The Experts below are selected from a list of 318 Experts worldwide ranked by ideXlab platform

Soib Taib - One of the best experts on this subject based on the ideXlab platform.

  • application of infrared thermography for predictive preventive maintenance of thermal defect in Electrical Equipment
    Applied Thermal Engineering, 2013
    Co-Authors: A Nazmul S Huda, Soib Taib
    Abstract:

    Internal heat of Electrical Equipment rises due to various reasons such as contact problems, unbalance loading, cracks in insulation, defective relays or terminal blocks, etc until eventual failure which can cause unplanned outages and possible injuries. Therefore, early prevention of thermal abnormalities in Electrical Equipment is necessary to avoid failure. Nowadays a fast, reliable, non-contact and cost effective infrared thermographic inspection system is being utilized widely for detecting where and how internal and external defects occur in Equipment. The system collects data for investigating thermal condition through the analysis of thermal image of Equipment. The image is captured by infrared camera without interrupting the running operation of system. Both preventive and predictive maintenance programs are adopted for defect diagnosis. Actually, the frequency and sequence of thermographic inspection depend on various factors including thermal condition, expense of a failure, type of production and age of Equipment, etc. The objectives of this article are to discuss about preventive and predictive maintenance, thermal defects in Electrical Equipment and also an intelligent thermal defect identification system for accelerating the predictive defect diagnosis technique. The intelligent system proposes the application of artificial neural network and statistical features to detect the existence of defect within Equipment by monitoring its thermal condition. Using discriminant analysis, the optimum features were chosen as the inputs of the neural network. The performances of the neural network were compared with the performances of discriminant analysis classifier. The comparison results showed that discriminant analysis classifier produced better performance with accuracy 82.40%.

A Nazmul S Huda - One of the best experts on this subject based on the ideXlab platform.

  • application of infrared thermography for predictive preventive maintenance of thermal defect in Electrical Equipment
    Applied Thermal Engineering, 2013
    Co-Authors: A Nazmul S Huda, Soib Taib
    Abstract:

    Internal heat of Electrical Equipment rises due to various reasons such as contact problems, unbalance loading, cracks in insulation, defective relays or terminal blocks, etc until eventual failure which can cause unplanned outages and possible injuries. Therefore, early prevention of thermal abnormalities in Electrical Equipment is necessary to avoid failure. Nowadays a fast, reliable, non-contact and cost effective infrared thermographic inspection system is being utilized widely for detecting where and how internal and external defects occur in Equipment. The system collects data for investigating thermal condition through the analysis of thermal image of Equipment. The image is captured by infrared camera without interrupting the running operation of system. Both preventive and predictive maintenance programs are adopted for defect diagnosis. Actually, the frequency and sequence of thermographic inspection depend on various factors including thermal condition, expense of a failure, type of production and age of Equipment, etc. The objectives of this article are to discuss about preventive and predictive maintenance, thermal defects in Electrical Equipment and also an intelligent thermal defect identification system for accelerating the predictive defect diagnosis technique. The intelligent system proposes the application of artificial neural network and statistical features to detect the existence of defect within Equipment by monitoring its thermal condition. Using discriminant analysis, the optimum features were chosen as the inputs of the neural network. The performances of the neural network were compared with the performances of discriminant analysis classifier. The comparison results showed that discriminant analysis classifier produced better performance with accuracy 82.40%.

Cao Mei-gen - One of the best experts on this subject based on the ideXlab platform.

  • Application of Base Isolation in High Voltage Electrical Equipment
    Power system technology, 2007
    Co-Authors: Cao Mei-gen
    Abstract:

    The insulation member of high voltage Electrical Equipment is constitutive of porcelain insulator. The porcelain insulator is made by a kind of brittle material and it has a poor flexural performance. The porcelain insulator endures the considerable bending moment in earthquake, which causes the brittle destroy of porcelain insulator. Especially, the uncoordinated deformation increases the destruction on the connection of porcelain insulator and other materials. In order to solve the damage of high voltage Electrical Equipment in earthquake and discuss the feasibility of base isolation in high voltage Electrical Equipment, the seismic response analysis of isolation and non-isolation in high-voltage disconnector is studied in this thesis.

Yang Jing-sha - One of the best experts on this subject based on the ideXlab platform.

Zhu Yun - One of the best experts on this subject based on the ideXlab platform.