Multicomponent gas detection in goaf can be used to determine the oxidation and spontaneous combustion status of residual coal in goaf,and to determine the development trend of spontaneous combustion of residual coal in goaf.Tunable diode laser absorption spectroscopy(TDLAS)gas detection technology is becoming increasingly widely used due to its narrow spectral lines,which can effectively avoid cross interference.The study adopts a structure that multiple lasers share an absorption pool to construct a laser multicomponent gas detection device,which greatly reduces the overall cost of the detection device,improves integration,and reduces the size of the detection device.Through the research of multi component gas TDLAS detection technology,the structure and hardware circuit of the detection device were designed.The developed multi component gas detection device was used to test the detection range,detection error and response time of six indicator gases including CH4、O2、CO2、CO、C2H4 and C2H2.The testing verified that the multi component gas detection device can accurately detect each indicator gas,and the detection range,detection error and response time meet the standard requirements.
Aiming at the problem that the engineering parameters related to drilling tools in the borehole cannot be directly obtained in various kinds of borehole construction in the coal mine at present, the engineering parameters while drilling measurement system suitable for underground working conditions of the coal mine is developed, and the system includes four parts: hardware, sensor components, electronic devices and supporting software. It can measure engineering parameters near the bottom of the hole such as drilling pressure, torque, inner and outer annular pressure, rotational speed, vibration and temperature, and measure drilling trajectory parameters such as azimuth, inclination angle, and tool facing angle. This paper fully introduces the working principle, components and main functions of the engineering parameters measurement while drilling system and carries out the ground pilot test. The test shows that the developed engineering parameter MWD system has continuous and stable working conditions, the engineering parameter measurement is accurate, and the data change trend is in accordance with the actual working condition, which can effectively guide the drilling construction. The deviation of the measured borehole trajectory parameters in the same borehole section is smaller than that of the conventional cable MWD system, which fully meets the requirements of directional drilling construction.
To improve the speed of fault diagnosis of the handling car transmission system, it is necessary to design and analyze the fault diagnosis method of the hydraulic support handling car transmission system for coal mines. Firstly, the coupling demodulation abnormal signal is obtained, and the initial fault identification is realized by using the improvement instruction. Based on this, the fault diagnosis method for the transmission system of the hydraulic support truck(FFT) high-frequency fault diagnosis model is designed, and the fault diagnosis is finally realized through database regulation. The test results show that the diagnostic response time of the designed method is only 1.05s, indicating that the designed method is faster in diagnosis during practical application and can quickly assist in the repair of the transmission system of the hydraulic bracket handling car for coal mines, which has practical application value.
In order to solve the problem that it is difficult to extract the fault features of rolling bearings under strong noise,a new feature enhancement method-fractional-order frequency weighted energy operator(FFWEO)was proposed.Firstly,Fourier transform was used to transform the signal from time domain to frequency domain,and obtained the amplitude function and phase function.Secondly,set the variation range and step size of differential order,perform fractional differential processing on the amplitude function of the signal in the frequency domain according to the time domain differential property of Fourier transform,combined the amplitude function with the phase function,and then used the inverse Fourier transform to obtain the modified signal.Finally,Hilbert transform was applied to differential signals of different orders to obtain envelope signals.The envelope kurtosis index was used to select the best differential order,and the envelope spectrum was obtained from differential signals in order to determine the bearing fault mode.The experimental results show that the method can effectively extract the fault features of rolling bearings under the strong noise background.
This paper studies the control strategy of mine electric vehicle driving system, the simulation model of the vehicle driving system cooling circuit is established based on the heat transfer relationship between the motor and the electronic control components. According to the bench test results, the simulation model is matched to verify the authenticity and accuracy of the simulation platform. In addition, this paper designs a model predictive controller for the vehicle driving system, which selects the coolant temperature as the thermal management target, and the coolant flow and heat dissipation air volume as the controlled pairs. The performance of temperature control efficiency and energy consumption are compared under the model predictive control (MPC), PID and switching strategies. The analysis results show that the thermal management method based on model predictive control can cool the electronic control system more efficiently and consume less system energy.
