Application of Neural Network on the Recognition of Sound Signals for Induction Machines

• Main Authors: CHEN, CHIEN YUAN, 陳建源
• Other Authors: TSAO, TA PENG
• Format: Others
• Language: zh-TW
• Published: 1996
• Online Access: http://ndltd.ncl.edu.tw/handle/15672769809060096430

碩士 === 國立中山大學 === 電機工程研究所 === 84 === In industry, induction motor is the most popular machine. It is used extensively to drive mechanical plant. It is un- avoidable to have the motor*s mechanical and electrical fault due to the continuously operating throughout the year. The faults of motors do not only cause the production line to shut down but also imperil personnel security seriously. So, the suitable motor maintenance will be a method to decrease the down stream time. However, the costs of main- tenance might take up to 90% of main equipment investment every year. Therefore, it would be a great help to use a practicable supervisory on expectative maintenance. If the fault of machine would be confirmed correctly and effective- ly,the maintenance efficiency would be increase by a wide range. In past ten years, manufacturers have already made great efforts to improve the basic design concept for establishing better and more reliable monitoring system on supervisal. Therefore we can let the fault of electrical machine be de- tected in initial stage, and we can also let the maintenance work to have fully and suitable opportunity to be done. Then the cost of shut down could be reduced significa- tively. But, these technology would cost more expensive due to the variable fault or the complex equipment. So the supervisal system can not be popular in the market.