Electric appliance type determination device
A technology of judgers and electrical appliances, applied in the fields of instruments, measuring electricity, measuring electrical variables, etc., can solve problems such as incomplete accurate identification, insufficient generalization ability, and single feature nature, and achieve rich feature information and high generalization ability. , get the effect of a simple method
Inactive Publication Date: 2016-08-31
HUNAN UNIV OF TECH
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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
[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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The invention discloses an electric appliance type determination device, comprising an information collection module, an information processing module, and a communication module. The electric appliance type determination device employs electric appliance starting current characteristics including starting process time, a starting current maximum value and starting current maximum value time and load current frequency spectrum characteristics of the electric appliance as identification characteristics, and the characteristic information is rich; the electric appliance type determination device adopts a combined classifier comprising a decision-making tree classifier and a Bayes classifier to perform identification classification and performs comprehensive identification in consideration of characteristics of the decision-making tree classifier and a Bayes classifier; and the identification accuracy is high. Provided methods for obtaining starting current characteristics and load current frequency spectrum characteristics are simple and reliable. The electric appliance type determination device can be used some collective public places like a students' dormitory, a large-scale pedlars market, etc, where need to perform electric appliance management and can also used in some other places where need to perform electric appliance type identification and statistics and to perform electric appliance management.
Description
technical field [0001] The invention relates to a device for identifying and classifying equipment, in particular to a device for determining the type of 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 invent...
Claims
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Login to View More IPC IPC(8): G06K9/00G06K9/62G01R31/00
CPCG01R31/00G06F2218/02G06F2218/12G06F18/285G06F18/24155
Inventor 郭艳杰凌云袁川来
Owner HUNAN UNIV OF TECH