Mechanical fault diagnosis method based on improved PSO-SOM-BPNN

• Main Authors: MA JIATENG, FAN YILIN, YAN YANG, MA NINGGE, FAN HONGWEI, CAO XIANGANG, ZHANG XUHUI
• Format: Patent
• Language: Chinese; English
• Published: 24.09.2021
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; ELECTRIC DIGITAL DATA PROCESSING; HANDLING RECORD CARRIERS; MEASURING; PHYSICS; PRESENTATION OF DATA; RECOGNITION OF DATA; RECORD CARRIERS; TESTING; TESTING STATIC OR DYNAMIC BALANCE OF MACHINES ORSTRUCTURES; TESTING STRUCTURES OR APPARATUS NOT OTHERWISE PROVIDED FOR

The invention discloses a mechanical fault diagnosis method based on improved PSO-SOM-BPNN. According to the scheme, a signal processing technology and two types of neural networks are connected in series and combined to carry out rapid and accurate identification on the state of a rotating machine. The method comprises the following steps: for a diagnosed rotating machine, after a vibration signal is collected, de-noising is immediately carried out on the vibration signal through wavelet analysis, and energy characteristics are extracted through wavelet packet decomposition; during the period, the primary function and the decomposition layer number of the two are optimized; and then the extracted energy features are used as SOM-BPNN input. According to the invention, an inertia weight and a learning factor of a PSO algorithm are adjusted in a self-adaptive mode, a speed item is abandoned to optimize SOM-BPNN parameters, and the self-adaptive speed-item-free particle swarm optimization-based SOM-BPNN mechanic