Electric appliance type identification method
A technology for type identification and electrical appliances, applied in character and pattern recognition, instruments, measuring electronics, etc., can solve the problems of incomplete and accurate identification, single identification means, and single feature properties, and achieve rich feature information, simple acquisition methods, and identification The effect of high accuracy
Active Publication Date: 2016-08-17
山东科德电子有限公司
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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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Embodiment 2
[0085] Example 2 selects the NBC classifier as the auxiliary classifier. Naive Bayes classification is defined as follows:
[0086] ⑴ Let x={a 1 ,a 2 ,...,a m} is an item to be classified, and each a is a characteristic attribute of x;
[0087] ⑵There is a category set C={y 1 ,y 2 ,...,y n};
[0088] (3) Calculate P(y 1 |x),P(y 2 |x),...,P(y n |x);
[0089] ⑷If P(y k |x)=max{P(y 1 |x),P(y 2 |x),...,P(y n |x)}, then x∈y k .
[0090] The specific method of calculating each conditional probability in step (3) is:
[0091] ① Find a set of items to be classified with known classification as the training sample set;
[0092] ②Statistically obtain the conditional probability estimates of each feature attribute under each category;
[0093] P(a 1 |y 1 ),P(a 2 |y 1 ),…,P(a m |y 1 );
[0094] P(a 1 |y 2 ),P(a 2 |y 2 ),…,P(a m |y 2 );
[0095] ...;
[0096] P(a 1 |y n ),P(a 2 |y n ),…,P(a m |y n ).
[0097] ③According to Bayes' theorem, there are: ...
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Disclosed is an electric appliance type identification method. The method is realized through an electric appliance type identification apparatus comprising an information acquisition module, an information processing module and a communication module. The electric appliance type identification method simultaneously employ a starting current feature of an electric appliance, a fundamental wave voltage current phase difference of the electric appliance and a load current frequency spectrum feature as identification features of electric appliance types, and thus feature information is abundant; a combined classifier including a decision tree classifier and a Bayes classifier is employed for identification classification, features of the decision-tree classifier and the Bayes classifier are taken into consideration for integrated identification, and the identification accuracy is high; and a provided method for obtaining the fundamental wave voltage current phase difference, the starting current feature and the load current frequency spectrum feature is simple and reliable. The electric appliance type identification method can be applied to some collective public places needing electric appliance management such as student dormitories, large-size markets and the like, and can also be applied to other occasions needing electrical equipment management including electric appliance type identification and statistics.
Description
technical field [0001] The invention relates to a device and method for identifying and classifying equipment, in particular to a method for identifying electrical appliances. 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 inventi...
Claims
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IPC IPC(8): G01R31/00G01R19/25G08C17/02G06K9/62
CPCG08C17/02G01R19/25G01R31/00G06F18/24155G06F18/2415
Inventor 郭艳杰凌云肖伸平
Owner 山东科德电子有限公司