Research On Optimization Design Method Of Barkhausen Signals Transmission And Detection Circuit Of Seamless Rail

In order to resloved the key research difficulties such as the lack of multiple factors assessment model for Barkhausen signal,and the research on the safety,stability,and efficient transmission of signal detection under the constraints of circuit resource configuration and complex electromagnetic environment,the dissertation established and analyzed the model between the change of detection depth,temperature and yoke lift-off with the stress and the Barkhausen signal eigenvalue.The accuracy of Barkhausen signal detection can be improved,with the compensation program is optimized for Barkhausen signal attenuation.The circuits are optimized to improve the signal transmission security,transmission rate and quality,and reduce the hardware resource consumption.The main work and innovations of the dissertation are as follows.The dissertation proposed the model equation for the detection depth change under compressive and tensile stress conditions.The measured data and the trend of the optimization curve all verify the correctness of the depth change model to some extent.Based on the RBF algorithm,the Barkhausen signal detection accuracy was improved.The dissertation deduced and simulated the depth model by the skin effect equation and the basic equations of Barkhausen effect.Using stress-stretching and four-point stress loading platforms,different stress conditions are applied to obtain the test data for the respective eigenvalues of the Barkhausen signal.Through the comparison of data normalization,the RMS value of the signal with linear variation of stress is selected as the eigenvalue of the analysis and comparison,and then the optimal input excitation signal frequency and amplitude combination for depth change analysis is determined.The combing comparison of the test data is carried out by 4groups of stress and four-point stress loading tests.The test results optimized by RBF algorithm,and compared with the measured data and the model simulation results.The results showed that the detection accuracy deviation can be controlled within the range of 6%.The dissertation proposed the temperature stress model equation and optimized the design of the signal attenuation wavelet reconstruction temperature compensation program based on RBF algorithm,which effectively reduced the temperature effect and greatly improved the detection accuracy.On the four-point stress loading test,the dissertation compared the Barkhausen signal eigenvalues,which measured at the temperature and stress changes,and analyzed the close correlation between the signal eigenvalues with temperature and pressure in combination with the temperature stress model.Data error analysis is also performed.For the reduction of the characteristic value caused by the temperature change,the temperature compensation optimization is performed using the RBF algorithm.Through the wavelet decomposition of the signal,the key layer signal is extracted and optimized.The test results showed that the initial optimization of the numerical deviation is controlled between 0.11%and 3.6%.The result of the optimization using the reconstructed signal is further increased by 1-2 orders of magnitude.The dissertation proposed the equation of lift-off change,optimized the sensor structure and the signal attenuation compensation scheme based on RBF algorithm,effectively reduced the lift-off effect,and greatly improved the detection accuracy.Based on the magnetic flux leakage equation,the dissertation deduced and analysed of the correlation between the lift-off distance,stress change,and Barkhausen signal eigenvalues.Combined with the yoke lift-off electromagnetic simulation results,the sensor structure circuit and signal attenuation compensation scheme are optimized.The test data showed that although the results of the optimization result in the deviation of the calibration value,the deviation is much lower than the improvement of the detection accuracy,and the optimization accuracy deviation can be controlled within 1%.The GF((2~2)~2)~2)AES masked S-box circuit is optimized and synthesized by the 0.18μm CMOS process.The multiplication inverse unit and the mask S-box reduced 74 gates and 83 gates,and area consumption decreased by 9.45%and 8.84%respectively.The dissertation designed an adaptive precoding/STBC baseband transceiver for the reconfigurable architecture.By adding the CSD feedback loop,the UCD and UCD+STBC modes can be flexibly transformed to achieve better transmission performance and better performance and higher data rate.The optimized results are achieved and verified at a working frequency of 150 MHz through a 0.18μm ASIC process and the Xilinx xc4vlx Virtex-4 FPGA.The dissertation optimized the ADDLL circuit controlled by the variable successive approximation register to achieve clock synchronization between chips and eliminate harmonic lock.Under the 65nm CMOS low-power process conditions,the longest lock time is fixed at 103 in the entire operating frequency range.The dissertation integrated the corresponding research results and developed a set of seamless steel rail stress detection devices that can be detected online.The feasibility of the testing program and the reliability of the testing device are tested through field measurements at different temperatures and in different types of work modes,and validated the analysis results of the model equations.