Detection Technology Of Ice,Snow And Water Condition On Road Surface Based On Smart Road Studs

With the rapid development of road traffic in our country,the frequency of traffic accidents is increasing year by year.Road icing is one of the main causes of road traffic accidents.Therefore,the pavement meteorological information monitoring and early warning system is of great significance to ensure traffic safety.At present,the commercial road monitoring equipment has the limitations of easy damage,large equipment volume,high cost and only single point detection.Therefore,this paper proposes a road embedded ice and snow water detection system based on Intelligent spikes.Relying on advanced communication technology,a set of road real-time detection and remote platform monitoring system is built.The whole system consists of road monitoring equipment and wireless Internet of things platform.First of all,this paper proposes the detection principle and system scheme of ice and snow water based on multi-source reflection and multi-sensor fusion detection technology.By studying the relationship between reflection and absorption of different wavelengths,a differential model of wavelength absorption is established.Secondly,the structure of ice and snow water detection system based on Intelligent spikes is determined.Sensor selection,circuit schematic and PCB design,embedded software programming,forming the prototype of the detection system.Thirdly,design experiments to verify the influence of environmental factors on the experimental device,calculate the significant difference level through one-way ANOVA,and exclude the influence of temperature and light intensity on the experimental device.The experiment of three-state process of ice and snow water is carried out,the characteristics of process waveform are analyzed,and the experiment is designed to verify the influence of non environmental factors(turbidity,bubble number and wear degree)on the state reference value.Finally,based on multi-sensor fusion detection technology to obtain road diversification information parameters,through multiple linear regression to build the calculation formula of state reference value,to solve the problem of base value drift caused by non environmental factors.A three-state recognition algorithm of ice and snow water based on state reference value is proposed,and its accuracy is verified by an example.Aiming at the problem that the mixed state of ice and snow water has a wide range of base values and is difficult to quantify,an algorithm based on process quantity is proposed to recognize the inter state of ice and snow water,and a model is built based on adaptive BP neural network to realize the recognition of the inter state process of ice and snow water,which is verified by an example.In the research process of this paper,consult a large number of references,verify the experimental principle,compare the research scheme,and select the overall scheme of the system which is suitable for the requirements of this paper.A large number of experiments are carried out to analyze various factors and design a three-state recognition algorithm for ice and snow water.Experiments show that the accuracy of the three-state recognition algorithm based on the state reference value is up to 90%,and the total error of the intermediate state recognition algorithm based on the process quantity is less than 5%,that is to say,the ice and snow water detection technology designed in this paper has high accuracy.