An active detection method and device for monitoring dangerous rock collapses

Abstract

The present application provides an active detection type monitoring method and device for dangerous rock collapse, belonging to the field of dangerous rock monitoring, and is used to solve the problem of poor reliability of dangerous rock collapse monitoring technology in the related art. In this method and device, a monitoring excitation signal is determined according to at least one local oscillation frequency of a target dangerous rock mass, and the monitoring excitation signal includes a plurality of excitation frequency ranges corresponding one by one to the local oscillation frequencies; according to the monitoring echo signal of the target dangerous rock mass under the monitoring excitation signal, a dominant frequency is determined for each excitation frequency range; it is judged whether the dominant frequency exceeds a pre-acquired confidence frequency range; if so, a collapse warning signal is generated. By adopting the above technical solution, it is possible to intelligently and reasonably determine whether the state of the target dangerous rock mass has changed, that is, whether there is a collapse risk for the target dangerous rock mass, so as to realize reliable monitoring of the collapse of the target dangerous rock mass.

Description

Technical Field

[0001] The present application relates to the field of dangerous rock monitoring, and in particular, to an active detection type dangerous rock collapse monitoring method and device. Background Art

[0002] A dangerous rock mass refers to a potential collapse body, usually located at a mountain spur or concave steep slope with a large height difference, isolated and steep, with developed internal fissures, incomplete rock mass structure, and a large number of fissures or weak zones extending in the same direction as or parallel to the slope inclination. In order to cope with the possible hazards brought by the collapse of dangerous rocks, it is generally necessary to use monitoring devices to monitor dangerous rocks, so as to notify relevant personnel to take measures in time when precursors of dangerous rock collapse appear. If the reliability of the monitoring device is insufficient, situations such as untimely and inaccurate monitoring of dangerous rock collapse may occur, resulting in the inability to effectively respond to the possible hazards brought by dangerous rock collapse in time. Summary of the Invention

[0003] The present application provides an active detection type dangerous rock collapse monitoring method and device, which is beneficial to reliably monitor dangerous rock collapse.

[0004] In a first aspect, the present application provides an active detection type dangerous rock collapse monitoring method. The method includes:

[0005] Determine a monitoring excitation signal according to at least one local oscillation frequency of a target dangerous rock mass, where the monitoring excitation signal includes a plurality of excitation frequency ranges corresponding one-to-one to the local oscillation frequencies;

[0006] Determine a dominant frequency for each excitation frequency range according to the monitoring echo signal of the target dangerous rock mass under the monitoring excitation signal;

[0007] Judge whether the dominant frequency exceeds a pre-acquired confidence frequency range;

[0008] If so, generate a collapse warning signal.

[0009] By adopting the above technical solution, it is possible to intelligently and reasonably determine whether the state of the target dangerous rock mass has changed, that is, whether there is a collapse risk for the target dangerous rock mass, so as to realize reliable monitoring of the collapse of the target dangerous rock mass.

[0010] Further, the excitation frequency range is centered on the corresponding local oscillation frequency.

[0011] Further, the method for obtaining at least one local oscillation frequency of the target dangerous rock mass includes:

[0012] Obtain a detection echo signal of the target dangerous rock mass under a detection excitation signal, where the frequency range of the detection excitation signal is wider than the frequency range of the monitoring excitation signal;

[0013] Perform spectral analysis on the detected echo signal to obtain multiple frequency point data and the amplitude data corresponding to each frequency point data. Assume there are n frequency point data, and the i-th frequency point data is and the corresponding amplitude data is ;

[0014] Determine that the frequency point data with amplitude data higher than the preset amplitude and the amplitude data being the maximum value is the local oscillator frequency. Assume the preset amplitude is and the local oscillator frequency is , then for the local oscillator frequency the satisfies and and .

[0015] Furthermore, the method for obtaining the confidence frequency range includes:

[0016] Obtain the historical monitoring records of the target dangerous rock mass, and the historical monitoring records include the historical dominant frequencies with time stamps;

[0017] Determine the distribution frequency range according to the historical dominant frequency distribution within a preset time period;

[0018] Determine the confidence frequency range according to the distribution frequency range. The center of the confidence frequency range is the same as the center of the distribution frequency range, and the width of the confidence frequency range is a preset multiple of the distribution frequency range.

[0019] Furthermore, the determining the distribution frequency range according to the historical dominant frequency distribution within a preset time period includes:

[0020] Calculate the frequency average value of the historical dominant frequencies within a preset time period. Assume there are i historical dominant frequencies within the preset time period, and the i-th historical dominant frequency is , and the frequency average value is , ;

[0021] Based on a pre-constructed range determination model, determine the distribution frequency range according to the frequency average value and the historical dominant frequencies within a preset time period. The frequency average value is the center of the distribution frequency range, and the distribution frequency range covers a specified number proportion of the historical dominant frequencies within a preset time period. Assume the lower limit of the distribution frequency range is and the upper limit of the range is , historical dominant frequencies are within the distribution frequency range, and the specified number proportion is , then .

[0022] Further, it further includes: determining the risk data of the target dangerous rock mass according to the historical excellent frequency;

[0023] The determining the risk data of the target dangerous rock mass according to the historical excellent frequency includes:

[0024] Set the historical moment before the preset duration at the current moment as the first historical moment, and the historical moment before twice the preset duration at the current moment as the second historical moment. The frequency average value of the historical excellent frequency between the first historical moment and the second historical moment is the pre-average frequency;

[0025] Based on the range determination model, determine the pre-frequency range according to the pre-average frequency and the historical excellent frequency within the first historical moment to the second historical moment;

[0026] Determine the risk data according to the absolute value of the difference between the frequency average value and the pre-average frequency and the absolute value of the difference between the width of the distribution frequency range and the width of the pre-frequency range. The risk data is positively correlated with both the absolute value of the difference between the frequency average value and the pre-average frequency and the absolute value of the difference between the width of the distribution frequency range and the width of the pre-frequency range. Let the lower limit of the pre-frequency range be and the upper limit of the range be , the pre-evaluation frequency is , and the risk data is z, then , where , are all greater than zero.

[0027] In a second aspect, the present application provides an active detection type dangerous rock collapse monitoring device. The device includes a signal transmitting module, a signal receiving module, and a device control module. The signal transmitting module is used to transmit an excitation signal to the target dangerous rock mass. The signal receiving module is used to receive the echo signal sent by the target dangerous rock mass. The device control module is connected to the signal transmitting module and the signal receiving module and is used to execute any one of the methods described in the first aspect above.

[0028] Further, the device control module is further configured to:

[0029] Generate a wake-up signal based on the internal clock timing, and the wake-up signal is used to wake up the device;

[0030] Based on the wake-up signal, trigger the signal receiving module to acquire the self-generated echo signal. The self-generated echo signal is the echo signal generated by the target dangerous rock mass under natural conditions. If the self-generated echo signal is acquired, analyze the state of the target dangerous rock mass according to the self-generated echo signal, otherwise trigger the execution of any one of the methods described in the first aspect above.

[0031] In summary, the present application at least includes the following beneficial effects:

[0032] A method and device for monitoring the collapse of actively detected dangerous rocks are provided, which can intelligently and reasonably determine whether the state of the target dangerous rock mass has changed, so as to reliably monitor the collapse of the target dangerous rock mass.

[0033] It should be understood that the content described in the invention content part is not intended to limit the key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In combination with the accompanying drawings and with reference to the following detailed description, the above and other features, advantages and aspects of the embodiments of the present application will become more obvious. In the drawings, the same or similar reference numerals represent the same or similar elements, where:

[0035] Figure 1 A block diagram of an actively detected dangerous rock collapse monitoring device in an embodiment of the present application is shown;

[0036] Figure 2 A flowchart of an actively detected dangerous rock collapse monitoring method in an embodiment of the present application is shown. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0037] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art without making creative efforts based on the embodiments in the present application belong to the scope of protection of the present application.

[0038] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after.

[0039] The present application provides a method and device for monitoring the collapse of actively detected dangerous rocks, which can intelligently and reasonably determine whether the state of the target dangerous rock mass has changed, so as to reliably monitor the collapse of the target dangerous rock mass.

[0040] In a first aspect, the present application provides an actively detected dangerous rock collapse monitoring device.

[0041] Figure 1The block diagram of an active detection type dangerous rock collapse monitoring device in an embodiment of the present application is shown.

[0042] Referring to Figure 1 , the device includes a signal transmitting module 110, a signal receiving module 120, and a device control module 130.

[0043] Among them, the signal transmitting module 110 is used to transmit an excitation signal to the target dangerous rock mass. The signal transmitting module 110 may specifically include a transmitting drive current and a transmitting transducer. The transmitting transducer is used to attach to the target dangerous rock mass to transmit an excitation signal to the target dangerous rock mass. The signal receiving module 120 is used to receive the echo signal emitted by the target dangerous rock mass. The signal receiving module 120 includes a receiving transducer and a receiving amplification circuit. The receiving transducer is used to attach to the target dangerous rock mass to receive the echo signal emitted by the target dangerous rock mass.

[0044] The device control module 130 is connected to the signal transmitting module 110 and the signal receiving module 120, and is used to control the signal transmitting module 110 to transmit an excitation signal to the target dangerous rock mass and receive the echo signal collected by the signal receiving module 120, so as to analyze the state of the target dangerous rock mass and realize reliable monitoring of dangerous rock collapse.

[0045] The device control module 130 has a built-in clock. The device control module 130 generates a wake-up signal at regular intervals based on the built-in clock. After generating the wake-up signal, the device control module 130 first controls the signal receiving module 120 to obtain the native echo signal. The native echo signal is the echo signal generated by the target dangerous rock mass under natural conditions, such as the echo signal that appears when the target dangerous rock mass vibrates under the influence of natural wind or internal structure changes. If the native echo signal is obtained, the state of the target dangerous rock mass is analyzed according to the native echo signal.

[0046] The device control module 130 can determine the state change of the target dangerous rock mass according to the maximum amplitude and frequency point distribution of the native echo signal, and issue a dangerous rock collapse warning signal when the maximum amplitude exceeds the amplitude threshold and / or the frequency point distribution exceeds the preset distribution rule.

[0047] When the device control module 130 fails to obtain the native echo signal, the signal transmitting module 110 and the signal receiving module 120 are triggered to work together, and cooperate with an intelligent algorithm to determine the pile body of the target dangerous rock mass. The intelligent algorithm is introduced based on the disclosure of the second aspect of the present application.

[0048] In the second aspect, the present application provides an active detection type dangerous rock collapse monitoring method. This method can be executed by Figure 1 the device control module 130 in

[0049] Figure 2The flowchart of an active detection type dangerous rock collapse monitoring method in an embodiment of the present application is shown.

[0050] Referring to Figure 2 , the method specifically includes the following steps:

[0051] S210: Determine a monitoring excitation signal according to at least one local oscillation frequency of a target dangerous rock mass obtained in advance.

[0052] The monitoring excitation signal includes an excitation frequency range corresponding one-to-one with the local oscillation frequency; the excitation frequency range takes the corresponding local oscillation frequency as the midpoint. In the embodiment of the present application, the excitation frequency range is equal to 0.9 times the local oscillation frequency to 1.1 times the local oscillation frequency.

[0053] In the method of this step, the method for obtaining at least one local oscillation frequency of the target dangerous rock mass includes: obtaining a detection echo signal of the target dangerous rock mass under a detection excitation signal, where the frequency range of the detection excitation signal is wider than the frequency range of the monitoring excitation signal; performing spectrum analysis on the detection echo signal to obtain a plurality of frequency point data and amplitude data corresponding to each frequency point data. Assume there are n frequency point data, and the i-th frequency point data is , and the corresponding amplitude data is ; determining that the frequency point data with amplitude data higher than a preset amplitude and the amplitude data being a maximum value is the local oscillation frequency. Assume the preset amplitude is , and the local oscillation frequency is , then for the relative local oscillation frequency 's satisfies , and , and .

[0054] The detection excitation signal is a wide-band excitation signal, and the corresponding detection echo signal is also a wide-band excitation signal. After performing a fast Fourier transform on the detection echo signal, the amplitude data and phase data of each frequency point can be determined.

[0055] After determining the amplitude data and phase data of each frequency point, a two-dimensional coordinate system is constructed with the frequency point information as the horizontal axis and the amplitude data as the vertical axis, and all the frequency point data and the corresponding amplitude data are substituted to obtain several coordinate points; all the coordinate points are connected in sequence with a smooth curve to obtain a frequency amplitude distribution curve; analyze and determine the maximum value of the frequency amplitude distribution curve, and determine whether the ordinate of each maximum value is higher than the preset amplitude. If so, take the corresponding frequency point data as the local oscillation frequency. In this way, one or more local oscillation frequencies can be obtained.

[0056] The excitation frequency ranges corresponding to different local oscillation frequencies do not overlap.

[0057] S220: Determine a dominant frequency for each excitation frequency range based on the monitored echo signal of the target dangerous rock mass under the monitored excitation signal.

[0058] Since there is an excitation frequency range corresponding one-to-one to the local oscillator frequency in the monitored excitation signal, and the monitored echo signal is the echo signal under the monitored excitation signal, the monitored echo signal can also be divided according to the excitation frequency range.

[0059] For each frequency range of the monitored echo signal corresponding to an excitation frequency range, a dominant signal can be determined. The specific determination method is to perform a fast Fourier transform on the part of the monitored echo signal corresponding to the excitation frequency range to obtain frequency point data, corresponding amplitude data, and phase data, and determine the frequency point data with the highest amplitude data as the dominant frequency under the corresponding excitation frequency range.

[0060] S230: Determine whether the dominant frequency exceeds the pre-acquired confidence frequency range.

[0061] In the method of this step, first, the confidence frequency range needs to be acquired. The acquisition method of the confidence frequency range includes: acquiring the historical monitoring record of the target dangerous rock mass, where the historical monitoring record includes the historical dominant frequencies with time stamps; determining the distribution frequency range according to the distribution of the historical dominant frequencies within a preset time period; determining the confidence frequency range according to the distribution frequency range, where the center of the confidence frequency range is the same as the center of the distribution frequency range, and the width of the confidence frequency range is a preset multiple of the width of the distribution frequency range.

[0062] The historical monitoring record is the monitoring record stored inside the device or uploaded to the host computer. The historical monitoring record includes the historical dominant frequencies with time stamps. A historical dominant frequency has multiple dominant frequencies corresponding one-to-one to the excitation frequency range of the local oscillator frequency. Each dominant frequency can be analyzed independently.

[0063] In the above content, the determination of the distribution frequency range according to the distribution of the historical dominant frequencies within a preset time period includes: calculating the frequency average value of the historical dominant frequencies within a preset time period. Suppose there are i historical dominant frequencies within the preset time period, and the i-th historical dominant frequency is , and the frequency average value is , ; based on a pre-constructed range determination model, determine the distribution frequency range according to the frequency average value and the historical dominant frequencies within a preset time period. The frequency average value is the center of the distribution frequency range, and the distribution frequency range covers a specified number proportion of the historical dominant frequencies within a preset time period. Suppose the lower limit of the distribution frequency range is , and the upper limit of the range is , A historical excellent frequency is within the distribution frequency range, and the specified quantity ratio is , then .

[0064] Specifically, the distribution frequency range is constructed centered on the frequency average value, so that a specified quantity ratio of historical excellent frequencies within a preset time period are within the distribution frequency range. The distribution frequency range carries confidence data, and the confidence data is equal to the specified quantity ratio.

[0065] In one example, the preset time period is 30 days, there is one historical monitoring record every day, and the specified quantity ratio is 95%, which means taking 0.95 times the total quantity. Here, the calculated value is 28.5, and rounding down gives 28. Each historical monitoring record has multiple excellent frequencies, and each excellent frequency corresponds to a local oscillator frequency and an excitation frequency range, that is, the excellent frequencies corresponding to a local oscillator frequency and an excitation frequency range can be analyzed independently.

[0066] Taking the excellent frequency corresponding to a local oscillator frequency and an excitation frequency range as an example, first calculate the frequency average value in the recent 30 days, and then construct the distribution frequency range centered on the frequency average value, so that 28 historical excellent frequencies in the recent 30 days are within the distribution frequency range. The distribution frequency range carries confidence data, and the confidence data is equal to 95%. The distribution frequency range is specifically the minimum frequency range covering 28 historical excellent frequencies closer to the frequency average value in the recent 30 days.

[0067] The preset multiple is specifically taken as 2 in this example, that is, the confidence frequency range is twice the width of the distribution frequency range, and the midpoint of the confidence frequency range is the frequency average value.

[0068] S240: If the judgment in step S230 is yes, then generate a collapse warning signal.

[0069] For each excellent frequency, it can be judged independently. That is, if there is a current excellent frequency exceeding the corresponding determined confidence frequency range, it indicates that the state of the target dangerous rock mass has changed significantly, indicating that the target dangerous rock mass is very likely to collapse. At this time, a collapse warning signal is generated.

[0070] In addition, in order to analyze the trend of the collapse of the target dangerous rock mass, the method further includes: determining the danger data of the target dangerous rock mass according to the historical excellent frequencies.

[0071] Specifically, the determining the danger data of the target dangerous rock mass according to the historical excellent frequencies includes:

[0072] Let the historical moment before the preset duration at the current moment be the first historical moment, and the historical moment two times the preset duration before the current moment be the second historical moment. The average frequency of the historical excellent frequencies between the first historical moment and the second historical moment is the pre-average frequency. Determine the model based on the range, and determine the pre-frequency range according to the pre-average frequency and the historical excellent frequencies within the first historical moment to the second historical moment; determine the hazard data according to the absolute value of the difference between the frequency average value and the pre-average frequency and the absolute value of the difference between the width of the distribution frequency range minus the width of the pre-frequency range. The hazard data is positively correlated with both the absolute value of the difference between the frequency average value and the pre-average frequency and the absolute value of the difference between the width of the distribution frequency range minus the width of the pre-frequency range. Let the lower limit of the pre-frequency range be and the upper limit of the range be , the pre-evaluation frequency is , and the hazard data is z, then , where in the formula, , are all greater than zero.

[0073] In one example, first calculate the average frequency and the distribution frequency range of the historical excellent frequencies in the recent 30 days, then calculate the average frequency and the distribution frequency range of the historical excellent frequencies between the recent 60 days and the recent 30 days, calculate the absolute value of the difference between the two average frequencies and the absolute value of the difference between the widths of the two distribution frequency ranges. The hazard data corresponding to the historical excellent frequency is equal to the sum of the two absolute values of the differences. The larger the two absolute values of the differences, the greater the cumulative change in the state of the target dangerous rock mass in the long term, indicating that the target dangerous rock mass is more dangerous. Since the historical excellent frequencies correspond one-to-one to the local oscillator frequencies and there may be multiple of them, if there are multiple historical excellent frequencies, the overall hazard data of the target dangerous rock mass is equal to the result of multiplying the hazard data of all historical excellent frequencies.

[0074] In summary, this method can achieve the collapse monitoring of the target dangerous rock mass, the monitoring is relatively reliable and can analyze the instantaneous state and long-term collapse trend of the target dangerous rock mass, so as to respond to the hazards brought by the collapse of the dangerous rock in a timely and effective manner.

[0075] It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that this application is not limited by the described action sequence, because according to the embodiments of this application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0076] In summary, this application at least includes the following beneficial effects:

[0077] A method and device for actively detecting and monitoring the collapse of dangerous rocks are provided, which can intelligently and reasonably determine whether the state of the target dangerous rock mass has changed, so as to reliably monitor the collapse of the target dangerous rock mass.

[0078] The above description is only a preferred embodiment of the present application and an explanation of the applied technical principles. Those skilled in the art should understand that the scope of disclosure involved in the present application is not limited to the technical solutions formed by the specific combination of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the foregoing disclosure concept. For example, the technical solutions formed by mutually replacing the above features with the technical features (but not limited to) having similar functions disclosed in the present application.

Claims

1. An active detection type dangerous rock collapse monitoring method, characterized in that: include: Determine a monitoring excitation signal according to at least one local oscillation frequency of the target dangerous rock mass acquired in advance, wherein the monitoring excitation signal includes a plurality of excitation frequency ranges corresponding to the local oscillation frequencies one by one; According to the monitoring echo signal of the target dangerous rock mass under the monitoring excitation signal, a dominant frequency is determined relative to each excitation frequency range; Determining whether the superior frequency exceeds a pre-acquired confidence frequency range; If so, a collapse warning signal is generated; The excitation frequency range takes the corresponding local oscillation frequency as the midpoint; The method for acquiring at least one local oscillation frequency of the target dangerous rock mass includes: Acquire a detection echo signal of the target dangerous rock mass under a detection excitation signal, wherein the frequency range of the detection excitation signal is wider than the frequency range of the monitoring excitation signal; Perform spectrum analysis on the detection echo signal to obtain multiple frequency point data and amplitude data corresponding to each frequency point data. Assume that there are n frequency point data and the i-th frequency point data is , the corresponding amplitude data is ; Determine the frequency point data whose amplitude data is higher than the preset amplitude and whose amplitude data is the maximum value as the local oscillation frequency, and set the preset amplitude as , the local oscillator frequency is , then the relative local oscillator frequency of satisfy ,and ,and .

2. The method according to claim 1, characterized in that The method for obtaining the confidence frequency range includes: Acquire historical monitoring records of the target dangerous rock mass, wherein the historical monitoring records include historical outstanding frequencies with timestamps; Determine the distribution frequency range based on the historical superior frequency distribution within a preset time period; The confidence frequency range is determined according to the distribution frequency range, the center of the confidence frequency range is the same as the center of the distribution frequency range, and the width of the confidence frequency range is a preset multiple of the distribution frequency range.

3. The method according to claim 2, characterized in that Determining the distribution frequency range according to the historical excellent frequency distribution within a preset time period includes: Calculate the frequency average of the historical excellent frequencies within the preset time length. Suppose there are i historical excellent frequencies within the preset time length, and the i-th historical excellent frequency is The average frequency is , ; Based on the pre-built range determination model, the distribution frequency range is determined according to the frequency average value and the historical excellent frequency within the preset time length. The frequency average value is the center of the distribution frequency range. The distribution frequency range covers a specified number of historical excellent frequencies within the preset time length. The lower limit of the distribution frequency range is set to , the upper limit of the range is , The historical excellence frequencies are within the distribution frequency range, and the specified quantity ratio is ,but .

4. The method according to claim 3, characterized in that Also includes: Determine the hazard data of the target dangerous rock mass based on the historical superiority frequency; The hazard data of the target dangerous rock mass determined according to the historical superior frequency include: Let the historical moment before the preset time length of the current moment be the first historical moment, the historical moment before twice the preset time length of the current moment be the second historical moment, and the frequency average of the historical excellence frequencies between the first historical moment and the second historical moment be the preceding average frequency; Based on the range determination model, determining a front frequency range according to the front average frequency and the historical superior frequency from the first historical moment to the second historical moment; The risk data is determined according to the absolute value of the difference between the frequency average value and the preceding average frequency and the absolute value of the difference between the width of the distribution frequency range and the width of the preceding frequency range. The risk data is positively correlated with the absolute value of the difference between the frequency average value and the preceding average frequency and the absolute value of the difference between the width of the distribution frequency range and the width of the preceding frequency range. The lower limit of the preceding frequency range is set to , the upper limit of the range is , the pre-evaluation frequency is , the hazard data is z, then , where , Both are greater than zero.

5. An active detection type dangerous rock collapse monitoring device, characterized in that: The invention comprises a signal transmitting module (110), a signal receiving module (120) and a device control module (130), wherein the signal transmitting module (110) is used to transmit an excitation signal to a target dangerous rock body, the signal receiving module (120) is used to receive an echo signal emitted by the target dangerous rock body, and the device control module (130) is connected to the signal transmitting module and the signal receiving module, and is used to execute the method according to any one of claims 1 to 4.

6. The device according to claim 5, characterized in that The device control module (130) is further configured to: Generate a wake-up signal based on the internal clock timing, wherein the wake-up signal is used to wake up the device; Based on the wake-up signal, the signal receiving module is triggered to obtain a Bunsen echo signal, where the Bunsen echo signal is an echo signal generated by the target dangerous rock body under natural conditions. If the Bunsen echo signal is obtained, the state of the target dangerous rock body is analyzed according to the Bunsen echo signal, otherwise the method described in any one of claims 1 to 4 is triggered to execute.

Images