Abstract This paper proposes a method for diagnosing bolt looseness faults using the principle of PCA to extract time-domain features monitoring data. First all, five dimensionless factors IMF are calculated after empirical mode decomposition (EMD) is performed on original Then, principal component analysis (PCA) applied data vectors, which processed by dimensionality reduction and residual spa...

Abstract The control technology of electromechanical actuator(EMA) and its fault diagnosis is one the key problems multi-electric aircraft study. method based on deep learning used to diagnose isolate classic faults EMA. simulation model EMA modeling according working principle law. Four typical are studied,including return channel jam, spall, motor fault, position sensor fault. Sparse Auto Enc...

The Time Triggered Architecture (TTA) and its related communication protocol, TTP/C is an emerging communication principle for distributed fault-tolerant real-time systems. Typical applications are safety-critical digital control systems such as drive-by-wire and fly-by-wire. This paper highlights the hardware / software architecture and design of the first industrial single chip communication ...

Fault detection for wireless sensor networks (WSNs) has been studied intensively in recent years. Most existing works statically choose the manager nodes as probe stations and probe the network at a fixed frequency. This straightforward solution leads however to several deficiencies. Firstly, by only assigning the fault detection task to the manager node the whole network is out of balance, and...

Stimulated by the enhancing requirements for system safety as well process reliability in complex industrial processes, this paper investigates a data-driven fault detection and fault-tolerant control scheme large-scale systems. To end, pair-wise decomposition approach is first presented based on inclusion principle, which expands original into set of disjointed subsystems. Then, subsystems, ob...

Because of the interlinking of process equipments in process industry, event informationmay propagate through the plant and affect a lot of downstream process variables. Specifying the causality and estimating the time delays among process variables are critically important for data-driven fault prognosis. They are not only helpful to find the root cause when a plant-wide disturbance occurs, bu...

In this paper, we adopt a novel topological approach to fault diagnosis. In our researches, global information will be introduced into electric power network, we are using mainly BFS of graph theory algorithms and linear discriminant principle to resolve fast and exact analysis of faulty components and faulty sections, and finally accomplish fault diagnosis. The results of BFS and linear discri...

One of the key bene ts of future hardware implementations of certain arti cial neural networks (ANN's) is their apparently \built-in" fault tolerance which makes them potential candidates for critical tasks with high reliability requirements. This paper investigates the fault-tolerance characteristics of time-continuous, recurrent ANN's that can be used to solve optimization problems. The princ...

Currently, Diagnostic parameters of analog circuits fault diagnosis based on SVM are adjusted in accordance with the principle to determine the global optimum or by trial. Parameter adjustment is not considered practical diagnostic system diagnostic requirements. It can not be part of various diagnostic parameters simultaneously adjust and optimize. The results are not satisfactory. The paper p...

In this work we investigate the problem of simultaneous privacy and integrity protection in cryptographic circuits. We consider a white-box scenario with a powerful, yet limited attacker. A concise metric for the level of probing and fault security is introduced, which is directly related to the capabilities of a realistic attacker. In order to investigate the interrelation of probing and fault...