A novel sensing method of fault in moving machine

• We propose a method to detect the fault, generating the periodic moving impulse.
• A model of periodic moving impulsive sound has been established and analyzed.
• The frequency of the signal depends on the impulse period and the moving speed.
• A method is feasible when the period is longer than 10 times the time constant.

Fault in rotating parts of a machine such as bearings and gears often causes periodic impulses and they are transmitted to adjacent parts while it is moving with a constant speed. It has been an issue, therefore, to find a best means that can tell us the existence of periodic impulse and the period as early as possible. Previous researches mainly use accelerometers since it can easily measure the vibration due to impulse. They normally require considerable measurement time and inconvenience, especially if we have to use them for many different machines. This is straightforward consequence because the sensor is to be removed from and attached to the machine elements as many time as required. This paper proposes a novel method to sense the periodic impulse of moving machinery, by using a non-contact sensor such as a microphone. The method uses the periodic impulsive sound radiated by the fault instead of the impulsive vibration. It is not only more convenient than using the accelerometers, but it can also promptly test a lot of machines; they only have to pass by the microphone during the measurement. However, because the machine under test is moving, the measured impulsive signal is not periodic due to Doppler effect. This makes it difficult to estimate the period of impulses as well as to find the existence of fault. In order to solve this, we firstly model and analyze the characteristics of the moving periodic impulsive sound. Based on this, a method to sense the existence of fault is introduced by utilizing characteristics of moving periodic impulsive sound. The performance is tested by theory and simulation with respect to the signal to noise ratio.