Modified Expression of Moisture Diffusion Factor for Non-Oil-Immersed Insulation Paper

Wang, Dongyang; Zhou, Lijun; Wang, Lujia; Guo, Lan-Ping; Liao, Wei

doi:10.1109/access.2019.2906905

Cited by 8 publications

(4 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…where X i j is the position of the ith follower in the jth dimension, and a is the acceleration and is calculated as a = v f inal − v 0 /∆t (5) where…”

Section: Salp Swarm Algorithmmentioning

confidence: 99%

“…In addition, the insulation degradation or moisture generated by the external environment can accelerate the aging process, reduce the dielectric strength, and lower the partial discharge initiation voltage. Insulation defects are the most common cause of failure in excitation transformers and directly affect the reliability of the equipment [ 4 , 5 ]. In today’s increasingly large power demand, if a power transformer fails, it will likely cause an interruption of power supply to the energy system and bring significant economic losses.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Transformers Fault Diagnosis Method Based on Probabilistic Neural Network and Bio-Inspired Optimizer

Tao

Yang

Zhou

et al. 2021

Sensors

View full text Add to dashboard Cite

Since it is difficult for the traditional fault diagnosis method based on dissolved gas analysis (DGA) to meet today’s engineering needs in terms of diagnostic accuracy and stability, this paper proposes an artificial intelligence fault diagnosis method based on a probabilistic neural network (PNN) and bio-inspired optimizer. The PNN is used as the basic classifier of the fault diagnosis model, and the bio-inspired optimizer, improved salp swarm algorithm (ISSA), is used to optimize the hidden layer smoothing factor of PNN, which stably improves the classification performance of PNN. Compared with the traditional SSA, the sine cosine algorithm (SCA) and disruption operator are introduced in ISSA, which effectively improves the exploration capability and convergence speed. To verify the engineering applicability of the proposed method, the ISSA-PNN model was developed and tested using sensor data provided by Jiangxi Province Power Supply Company. In addition, the method is compared with machine learning methods such as support vector machine (SVM), back propagation neural network (BPNN), multi-layer perceptron (MLP), and traditional fault diagnosis methods such as the international electrotechnical commission (IEC) ratio method. The results show that the proposed method has a strong learning ability for complex fault data and has advantages in accuracy and robustness compared to other methods.

show abstract

“…where X i j is the position of the ith follower in the jth dimension, and a is the acceleration and is calculated as a = v f inal − v 0 /∆t (5) where…”

Section: Salp Swarm Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Transformers Fault Diagnosis Method Based on Probabilistic Neural Network and Bio-Inspired Optimizer

Tao

Yang

Zhou

et al. 2021

Sensors

View full text Add to dashboard Cite

show abstract

“…In the simulation model, the moisture diffusion in the capacitor core obeys the Fick's second diffusion law [21]- [23], i.e. : here, C paper is the local moisture concentration in the insulation paper, expressed in wt%, t is the diffusion time.…”

Section: ) Governing Equationmentioning

confidence: 99%

Simulation for Transient Moisture Distribution and Effects on the Electric Field in Stable Condition: 110 kV Oil-Immersed Insulation Paper Bushing

et al. 2019

Self Cite

View full text Add to dashboard Cite

Oil-immersed insulation paper (OIP) bushing is one of the most important equipment in power transmission and distribution systems. Moisture is one of the most serious factors that affect the insulation status of OIP bushing. In this paper, the OIP bushing was assumed to be in a stable and simplicity condition, and then the transient moisture distribution of capacitor core and its effects on the electric field were studied. First, by dissecting a 110 kV OIP bushing, the specific sizes for modelling were obtained. Afterwards, a moisture diffusion model for OIP bushing was established based on COMSOL Multiphysics software, and it was also verified by moisture diffusion experiment. Then, the moisture distribution for different conditions were obtained and analyzed. Finally, a model for the electric field of OIP bushing was established, and then the effects of moisture on the electric field were studied. INDEX TERMS Oil-immersed insulation paper (OIP) bushing, 110 kV, capacitor core, transient moisture distribution, electric field.

show abstract

“…As two coupled parts for the oil-paper insulation system of the oil-immersed transformers, the kraft paper usually coordinates with mineral oil or nature ester to ensure the The associate editor coordinating the review of this manuscript and approving it for publication was Canbing Li. safe and stable operation of the transformer. The kraft paper, formed with 90% cellulose, 6%-7% lignin, and pentosans, can become very brittle once exposed to thermal, electrical stresses, or both of them within a specified period [3]- [5]. For cellulose, the depolymerization process can reduce its chain length of polymer molecular during long-term service, thus resulting in a decrease of the mechanical strength.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Health Index-Based Apparent Age Estimation for Power Transformers

Dong

et al. 2020

IEEE Access

View full text Add to dashboard Cite

This paper proposes a probabilistic health index-based method for estimating the apparent age of power transformer. Compared with the conventional weighted-score-sum based health index, the probabilistic health index is calculated as a data fusion result of kinds of transformer condition monitoring data through a constructed Bayesian belief network. The regression result of such a probabilistic health index is then applied to estimate the apparent age of the transformer through a few steps listed in the paper. The apparent age not only embodies an overall health status a transformer but also helpful for sorting a transformer fleet based on the estimated apparent age or even make it easy to make comparisons between transformer fleets. The estimated apparent age can be taken as a reference for power utilities to prioritize transformers and pay attention to the unit who owns the maximum apparent age among a fleet, thus helps to schedule replacement plans. Case studies with different transformers verify the usability and prove the advantages of the proposed method. INDEX TERMS Apparent age, Bayesian belief network, condition monitoring data, health index, power transformer.

show abstract

Modified Expression of Moisture Diffusion Factor for Non-Oil-Immersed Insulation Paper

Cited by 8 publications

References 23 publications

A Novel Transformers Fault Diagnosis Method Based on Probabilistic Neural Network and Bio-Inspired Optimizer

A Novel Transformers Fault Diagnosis Method Based on Probabilistic Neural Network and Bio-Inspired Optimizer

Simulation for Transient Moisture Distribution and Effects on the Electric Field in Stable Condition: 110 kV Oil-Immersed Insulation Paper Bushing

Probabilistic Health Index-Based Apparent Age Estimation for Power Transformers

Contact Info

Product

Resources

About