Vibration-Based Condition Monitoring indexes for Predictive Maintenance of timing gear systems in automotive applications

This work utilizes data acquisition and signal processing to differentiate the health status of an automotive timing system in a real-world scenario. Vibration data were collected using a triaxial accelerometer, and two types of tests were performed: idle and non-stationary at different percentages of Service Life. Then, two indicators were evaluated to assess the evolution of the damage and the cyclostationary behavior of the system: the sum of the meshing order harmonics of the Time Synchronous Average (TSA) spectrum and a statistical indicator (IGCS/GS) which is sensitive to the development of cyclostationary phenomena. As the results obtained from the idle signals were promising, the same signal processing was applied to portions of the signals extracted from the transient tests. This was done to process quasi-stationary parts of the signal, allowing for spectrum analysis and extraction of the TSA. Both the indicators were effective in distinguishing the healthy and the faulty stages, showing an increasing value at the end of life.