水电机组故障诊断系统信号预处理

随着水电站对水电机组安全稳定运行要求的不断提高，相应的对故障诊断系统中故障诊断的准确性提出了更高的要求。而信号处理是故障诊断成功与否的关键。监测得到的故障信号不可避免的受到水电机组运行中的各种噪声的干扰与影响，从而得到的故障信号中含有随机噪声、白噪声等，为得到真实的故障特征信息有必要进行除噪处理。自相关和小波分析可以很好地去除噪声。本文对自相关和小波分析除噪作了详细论述，并用实例做了分析。

Signal pre-treatment of hydroelectric set fault diagnosis system

Along with increasingly enhanced requirement for safe operation of hydroelectric sets, the fault diagnosis reliability of hydropower station operation was strengthened accordingly. The signal processing is the key point in fault diagnosing. Real fault signal may be intermixed with random noise, white noise and so on, during the hydroelectric units running. Noise can be effectively removed by means of the methods of auto-correlation and wavelet analysis so that real fault information can be revealed. The authors discussed the auto-correlation and wavelet analysis in detail, and applied the method for two cases of hydroelectric set operation with satisfactory result.