Research and application of hierarchical model for multiple fault diagnosis

Computational complexity of complex system multiple fault diagnosis is a puzzle at all times. Based on the well known Mozetic＇s approach, a novel hierarchical model-based diagnosis methodology is put forward for improving efficency of multi-fault recognition and localization. Structural abstraction and weighted fault propagation graphs are combined to build diagnosis model. The graphs have weighted arcs with fault propagation probabilities and propagation strength. For solving the problem of coupled faults, two diagnosis strategies are used： one is the Lagrangian relaxation and the primal heuristic algorithms; another is the method of propagation strength. Finally, an applied example shows the applicability of the approach and experimental results are given to show the superiority of the presented technique.

A Hierarchical Modeling and Fault Diagnosis Method for Complex Electronic Devices

Due to the shortcomings of the diagnosis systems for complex electronic devices such as failure models hard to build and low fault isolation resolution, a new hierarchical modeling and diagnosis method is proposed based on multisignal model and support vector machine （SVM）. Multisignal model is used to describe the failure propagation relationship in electronic device system, and the most probable failure printed circuit boards （PCBs） can be found by Bayes inference. The exact failure modes in the PCBs can be identified by SVM. The results show the proposed modeling and diagnosis method is effective and suitable for diagnosis for complex electronic devices.

Analysis and modeling of resistive switching mechanism oriented to fault tolerance of resistive memory based on memristor

With the progress of the semiconductor industry, resistive memories, especially the memristor, have drawn increasing attention. The resistive memory based on memrsitor has not been commercialized mainly because of data error. Currently, there are more studies focused on fault tolerance of resistive memory. This paper studies the resistive switching mechanism which may have time-varying characteristics. Resistive switching mechanism is analyzed and its respective circuit model is established based on the memristor Spice model.

Twin model-based fault detection and tolerance approach for in-core self-powered neutron detectors

The in-core self-powered neutron detector(SPND)acts as a key measuring device for the monitoring of parameters and evaluation of the operating conditions of nuclear reactors.Prompt detection and tolerance of faulty SPNDs are indispensable for reliable reactor management.To completely extract the correlated state information of SPNDs,we constructed a twin model based on a generalized regression neural network(GRNN)that represents the common relationships among overall signals.Faulty SPNDs were determined because of the functional concordance of the twin model and real monitoring sys-tems,which calculated the error probability distribution between the model outputs and real values.Fault detection follows a tolerance phase to reinforce the stability of the twin model in the case of massive failures.A weighted K-nearest neighbor model was employed to reasonably reconstruct the values of the faulty signals and guarantee data purity.The experimental evaluation of the proposed method showed promising results,with excellent output consistency and high detection accuracy for both single-and multiple-point faulty SPNDs.For unexpected excessive failures,the proposed tolerance approach can efficiently repair fault behaviors and enhance the prediction performance of the twin model.

Quantum generative adversarial networks based on a readout error mitigation method with fault tolerant mechanism

Readout errors caused by measurement noise are a significant source of errors in quantum circuits,which severely affect the output results and are an urgent problem to be solved in noisy-intermediate scale quantum(NISQ)computing.In this paper,we use the bit-flip averaging(BFA)method to mitigate frequent readout errors in quantum generative adversarial networks(QGAN)for image generation,which simplifies the response matrix structure by averaging the qubits for each random bit-flip in advance,successfully solving problems with high cost of measurement for traditional error mitigation methods.Our experiments were simulated in Qiskit using the handwritten digit image recognition dataset under the BFA-based method,the Kullback-Leibler(KL)divergence of the generated images converges to 0.04,0.05,and 0.1 for readout error probabilities of p=0.01,p=0.05,and p=0.1,respectively.Additionally,by evaluating the fidelity of the quantum states representing the images,we observe average fidelity values of 0.97,0.96,and 0.95 for the three readout error probabilities,respectively.These results demonstrate the robustness of the model in mitigating readout errors and provide a highly fault tolerant mechanism for image generation models.

Toward a Multi-Hop, Multi-Path Fault-Tolerant and Load Balancing Hierarchical Routing Protocol for Wireless Sensor Network

This paper describes a novel energy-aware multi-hop cluster-based fault-tolerant load balancing hierarchical routing protocol for a self-organizing wireless sensor network (WSN), which takes into account the broadcast nature of radio. The main idea is using hierarchical fuzzy soft clusters enabling non-exclusive overlapping clusters, thus allowing partial multiple membership of a node to more than one cluster, whereby for each cluster the clusterhead (CH) takes in charge intra-cluster issues of aggregating the information from nodes members, and then collaborate and coordinate with its related overlapping area heads (OAHs), which are elected heuristically to ensure inter-clusters communication. This communication is implemented using an extended version of time-division multiple access (TDMA) allowing the allocation of several slots for a given node, and alternating the role of the clusterhead and its associated overlapping area heads. Each cluster head relays information to overlapping area heads which in turn each relays it to other associated cluster heads in related clusters, thus the information propagates gradually until it reaches the sink in a multi-hop fashion.

T-PBFT: An EigenTrust-Based Practical Byzantine Fault Tolerance Consensus Algorithm

Blockchain with these characteristics of decentralized structure, transparent and credible, time-series and immutability, has been considering as a promising technology. Consensus algorithm as one of the core techniques of blockchain directly affects the scalability of blockchain systems. Existing probabilistic finality blockchain consensus algorithms such as PoW, PoS, suffer from power consumptions and low efficiency;while absolute finality blockchain consensus algorithms such as PBFT, HoneyBadgerBFT, could not meet the scalability requirement in a largescale network. In this paper, we propose a novel optimized practical Byzantine fault tolerance consensus algorithm based on EigenTrust model, namely T-PBFT, which is a multi-stage consensus algorithm. It evaluates node trust by the transactions between nodes so that the high quality of nodes in the network will be selected to construct a consensus group. To reduce the probability of view change, we propose to replace a single primary node with a primary group. By group signature and mutual supervision, we can enhance the robustness of the primary group further. Finally, we analyze T-PBFT and compare it with the other Byzantine fault tolerant consensus algorithms. Theoretical analysis shows that our T-PBFT can optimize the Byzantine fault-tolerant rate,reduce the probability of view change and communication complexity.

ONLINE MODEL AND ACTUATOR FAULT TOLERANT CONTROL FOR AUTONOMOUS MOBILE ROBOT

A novel fault-tolerant adaptive control methodology against the actuator faults is proposed. The actuator effectiveness factors （AEFs） are introduced to denote the healthy of actuator, and the unscented Kalman filter （UKF） is employed for online estimation of both the motion states and the AEFs of mobile robot. A square root version of the UKF is introduced to improve efficiency and numerical stability. Using the information from the UKF, the reconfigurable controller is designed automatically based on an enhancement inverse dynamic control （IDC） methodology. The experiment on a 3-DOF omni-directional mobile robot is performed, and the effectiveness of the proposed method is demonstrated.

Open-circuit fault diagnosis and fault tolerance for shunt active power filter

The open-circuit fault of the power switches in shunt active power filter(SAPF) would exacerbate the harmonic pollution of power grid, and degrade the reliability of the devices and system. A fault diagnosis method is proposed based on reference model and an over-modulation strategy under hardware fault tolerance for SAPF. First, a mathematic model is established for SAPF. Second, the residuals are generated by comparing the outputs of reference model and those of actual model, and open-switch fault is detected and diagnosed by residual evaluation. After that, hardware fault tolerance is performed with the three-phase four-switch(TPFS) topology to isolate the faulty phase. Finally, the over-modulation strategy is proposed to increase the voltage transfer ratio of the TPFS topology. Simulation and experimental results verified the feasibility and effectiveness of the proposed method.

A novel mitigation measure for normal fault-induced deformations on pile-raft systems

Evidence from recent earthquakes has shown destructive consequences of fault-induced permanent ground movement on structures.Such observations have increased the demand for improvements in the design of structures that are dramatically vulnerable to surface fault ruptures.In this study a novel connection between the raft and the piles is proposed to mitigate the hazards associated with a normal fault on pile-raft systems by means of 3D finite element(FE)modeling.Before embarking on the parametric study,the strain-softening constitutive law used for numerical modeling of the sand has been validated against centrifuge test results.The exact location of the fix-head and unconnected pile-raft systems relative to the outcropping fault rupture in the free-field is parametrically investigated,revealing different failure mechanisms.The performance of the proposed connection for protecting the pile-raft system against normal fault-induced deformations is assessed by comparing the geotechnical and structural responses of both types of foundation.The results indicate that the pocket connection can relatively reduce the cap rotation and horizontal and vertical displacements of the raft in most scenarios.The proposed connection decreases the bending moment response of the piles to their bending moment capacity,verging on a fault offset of 0.6 m at bedrock.

Fault tolerant synchronization of chaotic systems based on T-S fuzzy model with fuzzy sampled-data controller

In this paper the fault tolerant synchronization of two chaotic systems based on fuzzy model and sample data is investigated. The problem of fault tolerant synchronization is formulated to study the global asymptotical stability of the error system with the fuzzy sampled-data controller which contains a state feedback controller and a fault compensator. The synchronization can be achieved no matter whether the fault occurs or not. To investigate the stability of the error system and facilitate the design of the fuzzy sampled-data controller, a Takagi Sugeno （T-S） fuzzy model is employed to represent the chaotic system dynamics. To acquire good performance and produce a less conservative analysis result, a new parameter-dependent Lyapunov-Krasovksii functional and a relaxed stabilization technique are considered. The stability conditions based on linear matrix inequality are obtained to achieve the fault tolerant synchronization of the chaotic systems. Finally, a numerical simulation is shown to verify the results.

Superimposed characteristics and genetic mechanism of strike-slip faults in the Bohai Sea, China

Based on the 3 D seismic structure interpretation of Bohai Sea, combined with physical modeling of structure, structural style analysis and apatite fission track simulation, the structural characteristics and genetic mechanism of the Cenozoic strike-slip faults in Bohai Sea were investigated. The results show that Tanlu strike-slip fault experienced three stages of strike-slip activities in the Cenozoic,and the transition from left-lateral strike to right-lateral strike-slip was completed at the end of the fourth member of the Shahejie Formation. The strike-slip faults in the Bohai Sea have the characteristics of multi-stage and multi-strength stress superposition. According to the superimposed forms of different strengths, different properties and different ratios, they can be divided into three major genetic types,extension and strike-slip superimposition, extension and extrusion superimposition, extrusion and strike-slip superimposition, and fifteen typical structure patterns. Affected by multiple changes in the direction and rate of subduction of the Cenozoic Pacific plate, the difference between the Cenozoic extension and the strike-slip in the Bohai Sea area leads to the diversity of the fault system and the zoning of the depression structure. According to superimposition features of faults, the Bohai Sea area can be divided into the Liaoxi S-type weak strike-slip zone, Liaodong braided strong strike-slip zone, Boxi conjugated medium strike-slip zone, Bodong brush structure medium strike-slip zone and Bonan parallel strong strike-slip zone. These zones differ in oil and gas accumulation features.

Development of Fault Diagnosis System for Spacecraft Based on Fault Tree and G2

Some ideas in the development of fault diagnosis system for spacecraft are introduced. Firstly, the architecture of spacecraft fault diagnosis is proposed hierarchically with four diagnosis frames, i.e., system level, subsystem level, component level and element level. Secondly, a hierarchical diagnosis model is expressed with four layers, i.e., sensors layer, function layer, behavior layer and structure layer. These layers are used to work together to accomplish the fault alarm, diagnosis and localization. Thirdly, a fault-tree-oriented hybrid knowledge representation based on frame and generalized rule and its relevant reasoning strategy is put forward. Finally, a diagnosis case for spacecraft power system is exemplified combining the above with a powerful expert system development tool G2.

Reliability Growth Modeling and Optimal Release Policy Under Fuzzy Environment of an N-version Programming System Incorporating the Effect of Fault Removal Efficiency

Failure of a safety critical system can lead to big losses. Very high software reliability is required for automating the working of systems such as aircraft controller and nuclear reactor controller software systems. Fault-tolerant softwares are used to increase the overall reliability of software systems. Fault tolerance is achieved using the fault-tolerant schemes such as fault recovery （recovery block scheme）, fault masking （N-version programming （NVP）） or a combination of both （Hybrid scheme）. These softwares incorporate the ability of system survival even on a failure. Many researchers in the field of software engineering have done excellent work to study the reliability of fault-tolerant systems. Most of them consider the stable system reliability. Few attempts have been made in reliability modeling to study the reliability growth for an NVP system. Recently, a model was proposed to analyze the reliability growth of an NVP system incorporating the effect of fault removal efficiency. In this model, a proportion of the number of failures is assumed to be a measure of fault generation while an appropriate measure of fault generation should be the proportion of faults removed. In this paper, we first propose a testing efficiency model incorporating the effect of imperfect fault debugging and error generation. Using this model, a software reliability growth model （SRGM） is developed to model the reliability growth of an NVP system. The proposed model is useful for practical applications and can provide the measures of debugging effectiveness and additional workload or skilled professional required. It is very important for a developer to determine the optimal release time of the software to improve its performance in terms of competition and cost. In this paper, we also formulate the optimal software release time problem for a 3VP system under fuzzy environment and discuss a the fuzzy optimization technique for solving the problem with a numerical illustration.

Imprecise Computation Based Real-time Fault Tolerant Implementation for Model Predictive Control

Model predictive control (MPC) could not be deployed in real-time control systems for its computation time is not well defined. A real-time fault tolerant implementation algorithm based on imprecise computation is proposed for MPC, according to the solving process of quadratic programming (QP) problem. In this algorithm, system stability is guaranteed even when computation resource is not enough to finish optimization completely. By this kind of graceful degradation, the behavior of real-time control systems is still predictable and determinate. The algorithm is demonstrated by experiments on servomotor, and the simulation results show its effectiveness.

DESCRIPTION AND PREDICTION OF CATASTROPHE OF VIBRATION STATE FOR FAULTY ROTORS

A sudden increase of vibration amplitude with no foreboding often results in an abrupt breakdown of a mechanical system.The catastrophe of vibration state of a faulty rotor is a typical nonlinear phenomenon,and very difficult to be described and predicted with linear vibration theory.On the basis of nonlinear vibration and catastrophe theory,fhe eatastrophe of the vibration amplitude of the faulty rotor is described;a way to predict its emergence is developed.

Fault Geometry and Departure of Precursors From the Epicenter

Different tectonic elements may play different roles and their deformation styles and types of anomalies are also different in the process of deformation.Such differences may be the cause of the phenomena of the departure from the region with obvious anomalies from the coming epicenter,which are called "departure of precursors from epicenter." From some new experimental and numerical modeling results,five types of deformation elements are identified according to their roles in the process of deformation in a region.They are the brake(or locked),slip,yield,sensitive,and valve elements.Spatial distribution of different elements,especially sensitive and slip elements,are discussed by taking the bend fault,extension,compression,and complex en-echelon faults as examples.These elements with different roles may overlap each other in some cases or be separated in other cases.It is obvious that for different fault geometry,the spatial layout of these elements is different and thus the position and style of

A novel fault-tolerant scheduling approach for collaborative workflows in an edge-IoT environment

As a newly emerging computing paradigm, edge computing shows great capability in supporting and boosting 5G and Internet-of-Things (IoT) oriented applications, e.g., scientific workflows with low-latency, elastic, and on-demand provisioning of computational resources. However, the geographically distributed IoT resources are usually interconnected with each other through unreliable communications and ever-changing contexts, which brings in strong heterogeneity, potential vulnerability, and instability of computing infrastructures at different levels. It thus remains a challenge to enforce high fault-tolerance of edge-IoT scientific computing task flows, especially when the supporting computing infrastructures are deployed in a collaborative, distributed, and dynamic environment that is prone to faults and failures. This work proposes a novel fault-tolerant scheduling approach for edge-IoT collaborative workflows. The proposed approach first conducts a dependency-based task allocation analysis, then leverages a Primary-Backup (PB) strategy for tolerating task failures that occur at edge nodes, and finally designs a deep Q-learning algorithm for identifying the near-optimal workflow task scheduling scheme. We conduct extensive simulative case studies on multiple randomly-generated workflow and real-world edge-IoT server position datasets. Results clearly suggest that our proposed method outperforms the state-of-the-art competitors in terms of task completion ratio, server active time, and resource utilization.

A hierarchical byzantine fault tolerance consensus protocol for the Internet of Things

The inefficiency of Consensus protocols is a significant impediment to blockchain and IoT convergence development.To solve the problems like inefficiency and poor dynamics of the Practical Byzantine Fault Tolerance(PBFT)in IoT scenarios,a hierarchical consensus protocol called DCBFT is proposed.Above all,we propose an improved k-sums algorithm to build a two-level consensus cluster,achieving an hierarchical management for IoT devices.Next,A scalable two-level consensus protocol is proposed,which uses a multi-primary node mechanism to solve the single-point-of-failure problem.In addition,a data synchronization process is introduced to ensure the consistency of block data after view changes.Finally,A dynamic reputation evaluation model is introduced to update the nodes’reputation values and complete the rotation of consensus nodes at the end of each consensus round.The experimental results show that DCBFT has a more robust dynamic and higher consensus efficiency.Moreover,After running for some time,the performance of DCBFT shows some improvement.

Intelligent System for Parallel Fault-Tolerant Diagnostic Tests Construction

This investigation deals with the intelligent system for parallel fault-tolerant diagnostic tests construction. A modified parallel algorithm for fault-tolerant diagnostic tests construction is proposed. The algorithm is allowed to optimize processing time on tests construction. A matrix model of data and knowledge representation, as well as various kinds of regularities in data and knowledge are presented. Applied intelligent system for diagnostic of mental health of population which is developed with the use of intelligent system for parallel fault-tolerant DTs construction is suggested.