Diagnosis of inhomogeneous insulation degradation in electric cables by distributed shunt conductance estimation

Zhang, Qinghua; Tang, Huaibin

doi:10.1016/j.conengprac.2013.04.006

Cited by 8 publications

(5 citation statements)

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“…For future works, applications to mechanical structure vibration analysis will be investigated. Some previous studies on fault diagnosis will also be revisited in order to relax the limitation about fault parameter vectors, such as in [49].…”

Section: Discussionmentioning

confidence: 99%

Dynamic System Fault Diagnosis Under Sparseness Assumption

Zhang

2021

IEEE Trans. Signal Process.

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Dynamic system fault diagnosis is often faced with a large number of possible faults. The purpose of this paper is to propose an efficient method for such situations. To avoid intractable combinatorial problems, sparse estimation techniques appear to be a powerful tool for isolating faults, under the assumption that only a small number of possible faults can be simultaneously active. However, sparse estimation is often studied in the framework of linear algebraic equations, whereas model-based fault diagnosis is usually investigated for dynamic systems modeled with state equations involving internal states. The main contribution of this paper is a link between these two formalisms through efficient and reliable algorithms, mainly relying on advanced analyses of residuals generated with the Kalman and Kitanidis filters. Based on these results, it becomes straightforward to solve fault diagnosis problems by applying well known sparse estimation techniques, in the framework of general time varying state-space systems involving unknown inputs.

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Section: Discussionmentioning

confidence: 99%

Dynamic System Fault Diagnosis Under Sparseness Assumption

Zhang

2021

IEEE Trans. Signal Process.

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“…Then, the perturbation analysis linearizes the bilinear term G(x)V(t, x) and yields two fictive systems: the zero-order system characterizing the nominal behavior corresponding to G(x) = G 0 (x), and the first-order system describing the small deviation from the nominal behavior. See [15] for the details of the perturbation analysis in the particular case of G 0 (x) = 0. See also the footnote at the bottom of this page.…”

Section: Perturbation Analysis and Space-time Discretizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Compared to cable impedance, relatively few studies on shunt conductance monitoring have been reported [11][12][13][14][15], and they often assume constant conductance per unit length along the whole cable. Non-uniform shunt conductance has been considered in [13,15]. To estimate a large number of discretized shunt conductance values along a long cable with sufficient accuracy (shunt conductance is typically at the order of 10 −10 Siemens/meter), large data sets have to be processed, requiring considerable computer memory and computation time.…”

Section: Introductionmentioning

confidence: 99%

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Electric Cable Insulator Damage Monitoring by Lasso Regression

Zhang,

Drissi-Habti

2024

Machines

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Since the discovery of electricity, electric cables have become ubiquitous in human constructions, from machines to buildings. Insulators play a crucial role in ensuring the proper functioning of these cables, so it is important to monitor their possible damage, which can be caused by environmental contamination, severe temperature variations, and electrical and mechanical stress. While shunt conductance is a direct health indicator of cable insulation, measuring the cable average shunt conductance is not sufficient for the detection of localized insulator damage, since localized conductance variations are diluted over a long cable length in such measurements. The objective of this paper is to assess the feasibility of reflectometry techniques for the monitoring of insulator damage in electric cables. To this end, the estimation of localized conductance variations is investigated based on electrical measurements made at one end of a cable. To avoid estimating a large number of discretized conductance values along a long cable, the proposed method relies on sparse regression, which automatically focuses on localized conductance variations at unknown positions caused by accidental insulator damage. In order to efficiently apply sparse regression techniques, the telegrapher’s equations describing electric wave propagation in cables are transformed through several steps into a simple linear regression form. Then, Lasso (Least Absolute Shrinkage and Selection Operator) regression is applied to process the voltage and current data collected at a single end of the monitored cable. Numerical simulations show the potential of this method for fast estimation of localized shunt conductance variations.

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“…При эксплуатации распределительных электрических сетей основными требованиями, предъявляемыми к электрическим установкам, являются надежность снабжения потребителей электрической энергией и безопасность эксплуатации элек-трооборудования. Безопасность эксплуатации электрооборудования в значительной мере определяется состоянием изоляции электрических сетей и установок [1,3,11,[12][13][14][15][16][17].…”

Section: Introductionunclassified

Isolation Control in the “Tarror” Quarry Distribution Network

Boboev¹,

Averyanov²,

Bogdanov³

et al. 2021

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The reliability and operation safety of electrical equipment, as well as the level of electrical and fire safety at mining enterprises are directly related to the state of electrical networks insulation, and particularly the value of the total insulation resistance relative to the ground. Controlling these parameters in the electrical equipment operation allows increasing the efficiency and reliability of such equipment. The paper concentrates on the current problem of selecting methods to monitor the isolation parameters of the network phases relative to the ground in the distribution electric networks with an isolated neutral. It briefly describes “Zeravshan” joint venture, the isolation control system developed for it and the results of its computer model based operability tests. Studies have shown that at rated load in the network, the error in determining the total insulation resistance is under 20%, which proves the operability of the proposed network phase isolation monitoring system relative to the ground. Thus, the implementation of the developed insulation parameter monitoring system in distribution networks operation will improve the reliability and safety of power supply.

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Diagnosis of inhomogeneous insulation degradation in electric cables by distributed shunt conductance estimation

Cited by 8 publications

References 8 publications

Dynamic System Fault Diagnosis Under Sparseness Assumption

Dynamic System Fault Diagnosis Under Sparseness Assumption

Electric Cable Insulator Damage Monitoring by Lasso Regression

Isolation Control in the “Tarror” Quarry Distribution Network

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