基于混沌差分进化FCM的刮板输送机故障诊断

Fault Diagnosis of Scraper Conveyor Based on Chaotic Differential Evolution FCM

针对煤矿刮板输送机减速器故障耦合性强、传统诊断方法准确率较低的问题,提出了一种基于混沌差分进化模糊c均值(FCM)刮板输送机故障诊断方法。利用差分进化算法的全局优化能力和均匀遍历的优势,弥补了FCM对初始中心敏感、易收敛至局部极值点的不足,可以解决故障诊断难度大、准确率低的问题。以减速器故障为例,仿真实验结果表明,该方法能够高效完成故障诊断,准确率高,为进一步提高刮板输送机故障诊断的智能化水平提供了支持。

Aiming at the problems that the speed reducer of coal mine scraper conveyor has strong coupling and the accuracy of traditional diagnosis method is low,a fault diagnosis method of scraper conveyor based on chaos differential evolution fuzzy c-means(FCM)was proposed.By using the advantages of global optimization ability and uniform traversal of differential evolution algorithm,made up the shortcoming that FCM is sensitive to the initial center and easy to converge to the local extreme point,which can solve the problems that fault diagnosis is difficult and judge accuracy is low.Taking the reducer fault as an example,the simulation test results show that the method can complete fault diagnosis efficiently with high accuracy,which provides support for further improving the intelligent level of scraper conveyor fault diagnosis.