Method for fault detection of aluminum oxide grinding wheel cutting surfaces using a piezoelectric diaphragm and digital signal processing techniques

•New signal processing tools based on time-frequency and ratio of power are proposed.•The methodology takes advantage of the use of inexpensive piezoelectric transducers.•The proposed method was effective to quantify the evenness of the grinding wheels.•The results provide a reliable solution for industrial applications. A novel strategy to quantify evenness and prevent faults on the cutting surface of conventional aluminum oxide grinding wheels during the dressing operationwas proposed in this research work. The method is based on the use of low-cost piezoelectricdiaphragms and new signal processing parameters based on time-frequency and ratio of power metric.Dressing tests were performed on two structurally distinct aluminum oxide grinding wheels. An acoustic emission (AE) sensor was used as a reference for comparative purposes. Subsequently, AE and piezoelectric diaphragm signals were collected and processed through the proposed approach. The results obtained for both grinding wheels by the piezoelectric diaphragm reveal a strong correlation with those obtained by the AE sensor. This indicates that the piezoelectric diaphragm was as efficient as the AE sensor and can be used to monitor the dressing operation of conventional grinding wheels using the proposed method,thus contributing to optimize the grinding process.