實現無線感測網路在馬達故障診斷的應用

Implementation of Wireless Sensor Network on Motor Malfunction Diagnosis

江鴻錡(Hung-Chi Jiang)

指導教授 ： 蔡孟伸

國立臺北科技大學/機電學院/自動化科技研究所/碩士(2009年)

摘要

本論文應用無線感測網路的技術，實現在對馬達振動的檢測。由於無線感測網路有其架設容易的特點，本論文將感測節點架設於馬達上，透過感測節點上的加速度感測器擷取馬達的振動信號，擷取完畢後，感測節點會將振動訊號進行FFT運算。最後，再利用無線電的方式，將運算過後的資料傳回個人電腦，並將資料顯現在螢幕上。
本論文利用TinyOS所提供的Msp430Adc12MultiChannel介面實現三維振動的量測。在60Hz的待測訊號中，本研究設計各通道在一週期內取樣64個點，取樣完的三軸振動訊號在感測節點上進行定點FFT運算，取得各軸的1~11次諧波特徵後，再以無線電的方式傳回基地台(Basestation)，基地台再將資料由串列埠傳回電腦，顯示在螢幕上。本研究假設異常振動為機械性振動，不可能突然發生，突然結束，在任何取樣週期內均可以量測到振動訊號。因此以一秒為單位，進行訊號取樣、FFT計算與資料傳輸。為確保接收資料的正確性，本論文透過輸入已知訊號將求得諧波值和實際值進行比對，以驗證本系統的確可以實現在馬達故障振動檢測上。

關鍵字

無線感測網路 ； TinyOS ； 馬達振動 ； 故障診斷 ； 多通道取樣

並列摘要

This thesis applies wireless sensor network technology for the motor vibration inspection. Due to the fact that wireless sensor network is easy to be set up, a wireless sensor node with a three-axis accelerometer is installed on a motor. The vibration signal is retrieved from the build-in analog to digital converter. Fixed point Fast Fourier Transform (FFT) is performed on the acquired signals on the sensor node. The sensor node transmits the results of FFT calculation to a base-station through RF link. The frequency domain data of vibration is received by a personal computer and displayed on the screen.
The 3-axis vibration signals are retrieved using Msp430Adc12MultiChannel interface provided in TinyOS. 64 points are sampled per 60Hz cycle for each axis. It is assumed that the vibration is caused by mechanical malfunction. Thus, the vibration should not be started and stopped suddenly. The signal sampling, FFT calculation and data transmission is performed every second. In order to verify the correctness of the received information, a known signal is used for comparison purposes. The results show that the developed system is capable of retrieving frequency characteristics of motor vibration to the personal computer without any problem.

並列關鍵字

wireless sensor network ； TinyOS ； vibration ； Diagnosis

參考文獻

[17] 彭善謙，綜合振動信號於馬達故障診斷，碩士論文，中原大學機械工程學系，桃園，2004。

[18] 趙安民，馬達故障診斷之模糊類神經網路，碩士論文，中原大學機械工程學系，桃園，2004。

[1] NCKU CSIE. “Wireless Sensor Networks”, Internet: http://imus.csie.ncku.edu.tw/imus/sensor/index.html, May. 31, 2007.

[5] S. Nandi and H. A. Toliyat, “Condition Monitoring and Fault Diagnosis of Electrical Machine – A Review,” IEEE Industry Applications Conference, vol. 1, 1999, pp. 197-204.

[6] G. Goddu, B. Li, M. Y. Chow and J. C. Hung, “Motor Bearing Fault Diagnosis by a Fundamental Frequency Amplitude Based Fuzzy Decision System,” Proceedings of the 24th Annual conference of the IEEE, vol. 4, 1998, pp. 1961-1965.