复杂矿冶设备故障诊断数据质量工程学

Data Quality Engineering of Fault Diagnosis of Complex Mining and Metallurgical Equipment

文章详细介绍了矿冶设备数据的产生过程,提出了一种复杂矿冶设备故障诊断的数据质量工程学方法,其目的是通过提高数据质量来保障故障诊断的准确性,即从数据采集系统进行抗干扰能力的优化设计(线外)来降低数据变异效应和在后期使用维护(线内)进行变异源的识别、减少或预防变异发生的措施,使其在恶劣矿冶环境下仍能采集高质量的设备状态数据,从而保障设备故障诊断数据的可靠性。实例验证表明该方法可以为数据质量保障提供一种系统解决途径,减少故障诊断的虚警和漏报。

The paper introduced data production process of mining and metallurgical equipment in details, put forward a methodology of data quality engineering of fault diagnosis of complex mining and metallurgical equipment which can ensure veracity of fault diagnosis by improving data quality, namely the measure can reduce data variation through optimal design of anti-interference of data collection system （outline）, and recognise data variation source and decrease and prevent from variation in use and maintenance （inline）, in order to collect high-quality data of equipment state under bad mining and metallurgical environment and insure data reliability of fault diagnosis of equipment. Verification of practical example showed that the method can provide solution of data quality assuring, and can decrease false alarm or fail report.