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In this paper, a novel method of intermittent fault diagnosis based on dynamic power current in digital circuit is proposed. The intermittent fault model in digital circuit is introduced. The influence of intermittent fault of different magnitudes and types on the dynamic power current of logic gate circuit is analyzed. Then, an intelligent diagnosis method of intermittent fault based on power current information is put forward, which has been verified on ISCAS85-C17 circuit. The test shows the feasibility of using dynamic power current for digital circuit intermittent fault diagnosis.

The test path of solder joint intermittent connection faults under direct-current stimulus is examined in this paper. According to the physical structure of the circuit, a network model is establis...

Built-in-test (BIT) systems are added to electronic aviation systems to monitor the status of the system, communicate through alarms warnings of faults or failures in the system, and aide in diagnosing, or pinpointing, the problem down to the level of an individual replaceable unit [1,2]. As more circuits are added and lower working voltage used, electrical systems become more sensitive to electromagnetic interference.

The intermittent faults induced by environment stress such as extreme vibration have deep impact on the serviceability and reliability of equipment. In this paper, the term of the extreme vibration environment is defined. The finite element simulation model of the component is established, and the mechanism and laws that how the extreme vibration environmental stress induces intermittent faults are analyzed. Based on the elastic-plastic stress theory, a method of calculating component’s cumulative damage in extreme vibration environment is proposed. Then a hidden Markov model (HMM) based Tri-State (normal state, intermittent state and fault state) injury correlation model is built. Starting with the relationship analysing between the features in each state of components and the interior cumulative damage, the cumulative damage based HMM model for intermittent fault diagnosis is established. After that, a real-time fault diagnosis method is proposed. Tests are carried out on a helicopter attitude indicator in extreme vibration environment. The test results show that the occurrence probability of intermittent fault becomes large with the increase of the vibration magnitude and time. The proposed fault diagnosis method can detect the intermittent fault efficiently.

For the crack intermittency detection in circuit board, a detection method based on time domain reflectometry is proposed. And a time domain signal feature is extracted, the time domain signal feature is highly sensitive to the defect. Firstly, in order to analyze the change trend of time domain signal under intermittent disconnection. The influence of conductor crack on the physical parameters is analyzed. The physical parameters include AC/DC resistance, inductance and capacitance. And then the principle of signal reflection is described. The ringing phenomenon that caused by signal reflection is used for crack intermittency detection. Therefore the maximum, minimum and peak-peak values of time domain signal are used to detect intermittent disconnection. At last solder joint equivalent circuit is used to verify the effectiveness of the method. When the intermittent disconnection happened in circuit board, the time domain reflection phenomenon is observed clearly. The maximum, minimum and the peak-peak values of output voltage signal are changed greatly, simulation result shows that the high frequency signal is sensitive to intermittent disconnection, and the proposed method is effective.

The conventional model-based diagnosis usually potentially presumes faults are persistent and does not take intermittent faults into account, which is the major cause of the problems of false alarms, cannot duplicate and no fault found in aircraft avionics and present a tremendous challenge to prognostics and health management. Aiming at the problem that the logical automaton proposed by Sampath et al. cannot distinguish between strings or states that are highly probable and those that are less probable, a stochastic automaton approach is given to distinguish the fault types by extending the fault model to include both permanent faults and intermittent faults. The notions of A- and AA-diagnosability of permanent faults and intermittent faults for stochastic automaton are defined. Thereafter, the diagnoser with a probability matrix appended to each transition that can be used to update the probability distribution on the state estimate is constructed. Finally, an example of aeronautic gyroscope is presented to demonstrate the proposed approach, and the analysis results show that this approach is able to discriminate the fault types within bounded delay if the system is A- and AA-diagnosable. In our previous paper, we have extended the logical automaton model, and investigated the stochastic automaton approach in this article.

Hot Carrier Degraded(HCD), Electro-Static discharge(ESD) and Time-Dependent Dielectric Breakdown (TDDB) are the main failure modes of electronic devices. Identifying degraded state of electronic devices needs considering the combined effects of various factors. In this paper, On the basis of information such as real-time HCD damage, ESD damage, etc were obtained, with the help of fuzzy integral, which has the unique ability of information fusion, a new intelligent method of identifying degraded state of electronic devices was proposed based on neural network and fuzzy integral. Finally, an experiment based on a certain type of electronic device was introduced in detail, and the effectiveness of the intelligent method proposed in this paper was analyzed and validated by the experiment.