电钢琴琴键开关短路故障自动诊断方法研究

Study on automatic diagnosis method of short circuit fault of electric piano key switch

针对传统电钢琴琴键中开关短路故障诊断定位不准确、损耗时间长的问题,本研究基于EMD模态分解,提出一种电钢琴琴键开关机械故障自动化诊断方法。首先对琴键机械振动的信号特征进行提取,通过其显示电钢琴机械运行情况;然后建立一个机械故障估算模型,确立故障所在的具体位置;之后对该部位机械状况进行健康评价,对其运行等级进行调整,从而实现故障自动诊断。最后,为验证本研究提出的方法是否有效,本研究将其与传统ANN诊断方法进行对比实验。最终结果表明,相较于传统方法,本研究提出的方法诊断时间更短,关键部位的诊断时间降低了0.25~0.5,诊断准确率更高,具备可行性和有效性。

According to the inaccurate fault diagnosis of the traditional electric piano key switch, an automatic mechanical fault diagnosis method is proposed based on EMD mode decomposition.Firstly, the signal characteristics of key mechanical vibration are extracted to show electric piano mechanical operation;a mechanical fault estimation model is established to establish the specific position, the mechanical condition is evaluated and the operation level is adjusted to realize automatic fault diagnosis.Finally, to verify whether the method proposed in this study is effective, this study compares the experiments with traditional ANN diagnostic methods.The final results show that the proposed method in this study has a shorter time of diagnosis, 0.25 to 0.5 reduction at key sites, higher diagnostic accuracy and feasibility and effectiveness.