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Detection and classification of process flaws using fuzzy logic

A fuzzy set and defuzzification technology, applied in the field of fuzzy logic to distributed control system, can solve impossible and difficult problems

Inactive Publication Date: 2014-06-04
SAUDI ARABIAN OIL CO
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] Fuzzy logic builds on the work of Lofti Zadeh, who noted that as the complexity of a system increases, it becomes more difficult, and eventually impossible, to state precisely how it behaves

Method used

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  • Detection and classification of process flaws using fuzzy logic
  • Detection and classification of process flaws using fuzzy logic
  • Detection and classification of process flaws using fuzzy logic

Examples

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Embodiment Construction

[0023] FIG. 1 shows a method 100 of designing a fuzzy logic controller. In step 110, the user defines the controller's inputs and outputs, which contain process observations and controller actions to be considered. At step 120, the user defines a fuzzification by means of which the input is converted to a truth value. In step 130, the user designs a rule base that links outputs to inputs, determining which actions are to be applied to which conditions. In step 140, the fuzzy inference calculation unit derives the previous truth value from the one or more fuzzified truth values, applies the selected rule weighting and implicit method, derives the output fuzzy set for each rule, and fuzzy all the output Aggregation produces a combined output fuzzy set. Finally, step 150 defuzzifies the output fuzzy set to obtain a crisp value.

[0024] A more detailed description of the system and method, along with associated text, is at Figures 2 to 5 Utilization examples are provided. T...

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Abstract

A fuzzy logic controller for a distributed control system that monitors a large electrical machine in order to detect and identify faults. Variables to be monitored by the fuzzy logic controller include oil pressure, oil temperature, and other critical variables that are used under classical logic to trip the electrical machine offline. After the input and output membership functions are identified, and a rule set is defined, the fuzzy logic controller fuzzifies the monitored variables to the input membership functions, determines an antecedent truth value, and implicates the antecedent truth value onto the output membership function, establishing a fuzzy output set. Where multiple output fuzzy sets are to be combined, they are amalgamated. The output fuzzy set or amalgamated combined output fuzzy set is then converted to a crisp value.

Description

[0001] Cross Reference Related Applications [0002] This application is based on, and claims priority from, US Provisional Patent Application No. 61 / 507,822, filed July 14, 2011, the disclosure of which is incorporated herein by reference in its entirety. technical field [0003] The present invention generally relates to the application of fuzzy logic to distributed control systems in order to detect and classify faults in electrical machines, such as faults in air compressors. Background technique [0004] A definition statement of fuzzy logic, which is a form of multivalued logic derived from fuzzy set theory, that deals with approximate rather than exact reasoning. Whereas classical propositional logic has two truth values ​​of true (1) or false (0), fuzzy logic variables have truth values ​​ranging between 0 and 1, and are not limited to the two truth values ​​of classical propositional logic. [0005] In application, fuzzy logic does not provide a user with a binary ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N5/04G06N3/04G06N7/02
CPCG06N3/0436G06N5/048G06N7/02G06N3/043
Inventor Y·H·阿尔穆巴拉克
Owner SAUDI ARABIAN OIL CO
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