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Incomplete codeword recognition method for gas meter

A gas meter and codeword technology, applied in character recognition, character and pattern recognition, instruments, etc., can solve the problem of low accuracy of incomplete codeword recognition, achieve the effect of solving insufficient training and improving loss function

Active Publication Date: 2018-08-07
NORTHWEST UNIV(CN)
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Problems solved by technology

[0005] In view of the above problems, the object of the present invention is to provide a gas meter incomplete code word recognition method, which effectively solves the difficult problem of low recognition accuracy of incomplete code words

Method used

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  • Incomplete codeword recognition method for gas meter
  • Incomplete codeword recognition method for gas meter
  • Incomplete codeword recognition method for gas meter

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Experimental program
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Embodiment

[0067] The incomplete gas meter codeword recognition method of the present invention and other machine learning algorithms SVM, CNN and PSO-SVM are used to recognize the incomplete gas meter codeword respectively, and the recognition results shown in Table 1 are obtained. The operating system used is: Linux (GPU-NVIDIA GTX1060), and the deep learning library used is: TensorFlow.

[0068] Among them, see figure 1 , the convolutional neural network model in the method of the present invention comprises an input layer, a convolutional layer I, a pooling layer I, a convolutional layer II, a pooling layer II, a fully connected layer I, a fully connected layer II and In the output layer, the number of neurons in the input layer is 28*28; the convolution kernel scale of the convolutional neural network model is 3*3, and the step size of the convolution and pooling operations of the model is (1, 1 ), the activation function is RELU, the attribute value of adding padding is same, the ...

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Abstract

The invention discloses an incomplete codeword recognition method for a gas meter. On the basis of common features of a complete codeword and an incomplete codeword of a gas meter, a loss function ofa network model based on a convolutional neural network is improved to achieve an objective of training and identifying an incomplete codeword network model of the gas meter by using the complete codeword of the gas meter. Therefore, a problem that is caused by insufficient training of the deep learning model because of insufficient data volume of the incomplete codewords of the gas meter is solved completely.

Description

technical field [0001] The invention belongs to the technical field of natural gas metering, and relates to a method for identifying an incomplete code word of a gas meter. Background technique [0002] At present, among the natural gas metering tools, the traditional gas meter meter is basically a membrane type, that is, a large number of wheel-type code meters exist and use, which hinders the development and progress of information management to a certain extent. The traditional wheel-type gas meter is mainly Natural gas is counted by manual meter reading. Later, some scholars proposed feedforward (Back Propagation, BP) neural network, support vector machine (Support Vector Machine, SVM), convolutional neural network (Convolutional Neural Network, CNN), particle swarm Optimize machine learning methods such as SVM (Particle Swarm Optimization, PSO) to directly recognize the codewords of the gas meter codeword image to realize the automation of meter reading, but there are s...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/20G06K9/62
CPCG06V10/22G06V30/10G06F18/29
Inventor 张蕾苗成强卜起荣冯筠王红玉
Owner NORTHWEST UNIV(CN)
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