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Regression test selection is to select a subset of existing tests to run, so as to identify the possible faults in the modified program. A promising regression test selection technique needs to be safe, that is, to select tests from the original test suite that can expose faults in the modified program under controlled regression testing. Existing safe regression test selection techniques however...
This paper presents particle swarm optimization (PSO)-based support vector machine (SVM) to extract the optimal support vector from database for vibration fault diagnosis of steam turbine-generator sets (STGS). In this paper, the SVM is used to construct the vibration fault diagnosis model and the proposed PSO is then adopted to determine automatically the optimal parameters in the SVM. Test results...
Information fusion arises in a surprising number of fault diagnosis applications. In this paper, common faults are designed in the experiment according to the gear pump vibration mechanism. Fault signal is collected from vibration sensors of different positions, and wavelet packet energy percentage and RMS are extracted as features of the signal. RBF neural network is adopted to fuse thiese features...
To solve the computer description of Fault tree model, a new method based on the extended fault tree nodes' nonlinear linked lists representation is put forward according to the analysis of the fault tree mathematical model and inference mechanism. With this method, the process of fault tree diagnosis can be fully represented of this method and the process of fault tree diagnosis inference mechanism...
Mismatch of components in a time-interleaved ADC (TIADC) is a major problem which can significantly degrade the performance, even with a 0.5\% mismatch. This paper describes a new technique which uses checksums for diagnosing the mismatch of components among sub-ADCs in a TIADC. In our checksum formulation, a transition matrix is used to represent the transition relationship between the current state...
For the problem of little sample size and incomplete sample information which leads to the fact that fault diagnosis results are not ideal in the transformer fault diagnosis process, we combine the simplifying of rough sets with support vector machine classification .Then, we build the model of transformer fault diagnosis which is based on the rough sets and support vector machine .Proved by the simulation...
System level diagnosis is an important technique for fault detection and location in multiprocessor computing systems. The adaptive diagnosis, proposed by Nakajima, is a practical approach among many system level diagnosis schemes. However, only completely connected system has been discussed with the adaptive approach under the MM model as far as we know. Hence, we consider the problem of adaptive...
A new approach to detecting and diagnosing faults in quantum circuits is introduced. In order to account for the probabilistic nature of quantum circuits, collections of test experiments, called binary tomographic tests (BTTs), are generated. A BTT can identify a fault with respect to some user-defined confidence threshold τ. We present an algorithm to generate BTTs that either detect, or ensure the...
With the research and application of Virtual Instrument technology and networked testing technology, the networked virtual instruments appear great potential in remote testing field of electronic equipment. This paper first presents a novel testing system of complicated electronic equipments based on virtual instruments, then building the architecture of the network and designing the hardware, software...
According to the problem of small samples and nonlinear feature in fault diagnosis of marine diesel engine, comprehensively using the methods of grey relational analysis and kernel fuzzy c-means clustering, a method solving fault diagnosis of marine diesel engine is proposed. Firstly, kernel fuzzy c-means clustering was made on historical fault dataset. Secondly, the preliminary fault diagnosis was...
Aspect oriented programming is a new paradigm of software development. It introduces new types of faults. Mutation testing is a technique which can tackle these faults systematically. The effectiveness of testing depends on the coverage of testing locations to find faults and mutant generation based on these faults using different mutation operators. In this paper, we present an automated mutation...
The aim of this paper is to reduce the fault simulation effort required for the evaluation of test effectiveness in mixed-signal circuits. Exhaustive simulation of basic analog and mixed-signal structures in the presence of individual faults is used to identify potentially equivalent faults. Fault equivalence is finally evaluated based on the simulation of all faults in a case study -- a DCDC (switched...
F.P.Preparata et al. have proposed a fault diagnosis model to find all faulty units in the multicomputer system by using outcomes which each unit tests some other units. In this paper, for probabilistic diagnosis models, we show an efficient diagnosis algorithm to obtain a posteriori probability that each of units is faulty given the test outcomes. Furthermore, we propose a method to analyze the diagnostic...
AVR (Automatic Voltage Regulator) is the most important module, which can control the output voltage of generating sets, guarantee the voltage stability, improve power quality and decide the performance of electricity generating sets, so this paper introduces the design method of the AVR detecting and diagnostic system, which based on the fault database. The paper introduces the platform of the testing...
This paper presents an applying of march test algorithms to diagnose coupling faults (CFs) of SRAMs memories. Two phases of test algorithm is used to identify all the CFs. At Phase 1 march Cd is used to detect and diagnosis partially of the CFs. The March Distinguish Algorithm (MDA) is used in phase 2 to identify the identical fault syndromes which cannot be identified by the march Cd. Therefore,...
The procedure of testing the navigation electron system of the UAV in the traditional way is very complicated and costs lots of resources, which influences the formation of combating effectiveness of the UAV. In order to solve the problem mentioned above, this paper designed and implemented a portable testing equipment for navigation electron system on the UAV. By using the equipment, fast testing...
Against the difficulty of faults diagnosis for the equipment hydraulic system, a simple and applied faults diagnosis method is proposed in this article. The testing principle, basic hydraulic loop, diagnosis sequence and application of this method are introduced. This method combines quantitative detection of system parameters with logic analyses, which greatly improves faults diagnosis of hydraulic...
The thesis, in order to solve the fault diagnosis problem of oil Parameter, adaptive neural network-based fuzzy inference system (ANFIS) was applied to build a fault diagnosis model of automobile engine, with the construction of ANFIS, by using gradient descent genetic algorithm and optimization of system parameters of neutral network learning algorithm, inputs the fusion data into ANFIS, and introduces...
With powerful features and cross platform character, web service has been applied in the field of information technology widely. To meet dynamic needs of enterprises, it tends to generate new web applications through service compositions. Due to flaw of designed process or incorrect input, to composite service may encounter various faults during execution. Moreover, the faults often continue to accumulate...
This paper, in order to reduce fault and improve ratio of recognition, build adaptive neural network-based fuzzy inference system (ANFIS), which was applied to build a fault diagnosis model of automobile engine, adopts the method of information fusion in entropy method to optimize the input interface. To reduce the impact of excessive parameters on classification accuracy and cost, it also raises...
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