Self Powered Sensor Pavement Monitoring System Based On Compressed Sensing

In recent years,the importance of pavement in highway construction is becoming increasingly prominent,the premise of road maintenance is to know the road damage in advance.and the temperature and humidity are the key factors leading to the unbalanced deformation of the roadbed,so it is necessary to continuously monitor the temperature and humidity signals of the roadbed.The sensor technology based on compression sensing wireless is widely used in roadbed temperature and humidity data collection.Based on the research of wireless sensor technology,self-powered technology and compression perception theory,this paper presents a scheme of self-powered wireless sensor pavement monitoring system based on compression perception.the design of point-to-point communication,self-powered energy collection,PC management platform and compression reconstruction algorithm in this scheme are designed and studied.Wireless sensor data acquisition system designed in this paper using PC monitoring platform of base temperature and humidity data for the monitoring and treatment.At the same time,the communication state of the data acquisition and sending terminal is tested by serial debugging assistant,and the communication state of the transmitter is good by analyzing the test result.The system uses a self powered micro energy harvesting circuit of buried in the pavement surface using piezoelectric transducer by epoxy resin package rutmeter caused by compaction of electricity were collected.Finally,combining the experimental results of energy collection and the energy consumption analysis results of data acquisition and transmitter,the electric quantity analysis is carried out.The analysis shows that the sensor system based on traditional sampling can not achieve self power supply better.This paper uses compressed sensing and sparse sampling based mixed conventional Shannon sampling and power consumed for road base temperature humidity signal acquisition is simulated and analyzed based on,and use of compressed sensing is conducive to the realization of the self powered system was verified and analyzed.The simulation and analysis to know:(1)the conventional DCT,DWangT,DHT based sparse and mixed sparse matrix DHT+DWT can be realized on the temperature and humidity signal sparse expression;(2)the conventional sparse basis between only with Gauss and Bernoulli,part of the orthogonal random matrix showed low correlation,and mixed between the sparse base and Gauss,Bernoulli,part of the orthogonal and sparse random matrices showed low correlation,the Gauss random matrix based on DHT base and DHT+DWT base based on sparse randommatrices in OMP reconstruction algorithm can reconstruct the low compression temperature and humidity signal better;(3)the performance of road base temperature humidity signal reconstruction algorithm of BP DHT based random Gauss matrix of the superior based on based on sparse random matrices DHT+DWT based BP algorithm.Finally,according to the BP algorithm of Gauss random matrix DHT based knowledge measurement required for accurate reconstruction of road base temperature humidity signal are respectively 504 and 524,is about the traditional number of sampling required for 1/2,and a 61.72% reduction in energy consumption,so the CS sampling has better to realize the self power supply system.