis. Software design of the monitoring systemAccording to the modular design principle, the system software is divided into grading encryption module, system update module, parameter settings module, calibration module, data acquisition and processor module, lifting parameters monitoring module, alarm query module, work statistics module.Alarm thresholds are guarantee for safety operation of the tower crane. Operating data of tower crane are the basis of service life prediction, structural optimization, accident analysis, accident responsibility confirmation. According to key field, the database is divided into different security levels for security requirements. Key fields are grade encryption with symmetrical encryption algorithm, and data keys are protected with elliptic curve encryption algorithm. The association is realized between the users’ permission and security grade of key fields, which will ensure authorized users with different grades to access the equivalent encrypted key fields. The user who meets the grade can access equivalent encrypted database and encrypted key field in the database, also can access low-grade encrypted key fields. This ensures the confidentiality and integrity of key data, and makes the system a real black box.The system is divided into operating mode and management mode in order to make the system toggle between the two states conveniently. The default state is operating mode. As long as the power is on, the monitoring system will be started by the system guide program, and monitor the operating state of the tower crane. The real-time operating data will be displayed on the display screen. At the dangerous state, warning signal will be sent to the driver through voice alarm and light alarm, and corresponding control signal will be output to execution unit to cut off relevant power for tower crane’s safety.By clicking at the mode switch button on the initial interface, the toggle can be finished between the management mode and the operating mode. Under the management mode, there are 4 grades encrypted modes, namely the system update, alarm query, parameter setting and data query. The driver only can browse relevant information. Ordinary administrator can download the alarm information for further analysis. Senior administrator can modify the alarm threshold. The highest administrator can reinitialize system to make it adapt to different types of tower crane. Only browse and download function are available in the key fields of alarm inquiry, anyone can't modify the data. The overload fields in alarm database are encrypted, only senior administrator can browse. The sensitive fields are prevented from being tampered to the great extent, which will provide the reliable basis for the structural optimization and accident analysis. The system can be initialized through the USB interface. Before initialization, type, structural parameters, alarm thresholds, control thresholds, lifting torque characteristics of tower crane should be made as Excel files and then converted to XML files by format conversion files developed specially, then the XML files are downloaded to U disk. The U disk is inserted into USB interface, then the highest administrator can initialize the system according to hints from system. After initialization, senior administrator can modify structural parameters, alarm thresholds, control thresholds by clicking on parameters setting menu. So long as users can make the corresponding excel form, the system initialization can be finished easily according to above steps and used for monitoring. This is very convenient for user.Tower crane belongs to mobile construction machinery. Over time, sensor signals may have some drift, so it is necessary to calibrate the system regularly for guaranteeing the monitoring accuracy. Considering the tower is a linear elastic structure, sensors are linear sensors,in calibration linear equation is used:y=kx+b (1)where x is sample value of sensor, y is actual value. k, b are calibration coefficients, and are calculated out by two-points method. At running mode, the relationship between x and y is:y=[(y1-y0)/(x1-x0)](x-x0)+y0 (2)After calibration, temperature drift and creep can be eliminated, so the monitoring accuracy is improved greatly.Lifting torque is the most important parameter of condition monitoring of tower crane. Comparing the real-time torque M(L) with rated torque Me(L), the movement of tower crane can be controlled under a safe status.M (L)= Q (L)×L (3)Where, Q(L)is actual lifting weight, L is trolley luffing. Me(L) = Qe(L)×L (4)Where, Q e(L) is rated lifting weight. The design values of rated lifting weight are discrete, while trolley luffing is continuous. Therefore there is a rated lifting weight in any position. According to the mechanical characteristics of tower crane, the rated lifting weight is calculated out at any point by 3 spline interpolation according to the rated lifting weight at design points.When lifting weight or lifting torque is beyond rated value, alarm signal and control signal will be sent out. The hoist motor with high, medium and low speed is controlled by the ratio of lifting weight Q and maximum lifting weight Qmax,so the hoisting speed can be controlled automatically by the lifting weight. The luffing motor with high and low speed is controlled by the ratio of lifting torque M and rated lifting torque Me. Thus the luffing speed can be controlled by the lifting torque automatically. The flow chart is shown in figure 2. Fig. 2 real-time control of lifting weight and lifting torqueWhen accidents take place, power will be off suddenly. It is vital for identifying accident liability to record the operating data at the time of power-off. If measures are not taken to save the operating data, the relevant departments is likely to shirk responsibility. In order to solve the problem, the power-off protection module is designed. The module can save the operating data within 120 seconds automatically before power is off suddenly. In this 120 seconds, data is recorded every 0.1 seconds, and stores in a 2D array with 6 rows 1200 columns in queue method. The elements of the first line are the recent time (year-month-day-hour-minute-second), the elements of the second line to sixth line are lifting weight, lifting torque, trolley luffing, lifting height and wind speed in turn. The initial values are zero, when a set of data are obtained, the elements in the first column are eliminated, the elements in the backward columns move frontwards, new elements are filled into the last column of the array, so the array always saves the operating data at the recent 120 seconds. In order to improve the real-time property of the response, and to extend the service life of the nonvolatile memory chip EEPROM-93C46, the array is cached in volatile flip SDRAM usually. So long as power-off signal produces, the array will be shift to EEPROM, at once.In order to achieve the task, the external interruption thread and the power-off monitoring thread of program is set up, the power-off monitoring thread of program is the highest priority. These two threads is idle during normal operation. When power is off, the power-off monitoring thread of program can be executed immediately. When power-off is monitored by power-off control circuit, the external interruption pins produces interrupt signal. The ARM microprocessor responds to external interrupt request, and wakes up the processing thread of external interruption, then sets synchronized events as informing state. After receiving the synchronized events, the data cached in SDRAM will be written to EEPROM in time.ConclusionThe general intelligence embedded monitoring system of tower crane, which can be applicable to various types of tower crane operating under any lifting rates, uses U disk with the information of the tower crane to finish the system initialization and fits the lifting torque curve automatically. In dangerous state, the system will give out the voice and light alarm, link with the relay or PLC by the RS485 communication interface, and cut off the power. When power is down suddenly, the instantaneous operating data can be recorded automatically, and stored in a black box, which can be taken as the proof for identifying accident responsibility. The system has been used to monitor the "JiangLu" series of tower cranes successfully, and achieved good social and economic benefits.AcknowledgementsThe authors wish to thank China Natural Science Foundation(50975289), China Postdoctoral Science Foundation(20100471229), Hunan science & technology plan, Jianglu Machinery & Electronics Co. Ltd for funding this work.Reference Leonard Bernold. Intelligent Technology for Crane Accident Prevention. Journal of Construction Engineering and Management. 1997, 9: 122~124.Gu Lichen,Lei Peng,Jia Yongfeng. Tower crane' monitor and control based on multi-sensor. Journal of Vibration, Measurement and Diagnosis. 2006, 26(SUPPL.): 174-178.Wang Ming,Zhang Guiqing,Yan Qiao,et, al. Development of a novel black box for tower crane based on an ARM-based embedded system. Proceedings of the IEEE International Conference on Automation and Logistics. 2007: 82-87.Wang Renqun, Yin Chenbo, Zhang Song, et, al. Tower Crane Safety Monitoring and Control System Based on CAN Bus. Instrument Techniques and Sensor. 2010(4): 48-51.Zheng Conghai,Li Yanming,Yang Shanhu,et, al. Intelligent Monitoring System for Tower Crane Based on BUS Architecture and Cut IEEE1451 Standard. Computer Measurement & Control. 2010, 18, (9): 1992-1995.Yang Yu,Zhenlian Zhao,Liang Chen. Research and Design of Tower Crane Condition Monitoring and Fault Diagnosis System. 2010 Proceedings of International Conference on Artificial Intelligence and Computational Intelligence. 2010: 405-408.Yu Yang, Chen Liang, Zhao Zhenlian. Research and design of tower crane condition monitoring and fault diagnosis system. International Conference on Artificial Intelligence and Computational Intelligence, 2010, 3: 405-408.Chen Baojiang, Zeng Xiaoyuan. Research on structural frame of the embedded monitoring and control system for tower crane. 2010 International Conference on Mechanic Automation and Control Engineering. 2010: 5374-5377.

Weak signal detection is the key technique in developing through-casing resistivity logging tool. In this paper, ultra-low-noise preamplifier, oversampling method, sampling integration and sampling average method, digital phase-sensitive detection technique are applied in detecting logging signals and 30nV is achieved. The indoor calibration test and field experiment of through-casing resistivity logging model machine with those weak signal detection techniques were carried out. The result showed that the measurement range of formation resistivity is 0~200 Ω.m.

This paper reviewed the Application of Digital Signal Processing (DPS) and Machine Learning (ML) for Electromyography (EMG) by previous studies. There is a need of the DSP and ML application into the EMG study to classify the signal in order to minimize the EMG noise of signal and the EMG signal characteristic. The common techniques analysis of signal processing is disccussed and compared to identify the best techniques used in order to process from raw data of EMG signal info EMG signal analysis, then some types of machine learning is discussed to identify which types of machine learning have gave the best performance of EMG signal identification and signal characteristic with the highest percentage of the accuracy and efficiency. Digital signal processing and the technique of signal analysis and machine learning for classification method in order to provide the best method and classification for EMG signal.

Adherance of power quality standards is crucial for electricity network operation and bothindustrial and private customers. However, the transition to electricity supply based on renewable, de-centralized plants which feed in using inverters is accompanied by challenges regarding compliancewith power quality standards. Accordingly, detection and automated processing of relevant variablesof power quality is of increased importance. Digital signal processing offers various approaches of sig-nal evaluation each having individual advantages and disadvantages regarding different power qualityvariables. As a result of incresing decentralized feed in of regenerative plats using inverters, the si-nusoidal fundamental of the power system is distorted and harmonics occur. For elimination of thoseunwanted signal components, a variety of methods is available. Supple- menting current research ac-tivites a laboratory model of an active filter using low budget prototyping hardware is developed andevaluated. Therefore, an experimental circuit containing a band pass filter for signal adjustment aswell as a PWM with amplification circuit for signal correction have been elaborated. Necessary cal-culations are performed by a standard Atmel microprocessor as used by Arduino Uno, including an8-bit analog to digital converter (ADC).

On-line near infrared (NIR) analysers are used widely for quantitative composition measurements in real-time process control systems. The accuracy and repeatability of the measurements are amongst the most important factors when evaluating the total performance of these analysers, but the lower detection limit is often limited by noise in the measurement signal. There are two major alternatives for reducing noise in an optical analyser: prevention of noise contamination and post-processing of the signal by filtering. In the second alternative, the measurement signal can be post-processed by digital filtering techniques, for example, to enhance the desired signal component. Although digital signal processing (DSP) technology offers many advantages for on-line process measurements, the behaviour of the signal must be understood thoroughly before a successful application of this technology can be developed. A digital filtering technique called matched filter was used in an experimental set-up. The performance of this filter was compared to an analog filtering of a pulse shaped signal. Experimental data were collected and filtered with a novel digital spectrometer which consists of a modulated light source, a spectrograph, a linear array detector and the analog and digital signal processing electronics needed to control and filter the signal. In this case the matched filter gave a clear improvement of 2.2–4.6 dB in the signal-to-noise ratio (SNR) relative to an analog lock-in amplifier. Among the other advantages afforded by digital filters are that they are programmable, easy to design, test and implement on a PC and do not suffer from drift. Also digital filters are extremely stable with respect to both time and temperature and versatile in their ability to process signals in a variety of ways.

Data simulation is an important auxiliary method for baseband signal processing algorithm design of digital IF GNSS receiver. Especially when the high sensitivity and high dynamic receivers are developed, or multipath and cross correlation mitigation techniques are considered, exact and complete tests under all kinds of necessary scenes can be carried out with the IF signal data which is generated by software simulation method. With this method, the developing efficiency can be improved and the cost can be cut down. In this paper, precise model of the IF signal is given firstly through analyzing GNSS receivers RF processing flow. Then, considering the discrete characteristic of software processing, the IF signal simulation flow and block of the simulation software are designed. Finally, the specific design process is given through a design example. When the IF signal simulation software is used for testing baseband signal processing algorithms, GNSS receivers IF signal data under every necessary test scene can be generated just by parameter adjustment.

Abstract Alternative to the traditional analog methods, several digital data preprocessing, shaping and postprocessing techniques have been investigated for the improvement in energy resolution of energy dispersive x-rays detectors. Initial experimental results show that by preprocessing the data, better energy resolution can be obtained at shorter shaping times; thus, it will allow good energy and time resolution at high count rates.

Abstract Noise in an image is a random variation of brightness or color information in the original image. Noise is consistently presented in digital images during picture obtaining, coding, transmission, and processing steps. Image noise is most apparent in image regions with a low signal level. There are various reasons for the creation of noise in an image, such as electronic noise in amplifiers or detectors, disturbances and overheating of the sensor, disturbances in the medium of traveling for a digital image, etc. Noise is exceptionally hard to eliminate from the digital pictures without the earlier information of the noise model. There are various types of noise that can be available in a noise model. Filters are used to remove these types of noises in a digital image in image processing. In this research, we have implemented different filtering techniques that have been used to remove the noises in an image.

Recently robotic is a playing vital role in the life In our modern society, the usage of robotic arms are increasing and much of the work in the industry is now performed by robots. As robots begin to behave like humans in an intelligent manner, control system becomes a major concern. In this paper, design and analyses of the pick and place robot due to control, the forearm, wrist, desired turntable and desired bicep is introduced to construct a closed system with four degrees of freedom (4DOFs). The main performance specifications are the accuracy and stability of the input system for obtaining a good system performance. Implementation of the control system using PID parameters for stability, minimum steady state error, minimum overshoot and faster system response has been carried out. The design of two degree of freedom PID(2DoFPID) to control robotic arm along with first order low pass filter(LPF) to compensate the unwanted signal is improved. To be able to implement such a precise and effective system, feedback system has to be made to improve the overall performance specifications. The digital signal processing controller (Arduino Uno) is used as it is active, cheap , it has open source code and easy to use in the software and hardware applications.Experimental set up developed in addition to the Matlab/Simulink implementation of the complete system. The results and the communication signals test ensure smooth operation of the control system and the effectiveness of the proposed algorithm.