Rayleigh Wave Method In The Application Of The Railway Roadbed Compaction Degree Test And Theory Research

Under the background of our country put forward ‘One Belt and One Road’ project Railway as the foundation engineering occupies a very important position, the key area of Xinjiang region and as a development strategy, and therefore is given priority to with desert landscape of Xinjiang area building project will be more and more frequent, including the Gobi area of engineering the middle base project very large proportion, and the roadbed and the embankment compaction quality is the key to railway construction quality control and inspection of indicators. Current there are many different kinds of roadbed compaction quality detection method and some detection methods already form a very mature testing system, but the current detection method has many defects, its has been more and more difficult to be rapid, comprehensive and accurate reflection of the roadbed compaction quality, Simple and rapid method of compaction test is the urgent requirement of railway construction situation.Under construction and completed in this paper based on Xinjiang’ two railways compaction test, analyzed the home and abroad relevant results and a new method for the detection of railway roadbed compaction degree, on the basis of Rayleigh wave detection method research, conducted in three different Gobi packing cases.Rayleigh wave method and the roadbed mechanics index ’K30’ correlation statistical experiment. Through different packing method of Rayleigh wave velocity value and ‘K30’ empirical formula, using mechanical index of the stability of roadbed, Rayleigh wave was deduced under three different packing inspection standard, solved the inspectors in the Gobi desert soil application of Rayleigh wave technique to packing area not specification can be according to the situation, found a new way to solve the problem.With Rayleigh wave velocity value by ‘K30’ as an example, the relationship between, the advantages of using the method of Rayleigh wave detection method, based on Rayleigh wave method in the roadbed quality statistical evaluation mathematical model, based on the test results of Rayleigh wave method, directly to the comprehensive analysis of roadbed and other physical parameters of roadbed quality inspection is necessary, while save the detection time, and saving the cost of engineering detection.In the application of Rayleigh wave method to calculate the roadbed compaction degree, the existing application method is mainly to establish the experience formula of the dry density and wave velocity values, and then through the check formula, calculate the stretch maximum dry density of the maximum wave velocity, then calculate the corresponding testing point of compaction. The disadvantages of this kind of calculation method for the calculation method is tedious, and in the process of calculating data loss is big, and then make the Rayleigh wave method to calculate the degree of compaction of the error is bigger, affect the Rayleigh wave method in the application of the compaction test. the Artificial Neural Network model is applied in this article, through directly compaction degree and the method of Rayleigh wave velocity value, through the network training, the generalization ability of network authentication, quick to calculate the wave velocity value that corresponds to the degree of compaction, reduces the calculation error, simplifies the Rayleigh wave method to calculate the calculation of degree of compaction process. In the application of Rayleigh wave method to the railway roadbed detection process, a large number of indoor and outdoor geotechnical experiment was carried out, has carried on the detailed study the characteristic of the Gobi packing, found the unique property of filler is common Gobi, at the same time, also optimized the Rayleigh wave method in the application in the process of testing parameters.All in all, this article through to the current railway roadbed quality double control index, the degree of compaction coefficient ‘K ‘and foundation ‘K30’, establish correlation, standardizes the Rayleigh wave applied in the railway roadbed quality testing. Also targeted to study the two railway lines along the Gobi packing, in the Hong nao san railway mainly studies the three types of roadbed filling: such as sand soils in medium sand, gravel coarse breccia, such as soil, gravel fine breccia in the soil. The main research in the E ha railway, such as sand soil in the gravel soil and gravel soil. Mathematical statistics analysis of the study the method of Rayleigh wave velocity value and ‘K30’ and compaction degree K under specific packing of empirical formula, and combined with ‘K30’ and Rayleigh wave method, the relationship between roadbed quality evaluation mathematical model is established, the application of BP neural network model simplifies the Rayleigh wave new algorithm for calculating the degree of compaction, reduces the error of the Rayleigh wave method, improve the detection accuracy.