Fault diagnosis of a vacuum cleaner motor by means of sound analysis

Achieving high quality standards and 100% defect-free deliverables is becoming a trend among manufacturers of household appliances. In that respect, thorough and reliable end-tests represent an important step towards this goal. This paper deals with the design of end-test procedures for vacuum cleaner motors based on sound analysis. It is well known that sound carries important information about the condition of contact surfaces in rotating parts. The paper aims first to provide a thorough analysis of sound sources within the motor. Second, by using simple yet effective signal processing tools, it is shown that with sound analysis alone it is possible to clearly distinguish fault-free motors from those with mechanical faults. Moreover, the proposed algorithm exhibits a certain isolation capability, i.e., it is able to distinguish three clusters of faults. Finally, a summary of experimental results obtained on a sample of 75 motors is provided.