A new diagnosis algorithm for sensors based on morphology-wavelet

For the purpose of increasing the effectiveness of sensors used for control systems, a new fault detecting and diagnosing algorithm, using in connection with morphological -wavelet analysis, is being proposed. The mathematical characterization of singularities with Lipschitz exponents is explained. With the algorithm, firstly, generalized morphological filter with multi-structure elements is designed to filter the random noise and impulse noise in sensor´s input and output signals. And secondly, to effectively extract the incipient fault and abrupt fault characteristic, a wavelet transform was used to decompose and analyze the filtered signals in this paper. By the multi resolution analyzing (MRA), the fault can be located accurately. The type of abrupt and incipient fault concerned can simultaneously be distinguished by using Lipschitz exponent, according to the fault´s point of sudden change. The typical sensor faults such as fix, gain, bias, drift faults were studied. The simulation results show that this algorithm is capable of locating accurately and diagnosing effectively.