A new technology for motor rotor bar fault detection under no load conditions

电动机通常用于各种家庭和工业应用。mahon Electric Co Ltd （in Thunder Bay, Ontario）提出的问题是如何在低负载或无负载的情况下检测转子断条故障，这也是业界一直存在的问题，也是本研究领域的一项具有挑战性的任务。较低的负载对应较小的转差，这使得转子故障的检测更加困难。为了应对这一挑战，该项目的目标是与马洪电气合作，开发一种新的滑移谱（SS）技术，用于低负载或无负载情况下转子断条故障检测。该方法将电流信号和振动信号同时用于故障检测。具体而言，1)将开发一种智能传感器，用于更精确的转子转速识别和转差估计；2)提出自适应去噪滤波技术，提高故障转子转子到电流传感器的复杂信号路径的信噪比；3)提出了一种新的带脉冲的平均频谱特征解调方法，用于空载条件下转子棒故障检测。该项目将与马洪电气密切合作。相关的研究和测试将在公司进行。公司员工丰富的实践经验将有助于这个项目取得丰硕成果。所提出的SS技术也可用于一般在线运动健康状态监测，在早期识别运动缺陷，防止机械性能下降，故障，甚至破坏性故障。SS技术可以通过提高生产质量和系统可靠性以及降低成本，使众多加拿大公司在相关市场上获得竞争优势。

Electric motors are commonly used in various domestic and industrial applications. The problem raised byMahon Electric Co Ltd. (in Thunder Bay, Ontario) is how to detect a broken rotor bar fault under low or noload conditions, which is also an ongoing problem in the industry, and a challenging task in this research field.A lower load corresponds to a smaller slip, which makes it more difficult to detect rotor fault. To tackle thischallenge, the objective of this project, in collaboration with Mahon Electric, is to develop a new slip spectral(SS) technique for broken rotor bar fault detection, under low or no loading. The proposed SS techniqueapplies both electric current and vibration signals for fault detection. Specifically, 1) a smart sensor will bedeveloped for more accurate rotor speed recognition and slip estimation; 2) Adaptive denoising filteringtechnique will be proposed to improve signal-to-noise ratio of the complex signal path from the faulty rotor barto the current sensors; 3) A new approach will be suggested to demodulate average spectral characteristics overthe bands with impulses for rotor bar fault detection under no load conditions. This project will be undertakenwith close collaboration with Mahon Electric. The related research and testing will be performed in thecompany. The rich hands on experience the company's staff will be very helpful to make productive results ofthis project. The proposed SS technology can also be used for general online motor health conditionmonitoring to recognize the motor defect at its earliest stage so as to prevent machinery performancedegradation, malfunction, or even devastating failures. The SS technology can benefit a wide array of Canadiancompanies to gain a competitive advantage in the related market by improving production quality and systemreliability, and reducing costs.