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Sensor fault diagnosis is one of the important parts of a vehicle control system. Normally we sort sensor faults as incipient-faults and abrupt-faults [5]. In this paper, we focus on the sensor abrupt-faults of Hybrid electric vehicles (HEV) control system. A novel method for diagnosing sensor abrupt-faults is proposed based on the wavelet packet neural network (WPNN). The simulating test is conducted...
The possible faults of a sensor may be classified as abrupt (sudden) faults and incipient (slowly developing) faults. This paper focuses on the abrupt faults of a sensor. Due to the limited number of scales, a single wavelet amplitude map has not enough scales to describe all details of the signal. The sampling grid in the scale direction is rather sparse, Some of the fault information will be leaked...
The possible faults of a sensor may be classified as abrupt (sudden) faults and incipient (slowly developing) faults. This paper focuses on the abrupt faults of a sensor. Due to the limited number of scales, a single wavelet amplitude map has not enough scales to describe all details of the signal. The sampling grid in the scale direction is rather sparse, Some of the fault information will be leaked...
In this paper an arc fault detection method is proposed based on characteristics of the fault current of an electric arc. A localized signal processing method is developed using wavelet analysis to decompose the differential current signal into a series of wavelet components, each of which is a time-domain signal that covers a specific frequency band. Thus, more distinctive signal features that represent...
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