A novel test optimizing algorithm for sequential fault diagnosis

Yang, Chen; Jiang, Yan; Li, Bing; Liu, Zhen

doi:10.1016/j.mejo.2014.03.005

Cited by 20 publications

(6 citation statements)

References 14 publications

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“…This problem has seen a variety of applications beyond medical testing and quality assurance in manufacturing. It is closely related to the machine scheduling problem [12,13,14,15], and is very similar to the fault detection problem, which seeks to find (and sometimes repair) the fault-causing component in a downed system [16,17,18,19,20]. It also has relevance to machine learning applications, such as rapid object detection for image classification [21].…”

Section: Background On the Stpmentioning

confidence: 99%

The Single-Dependence Sequential Testing Problem for the Living Kidney Donor Workup Process

Nielsen,

El-Amine,

Gentili

et al. 2024

Preprint

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The Sequential Testing Problem (STP) seeks to minimize the total expected cost of administering a series of tests which determine the quality of a system. When the probabilities of passing or failing a test are independent there exist many methods to solve the problem efficiently, but there is little research exploring the effect of dependency between tests. Motivated by the process of evaluating living kidney donors, we explore a variant of the STP which assumes that the probability of passing a given test is conditional upon passing the preceding test, and refer to this variant as the Single-Dependence Sequential Testing Problem (SDSTP). We present an optimization model to solve the SDSTP to optimality and simple - but effective methods to approximate the solution. Though we conjecture that the problem is NP-Complete, our experiments show that the model can be solved to optimality for many practical applications where the set of tests is small (say, less than 20), and our proposed algorithms also find near-optimal solutions in rapid time even for large numbers of tests.

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Section: Background On the Stpmentioning

confidence: 99%

The Single-Dependence Sequential Testing Problem for the Living Kidney Donor Workup Process

Nielsen,

El-Amine,

Gentili

et al. 2024

Preprint

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show abstract

“…By the combination of the WFD and WFI, Tsai and Hsu 14 developed a function-based diagnostic strategy that constructed diagnosis trees for systems based on a functional block diagram comprising function elements. Yang et al 15 optimized the test set and test sequence with a greedy method to reduce the test cost while maintaining the required fault isolation rate. The greedy method was then combined with discrete binary particle swarm optimization to construct a test sequential tree.…”

Section: Introductionmentioning

confidence: 99%

Novel algorithms for sequential fault diagnosis based on greedy method

Tian

Duan

Sang

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part O:

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Test sequencing for binary systems is a nondeterministic polynomial-complete problem, where greedy algorithms have been proposed to find the solution. The traditional greedy algorithms only extract a single kind of information from the D-matrix to search the optimal test sequence, so their application scope is limited. In this study, two novel greedy algorithms that combine the weight index for fault detection with the information entropy are introduced for this problem, which are defined as the Mix1 algorithm and the Mix2 algorithm. First, the application scope for the traditional greedy algorithms is demonstrated in detail by stochastic simulation experiments. Second, two new heuristic formulas are presented, and their scale factors are determined. Third, an example is used to show how the two new algorithms work, and four real-world D-matrices are employed to validate their universality and stability. Finally, the application scope of the Mix1 and Mix2 algorithms is determined based on stochastic simulation experiments, and the two greedy algorithms are also used to improve a multistep look-ahead heuristic algorithm. The Mix1 and Mix2 algorithms can obtain good results in a reasonable time and have a wide application scope, which also can be used to improve the multistep look-ahead heuristic algorithm.

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“…But the combination explosion, large amount of calculation, easy to get stuck in backtracking and iteration proliferation of them can't meet the current diagnostic requirements in complexity systems. In the recent years, the intelligent algorithms such as the genetic algorithm [7], ant colony algorithm [8], particle swarm optimization [9], support vector machine [10] applied in sequential diagnosis have been advised to get the optimal solution in large complex real-world systems for their powerful calculation ability and optimization mechanism.…”

Section: Introductionmentioning

confidence: 99%

A POMDP-Based Optimization Method for Sequential Diagnostic Strategy With Unreliable Tests

et al. 2019

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This paper considers the sequential fault diagnosis problem with unreliable tests which exist widely in practice. This problem involves real-time inference of the most likely set of failure sources, i.e., fault state, based on unreliable test outcomes. The purpose of this paper is to optimize test set and diagnostic strategy so as to cut down the test cost while isolating the fault accurately, and a method for optimal diagnosis strategy based on partially observable Markov decision process (POMDP) is presented. The components of the POMDP tailed to optimizing the diagnostic strategy are specified, and the solution to the POMDP-based model, namely the optimal strategy, is obtained to describe the optimal test sequence for fault diagnosis. The performance of the proposed method is evaluated with simulation experiments. All the results indicate that this method performs good in diagnostic efficiency and accuracy, even compared with the strategies of traditional methods.INDEX TERMS Sequential fault diagnosis, optimal diagnostic strategy, unreliable tests, POMDP.

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A novel test optimizing algorithm for sequential fault diagnosis

Cited by 20 publications

References 14 publications

The Single-Dependence Sequential Testing Problem for the Living Kidney Donor Workup Process

The Single-Dependence Sequential Testing Problem for the Living Kidney Donor Workup Process

Novel algorithms for sequential fault diagnosis based on greedy method

A POMDP-Based Optimization Method for Sequential Diagnostic Strategy With Unreliable Tests

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