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Low-Frequency Extended Signal

Design of Low-Frequency Extended Signal Conditioning Circuit for Coal Mine Geophone



The traditional magnetoelectric geophone is widely used in the microseismic monitoring of coal mines. However, its measurement capability in the low-frequency range is insufficient and cannot fully meet the monitoring requirements of underground coal mines, which extend as low as 0.1 Hz. This paper proposes a signal conditioning (SC) circuit based on the extended filtering method to improve the low-frequency response capability of the geophone. Through simulation and experimental tests, it is verified that the designed SC circuit can reduce the cut-off frequency of the EST-4.5C geophone from 4.5 Hz to 0.16 Hz.

Meanwhile, the noise introduced by this SC circuit is relatively low thanks to its simple and easy-to-implement structural model. The test results also indicate that it provides a strong ability to resist noise interference for the geophone, which is valuable under complex working conditions. Overall, this circuit offers a feasible option for enhancing the capability of the seismic geophones used in coal mines to detect low-frequency vibration signals.

The magnetoelectric geophone, as the most commonly used vibration sensor in the microseismic monitoring system of underground coal mines, restricts the performance of the microseismic monitoring system due to its working characteristics. Due to its strong attenuation characteristics for signals lower than its cut-off frequency, the traditional geophone can no longer meet the monitoring requirements of low-frequency vibration signals in the coal mine microseismic monitoring system. This paper, examining the characteristics of the geophone and considering the underground environment of coal mines, proposes a signal conditioning circuit for the low-frequency expansion of coal mine seismic geophones. The circuit design is based on the principle of the extended filtering method and incorporates damping ratio correction and differential, as well as high-pass and low-pass filtering links, to assist in adjusting the circuit properties.

This paper selected the EST-4.5C geophone with high sensitivity and an appropriate damping ratio as the research object. Based on the data of this geophone, we accurately restored its electrical model in simulation software. Starting from this model, the structure and parameters of the signal conditioning circuit were designed. The SC circuit reduced the use of operational amplifier groups and large numerical resistors through structural optimization. An experiment was conducted using vabration table system. The data show that the signal conditioning circuit could reduce the cut-off frequency of the EST-4.5C magnetoelectric geophone from 4.5 Hz to 0.16 Hz. We also tested the self-noise level and the ability to resist the external interference of the signal conditioning circuit in a quiet environment and a simulated power frequency noise environment. The results show that the noise level of the circuit meets the qualification. Moreover, this circuit has a certain ability to suppress external noise interference.

Combining theoretical analysis and experimental tests, this paper demonstrates that the signal conditioning circuit enhances the magnetoelectric geophone’s ability to detect low-frequency vibration signals. Meanwhile, the circuit design is simple and easy to implement, providing strong support for the need to fully arrange geophones in underground coal mines to pick up low-frequency vibration signals.

Signal processing, signal strength, wireless signal, digital signal, analog signal, weak signal, strong signal, modulation, demodulation, frequency signal, noise signal, signal analysis, signal integrity, communication signal, electrical signal, biomedical signal, control signal, signal transmission, signal detection, signal measurement

#SignalProcessing, #SignalStrength, #DigitalSignal, #AnalogSignal, #WeakSignal, #StrongSignal, #ModulationSignal, #DemodulationSignal, #FrequencySignal, #NoiseSignal, #SignalAnalysis, #SignalIntegrity, #CommunicationSignal, #ElectricalSignal, #BiomedicalSignal, #ControlSignal, #SignalTransmission, #SignalDetection, #SignalMeasurement, #WirelessSignal

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