基于改進(jìn)型HILBERT-HUANG變換的旋轉(zhuǎn)機(jī)械故障診斷系統(tǒng)設(shè)計(jì)
[Abstract]:Rotating machinery is a key equipment in medical, electric, aviation and other fields. It is of great significance to ensure their safe operation. As the mechanical vibration parameters can directly reflect the operating state of the equipment, the vibration signal analysis is often used for maintenance and monitoring of the rotating equipment. In this paper, a fault diagnosis system for rotating machinery based on improved Hilbert-Huang transform is developed in this paper. The system not only has many characteristics of acquisition channel, fast sampling speed and high precision, but also can automatically analyze vibration signal and diagnose equipment obstacle. The system is mainly composed of external sensors and integrated vibration. The dynamic signal collector and the upper computer software are composed of three parts. For the vibration signal collector, it mainly uses ARM and FPGA as the core structure to realize the synchronous acquisition function of the 8 road vibration signals. All channels are designed with sensor interface switching circuit, signal conditioning circuit and analog to number conversion (ADC) circuit. Interface switching circuit can be based on The actual needs are connected to different types of sensors. The sampling rate of 8 channels is synchronized with 150KHz.. The collector also designs a serial port and Ethernet card interface to communicate with the host computer. The upper computer software is designed under the LabVIEW development environment, and the acquisition parameter setting, data preservation and signal need to be realized. The analysis and processing of three functions. The software is used to configure the collector through the network. The data collected can be saved and replayed by the mass storage resources of the computer. In the analysis and processing of the signal, the principle of the Hilbert-Huang transform algorithm is studied in this paper, and the related matching extension method and the adaptive set are proposed. The empirical mode decomposition algorithm not only reduces the decomposition error caused by the vibration signal in the empirical mode decomposition, but also solves the parameter selection problem in the set of empirical mode decomposition, effectively improves the analysis results of the Hilbert-Huang transform algorithm in the fault diagnosis of rotating machinery equipment. Finally, the fault is built by building a vibration experimental platform. The diagnosis system has been tested. The test results show that the system can better extract the fault characteristics of rotating machinery.
【學(xué)位授予單位】:天津工業(yè)大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2017
【分類號(hào)】:TH17
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