A remote early warning system for complex coal mine underground environment safety

Abstract

The present application relates to the technical field of coal mine safety early warning, in particular to a remote early warning system for safety of complex underground coal mine environment. The system synchronously collects cutting current and channel state vector, extracts harmonic frequency and harmonic power of interference harmonic, center frequency and fading depth of channel fading point respectively; determines harmonic frequency shift range dynamically based on cutting current, calculates effective overlap degree of harmonic and trap wave in frequency domain, and generates cumulative risk value by fusing harmonic power and fading depth; then constructs spectrum overlap matrix, solves structural resonance index by using maximum weight matching algorithm, realizes accurate identification and early warning of harmonic slip alignment channel trap wave this structural metastable state, and overcomes the defect that traditional method only relies on signal-to-noise ratio and cannot predict instantaneous communication interruption.

Description

Technical Field

[0001] This invention relates to the field of coal mine safety early warning technology, specifically to a remote early warning system for safety in complex underground coal mine environments. Background Technology

[0002] High-power coal mining machines' cutting motors, under frequency conversion control, generate broadband electromagnetic interference. This interference includes both underlying switching noise and high-order harmonics that drift in frequency due to fluctuations in cutting resistance. The narrow underground tunnel spaces and metal support structures cause multipath propagation of wireless signals, forming fixed deep fading notches in the frequency domain.

[0003] Existing safety quality assessment methods typically only detect received signal strength or signal-to-noise ratio (SNR). This can lead to a shift in the harmonic frequencies emitted by a coal mining machine when cutting hard rock and causing a sudden increase in load. If the shifted frequency happens to fall within the deep fading notch of the channel, the communication link can momentarily break down even when the SNR appears normal. Current technologies struggle to distinguish this structural failure caused by frequency misalignment, resulting in poor reliability of remote early warning systems. Summary of the Invention

[0004] To address the technical problem in related technologies where it is difficult to distinguish structural failures caused by frequency alignment, leading to poor reliability of remote early warning systems, this invention provides a remote early warning system for safety in complex underground coal mine environments. The specific technical solution adopted is as follows: This invention proposes a remote early warning system for safety in complex underground coal mine environments. The system includes: The acquisition module is used to synchronously acquire the cutting current of the coal mining machine's cutting motor and the channel state vector of the wireless node during each sampling period; perform time-series analysis on the cutting current to determine the harmonic frequency and harmonic power of the interference harmonics; and determine the center frequency and fading depth of the channel fading point based on the channel state vector. The risk analysis module is used to determine the harmonic frequency shift range based on the cut-off current. Within the harmonic frequency shift range, based on the harmonic frequency of the interfering harmonic and the center frequency of the deep fading point of the channel, the effective overlap between each interfering harmonic and the channel fading point is calculated. Combining the effective overlap, the harmonic power of the interfering harmonic, and the fading depth of the channel fading point, the cumulative risk value of effective coupling is determined. The early warning module is used to construct a spectral overlap matrix based on the cumulative risk value of each interference harmonic and each channel fading point, and to perform maximum weight matching calculation on the spectral overlap matrix to obtain the structural resonance index; and to perform structural metastability early warning based on the structural resonance index.

[0005] Furthermore, the method for determining the harmonic frequency shift range includes: Calculate the standard deviation of the cutting current during the sampling period and perform a preset sensitivity conversion as the harmonic offset value. With the harmonic frequency of the sampling period as the center and the numerical interval of the harmonic frequency shift values ​​on both sides as the range, the total harmonic frequency shift range is obtained.

[0006] Furthermore, the method for calculating the effective overlap includes: Construct a notch filter influence domain function based on the frequency domain fading shape of the channel fading point; The influence domain function of the notch filter is integrated within the frequency drift range of the interference harmonics, and the integral value is normalized to obtain the effective overlap degree.

[0007] Furthermore, the method for constructing the notch influence domain function includes: The notch filter influence domain function is a Gaussian kernel function, and its bandwidth parameter is set to the orthogonal frequency division multiplexing subcarrier spacing of the communication system.

[0008] Furthermore, the method for calculating the cumulative risk value includes: The harmonic power of the interference harmonics is normalized to obtain the first risk index; The fading depth of the channel fading point is normalized to obtain the second risk index; The cumulative risk value is obtained by multiplying the first risk indicator, the second risk indicator, and the effective overlap.

[0009] Furthermore, the method for constructing the spectral overlap matrix includes: Using interference harmonics and channel fading points as the two dimensions of a two-dimensional spectral overlap matrix, and cumulative risk values ​​as matrix elements, a positive matrix with the same number of data points in both dimensions is constructed, and blank areas in the matrix are filled with the value 0.

[0010] Furthermore, the method for calculating the structural resonance index includes: The optimal pairing combination of interference harmonics and channel fading points that maximizes the total cumulative risk value is determined based on the KM algorithm and is used as the resonant combination. The sum of the cumulative risk values ​​of all pairs within the resonance combination is taken as the resonance value; By combining the resonance value with the mean of all non-zero values ​​in the spectral overlap matrix, the resonance value is normalized to determine the structural resonance index.

[0011] Furthermore, the structural metastable state early warning based on the structural resonance index includes: When the structural resonance index exceeds the preset resonance threshold, a structural metastability warning is issued.

[0012] Furthermore, the resonance determination threshold is obtained from historical operating condition statistics.

[0013] Furthermore, after the structural metastability warning, the method further includes: triggering a frame-level time slot redundancy transmission mechanism based on time diversity technology, and repeatedly sending the same data frame for frequency decoupling and tuning within a preset short protection interval after the current data frame is sent.

[0014] The present invention has the following beneficial effects: To address the shortcomings of existing safety quality assessment methods that rely solely on received signal strength or signal-to-noise ratio (SNR), making it difficult to identify structural communication interruptions caused by harmonic frequency shifts resulting from coal mining machines cutting hard rock and falling into deep fading notches, this invention simultaneously acquires the cutting current and channel state vector. This allows for precise extraction of the frequency and power of interfering harmonics, as well as the center frequency and fading depth of the channel fading point. Based on the cutting current, the harmonic frequency shift range is dynamically determined, and the effective overlap between harmonics and notches is calculated within this range. Furthermore, a cumulative risk value characterizing the severity of coupling is generated by combining harmonic power and fading depth. Furthermore, a spectral overlap matrix is ​​constructed, and the structural resonance index is solved using maximum weight matching. This enables the identification of structural metastable states formed by harmonic drift trends and alignment with channel vulnerabilities even before the SNR deteriorates. This technique provides proactive and accurate early warning of instantaneous interruption risks, significantly improving the communication reliability and safety warning effectiveness of underground coal mine remote monitoring systems in highly dynamic interference environments. Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a structural diagram of a remote early warning system for safety in a complex underground coal mine environment, provided as an embodiment of the present invention. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a remote early warning system for safety in complex underground coal mine environments proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0019] The following description, in conjunction with the accompanying drawings, details the specific scheme of a remote early warning system for safety in complex underground coal mine environments provided by this invention.

[0020] Please see Figure 1 The diagram illustrates a remote early warning system for safety in complex underground coal mine environments, according to an embodiment of the present invention. The system includes: The acquisition module 101 is used to synchronously acquire the cutting current of the coal mining machine cutting motor and the channel state vector of the wireless node in each sampling period; perform time-series analysis on the cutting current to determine the harmonic frequency and harmonic power of the interference harmonics; and determine the center frequency and fading depth of the channel fading point based on the channel state vector.

[0021] High-power coal mining machines' cutting motors, under frequency conversion control, generate broadband electromagnetic interference. This interference includes both underlying switching noise and high-order harmonics that drift in frequency due to fluctuations in cutting resistance. The narrow underground tunnel spaces and metal support structures cause multipath propagation of wireless signals, forming fixed deep fading notches in the frequency domain.

[0022] Existing safety quality assessment methods typically only detect received signal strength or signal-to-noise ratio (SNR). This can lead to a shift in the harmonic frequencies emitted by a coal mining machine when cutting hard rock and causing a sudden increase in load. If the shifted frequency happens to fall within the deep fading notch of the channel, the communication link can momentarily break down even when the SNR appears normal. Current technologies struggle to distinguish this structural failure caused by frequency misalignment, resulting in poor reliability of remote early warning systems.

[0023] To correlate interference source behavior and channel response under a unified time reference, the system first acquires the current signal of the coal mining machine's cutting motor and the channel state information of the wireless node in parallel, based on a preset synchronous acquisition frame length. That is, the cutting motor current signal and the wireless channel state vector are acquired in parallel during each sampling period, and the frequency and power of interference harmonics, as well as the center frequency and fading depth of the channel fading point, are extracted from them respectively.

[0024] Specifically, a sampling period of 20 milliseconds can be used. The current acquisition module on the coal mining machine side and the wireless access point on the roadway side are both connected to a timing network based on the IEEE 1588 PTP (Precision Time Protocol) protocol to obtain a clock signal with microsecond-level synchronization accuracy.

[0025] In this embodiment of the invention, the cut-off current for any sampling period is subjected to a Fast Fourier Transform (FFT) to obtain the harmonic frequency of the corresponding sampling period. It should be noted that the harmonic frequency of the cut-off current can be mapped to the harmonic frequency of the radiated interference characteristic of the radio frequency band by using the inverter's radiated emission frequency multiplication factor matrix obtained in advance through offline calibration. Subsequent harmonic frequency shift range and effective overlap integral are calculated based on the harmonic frequency of this radiated interference characteristic.

[0026] Peak analysis is performed at harmonic frequencies using a peak search algorithm to identify the M local maxima (M being a preset positive integer, e.g., 10) with the largest amplitudes as interfering harmonics. For each identified interfering harmonic, the square of its harmonic frequency amplitude is recorded as the harmonic energy. This harmonic energy is then normalized to obtain the harmonic power. The normalization method involves first calculating the harmonic energy at each sampling time interval, then using the sum of the energies of all identified interfering harmonics within the current sampling time interval as the denominator and the harmonic energy of the interfering harmonic as the numerator, and calculating the fraction to achieve normalization. It should be noted that if the sum of the harmonic energies across all sampling time intervals is 0, it indicates that the system has not performed any detection analysis or that a detection error has occurred. In this case, no fractional calculation is performed, and the harmonic power is directly set to 0.

[0027] The confined space and metallic support structure in underground mines can lead to severe multipath propagation of wireless signals. This multipath effect manifests as frequency-selective fading in the frequency domain, forming channel fading points (i.e., notches). The complex vector of Channel State Information (CSI) calculated from the pilot signal by the wireless access point in each sampling period is used as the channel state vector. When the high-power interference harmonics generated by the coal mining machine drift and fall into the deep fading notch frequency point of the useful signal, the useful signal is in an extremely weak state while the interference is in an extremely strong state. This causes the signal-to-interference ratio (SINR) at the receiver to deteriorate rapidly and instantaneously, leading to communication interruption. The channel depth spectrum is constructed by reciprocating the magnitude of the channel state vector. Search for the largest value on this spectral line. Extreme points ( These points (preset positive integers, such as 20) correspond to the frequency positions where the signal fades the most, i.e., the center frequency. The depth spectrum value of this point is then normalized to obtain the fading depth. The specific normalization method is as follows: obtain the global maximum fading depth value and the global minimum fading depth value under long-term historical monitoring (obtained based on historical prior experience, or customized by relevant technical personnel), and perform maximum and minimum value normalization processing to obtain the fading depth. It should be noted that if the maximum and minimum values ​​are the same, the fading depth is directly set to 0, and no normalization processing is performed. This represents an extremely small positive number, whose value can be, for example, 0.001, and is used to prevent the denominator from being... A value of 0 will cause calculation errors.

[0028] Risk analysis module 102 is used to determine the harmonic frequency shift range based on the cut-off current. Within the harmonic frequency shift range, based on the harmonic frequency of the interfering harmonic and the center frequency of the deep fading point of the channel, the effective overlap between each interfering harmonic and the channel fading point is calculated. Combining the effective overlap, the harmonic power of the interfering harmonic, and the fading depth of the channel fading point, the cumulative risk value of effective coupling is determined.

[0029] In fully mechanized coal mining faces, the random fluctuations in the cutting load of the coal mining machine cause the resulting interference harmonic frequencies to drift dynamically within a certain range, rather than remaining fixed. Since the cutting motor is an induction asynchronous motor, there is an inherent slip relationship between its speed and load torque. When the drum cutting resistance suddenly increases, the motor speed decreases, causing the harmonic center frequency output by the frequency converter to drift downwards. Simultaneously, the location of the deep fading point in the channel formed by the multipath effect in the roadway remains relatively fixed. Traditional risk assessment methods rely solely on binary judgment based on whether the instantaneous frequencies of harmonics and notch waves coincide, failing to quantify the cumulative exposure risk of harmonics sweeping through the notch wave region during drift, and especially struggling to capture the "metastable state" where the harmonics are not fully aligned but have already entered a high-risk coupling range.

[0030] In this embodiment of the invention, the frequency drift range of each interference harmonic is first determined based on the fluctuation characteristics of the cutoff current. Then, within this uncertainty range, the effective overlap between the center frequency of the interference harmonics and the center frequency of the channel fading point is calculated in the frequency domain. Furthermore, the harmonic power and fading depth are fused to generate a cumulative risk value characterizing the severity of coupling. This operation achieves a leap from "static collision detection" to "dynamic probability integration," providing a continuous, differentiable, and physically interpretable quantitative basis for accurately quantifying the risk of structural communication interruptions.

[0031] The method for determining the harmonic frequency shift range includes: determining a preset time sliding window with each sampling period as the time sequence center; calculating the standard deviation of the cutting current within the sampling period and performing a preset sensitivity conversion as the harmonic offset value; taking the harmonic frequency of the sampling period as the center and the numerical interval of the harmonic frequency shift values ​​on both sides as the range to obtain the total harmonic frequency shift range.

[0032] In this embodiment of the invention, the standard deviation of the cut-off current amplitude is read from the synchronization feature data frame. The harmonic frequency shift range of the k-th sampling period is calculated using the following formula. : In the formula, The preset sensitivity, expressed in Hz / A, is obtained offline by linear regression fitting of load current fluctuation and radiated frequency drift under calibrated test conditions. This is an inherent property of the device and ranges from 0.01 Hz / A to 0.1 Hz / A, specifically 0.05 Hz / A. This represents the basic protection bandwidth, used to cover the inverter's own switching frequency jitter error (e.g., 0.5% of the modulation frequency). This calculation maps the load fluctuation characteristics in the time domain to the frequency uncertainty range in the frequency domain.

[0033] Then, the harmonic frequencies of the interference harmonics in each sampling period are... This yields the corresponding harmonic frequency shift range.

[0034] Furthermore, in some embodiments of the present invention, the method for calculating the effective overlap includes: constructing a notch influence domain function based on the frequency domain fading shape of the channel fading point; integrating the notch influence domain function within the frequency drift range of the interference harmonics; and normalizing the integral value to obtain the effective overlap.

[0035] The method for constructing the notch influence domain function includes: the notch influence domain function is a Gaussian kernel function, and its bandwidth parameter is set to the orthogonal frequency division multiplexing subcarrier spacing of the communication system.

[0036] Specifically, the formula for calculating the effective overlap is: In the formula, from arrive By performing integration, the effective overlap degree is obtained. The center frequency of the deep fading point in the channel is represented by the symbol f, which is the integral variable, representing a continuous frequency variable in the frequency domain, and is the frequency value that changes continuously between the upper and lower limits of integration. norm indicates the normalization process, which divides the integral value by the "theoretical maximum integral value of the notch influence domain function in the full frequency domain", thereby achieving normalization and mapping the effective overlap to the interval [0,1]. This theoretical maximum value is obtained based on prior experience.

[0037] and The influence domain function of the notch filter is represented, and its specific calculation is as follows: Among them, bandwidth parameters The subcarrier spacing of the Orthogonal Frequency Division Multiplexing (OFDM) system is set, for example, 312.5 kHz. exp represents an exponential function with the natural constant as its base. This integral operation addresses metastability risks that cannot be quantified by simple frequency comparison by calculating the overlap area between the slip interval and the notch distribution.

[0038] The method for calculating the cumulative risk value includes: normalizing the harmonic power of the interference harmonics to obtain the first risk index; normalizing the fading depth of the channel fading point to obtain the second risk index; and calculating the product of the first risk index, the second risk index, and the effective overlap to obtain the cumulative risk value.

[0039] Since the harmonic power and fading depth are already normalized values ​​in the acquisition module 101, they can be used directly in this embodiment. Therefore, in this embodiment of the invention, the normalized values ​​are directly used as the first risk indicator and the second risk indicator. The first risk indicator and the second risk indicator aim to achieve data standardization and avoid mutual interference and inaccuracy when data from different dimensions are combined for analysis.

[0040] It should be noted that harmonic power represents the energy intensity of a harmonic under the current operating conditions. If the harmonic completely coincides with the channel notch (maximum integral term), and if its power is extremely low (such as a weak 5th harmonic), the interference to communication will be limited. Conversely, if it is a high-power harmonic (such as a strong 7th harmonic generated by a frequency converter), even if it only partially sweeps across the notch region, it will cause significant signal attenuation. The greater the harmonic power, the more severe the link damage will be once it aligns with the notch.

[0041] Fading depth represents the depth coefficient of the channel notch, reflecting the degree of attenuation of the channel gain at that frequency. If the harmonic sweeps through a shallow fading region (fading depth value of 0.1), even if the harmonic power is high, the receiver may still demodulate successfully. However, if it sweeps through a deep fading region (fading depth value of 0.9), even if the harmonic power is moderate, it may cause a sharp drop in the subcarrier signal-to-noise ratio, resulting in a high coupling risk.

[0042] Therefore, in this embodiment of the invention, the cumulative risk value is obtained by directly calculating the product of the first risk index, the second risk index, and the effective overlap. By integrating the power intensity of the interfering harmonic, the fading depth of the channel notch, and the dynamic overlap between the two in the frequency domain, the comprehensive risk level of structural coupling between a specific harmonic and a specific notch is quantitatively characterized. The larger the value, the higher the "attack exposure" of the harmonic to the vulnerable channel point during its frequency drift, and the more likely the communication link is to be suddenly interrupted due to frequency alignment.

[0043] The early warning module 103 is used to construct a spectrum overlap matrix based on the cumulative risk value of each interference harmonic and each channel fading point, and to perform maximum weight matching calculation on the spectrum overlap matrix to obtain the structural resonance index; and to perform structural metastability early warning based on the structural resonance index.

[0044] In underground wireless communication in coal mines, multiple interference harmonics and multiple channel fading points may simultaneously have varying degrees of coupling risk. If only a single harmonic-notch pair is considered, the most dangerous combination of "strong harmonics aligned with deep notches" in the system is easily overlooked, leading to insufficient early warning sensitivity or misjudgment.

[0045] In this embodiment of the invention, the cumulative risk values ​​between all harmonics and notch waves are organized into a spectral overlap matrix, and the optimal pairing combination with the highest total coupling risk is identified from it by the maximum weight matching algorithm, thereby generating a structural resonance index, and structural metastability early warning is performed based on the structural resonance index.

[0046] Furthermore, in some embodiments of the present invention, the method for constructing the spectrum overlap matrix includes: using interference harmonics and channel fading points as the two dimensions of the two-dimensional spectrum overlap matrix, using the cumulative risk value as the matrix element, constructing a positive matrix with the same amount of data in both dimensions, and filling the blank areas in the matrix with the value 0.

[0047] That is, an M×N spectrum overlap matrix is ​​constructed, where M represents the number of interference harmonics and N represents the number of channel fading points (detailed in the acquisition module 101). If M is 10 and N is 20, the interference harmonic dimension needs to be padded with zeros to make it a 20×20 positive matrix for subsequent analysis.

[0048] Furthermore, in some embodiments of the present invention, the method for calculating the structural resonance index includes: solving for the optimal pairing combination of interference harmonics and channel fading points that maximizes the total cumulative risk value based on the KM algorithm, as the resonance combination; taking the sum of the cumulative risk values ​​of all pairs within the resonance combination as the resonance value; and normalizing the resonance value by combining the resonance value with the mean of all non-zero values ​​within the spectral overlap matrix to determine the structural resonance index.

[0049] Among them, the KM algorithm is the Kuhn-Munkres algorithm. Based on the KM algorithm, the cumulative risk value is used as the edge weight connecting the vertices and injective matching is performed to maximize the sum of the matching edge weights. The matching combination corresponding to the maximum value is the resonance combination. The sum of the cumulative risk values ​​of all pairs in the resonance combination is used as the resonance value. The resonance value is normalized to obtain the structural resonance index.

[0050] The specific normalization method is as follows: calculate the mean of all non-zero values ​​in the spectral overlap matrix as the analysis value, and use the sum of the resonance value and the analysis value as the normalized structural resonance index.

[0051] Calculate the structural resonance index using the normalized formula. : In the formula, Indicates the resonance value. Indicates the analysis value. For example, the smallest positive number (e.g.) (), used to prevent the denominator from being zero.

[0052] when When the value approaches 1, the characterization system is in a structurally sensitive state, meaning that specific strong harmonics are aligned with the deep-seated wave; when When the value approaches 0, the system is in a state of energy dissipation.

[0053] In other words, when the structural resonance index approaches 1, the system is in a structurally sensitive state, and there are specific strong harmonics aligned with the deep-seated wave, resulting in structural metastability. Therefore, structural metastability warning can be carried out based on the structural resonance index, specifically including: when the structural resonance index is greater than the preset resonance judgment threshold, structural metastability warning can be carried out.

[0054] The preset resonance judgment threshold is the threshold value of the structural resonance index. The resonance judgment threshold is obtained from historical operating conditions, that is, it can be obtained based on prior experience. Specifically, it can be, for example, 0.5. That is, when the structural resonance index is greater than 0.5, it is judged that a structural metastable anomaly has occurred, and a structural metastable state warning is issued.

[0055] Specifically, structural metastability early warning can be, for example, alerting relevant personnel to structural metastability anomalies. After the structural metastability early warning, it also includes: triggering a frame-level time slot redundancy transmission mechanism based on time diversity technology, and repeatedly sending the same data frame for frequency decoupling and tuning within a preset short protection interval after the current data frame is sent.

[0056] In other words, when a structural metastable state is determined, the system generates a "frame-level time slot redundancy" command. Since structural resonance originates from instantaneous frequency alignment and is extremely time-sensitive, even a tiny time-domain misalignment can disrupt the resonance condition. When executing this command, the same data frame is repeatedly transmitted (e.g., retransmitted twice) within a preset short guard interval after the current data frame is sent. Using time diversity techniques, it is ensured that even if the first frame happens to fall at the resonance point and is disrupted, subsequent frames can be successfully demodulated using the slight frequency mismodulation caused by load fluctuations.

[0057] The preset short protection interval can be, for example, 2 milliseconds to 10 milliseconds, preferably 2 milliseconds, so that it can effectively isolate the sampling period of the preceding and following frames, and ensure that the two transmissions are within the same channel coherence time, so as to take into account the effectiveness of multipath isolation and time diversity.

[0058] To address the shortcomings of existing safety quality assessment methods that rely solely on received signal strength or signal-to-noise ratio (SNR), making it difficult to identify structural communication interruptions caused by harmonic frequency shifts resulting from coal mining machines cutting hard rock and falling into deep fading notches, this invention simultaneously acquires the cutting current and channel state vector. This allows for precise extraction of the frequency and power of interfering harmonics, as well as the center frequency and fading depth of the channel fading point. Based on the cutting current, the harmonic frequency shift range is dynamically determined, and the effective overlap between harmonics and notches is calculated within this range. Furthermore, a cumulative risk value characterizing the severity of coupling is generated by combining harmonic power and fading depth. Furthermore, a spectral overlap matrix is ​​constructed, and the structural resonance index is solved using maximum weight matching. This enables the identification of structural metastable states formed by harmonic drift trends and alignment with channel vulnerabilities even before the SNR deteriorates. This technique provides proactive and accurate early warning of instantaneous interruption risks, significantly improving the communication reliability and safety warning effectiveness of underground coal mine remote monitoring systems in highly dynamic interference environments.

[0059] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0060] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A remote early warning system for safety in complex underground coal mine environments, characterized in that, The system includes: The acquisition module is used to synchronously acquire the cutting current of the coal mining machine's cutting motor and the channel state vector of the wireless node during each sampling period; perform time-series analysis on the cutting current to determine the harmonic frequency and harmonic power of the interference harmonics; and determine the center frequency and fading depth of the channel fading point based on the channel state vector. The risk analysis module is used to determine the harmonic frequency shift range based on the cut-off current. Within the harmonic frequency shift range, based on the harmonic frequency of the interfering harmonic and the center frequency of the deep fading point of the channel, the effective overlap between each interfering harmonic and the channel fading point is calculated. Combining the effective overlap, the harmonic power of the interfering harmonic, and the fading depth of the channel fading point, the cumulative risk value of effective coupling is determined. The early warning module is used to construct a spectral overlap matrix based on the cumulative risk value of each interference harmonic and each channel fading point, and to perform maximum weight matching calculation on the spectral overlap matrix to obtain the structural resonance index; and to perform structural metastability early warning based on the structural resonance index.

2. The remote early warning system for safety in complex underground coal mine environments as described in claim 1, characterized in that, The method for determining the harmonic frequency shift range includes: Calculate the standard deviation of the cutting current during the sampling period and perform a preset sensitivity conversion as the harmonic offset value. With the harmonic frequency of the sampling period as the center and the numerical interval of the harmonic frequency shift values ​​on both sides as the range, the total harmonic frequency shift range is obtained.

3. The remote early warning system for safety in complex underground coal mine environments as described in claim 1, characterized in that, The method for calculating the effective overlap includes: Construct a notch filter influence domain function based on the frequency domain fading shape of the channel fading point; The influence domain function of the notch filter is integrated within the frequency drift range of the interference harmonics, and the integral value is normalized to obtain the effective overlap degree.

4. The remote early warning system for safety in complex underground coal mine environments as described in claim 3, characterized in that, The method for constructing the notch influence domain function includes: The notch filter influence domain function is a Gaussian kernel function, and its bandwidth parameter is set to the orthogonal frequency division multiplexing subcarrier spacing of the communication system.

5. A remote early warning system for safety in complex underground coal mine environments as described in claim 1, characterized in that, The method for calculating the cumulative risk value includes: The harmonic power of the interference harmonics is normalized to obtain the first risk index; The fading depth of the channel fading point is normalized to obtain the second risk index; The cumulative risk value is obtained by multiplying the first risk indicator, the second risk indicator, and the effective overlap.

6. A remote early warning system for safety in complex underground coal mine environments as described in claim 1, characterized in that, The method for constructing the spectral overlap matrix includes: Using interference harmonics and channel fading points as the two dimensions of a two-dimensional spectral overlap matrix, and cumulative risk values ​​as matrix elements, a positive matrix with the same number of data points in both dimensions is constructed, and blank areas in the matrix are filled with the value 0.

7. A remote early warning system for safety in complex underground coal mine environments as described in claim 1, characterized in that, The method for calculating the structural resonance index includes: The optimal pairing combination of interference harmonics and channel fading points that maximizes the total cumulative risk value is determined based on the KM algorithm and is used as the resonant combination. The sum of the cumulative risk values ​​of all pairs within the resonance combination is taken as the resonance value; By combining the resonance value with the mean of all non-zero values ​​in the spectral overlap matrix, the resonance value is normalized to determine the structural resonance index.

8. A remote early warning system for safety in complex underground coal mine environments as described in claim 1, characterized in that, The structural metastability early warning based on the structural resonance index includes: When the structural resonance index exceeds the preset resonance threshold, a structural metastability warning is issued.

9. A remote early warning system for safety in complex underground coal mine environments as described in claim 8, characterized in that, The resonance determination threshold is obtained from historical operating conditions.

10. A remote early warning system for safety in complex underground coal mine environments as described in claim 1, characterized in that, Following the structural metastability warning, the method further includes: triggering a frame-level time slot redundancy transmission mechanism based on time diversity technology, and repeatedly sending the same data frame for frequency decoupling and tuning within a preset short protection interval after the current data frame is sent.

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