火力发电厂发电设备轴承故障自适应监测系统设计

Design of Self-adaptive Monitoring System for Bearing Faults of Power Generation Equipment in Thermal Power Plant

本文设计了火力发电厂发电设备轴承故障自适应监测系统。基于发电设备的组成结构,分析轴承的振动原理;根据经验模态分解与瞬时频率转换实现故障检测时间序列的归一化处理,确定故障种类;依据轴承结构参数与相应算法获取不同轴承组件的特征频率值;采用过阻尼布朗粒子分析双稳态系统特性,依据克莱默斯跃迁概率分析产生的随机共振,进而实现轴承故障监测;利用单片机实现数字电位器的驱动控制,根据数字电位器编码调整双稳态随机共振电路的电阻分压比,完成自适应监测系统架构设计。实验表明,本文系统不仅能够有效监测出轴承的故障类别,判别准确度也较高。

Based on the structure of power generation equipment, the vibration principle of bearing is analyzed in this paper. According to empirical mode decomposition and instantaneous frequency conversion, the time series of fault detection is normalized and the fault types are determined. According to the bearing structure parameters and the corresponding algorithm,the characteristic frequency values of different bearing components are obtained. The characteristics of the bistable system are analyzed by the over-damped Brownian particles, and the stochastic resonance generated by the kramers transition probability analysis is used to realize the bearing fault monitoring. The drive control of digital potentiometer is realized by using single chip microcomputer, and the resistance partial voltage ratio of bistable stochastic resonance circuit is adjusted according to the code of digital potentiometer to complete the architecture design of adaptive monitoring system. Experiments show that the system can not only detect the fault types of bearings effectively, but also has a high accuracy.