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Wireless sensor fault diagnosis algorithm based on convolutional neural network

A convolutional neural network and fault diagnosis algorithm technology, applied in biological neural network models, neural learning methods, network planning, etc., can solve problems such as nodes unable to communicate, how high the algorithm requires neighbor nodes, and fault diagnosis prone to errors.

Active Publication Date: 2019-04-16
FUJIAN NORMAL UNIV
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Problems solved by technology

[0005] (2) Hard failure node: the node cannot communicate, so the sensing data of the node cannot be received;
Although the distributed fault diagnosis algorithm alleviates the problem of excessive energy consumption of network nodes, the algorithm has high requirements for neighbor nodes. Accurate fault detection for nodes in wireless sensor networks with high rate

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  • Wireless sensor fault diagnosis algorithm based on convolutional neural network

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Embodiment Construction

[0028] Such as figure 1 Shown, the wireless sensor fault diagnosis algorithm based on convolutional neural network of the present invention, it comprises the following steps:

[0029] 1) Construct a wireless sensor network system model, which consists of a base station, a mobile car and several rechargeable wireless sensor nodes statically arranged in the monitoring area;

[0030] 2) Construct a convolutional neural network at the base station. The structure of the convolutional neural network is a sequentially connected input layer, hidden layer, fully connected layer, and output layer, where the hidden layer consists of at least one set of sequentially connected convolutional layers and pooling layers;

[0031] 3) Use the mobile car to collect the sensing data of all nodes in the wireless sensor network and transmit it to the base station. The base station stores the sensing data of all nodes and converts it into a matrix and inputs it into the convolutional neural network;...

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Abstract

The invention relates to a wireless sensor fault diagnosis algorithm based on a convolutional neural network. The algorithm comprises the following steps of (1) constructing a wireless sensor networksystem model formed by a base station, a movable trolley and a plurality of chargeable wireless sensor nodes; (2) constructing the convolutional neural network which is connected to an input layer, ahidden layer, a full-connection layer and an output layer in sequence on the base station; (3) utilizing the movable trolley to collect sensing data of all the nodes and transmit the sensing data to the base station for storage, and converting the sensing data into a matrix form; (4) inputting the sensing data in the matrix form into the convolutional neural network for training and self-learning,extracting data features through a convolution kernel of a convolution layer, compressing the data features through a pooling layer, connecting the full-connection layer to the last two layers, and outputting a final data classification result through the output layer; and (5) making the convolution neural network carry out fault diagnosis on the corresponding sensor fault type corresponding to each type according to the data classification result, and outputting a node diagnosis state through the output layer.

Description

technical field [0001] The invention relates to the technical field of wireless sensors, in particular to a convolutional neural network-based wireless sensor fault diagnosis algorithm. Background technique [0002] A wireless sensor network is composed of several wireless sensor nodes in the form of self-organization. A wireless sensor node is mainly composed of four parts: sensor module, CPU module, wireless communication module and power module. Among them, the sensor module is mainly used to sense data, and the CPU module The role of the sensor is to process and calculate data, the wireless communication module ensures that the sensor node communicates with other sensor nodes, and the power supply module carries limited energy to provide energy for the sensor node. Due to the small size, easy deployment, and low price of wireless sensor nodes, they are widely used in all aspects of life. With the enhancement of wireless sensor computing power and storage capacity, wirele...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W16/22H04W24/04H04W40/02H04W40/10G06N3/04G06N3/08H04W84/18
CPCH04W16/225H04W24/04H04W40/02H04W40/10H04W84/18G06N3/08G06N3/045
Inventor 陈志德马梦莹龚平郑金花许力黄欣沂
Owner FUJIAN NORMAL UNIV