风力电网故障下的机械载荷优化测试分析

Test Analysis of Mechanical Load in Wind Power Network Fault

风力发电网络受到外界的不确定因素干扰较大,容易产生故障。分析风力电网故障下的电机机械载荷,实现对风力电网的故障诊断。传统方法采用风力电网故障信号采集和特征提取方法,在非线性耦合干扰下对电机机械载荷的测试效果不好。提出一种基于机械载荷线性反馈和谐波抑制的风力电网故障诊断方法,实现对故障下机械载荷优化测试。构建风力电网故障下的机械载荷数据采集和信号生成模型,采用双曲调频信号的自连续小波变换来分析机械载荷的电流信号、差压信号、绝压信号和振动信号,采用机械载荷线性反馈和谐波抑制方法,实现对风力电网故障下机械载荷数据的干扰滤波和特征优化测试,输入到风力电网故障诊断专家系统中,比对故障数据中的可用知识,实现对风力电网故障的准确诊断。仿真结果表明,采用该方法能实现对载荷数据的准确采集和测试,提高风力电网的故障准确诊断性能。

The wind power network is often disturbed by external uncertain factors and interference and therefore is prone to faults. Analyzing the motor mechanics helps to realize the fault diagnosis of faults in the wind power system. The traditional method uses the fault signal acquisition and feature extraction for the wind power network, but the testing performance of the motor mechanical load under the nonlinear coupling is not good. This paper proposed a wind power network fault diagnosis method based on the mechanical load linear feedback and harmonic suppression to realize the mechanical load optimization test under faults. The mechanical load data acquisition and signal generation model is constructed under the wind power network failure and the self-continuous wavelet transform of the hyperbolic frequency modulated signal is used to analyze the current signal and differential pressure signal and absolute pressure signal and vibration signal of the mechanical load. The mechanical load linear feed-back and harmonic suppression method is used for the interference filtering and feature optimization test of the mechanical loading data under the wind power system fault,and the data is input into the wind power system fault diagnosis expert system for fault data comparison of available knowledge,and to achieve the accurate diagnosis of the wind power system fault. The simulation results show that the method can achieve accurate collection and test of the load data,and improve the accuracy of fault diagnosis for the wind power network.