Application of SA-SVM Incremental Algorithm in GIS PD Pattern Recognition

Tang, Ju; Zhuo, Ran; Wang, DiBo; Wu, Jianrong; Zhang, Xiaoxing

doi:10.5370/jeet.2016.11.1.192

Cited by 12 publications

(12 citation statements)

References 17 publications

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“…A large number of PD pattern recognition applications of the SVM algorithm prove the superior performance of the algorithm. In this study [26,27], SVM is directly selected as the classification method for PD severity assessment.…”

Section: Evaluation Effect Testmentioning

confidence: 99%

Feature Selection for Partial Discharge Severity Assessment in Gas-Insulated Switchgear Based on Minimum Redundancy and Maximum Relevance

et al. 2017

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Scientific evaluation of partial discharge (PD) severity in gas-insulation switchgear (GIS) can assist in mastering the insulation condition of in-service GIS. Limited theoretical research on the laws of PD deterioration leads to a finite number of evaluation features extracted and subjective features selected for PD severity assessment. Therefore, this study proposes a minimum-redundancy maximum-relevance (mRMR) algorithm-based feature optimization selection method to realize the scientific and reasonable choice of PD severity features. PD ultra-high frequency data of varying severities are produced by simulating four typical insulation defects in GIS, which are then collected in the lab. A 16-dimension feature set describing PD original characteristics is abstracted in phase-resolved partial discharge (PRPD) mode, and the more informative evaluation feature set characterizing PD severity is further excavated by the mRMR method. Finally, a support vector machine (SVM) algorithm is employed as the classifier for intelligent evaluation to compare the evaluation effects of PD severity between the feature set selected by mRMR and the feature set is composed of discharge times, amplitude value, and time intervals obtained traditionally based on discharge change theory. The proposed comparison test showed the effectiveness of the mRMR method in informative feature selection and the accuracy of PD severity assessment for all defined defects.

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Section: Evaluation Effect Testmentioning

confidence: 99%

Feature Selection for Partial Discharge Severity Assessment in Gas-Insulated Switchgear Based on Minimum Redundancy and Maximum Relevance

et al. 2017

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“…However, GIS has a complex structure that internal defects may come into being during process of manufacturing, transferring, and installing [5,6]. These defects will induce partial discharge (PD) [7][8][9], which causes potential internal insulation aging. The insulation aging may develop into serious fault and blackout [10,11].…”

Section: Introductionmentioning

confidence: 99%

Typical Internal Defects of Gas-Insulated Switchgear and Partial Discharge Characteristics

Zeng¹,

Tang²,

Zhang³

et al. 2018

Simulation and Modelling of Electrical Insulation Weaknesses in Electrical Equipment

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Gas-insulated switchgear (GIS) is a common electrical equipment, which uses sulfur hexafluoride (SF 6) as insulating medium instead of traditional air. It has good reliability and flexibility. However, GIS may have internal defects and partial discharge (PD) is then induced. PD will cause great harm to GIS and power system. Therefore, it is of great importance to study the intrinsic characteristics and detection of PD for online monitoring. In this chapter, typical internal defects of GIS and the PD characteristics are discussed. Several detection methods are also presented in this chapter including electromagnetic method, chemical method, and optical method.

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“…The existing literature covers a wide range of specific countermeasures, including mechanism dynamic features [8][9][10], dynamic contact resistance [11], partial discharge signal [12,13], decomposition gas [14], vibration [15], and spectroscopic monitoring [16]. Furthermore, numerous studies applied neural networks [8], support vector machine (SVM) [17], fuzzy logic [18], and other methods [19], to introduce more automation and intelligence into the signal analysis. However, these efforts were often limited to one specific aspect in their diagnosis of the failure conditions.…”

Section: Introductionmentioning

confidence: 99%

Failure Prognosis of High Voltage Circuit Breakers with Temporal Latent Dirichlet Allocation

Wang

Yang

et al. 2017

Energies

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Abstract:The continual accumulation of power grid failure logs provides a valuable but rarely used source for data mining. Sequential analysis, aiming at exploiting the temporal evolution and exploring the future trend in power grid failures, is an increasingly promising alternative for predictive scheduling and decision-making. In this paper, a temporal Latent Dirichlet Allocation (TLDA) framework is proposed to proactively reduce the cardinality of the event categories and estimate the future failure distributions by automatically uncovering the hidden patterns. The aim was to model the failure sequence as a mixture of several failure patterns, each of which was characterized by an infinite mixture of failures with certain probabilities. This state space dependency was captured by a hierarchical Bayesian framework. The model was temporally extended by establishing the long-term dependency with new co-occurrence patterns. Evaluation of the high voltage circuit breakers (HVCBs) demonstrated that the TLDA model had higher fidelities of 51.13%, 73.86%, and 92.93% in the Top-1, Top-5, and Top-10 failure prediction tasks over the baselines, respectively. In addition to the quantitative results, we showed that the TLDA can be successfully used for extracting the time-varying failure patterns and capture the failure association with a cluster coalition method.

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Application of SA-SVM Incremental Algorithm in GIS PD Pattern Recognition

Cited by 12 publications

References 17 publications

Feature Selection for Partial Discharge Severity Assessment in Gas-Insulated Switchgear Based on Minimum Redundancy and Maximum Relevance

Feature Selection for Partial Discharge Severity Assessment in Gas-Insulated Switchgear Based on Minimum Redundancy and Maximum Relevance

Typical Internal Defects of Gas-Insulated Switchgear and Partial Discharge Characteristics

Failure Prognosis of High Voltage Circuit Breakers with Temporal Latent Dirichlet Allocation

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