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A Labview Based Electromotor Data Acquisition and

By Annie Greene,2014-09-18 15:03
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A Labview Based Electromotor Data Acquisition and

    A Labview Based Electromotor Data Acquisition and Analysis

    System

    [a][b][a][a][a]

    Wu Bing, Yang Tiemei, Zhang HongXiong Shibo,Wang Ranfeng

    [a] Research Institute of Methanol-electronic Engineering, Tai Yuan University of Technology,

    Tai Yuan, Shan Xi, China,

    Phone (+86)0351-6014551, E-mail: wb0616@sina.com

    [b] Tai Yuan University of science & technology, Tai Yuan, Shan Xi, China

     Abstract-LabVIEW (Laboratory Virtual Instrument Engineering Workbench) is the graphical development environment for creating flexible and scalable test, measurement, and control applications rapidly and at minimal cost. LabVIEW is gaining its popularity as a graphical programming language especially for data acquisition and measurement. This is due to the vast array of data acquisition cards and measurement systems, which can be supported by the LabVIEW as well as the relatively easy by which advanced software can be programmed.

    In this paper, a LabVIEW based monitoring and analysis system developed for electromotor monitoring and predictive maintenance is presented. The data set were created for different faults from the synthetically generated fault data and the normal base line data acquired from the motor system. The analysis and monitoring of the signals are of the concern for fault detection and implementing predictive maintenance. The data were processed and extracted features were used to report motors health and predict period of maintenance. Implementation details are presented including power quality disturbances such as voltage sags, swells, outages, harmonics and unbalance, vibration signals process such as FFT and Window, temperature display. The design is to be implemented on an on-line basis.

    ?. INTRODUCTION

    The monitoring of the motor performance and detection of the motor fault are very important as almost organizations can afford the expense of shut

     down maintenance. It is important to minimize the occurrences of extensive maintenance outages [1]. However, the prediction and fault trend evaluation are based on the technologies of synthetic data acquisition and analysis. In this paper, with analyzed motor fault mode, an on-line electromotor data acquisition and analysis system is implemented by LabVIEW. It includes integrated data acquisition, time and frequency analysis, real time alarming and data distributed in network.

    ?. MOTORS FAULTS

    Induction motors play an important role in the safe and efficient operation of industrial plants. Many electric machine components are especially susceptible to failures. For example, the stator windings are subject to insulation breakdown caused by mechanical vibration, heat, age, damage during installation, and contamination by oil [2]. The motors faults can

    be classified to mechanical part and electrical part.

    A. Mechanical faults

    1) Motors vibration or noise rise. Many faults can cause the results. It includes nonstandard installation, the base not holds

    up, rotor unbalance or shaft bends.

    2) Bearings faults cause temperature, vibration and noise rising. The vibration signals of bearings can be classified 15

    different signals, as given below[3]

    a. Normal

    b. Tight Fit

     c. Misalign Outer Ring

    d. Fatigue Wear Outer Ring

    e. Spalling Outer Ring

    f. Fatigue Wear Inner Ring

    g. Spalling Inner Ring

    h. Cage/Roll Elements Wear

    i. Ball Spalling

    j. Corrosion

    k. Loose Fit/Slippage

    l. Lubrication

    m. Contamination

    n. False Brinell

    o. True Brinell

    B. Electrical faults Electrical faults include voltage sags, swells, outages, unbalance, and capacitor switching transients. Productivity loss due to deep voltage sags and brief power interruptions has been called the most important concern

    affecting most industrial and commercial customers [4].

    Three-phase electric power systems generally provide voltage supply at the generating station that is well balanced in both magnitude and phase. At the distribution level, the unbalanced single phase and nonlinear loads being fed cause unequal voltage drops in the transformer and line impedances, resulting in unbalanced supply voltage at the point of utilization. Here, the degree of three-phase power supply imbalance is defined as

100max(%)Im×?=rmsmeanrmsmeanrmsxxVVVbalance (1)

    ,where is the mean of the rms values of the three-phase voltages, and is the rms value of each of the three-phase voltage.

    The subscript x denotes the three motor phases, a, b, c. Even with a well-balanced motor stator, the three-phase motor

    current becomes unbalanced giving rise to negative sequence currents. The majority of the methods developed to date for detecting motor electrical faults, such as those caused by stator insulation failures, are based on monitoring the negative sequence of the the stator current. Stator insulation problems result in unbalanced impedance and stator currents. As such, either if the supply becomes unbalanced or the stator develops insulation problems, a negative sequence current is detected. [5] rmsmeanVrmsxV

    ?. LABVIEW

    LabVIEW is a program development application, much like various C++ or BASIC development system. However, it is different from those applications in one important respect. LabVIEW is a graphical programming language that uses icons instead of lines of text to create applications. In contrast to text-based programming languages, where instructions determine program execution, LabVIEW uses dataflow programming, where the flow of data determines execution. LabVIEW can acquire data and control devices via IEEE-488 (GPIB), RS-232/422 and modular (VXI or CAMAC) instruments as well as plug-in I/O boards [6]. LabVIEW programs are called virtual instruments (VIs) because their appearance and operation imitate actual instrument.

    . ?DESINGED the SYSTEM

    The electromotor data acquisition and analysis system is developed for motor monitoring and fault alarming. It provides a user-friendly data acquisition interface to display the on-line vibration, currents and voltages signal. The real-time data can

    be stored to hard disk and compressed. Using the DataSocket, provided by the LabVIEW, it is implemented that the data are exchanged in network. Important components of the system and the network are as shown in Fig 1 and Fig 2.

    Figure 1 PC based DAQ system

Software

    A. Designed Strategy

    The data acquisition and monitoring system is used high-performance, reliable high-speed multi-channel card to synchronously acquire vibration and three-phase currents and voltages data as well as temperature data.

    The system is designed a series of threshold to alarm when the temperature up to the threshold. Through calculating and comparing the values of RMS (Root Mean Square) of the three-phase currents and voltages data and comparing with predicted threshold, it can make an alarming to the different current or voltage defects, such as voltage or current sags, swells, outages, unbalance. The vibration data are used to on-line detect and analyze the status of electromotor with the FFT and related functions provided by LabVIEW.

    Normally, it is a long time to detect the fault or performance reduced. The system is designed can synchronously record the data of voltages, currents, temperature and vibration. Using the DataSocket (based on TCP/IP) developed by the LabVIEW, local data can be distributed to the control center or other users.

    B. DAQ Components

    The equipment used has 10 temperature sensors and 4 acceleration sensor. It can acquire the voltage and current signals through measurement of a piece of lead. This system gets 12 three-phase voltage and current both sides of the converter. A 16 bit, 16 channels DAQ PCI card is used to acquire temperature signal. And a 24 bit, 16channels card is used to synchronously acquire 12 current and voltage signals as well as 4 vibration signals.

    C. Software All the software has been programmed using LabVIEW. Figure 3 shows a part module of the developed tool. The data acquisition and on-line analysis are implemented in the block diagram. Figure 4 is shown the interface of fault alarming. The front panel also includes currents, voltages and vibrations waveform of amplitude and power spectrum as well as temperatures waveform. The data are distributed to control centers computers or others using the DataSocket

    provided by LabVIEW. Then they can be analyzed off-line as well as stored in the disk. D. Application

    This electromotor data acquisition and analysis system has been installed and monitoring in a coal preparation plant.

    .? CONCLUSION

    The proposed method is based on integrated testing and analyzed technology and an easy-to use graphical environment, based on the LabVIEW program, for processing, displaying, storing and distributing the collected data. The system operator can easily process the measured parameters using any LabVIEW built-in function available. The proposed architecture has the advantages of rapid development the system operation.

    ACKNOWLEDGMENT

    The research is financially supported by the Key Program of National Natural Science Foundation of China (No.50335030), and Shan Xi S&T research develop project of colleges and universities (No. 20041313).

    REFERENCES

[1] Sujatha Srinivasan, M.Bodruzzaman, LABVIEW program design for on-line data acquisition and

    predictive maintenance. 0-7803-4547-9/98, IEEE. [2] Tavner, P. J., and Penman, J., 1987, Condition

    Monitoring of Electrical Machines, Research Studies Press, Letchworth, England.

    [3] Senthil Kumar Muthuswamy, Predictive and Preventive Maintenance of Bearings, September 1997

    [4] William E. Brumsickle, Robert S. Schneider, Glen A. Luckjiff, Deepak M. Divan, and Mark F. McGranaghan, Dynamic Sag Correctors: Cost-Effective Industrial Power Line Conditioning, IEEE

    Transactions on Industry Applications, vol. 37, no.1, pp. 212-217, January/February 2001.

    [5] Kyusung Kim, Alexander G. Parlos, Department of Mechanical Engineering, Texas A&M University, College Station. Reducing the Impact of False Alarms in Induction Motor Fault Diagnosis

    [6] LabVIEW7.0 user manual, 2003 edition.

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