The Calibration Of Coal Mine Production Monitoring Equipment’s Data

With the promotion of China’s coal industry digitization and the expansion of productionprocess safety monitoring range in-depth, many detection techniques are gradually introducedinto the process of real-time monitoring in mine production, such as microseisms, ultrasonic,radar, sonar, infrared, optical fiber. Various types of data gathering from production site is astrong guarantee to ensure mine safety production. The correction method of mineproduction’s accurate monitoring data is studied in this paper, including modeling,measurement, self-testing and and error compensation of the mine equipment’s dataacquisition part, and the purpose is to ensure the performance of coal mine production safetymonitoring equipment, to access to accurate monitoring data, help the safe coal production.There is a wide range of monitoring devices for coal mine safety production, whichinvolving a considerable number of sensor types and different data acquisition unit models.There are several indicators to measure its performance, the key is sampling accuracy,sampling rate, effective number of bits, input passband etc. The nonlinear error of the generaldata acquisition unit is caused by both static and dynamic aspects of distortion, therefore it’snecessary to weigh test methods carefully. For the purpose of determining the key parameters,there analyzed the obtained data of several types of typical devices in mine, established aforward channel data model and several different types of core models. Integral nonlinearityas its key performance indicator is proposed, and the expression of relationship among otherparameters is derived, with the given simulation test results.Aiming at the data requirements of timeliness and accuracy in coal safety productionmonitoring system, based on the analysis of static and dynamic testing methods in the dataacquisition unit, an improved weighted least squares dynamic curve fitting method isproposed. Data selection formula of sampling frequency and amount of sampling data arederived in histogram test methods, and the validity of test signal is estimated using the Cramér–Rao bounds.Aiming at the problem of self-test function of mine safety production monitoring devices,a short-term self-test method which is suitable for coal mine monitoring devices is proposed,which is the test method of the ramp test signal code. According to nonlinear analysis of theramp signal, the algorithm formula of power-on-self-test in mine production monitoringsystem is derived. The error analysis shows that nonlinear terms of the input signal can beestimated. Simulation and measured data show that the required test data in this methodaccount for a small storage space and need short test time. But test accuracy is equivalent tothe histogram test method and able to achieve self-test for the coal mine monitoring devices.Aiming at the problem of too large errors existing in data acquisition unit channel ofmine monitoring devices which greatly limits the accuracy of system detect, the dithersignal’s characteristics are analyzed, which digged out that it has compensation to thedynamic and static performance of data acquisition unit in mine production monitoringdevices. On this basis, a data correction method based on Dither is proposed and aperformance calibration framework of complex data acquisition system is designed.Comparing Dither correction method with Volterra series correction method and correctivematrix correction method from aspects of calibration time and correction algorithm show thatthis method is easy to implement and fit for online or offline correction of mine productionmonitoring devices with good test accuracy.Based on the analysis of the advantages and disadvantages of several different correctionmethods currently exist, the nonlinear error of data acquisition unit in mine monitoringdevices are expanded to two-dimensional space. A dither combined with correction nonlinearmatrix method is proposed. The impact of three components which constitute a correctivenonlinear matrix, the constitute of corrective matrix and restrictions of corrective matrixcorrection are discussed. The feasibility of two-dimensional corrective matrix correction areverified. Thereby, the evaluation method of correction validity is established. The simulationresults show that the DCNM method can effectively improve the performance of the system.At last, high-speed acquisition hardware for obtaining radar data which can be used forgeology and mineral exploration is designed and made. It not only supports the generalacquisition task, but also can be able to complete self-test and correction function. Then theDCNM method is used to test and track the standard high-frequency signal, blasting signal.The method is compared with the traditional test methods, which show that the DCNMmethod has the characteristics of short test time and high accuracy of correction data. Thiscorrection method can be extended the application to other coal mine monitoring devices.