The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Condition monitoring and fault diagnosis is the groundwork of condition-based maintenance, and much research has been done about diagnostic algorithm and monitoring manufactures, but less research about diagnostics strategy and management. Plenary diagnostics based on event driven threads of data propagated through successive diagnostic levels is an improving attempt about it. In this approach, abnormities...
Power companies arrange regular training sessions to keep their operators ready to face blackout events, and expert systems play an important role in achieving this goal. Expert systems [1] have been proven to be an effective platform for diagnostic and control applications in power industry. Conventional expert systems are PC based and are not of much use where the expertise is required over a large...
Incipient fault diagnosis of a power transformer is greatly influenced by the condition assessment of its insulation system specifically oil/paper insulation. In recent times, a number of intelligent methods based on AI techniques, Artificial Neural Network and Fuzzy Logic have been used to predict incipient faults in a power transformer based on its insulation studies under various kinds of stresses...
Based on investigation within China, The introduction of CMD to power utilities was developed more quickly than before. And a lot of experience and useful lessons were analyzed, and by the way many ineffective or unstable apparatuses or systems for testing or monitoring were eliminated step by step. More utilities realized, that the first thing is how to realize the actual condition of power equipment...
Transformer fault diagnosis based on artificial neural networks (ANN) is widely used, because ANN has essential nonlinear character, parallel processing ability and the ability of self organize and self learning. But there exist problems if we use traditional ANN method alone to diagnose transformer fault, the large input vector dimension and complex training database will cause the computation complexity...
This paper is a review and evaluation of different on-line methods for diagnosing winding fault in induction motors presented in literature. Many methods can be found in literature; in some references, frequency analysis of motor signals such as current, speed, instantaneous power, Parkpsilas vector modulus and so on are introduced. Evaluation of negative sequence of current is also among the proposed...
Dissolved gas analysis (DGA) is one of the most useful techniques to detect the incipient faults of power transformer. This paper is a study of artificial neural networks (ANN) applications for the diagnosis of power transformer incipient fault. The fault diagnosis is based on dissolved gas-in-oil analysis (DGA). Using historical transformer failure data, a multi-layer perceptron (MLP) neural network...
Hydro generator excitation system is one of the most maintenance intensive subsystem in hydro power plants. A real time embedded maintenance system of the excitation system is studied. A knowledge bank, which summarizes both the expert knowledge and the analytical knowledge on the failure modes and their manifestations as well as their effects, is established. An expert system is developed to optimize...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.