Design of poka-yoke system based on fuzzy neural network for rotary-machinery monitoring

Conference on Innovation in Technology and Engineering Science

工业技术（总论）

Muharam, M.^1 ; Latif, M.^1

Department of Electrical Engineering, University of Andalas, Padang, Indonesia^1

关键词: Frequency domains;    Fuzzy membership function;    Machine failure;    Machinery monitoring;    Production process;    Statistical parameters;    Time-domain signal;    Vibration signal;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/602/1/012003/pdf
DOI  :  10.1088/1757-899X/602/1/012003

学科分类：工业工程学

来源: IOP

【 摘 要 】

Early detection of machine failure will improve the performance of the production process. The Poka-Yoke device was developed to monitor the machine. The vibration signal is captured by sensors and inputted in Poka-yoke device for processing. Poka-Yoke device has two components, Fuzzy-Neural Network identification and decision maker. The first component, the time-domain signal is transformed into the frequency domain, magnitude and frequency are treated as Fuzzy membership functions by using the statistical parameters as mechanical harmonic distortion and then are trained by Neural Network. The second component, the decision is in the form of machine condition statements such as normal, alarm, and shutdown. Simulation's results show that the method can be applied to identify the machine condition in term of bearing faults. Moreover, the Poka-yoke system that developed can be used to monitor machine condition automatically.