A time–frequency analysis based internal leakage detection method for hydraulic actuators

Abstract

Internal leakage in the hydraulic actuators is concerned in this article, which is caused by seal damage, resulting in the limited performance of the system. To study the issue, this article proposes a method based on time–frequency analysis for the detection in hydraulic actuators. First, the pressure signal after filtering of the actuator in one side is collected when the control valve is affected by sinusoidal-like inputs. Second, the time–frequency image of pressure signal in a period at different leakage levels is obtained after continuous wavelet transform. Third is the sum of pixels in the time–frequency image. It is shown that the feature pattern is established by the sum of pixels in the time–frequency image that internal leakage and its severity could be detected effectively. The proposed method required two baselines and premeasured the pressure signal at 11 leakage levels. Once the sum of pixels in the time–frequency image values, obtained from the time–frequency image by continuous wavelet transform based on wavelet Cmor1-1 in subsequent offline tests, are greater than the first baseline, a leakage alarm is triggered. Furthermore, a severe leakage alarm is triggered when the value is greater than the second baseline. Experimental tests show the accuracy of the proposed scheme at different mother wavelets, and it is done without knowing the model of actuator or leakage.