小波变换在电机性能测试中的应用研究
摘要
本论文主要关注小波分析在电机性能自动测试系统中的应用，针对传统电机测试系统以及信号处理技术在电机测试领域中应用的不足，以直流电机为例，提出了将时频分析、小波包变换以及基于小波脊的瞬时频率提取方法应用到电机测试领域的新思路；较系统地总结了时频分析和小波变换的基本理论，深入探讨了基于小波脊线和小波曲线的瞬时频率提取，并成功开发了基于正交小波包分析和基于小波脊线的瞬时频率提取的无转矩转速传感器的直流电机快速测试系统。
在分析了现有的各种电机性能自动测试系统的基础上，本论文讨论了基于PC机和数字化测试仪的电机性能自动测试系统，提出了基于PC机和数据采集卡的电机性能自动测试系统。论文中介绍了一种无转矩转速传感器直流电机快速测试系统，在硬件上，本系统由WB电流传感器与PCI-1202数据采集卡共同完成电枢电流数据采集功能，论文详细讨论了WB电流传感器，外围驱动电路，PCI-1202数据采集卡及其与PC机的接口及其编程等等与软硬件有关的问题。该系统可以作为基于PC机与数据采集卡的自动测试系统的一个很好的例子，它充分利用了PC机丰富的计算资源与快速的运算速度，在间接法测试中具有独到的优势。
论文较系统全面地介绍了小波分析理论，提出了利用正交小波包变换进行时频分析，直接从小波包分解系数中提取电机电枢电流中高频分量变化规律的方法，从而实现了一种无转矩转速传感器电机的快速测试方法。系统地研究了基于多分辨分析的离散正交小波变换和小波包变换的快速算法及其编程实现。并深入探讨了小波分析在电机测试领域的其他应用，包括小波去噪和小波滤波等。
论文从时频分析的基本理论出发，在渐进信号小波分析的基础上，研究了渐进信号小波变换的渐进估计方法，提出了利用小波脊线来提取信号频率随时间连续变化规律(即瞬时频率)的方法。并通过提取直流电机起动过程电流信号的瞬时频率有效地研制了一套无转矩转速传感器直流电机的快速测试系统。仿真和试验结果表明，本系统不仅有较快的测试速度，而且具有相当的精度，再加上其无需转矩转速传感器的优点，特别适用于一些不适合安装转矩转速等非电量传感器和需要进行快速测试的场合。类似的方法和原理经过适当的改进，同样也可以适用于交流电机测试系统。
This paper focuses on the applications of wavelet analysis theory in the domain of motor test. Taking DC motor test as an example, a creative idea of applications of some advanced signal processing tools, such as time-frequency analysis, wavelet, and instantaneous frequency (IF) evaluation, in motor testing field is presented. The paper systematically summarizes basic theories of time-frequency analysis and wavelet transform based on which an in-depth research of effective IF evaluation based on wavelet ridge and wavelet curve is carried out. In the end a fast T-n characteristic testing system with neither torque nor speed sensor is successfully developed.
After carefully comparing various existing motor performance testing systems and PCs and digital instruments based automatic testing systems, an effective testing system with PC and data acquisition card is proposed. The fast T-n characteristic testing system with neither torque nor speed sensor implemented in the paper is an excellent example of this new type. In the hardware level, the system acquires motor armature current by WB current sensor and PCI-1202 card. Hence WB current sensor, peripheral driving circuits, PC-1202 card and its interfaces are respectively discussed in detail in the paper. As a perfect example of the new pattern testing system previously mentioned, the system has distinct advantages because it fully exploits abundant resources and rapid speed of PCs.
This paper synoptically and comprehensively introduces basic theory of wavelet analysis. Due to the distinct superiority of wavelet transform (WT) and wavelet packet transform (WPT) in time-frequency analysis of non-stationary signals, instantaneous frequency law can be obtained directly from amplitude of WPT coefficients. Thus an indirect T-n characteristic testing method can be implemented with satisfying precision. The paper also studies fast arithmetic and programming of discrete time quadrature WT and WPT and takes a deep look into their additional applications in motor testing, including denoising, filtering and so on.
Starting from basic theory of time-frequency analysis and wavelet analysis of asymptotic signals, this paper investigates several IF law extraction methods and presents an especially effective one using wavelet ridge. This method can rapidly extract speed law from starting current of DC motor with fairly good precision, and thus the torque-speed characteristic can be acquired. Simulations and experiment results show that this system is provided with high speed and satisfactory precision besides getting rid of both torque and speed sensors. Therefore it is particularly fit for those occasions for which torque and speed sensors are difficult to amount. Indeed similar method can be generalized to AC motor performance testing after properly adaptation.
在分析了现有的各种电机性能自动测试系统的基础上，本论文讨论了基于PC机和数字化测试仪的电机性能自动测试系统，提出了基于PC机和数据采集卡的电机性能自动测试系统。论文中介绍了一种无转矩转速传感器直流电机快速测试系统，在硬件上，本系统由WB电流传感器与PCI-1202数据采集卡共同完成电枢电流数据采集功能，论文详细讨论了WB电流传感器，外围驱动电路，PCI-1202数据采集卡及其与PC机的接口及其编程等等与软硬件有关的问题。该系统可以作为基于PC机与数据采集卡的自动测试系统的一个很好的例子，它充分利用了PC机丰富的计算资源与快速的运算速度，在间接法测试中具有独到的优势。
论文较系统全面地介绍了小波分析理论，提出了利用正交小波包变换进行时频分析，直接从小波包分解系数中提取电机电枢电流中高频分量变化规律的方法，从而实现了一种无转矩转速传感器电机的快速测试方法。系统地研究了基于多分辨分析的离散正交小波变换和小波包变换的快速算法及其编程实现。并深入探讨了小波分析在电机测试领域的其他应用，包括小波去噪和小波滤波等。
论文从时频分析的基本理论出发，在渐进信号小波分析的基础上，研究了渐进信号小波变换的渐进估计方法，提出了利用小波脊线来提取信号频率随时间连续变化规律(即瞬时频率)的方法。并通过提取直流电机起动过程电流信号的瞬时频率有效地研制了一套无转矩转速传感器直流电机的快速测试系统。仿真和试验结果表明，本系统不仅有较快的测试速度，而且具有相当的精度，再加上其无需转矩转速传感器的优点，特别适用于一些不适合安装转矩转速等非电量传感器和需要进行快速测试的场合。类似的方法和原理经过适当的改进，同样也可以适用于交流电机测试系统。
This paper focuses on the applications of wavelet analysis theory in the domain of motor test. Taking DC motor test as an example, a creative idea of applications of some advanced signal processing tools, such as time-frequency analysis, wavelet, and instantaneous frequency (IF) evaluation, in motor testing field is presented. The paper systematically summarizes basic theories of time-frequency analysis and wavelet transform based on which an in-depth research of effective IF evaluation based on wavelet ridge and wavelet curve is carried out. In the end a fast T-n characteristic testing system with neither torque nor speed sensor is successfully developed.
After carefully comparing various existing motor performance testing systems and PCs and digital instruments based automatic testing systems, an effective testing system with PC and data acquisition card is proposed. The fast T-n characteristic testing system with neither torque nor speed sensor implemented in the paper is an excellent example of this new type. In the hardware level, the system acquires motor armature current by WB current sensor and PCI-1202 card. Hence WB current sensor, peripheral driving circuits, PC-1202 card and its interfaces are respectively discussed in detail in the paper. As a perfect example of the new pattern testing system previously mentioned, the system has distinct advantages because it fully exploits abundant resources and rapid speed of PCs.
This paper synoptically and comprehensively introduces basic theory of wavelet analysis. Due to the distinct superiority of wavelet transform (WT) and wavelet packet transform (WPT) in time-frequency analysis of non-stationary signals, instantaneous frequency law can be obtained directly from amplitude of WPT coefficients. Thus an indirect T-n characteristic testing method can be implemented with satisfying precision. The paper also studies fast arithmetic and programming of discrete time quadrature WT and WPT and takes a deep look into their additional applications in motor testing, including denoising, filtering and so on.
Starting from basic theory of time-frequency analysis and wavelet analysis of asymptotic signals, this paper investigates several IF law extraction methods and presents an especially effective one using wavelet ridge. This method can rapidly extract speed law from starting current of DC motor with fairly good precision, and thus the torque-speed characteristic can be acquired. Simulations and experiment results show that this system is provided with high speed and satisfactory precision besides getting rid of both torque and speed sensors. Therefore it is particularly fit for those occasions for which torque and speed sensors are difficult to amount. Indeed similar method can be generalized to AC motor performance testing after properly adaptation.
引文
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[2] 李颂伦，电气测试技术，西北工业大学出版社，1992
[3] 蒋焕文，电子测量，第二版，高等教育出版社，1988
[4] 王毓东，电机学(上，下)，浙江大学出版社，1990
[5] 汤蕴璆，史乃，电机学，机械工业出版社，1999
[6] 电机工程手册(4)，机械工业出版社，1982
[7] 徐伯雄，窦玉琴，电机量测，清华大学出版社，1990
[8] 李永敏，数字化测试技术，航空工业出版社，1987
[9] 陈雅文，直流微电机测速新方法，微电机1999年第32卷第1期
[10] 黄建华，小波分析在电机性能自动测试系统中的应用，浙江大学硕士学位论文，1998
[11] D.Gabor, Theory of Communication, J. IEE(London), vol. 93, pp.429-457,1946
[12] E.P. Wigner, On the quantum correction for thermodynamic equilibrium, Phys. Rev., vol. 40, pp.749-759, 1932
[13] L. Cohen, Generalized phase-space distribution functions, J. Math. Phys., vol. 7, pp.781-786, 1966
[14] 秦前清，杨宗凯，实用小波分析，西安交通大学出版社，1998
[15] L.Cohen，白居宪译，时—频分析：理论与应用，西安交通大学出版社，1998
[16] A.V.奥本海姆[美]著，刘数棠译，信号与系统，西安交通大学出版社，1985
[17] 张贤达．现代信号处理．北京：清华大学出版社，1995
[18] Daubechies I., The wavelet transform, time-frequency localization and signal analysis, [J]. IEEE Trans. IT, vol. 36(5), pp961-1005, 1990
[19] Mallat S. G., A theory for multiresolution signal decomposition: the wavelet representation, [J].IEEE Trans. PAMI, vol. 11(7), pp. 674-693, 1989
[20] Nielsen N. H., Wickerhauser M. V., Wavlets and time-frequency analysis, [J]. Proceedings of the IEEE, vol. 84. pp. 523-540, 1996
[21] J.Betrand, P. Betrand, Affine time-frequency distributions,
Time-frequency signal Analysis, pp. 118-140, 1992
[22] B. Boashash, Time-frequency signal analysis, Ed. S. Haykin, Prentice Hall, 1990
[23] B. Boashash, Estimating and interpreting the instantaneous frequency of a signal-Part Ⅰ: fundamentals, Proceeding of the IEEE, vol. 80, pp. 520-538, 1992
[24] L. Cohen, A critical review of the fundamental ideas of joint time-frequency distributions, IEEE Proc. Int. Symp. on Circuits and Systems, vol. 1, pp. 28-33, 1986
[25] L. Cohen, Time-frequency Distributions- A review, Proc. Of the IEEE, vol. 77, pp. 941-981, 1989
[26] L. Cohen and C. Lee, Instantaneous bandwidth for signals and spectrogram, Proc. IEEE ICASSP90, pp. 2451-2454, 1990.
[27] L. Cohen, A Primer on Time Frequency Distributions, Time-frequency Signal Analysis, edited by B. Boashash, pp. 3-42, Longman Cheshire, 1992
[28] L. Cohen, The scale representation, IEEE Trans. On Signal Processing, vol. 41, pp. 3275-3293, 1993
[29] L. Cohen and C. Lee, Instantaneous Frequency, Its Standard Deviation and Multicomponent Signals, Proc. SPIE, vol. 975, pp. 186-208, 1998
[30] I. Daubechies, The Wavelets Transform, Time-frequency Localization and Signal Analysis, IEEE Trans. on Information Theory, 36(5), 961-1005, 1990
[31] L. Cohen, C. Lee, Instantaneous Frequency and Time-frequency Distributions, IEEE Proc. ISCAS, 1231-1236, 1989
[32] L. Griffiths, Rapid measurement of digital instantaneous frequency, IEEEE Trans. Acoust., Speech, Signal Processing, vol. 23, pp. 207-222, 1975
[33] [美]A.V.奥本海姆著，刘数棠译，信号与系统，西安交通大学出版社，1985
[34] 程佩青，数字信号处理教程，清华大学出版社，1995
[35] Alan V. Oppenheim, Alan S. Willsky, Signals & Systems, PRENTICE HALL, 1997
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