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Electric appliance type identification device

A technology for type identification and electrical appliances, applied in measuring devices, instruments, measuring electricity and other directions, can solve problems such as incomplete accurate identification, insufficient generalization ability, and single feature nature, and achieve rich feature information, high generalization ability, and acquisition. simple method effect

Inactive Publication Date: 2016-08-24
HUNAN UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Various methods can realize the identification of electrical load properties to a certain extent, but due to the single feature nature and single identification means, there are generally problems of insufficient generalization ability and incomplete and accurate identification.

Method used

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  • Electric appliance type identification device
  • Electric appliance type identification device
  • Electric appliance type identification device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 2

[0076] Example 2 selects the NBC classifier as the auxiliary classifier. Naive Bayes classification is defined as follows:

[0077] ⑴ Let x={a 1 ,a 2 ,...,a m} is an item to be classified, and each a is a characteristic attribute of x;

[0078] ⑵There is a category set C={y 1 ,y 2 ,...,y n};

[0079] (3) Calculate P(y 1 |x),P(y 2 |x),...,P(y n |x);

[0080] ⑷If P(y k |x)=max{P(y 1 |x),P(y 2 |x),...,P(y n |x)}, then x∈y k .

[0081] The specific method of calculating each conditional probability in step (3) is:

[0082] ① Find a set of items to be classified with known classification as the training sample set;

[0083] ②Statistically obtain the conditional probability estimates of each feature attribute under each category;

[0084] P(a 1 |y 1 ),P(a 2 |y 1 ),…,P(a m |y 1 );

[0085] P(a 1 |y 2 ),P(a 2 |y 2 ),…,P(a m |y 2 );

[0086] ...;

[0087] P(a 1 |y n ),P(a 2 |y n ),…,P(a m |y n ).

[0088] ③According to Bayes' theorem, there are:...

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Abstract

An electric appliance type identification device comprises an information acquisition module, an information processing module and a communication module, is abundant in characteristic information by adopting the electric appliance starting current characteristics comprising the starting process time, the starting current maximum value and the starting current maximum value time and the load current frequency spectrum characteristics of the electric appliances simultaneously as the identification characteristics, and is high in identification accuracy by adopting a combined classifier comprising a BP neural network classifier and a Bayes classifier to identify and classify, and simultaneously considering the characteristics of the BP neural network classifier and the Bayes classifier to identify comprehensively, and the provided starting current characteristic and load current frequency spectrum characteristic obtaining methods are simple and reliable. The electric appliance type identification device can be used in the collective public places needing the electrical appliance management, such as the student dormitories, the large-scale pedlars' markets, etc., and also can be used at other power consumption equipment management places needing the electric appliance type identification and statistics.

Description

technical field [0001] The invention relates to an equipment identification and classification device, in particular to an electrical appliance type identification device. Background technique [0002] At present, the mainstream electrical load identification methods include the electrical load identification method based on the load power comprehensive coefficient algorithm, the electrical load identification method based on electromagnetic induction, the electrical load identification method based on the neural network algorithm, and the electrical load identification method based on the periodic discrete transformation algorithm. identification method, etc. Various methods can realize the identification of electrical load properties to a certain extent, but due to the single characteristic properties and single identification means, there are generally problems of insufficient generalization ability and incomplete and accurate identification. Contents of the invention ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/00
CPCG01R31/00
Inventor 凌云肖伸平王兵唐文妍
Owner HUNAN UNIV OF TECH
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