Cosine Similarity Measure between Vague Sets and Its Application of Fault Diagnosis

Lu, Zhikang; Ye, Jun

doi:10.19026/rjaset.6.3749

Cited by 8 publications

(7 citation statements)

References 6 publications

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“…Therefore, the intelligent fault diagnosis frameworks have been developed based on fuzzy integral [13]. Some researchers have developed the fault diagnosis methods of steam turbine based on the similarity measures of vague sets [14][15][16] and based on the cross entropy of vague sets [17]. However, existing diagnosis methods cannot deal with fault diagnosis problems with incomplete, indeterminate and inconsistent information comprehensively, which exist in real world.…”

Section: Introductionmentioning

confidence: 99%

Fault diagnoses of hydraulic turbine using the dimension root similarity measure of single-valued neutrosophic sets

Ye¹

2018

AUTOSOFT

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This paper proposes a dimension root distance and its similarity measure of single-valued neutrosophic sets (SVNSs), and then develops the fault diagnosis method of hydraulic turbine by using the dimension root similarity measure of SVNSs. By the similarity measure between the fault diagnosis patterns and a testing sample with single-valued neutrosophic information and the relation indices, we can determine the fault type and rank faults. Then, the vibration fault diagnosis of hydraulic turbine is presented to demonstrate the effectiveness and rationality of the proposed diagnosis method by the comparative analysis. The fault diagnosis results of hydraulic turbine show that the proposed diagnosis method not only gives the main fault types of hydraulic turbine but also provides useful information for multi-fault analyses and future fault trends. The developed method is effective and reasonable in the fault diagnosis of hydraulic turbine under single-valued neutrosophic environment.

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Section: Introductionmentioning

confidence: 99%

Fault diagnoses of hydraulic turbine using the dimension root similarity measure of single-valued neutrosophic sets

Ye¹

2018

AUTOSOFT

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“…Further, Ye [14] proposed a vibrational fault diagnosis method of steam turbine based on the fuzzy cross entropy measure of VSs. Based on the cosine of the included angle between two vectors, Lu and Ye [15] put forward a similarity measure with the weight of cosine similarity measures (CSMs) between VSs and applied it to the vibrational fault diagnosis of steam turbine. Furthermore, Shi and Ye [16] indicated some insufficiency of existing CSMs and further presented an improved CSM of VSs by considering the degree of hesitation and applied it to the vibrational fault diagnosis of the steam turbine.…”

Section: Introductionmentioning

confidence: 99%

Logarithmic Similarity Measure between Interval-Valued Fuzzy Sets and Its Fault Diagnosis Method

2018

Information

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Fault diagnosis is an important task for the normal operation and maintenance of equipment. In many real situations, the diagnosis data cannot provide deterministic values and are usually imprecise or uncertain. Thus, interval-valued fuzzy sets (IVFSs) are very suitable for expressing imprecise or uncertain fault information in real problems. However, existing literature scarcely deals with fault diagnosis problems, such as gasoline engines and steam turbines with IVFSs. However, the similarity measure is one of the important tools in fault diagnoses. Therefore, this paper proposes a new similarity measure of IVFSs based on logarithmic function and its fault diagnosis method for the first time. By the logarithmic similarity measure between the fault knowledge and some diagnosis-testing samples with interval-valued fuzzy information and its relation indices, we can determine the fault type and ranking order of faults corresponding to the relation indices. Then, the misfire fault diagnosis of the gasoline engine and the vibrational fault diagnosis of a turbine are presented to demonstrate the simplicity and effectiveness of the proposed diagnosis method. The fault diagnosis results of gasoline engine and steam turbine show that the proposed diagnosis method not only gives the main fault types of the gasoline engine and steam turbine but also provides useful information for multi-fault analyses and predicting future fault trends. Hence, the logarithmic similarity measure and its fault diagnosis method are main contributions in this study and they provide a useful new way for the fault diagnosis with interval-valued fuzzy information.

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“…The easily measured voltages of some circuits are generally taken as extracted features. For example, in the literature [5][6][7][8][9][10][11], the voltage signals in the amplitude-frequency response curve were uniformly extracted as eigenvalues. Owing to the large dataset, the voltage amplitudes of frequency response corresponding to typical frequencies were selected as eigenvalues [7,12,13].…”

Section: Introductionmentioning

confidence: 99%

“…The health of an element is generally measured on the basis of distance. For example, in the literature [6,12,13], the degradation of elements was measured using cosine distance and Pearson's correlation coefficient and calculated by extracting signals containing the frequency-domain response of circuits under test to characterise the health of circuit elements. The change range of cosine distance and Pearson's correlation coefficient in literature is [1 0.996], in the literature [10], Euclidean distance was applied as the FI.…”

Section: Introductionmentioning

confidence: 99%

“…In the literature [8][9][10], the eigenvalues were extracted by applying a wavelet packet transform and the health of elements was measured based on Pearson's correlation coefficient and Euclidean distance. Afterwards, the RUL of electronic elements was predicted by carrying out regression analyses using support vector machines [5][6][7][8][9][10][11][12][13] and particle filters [14] based on FI. Gradient boosting decision tree (GBDT) can be applied to both regression and classification, with the advantages of completeness, robustness, and a good explanation therewith.…”

Section: Introductionmentioning

confidence: 99%

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Application of Relative Entropy and Gradient Boosting Decision Tree to Fault Prognosis in Electronic Circuits

Zhou

Zhang

et al. 2018

Symmetry

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Fault prognosis of electronic circuits is the premise of guaranteeing normal operation of a system and carrying out on-condition maintenance. In this work, the remaining useful life (RUL) of electronic elements was estimated by selecting fault features based on variance, measuring fault severity based on relative entropy distance, and conducting fault prognosis based on the gradient boosting decision tree (GBDT) model. At first, the corresponding voltages of amplitude-frequency response, under conditions of changing full-band element parameters, were extracted, and then the frequency bands with large change amplitude were further selected based on variance. Afterwards, using relative entropy distance, the degradation of element parameters was measured, and then the RUL of electronic elements was diagnosed through regression analysis by GBDT. By comparing the data with those arising from the use of other distance-measuring methods, the relative entropy distance shows a larger change range and less apt to suffer interference from noise, which is favorable to subsequent regression prediction. The regression analysis through GBDT is easy to understand and conveniently applied in engineering practice. The application of the method proposed in the study in two examples of electronic circuits indicates that the prediction accuracy of the method for RUL of electronic elements is higher than that of the other distance-measuring methods, and its application in engineering practice is convenient.

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Cosine Similarity Measure between Vague Sets and Its Application of Fault Diagnosis

Cited by 8 publications

References 6 publications

Fault diagnoses of hydraulic turbine using the dimension root similarity measure of single-valued neutrosophic sets

Fault diagnoses of hydraulic turbine using the dimension root similarity measure of single-valued neutrosophic sets

Logarithmic Similarity Measure between Interval-Valued Fuzzy Sets and Its Fault Diagnosis Method

Application of Relative Entropy and Gradient Boosting Decision Tree to Fault Prognosis in Electronic Circuits

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