基于大数据分析的燃煤发电机组回热系统故障远程诊断

Remote Fault Diagnosis of Coal-fired Generator Regeneration System Based on Big Data Analysis

为提高燃煤发电机组运行经济性及安全性,对机组回热系统故障进行远程诊断。通过建立抽汽回热系统计算模型,对各级加热器性能进行分析,并远程诊断机组给水温度偏低问题。结果表明:回热系统抽汽参数与加热器性能匹配性不佳;多台加热器温升未达到设计值,以二号高压加热器尤为明显;设备解体检修验证了分析判断的准确性,问题处理后机组给水温度提升3.2℃,提高了机组运行经济性。可见以大数据为依托对机组故障进行远程诊断,可有效缓解机组给水温度偏低问题,具有重要的工程实践意义。

In order to improve the operating economy and safety of coal-fired power generating units,the remote diagnosis of regenerative system fault was carried out.By establishing the calculation model of steam extraction and heat return system,the performance of all levels of heaters was analyzed,and the problem of low feed water temperature of unit was diagnosed remotely.The results show that the extraction parameters of the regenerative system do not match well with the performance of the heater.The temperature rise of several heaters has not reached the design value,especially the No.2 high pressure heater.The accuracy of the analysis and judgment was verified by the equipment disassembly and maintenance.After the problem was solved,the water supply temperature of the unit was increased by 3.2℃,which improved the operation economy of the unit.It is concluded that it is of great engineering practical significance to carry out remote diagnosis of unit faults based on big data and effectively alleviate the problem of low feed water temperature of the unit.