Research On Gap Fixing And Data Transmission Technology Of Wireless Sensor Network For Harmful Gas Detection

With the development of industry in China,chemical fuels have been intensively applied to industrial production,generating a huge amount of harmful gases?e.g.Cl ₂,CO,NO₂ and SO₂?.If the harmful gases are released into the air,these will pollute the environment,affect the ecological balance,and cause disasters like poisoning,fire and explosion,etc.,posing a serious threat to human life and property safety.To protect the environment and prevent the disasters,it is of great necessity to detect the leakage of harmful gasses in an effective manner.The classical harmful gas detection methods mainly include wired fixtures and portable instruments,which have some shortcomings,such as poor flexibility,poor real-time performance,to inaccurate positioning of leak points.The WSN enjoys a low cost,and does well in real-time detection and collaboration,which provides a new idea for remote detection of harmful gases.However,the energy of WSN is rather limited.To apply WSN in harmful gas detection,the main technical difficulty lies in the way to increase network coverage without sacrificing the balance of energy consumption and network life.This paper focuses on harmful gases detection for WSN in industrial environment from the following aspects:developing mobile detection nodes,fixing coverage gap of WSN,as well as the collection and transmission of network data.The main research contents are as follows:1.The development of mobile detection nodes for harmful gas in WSN:A wireless detection system for harmful gases based on multi-sensor was developed to overcome the defect of the WSN with static nodes,that is,the few immovable nodes cannot effectively cover every leak position in the detection area.The system can realize remote wireless detection of such four harmful gases as Cl₂,CO,NO₂ and SO₂.The front-end detection device of the system can be used as a mobile detection node in the process of WSN formation to improve the coverage of network detection.2.The improved WSN coverage gap fixing method:The harmful gas leakage area cannot be pre-determined,and the random deployment of static nodes may create coverage gaps.However,the classical gap fixing method covers the gaps randomly with mobile sensor nodes,failing to achieve a high coverage despite the huge resource consumption.To solve the problem,the paper proposes an improved WSN coverage gap fixing method based on the fixing priority.Firstly,the fixing priority was determined based on the size of coverage gaps,ensuring the post-fixing coverage.Next,the gap fixing method was improved to eliminate the sensing range overlap between fixing nodes that are close to each other.The improved method reduces node redundancy and balances resource allocation.3.The WSN data transmission method based on non-uniform clustering:Under the traditional clustering routing protocol,the cluster head nodes close to the base station may die prematurely due to excessive energy consumption.In light of this,a routing protocol was put forward based on non-uniform clustering.The competition radius was introduced to save more energy for data transmission.The farther a node is from the base station,the greater its competition node and the larger the resulting cluster.To further optimize the energy consumption in the network,the optimal cluster head was selected by the entropy weight method,after overall consideration of indices like the relative residual energy,relative distance,relative density and relative centrality.On this basis,the cost function for inter-cluster communication was established from distance and energy,thus reducing the energy loss and extending the life of the network.4.The WSN data acquisition method based on compressed sensing:The sensor nodes in the WSN have limited computing and communication capabilities,which seriously affect the network life.The compressed sensing theory can compress sparse signals and reconstruct the original signal with high probability,reducing the signal acquisition cost.Considering the sparsity of harmful gas content in industrial WSNs and the high cost of WSN data acquisition,the paper compresses and reconstructs the collected data on harmful gas content based on the compressed sensing theory and the iteratively smoothed l₀ norm minimization algorithm.The algorithm solves the minimum l₀ norm by descending iteration and then restores the original signal by finding the sparse solution,thus effectively reducing the data acquisition cost of the WSN.