Vehicles produce sound signals with varying temporal and spectral properties under different working conditions. These sounds are indicative of the condition of the engine. Fault diagnosis is a significantly difficult task in geographically remote places where expertise is scarce. Automated fault diagnosis can assist riders to assess the health condition of their vehicles. This paper presents a...

Integrated Systems Health Management includes fault detection, fault diagnosis (or fault isolation), and fault prognosis. We define prognosis to be detecting the precursors of a failure, and predicting how much time remains before a likely failure. Algorithms that use the data-driven approach to prognosis learn models directly from the data, rather than using a hand-built model based on human e...

steering assist system controls the force transfer behavior of the steering system and improves the steering probability of the vehicle. moreover, it is an interface between the diver and vehicle. fault detection in electrical assisted steering systems is a challenging problem due to frequently use of these systems. this paper addresses the fault detection and reconstruction in automotive elect...

In the building energy efficiency field, developing automatic and accurate fault detection and diagnosis methods is necessary in order to ensure optimal operations of systems and to save energy. In this paper first, fault detection analysis based on statistical methods where anomalies are detected through a comparison with neighborhood and averaged fault-free values and through a clustering tec...

The large aircraft engine fault diagnosis in the problem of accurate. General components with different, large aircraft engine structure and its complex, the work in higher frequency failure, failure appear in a relatively short time, and it is difficult to retrieval, leading to establish the connection between the fault occurs when the connection breaks. The traditional fault detection method ...

This paper propose a diagnosis architecture that integrates consistency based diagnosis with induced time series classifiers, trying to combine the advantages of both methods. Consistency based diagnosis allows fault detection and localization without prior knowledge of the device fault modes. Machine learning techniques are able to induce time series classifiers that may be used to identify fa...

The improvement of the detection and diagnosis capability for the unanticipated fault is a tendency in the research and application of fault diagnosis. In this paper, some notions and the basic principles for the unanticipated fault detection and diagnosis are given. A general process model applied to the diagnosis for the unanticipated fault is designed, by adopting a three-layer progressive s...