WO2023115811A1 - 硬岩多尺度破裂的多频段声信号监测方法、装置、设备以及存储介质 - Google Patents

硬岩多尺度破裂的多频段声信号监测方法、装置、设备以及存储介质 Download PDF

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WO2023115811A1
WO2023115811A1 PCT/CN2022/095164 CN2022095164W WO2023115811A1 WO 2023115811 A1 WO2023115811 A1 WO 2023115811A1 CN 2022095164 W CN2022095164 W CN 2022095164W WO 2023115811 A1 WO2023115811 A1 WO 2023115811A1
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scale
hard rock
fracture
acoustic
acoustic signal
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PCT/CN2022/095164
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English (en)
French (fr)
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苏国韶
许华杰
李培峰
陈炳瑞
蓝兰
蓝日彦
李建合
刘宗辉
胡小川
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广西大学
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    • E—FIXED CONSTRUCTIONS
    • E21—EARTH OR ROCK DRILLING; MINING
    • E21F—SAFETY DEVICES, TRANSPORT, FILLING-UP, RESCUE, VENTILATION, OR DRAINING IN OR OF MINES OR TUNNELS
    • E21F17/00—Methods or devices for use in mines or tunnels, not covered elsewhere
    • E21F17/18—Special adaptations of signalling or alarm devices
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/14—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object using acoustic emission techniques
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
    • G01V1/30—Analysis

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  • the invention belongs to the technical field of geological disaster prevention engineering, and relates to a method, device, equipment and storage medium for monitoring the whole process of multi-scale fracture of hard rock by using multi-frequency band acoustic signals, and is suitable for real-time early warning of the whole process of surface and underground hard rock catastrophe breeding.
  • Effective monitoring of hard rock geological disasters is an important technical means to prevent geological disasters.
  • the essence of the breeding process of hard rock geological disasters is the fracture process of hard rock, that is, the sequential process of micro-crack initiation, crack development and expansion, crack penetration and instability in hard rock. Therefore, monitoring the fracture process of hard rock is an important way to effectively monitor hard rock geological disasters.
  • the strain energy accumulated inside releases a variety of acoustic and physical signals in the form of elastic waves, vibration waves, and stress waves.
  • the physical signals of these acoustic signals are monitored by means of acoustic signal instruments and equipment, so as to realize the effective monitoring of the fracture process of hard rock.
  • rock mass acoustic signals are generally divided into acoustic emission (10 4 Hz ⁇ 10 6 kHz, high frequency, suitable for characterizing hard rock fractures in the micrometer to centimeter scale), sound (20Hz ⁇ 20kHz, intermediate frequency, suitable for Acoustic signals in three frequency bands, including centimeter-meter-scale hard rock fractures) and microseismic (1Hz-100Hz, low frequency, suitable for meter-scale hard rock fractures).
  • acoustic signal monitoring generally adopts a single frequency band signal monitoring technical solution, which cannot effectively monitor the whole process of hard rock small-scale fractures developing to mesoscale and even large-scale fractures during the breeding process of hard rock geological disasters .
  • the present invention introduces acoustic signals of three different frequency bands into hard rock fracture monitoring, and proposes a multi-frequency band acoustic signal monitoring method, device, equipment and storage medium for multi-scale fracture of hard rock, so as to realize micro-crack initiation and crack development of hard rock.
  • the fine monitoring of the whole process from crack expansion, crack penetration to instability, and real-time evaluation of the fracture stage and state of hard rock have important application value for disaster prevention and mitigation of hard rock geological disasters.
  • the purpose of the present invention is to propose a multi-frequency band acoustic signal monitoring method, device, equipment and storage for monitoring the whole process of multi-scale fracture of hard rock, aiming at the problems of lack of frequency bands for acoustic signal monitoring in the cracking process of hard rock and insufficient cracking scale information.
  • Medium in order to effectively obtain the acoustic signal of multi-scale rupture of hard rock from micron to meter level, so as to realize the effective early warning of hard rock geological disasters.
  • the present invention adopts technical scheme as follows:
  • the present invention provides a method for monitoring multi-frequency band acoustic signals of multi-scale fractures in hard rock, comprising the following steps:
  • Step S1 Acoustic signals in three frequency bands of acoustic emission, sound, and microseismic signals in the process of hard rock fracture are collected in real time, and noise reduction is performed on the three acoustic signals;
  • Step S2 According to the activity of acoustic signals in three different frequency bands of acoustic emission, sound, and microseismic signals in the hard rock fracture process, determine the current stage of the hard rock fracture scale;
  • Step S3 According to the analysis and decision-making of the b-value of the acoustic signal at the current stage of the fracture scale of the hard rock, the b-value of the acoustic signal is calculated at a certain interval, and the trend of the b-value over time is analyzed to obtain the quantitative evaluation result of the evolution of the fracture scale of the hard rock;
  • Step S4 According to the hard rock instability early warning standard, that is, the current stage of the hard rock fracture scale and the time evolution trend of the b value, the monitored hard rock is subjected to an early warning of instability and damage.
  • step 2 the specific instructions are as follows:
  • the activity analysis method of the three kinds of acoustic signals adopts waveform analysis, and according to the differences in the sensitivity of each acoustic signal to the fracture scale of hard rock, the analysis means of each acoustic signal waveform are: acoustic emission signal-number of impacts, acoustic signal - waveform amplitude, microseismic signal - waveform amplitude;
  • the criterion for judging the stage of the rupture scale can be interpreted as: Criterion 1, the number of acoustic emission impacts presents a low value, an upward trend, or a high value that fluctuates steadily, and the amplitude of the sound or microseismic waveform is at a low level of activity, Hard rock fractures are at the centimeter level and below, and the crack development is in the "stable development" stage; Criterion 2, the number of acoustic emission impacts has a quiet period, and the amplitude of the sound waveform is obviously active, and the amplitude of the microseismic waveform is still low Activeness, the fracture of hard rock is below the meter scale, and the crack development is in the stage of "unstable development”; Criterion 3, the number of acoustic emission impacts occurs in a quiet period, and the waveform amplitudes of sound and microseismic are obviously active, hard rock The crack is at the meter level or above, and the crack development is in the
  • the crack development of hard rock when the crack development of hard rock is in the "stable fracture” stage, the high-frequency acoustic emission signal is relatively active, and the corresponding hard rock stress level is low, generally less than 80% of the peak stress of the rock mass;
  • the corresponding hard rock stress level when the crack development in the hard rock enters the "unstable development” stage, when the intermediate frequency sound signal becomes active, the corresponding hard rock stress level is relatively high, generally about 80% of the peak stress of the rock mass;
  • the crack development in the hard rock enters the "accelerated expansion” stage, when low-frequency microseismic signals become active, the corresponding hard rock stress level is high, generally about 95% or more of the peak stress of the rock mass.
  • step 3 the specific instructions are as follows:
  • the acoustic signal b value is a related parameter obtained based on the statistical relationship between earthquake magnitude and frequency.
  • Acoustic emission, sound and microseismic multi-band acoustic signals all have a high degree of correlation with seismic activity, so all The fracture evolution process of hard rock at various scales can be analyzed by the seismological b-value method;
  • the change of the b value of the acoustic signal is closely related to the evolution process of cracks inside the hard rock.
  • An increase in the b value means that the proportion of small events increases, mainly small-scale micro-cracks; a decrease in the b value means that large events When the proportion increases, the large-scale micro-cracks increase, and the b-value decreases significantly, indicating that the development of cracks changes drastically, which indicates that the hard rock may be destabilized and damaged;
  • the b-value analysis decision of the acoustic signal is: Decision 1, if the hard rock fracture scale is in the "stable development" stage, that is, when the centimeter-level scale and below the stage, the b-value calculation is performed on the acoustic emission signals at a certain interval of the same time ; Decision 2, if the hard rock fracture scale is in the "unstable development” stage, that is, when the centimeter-level scale reaches the meter-level stage, the b-value calculation is performed on the two acoustic signals such as acoustic emission and sound at the same time interval; decision 3, If the scale of hard rock fracture is in the stage of "accelerated expansion", that is, the stage of meter-level scale and above, the b value is calculated for the three acoustic signals of acoustic emission, sound and microseismic signals with a certain interval of the same time;
  • the acoustic signals of the three frequency bands have different characterization performances for different hard rock fracture scales, which in turn leads to differences in the characteristic variation trends of the b-values of the signals.
  • the acoustic emission signal is sensitive to small-scale ruptures, and falls first, and the rate of decline is relatively slow;
  • the acoustic signal is sensitive to medium-scale ruptures, and the fall time is slightly delayed, and the rate of decline is slightly accelerated;
  • the microseismic signal Sensitive to large-scale fractures it is shown as the latest decline time and the fastest decline rate; therefore, the evolution of each fracture scale stage of hard rock can be better evaluated by combining the variation trends of the three acoustic signal b values;
  • the fracture scale of the hard rock is in the "accelerated expansion" stage, it indicates that the fracture of the hard rock is at a fracture stage of more than one meter scale, and the stress level of the hard rock is about 95% of the peak stress of the rock mass, with a high failure rate.
  • the b-values of the three acoustic signals all show a downward trend, and the b-values of the acoustic and microseismic signals continue to increase, this indicates that hard rock fractures at the meter scale continue to grow and have a very high failure rate. To stabilize the risk of damage, give an immediate warning.
  • the present invention also provides a multi-band acoustic signal monitoring device for multi-scale fracture of hard rock, including:
  • Acoustic signal acquisition unit used for real-time acquisition of acoustic emission, sound, and microseismic multi-band acoustic signals in the process of hard rock fracture;
  • Acoustic signal transmission unit used for wireless transmission of effective data of three acoustic signals of hard rock fracture
  • Acoustic signal processing unit used for real-time preprocessing and noise reduction of hard rock fracture acoustic signals, and activity analysis of the three processed signals, so as to determine the current stage of hard rock fracture scale;
  • Acoustic signal evaluation unit used to analyze and make decisions based on the b value of the acoustic signal at the current stage of the hard rock fracture scale, calculate the b value of the acoustic signal at a certain interval, analyze the trend of the b value over time, and obtain a quantitative evaluation of the evolution of the hard rock fracture scale result;
  • Disaster early warning unit It is used to provide early warning of instability and failure of the monitored hard rock according to the hard rock instability early warning standard, that is, the current stage of hard rock fracture scale and the time evolution trend of b value.
  • the acoustic signal processing unit includes:
  • Acoustic signal preprocessing subunit used for noise reduction processing of acoustic emission, sound, and microseismic signal data received from hard rock fractures, so as to obtain relatively pure and high-quality signals to be analyzed;
  • Fracture scale stage discrimination sub-unit used to analyze the activity of the three types of signals after processing, and judge the current stage of the hard rock fracture scale.
  • the number of acoustic emission impacts presents a low value, an upward trend, or a high value that fluctuates steadily, and the amplitude of the sound or microseismic waveform is at a low level of activity;
  • Criterion 2 the crack "unstable development” stage, the hard rock fracture is below the meter-scale scale, the number of acoustic emission impacts has a quiet period, and the amplitude of the sound waveform is obviously active, and the amplitude of the microseismic waveform is still relatively active;
  • Criterion 3 the "accelerated expansion" of cracks stage, that is, hard rock fractures are at the meter level or above, the number of acoustic emission impacts has a quiet period, and the amplitudes of sound and microseismic waveforms are obviously active.
  • the acoustic signal evaluation unit includes:
  • Acoustic signal first evaluation subunit used to evaluate the evolution process of the "stable development” stage of the hard rock fracture scale through the characteristic change trend of the b-value of the high-frequency acoustic emission signal;
  • Acoustic signal second evaluation subunit used to evaluate the evolution process of the "unstable development" stage of the hard rock fracture scale through the characteristic change trend of b-value of intermediate frequency sound and high frequency acoustic emission signal;
  • the third evaluation subunit of the acoustic signal it is used to evaluate the evolution process of the "accelerated expansion" stage of the hard rock fracture scale through the characteristic change trend of low-frequency microseisms, medium-frequency sounds, and high-frequency acoustic emission b-values.
  • the present invention also provides a multi-band acoustic signal monitoring device for multi-scale fracture of hard rock, including:
  • the field device is used for real-time monitoring of the acoustic signal of engineering rock mass rupture, and will be wirelessly transmitted to the cloud device through 5G. It may include signal collector, power supply, high-speed AD converter, memory, clock, FGPA microcontroller, and one or more communication components. Step 1 of the above-mentioned multi-frequency band acoustic signal monitoring method for multi-scale fractures in hard rock can be completed.
  • the cloud device is used to receive the acoustic signal data of the rock mass rupture acquired by the field device, and through the noise filtering, waveform analysis and b-value analysis of the acoustic signal, further complete the rock mass rupture stage discrimination and fracture state evaluation, and finally Realize early warning of rock mass instability and damage risk.
  • It may include one or more of a memory, a multimedia component, an I/O interface, a communication component, and a processor.
  • the present application also provides a readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the above-mentioned multi-band acoustic signal monitoring of multi-scale fracture of hard rock is realized method steps.
  • the present invention provides an effective monitoring method for multi-scale fracture of hard rock for hard rock engineering, which can effectively solve the problem that a single acoustic signal monitoring method and its device cannot effectively characterize micro-crack initiation, crack propagation, and crack penetration of hard rock Up to the instability and failure, that is, the lack of the whole process of multi-scale fracture that evolves from small scale (micron scale) to large scale (meter scale), it is beneficial to significantly improve the accuracy of early warning of hard rock instability;
  • the present invention can not only be used to judge the current fracture scale stage of hard rock, but also quantitatively evaluate the evolution trend of hard rock fracture scale over time, which is conducive to the realization of advanced prediction and early warning of geological disasters induced by hard rock instability , which in turn helps to prolong the disaster avoidance time and reduce the risk of safety accidents caused by disasters;
  • the present invention proposes a multi-directional, grid-based intelligent monitoring system suitable for geological disasters of hard rock instability.
  • the system automatically collects multi-frequency band acoustic signals of hard rock ruptures, and transmits them to the convergence node by wire through sensors.
  • the processing module in the aggregation node filters out invalid data in an effective way, and then transmits the valid data within a certain period of sampling time to the cloud server, and stores, processes and analyzes the data in the cloud server, which can provide real-time early warning of hard rock Instability risk, compared with the traditional hard rock acoustic signal automatic monitoring system, the system has stronger perception ability, higher level of automation and intelligence, and has important practical value for the prevention of geological disasters caused by hard rock rupture and instability.
  • Fig. 1 is a flowchart of a multi-frequency band acoustic signal monitoring method for multi-scale fractures in hard rock provided by Embodiment 1 of the present invention.
  • FIG. 2 is a layout diagram of a multi-band acoustic signal monitoring network for a ground hard rock project—dangerous rock mass—provided in Embodiment 1 of the present invention.
  • Fig. 3 is a curve diagram of the characteristic variation of multi-band acoustic signal waveforms in the whole process of dangerous rock collapse and instability provided by Embodiment 1 of the present invention.
  • Fig. 4 is a characteristic change curve of the multi-band acoustic signal b value of the whole process of dangerous rock collapse and instability provided by Example 1 of the present invention.
  • Fig. 5 is a layout diagram of a multi-band acoustic signal monitoring network for tunnel surrounding rock in underground hard rock engineering provided by Embodiment 2 of the present invention.
  • Fig. 6 is a graph showing the characteristic variation of multi-band acoustic signal waveforms in the whole process of tunnel surrounding rock collapse provided by Embodiment 2 of the present invention.
  • Fig. 7 is a characteristic change curve of the multi-band acoustic signal b value of the whole process of tunnel surrounding rock collapse provided by Embodiment 2 of the present invention.
  • Fig. 8 is a schematic structural diagram of a multi-band acoustic signal monitoring device for multi-scale fracture of hard rock provided by Embodiment 3 of the present invention.
  • FIG. 9 is a schematic structural diagram of an acoustic signal acquisition unit provided in Embodiment 3 of the present invention.
  • FIG. 10 is a schematic structural diagram of an acoustic signal transmission unit provided by Embodiment 3 of the present invention.
  • FIG. 11 is a schematic structural diagram of an acoustic signal processing unit provided by Embodiment 3 of the present invention.
  • FIG. 12 is a schematic structural diagram of an acoustic signal evaluation unit provided by Embodiment 3 of the present invention.
  • Fig. 13 is a schematic diagram of a multi-band acoustic signal monitoring field device for multi-scale fracture of hard rock provided by Embodiment 4 of the present invention.
  • Fig. 14 is a schematic diagram of a multi-band acoustic signal cloud device for multi-scale fracture of hard rock provided by Embodiment 4 of the present invention.
  • Step S1-1 Embodiment 1 of the present invention conducts real-time monitoring on a local part of a limestone mountain with relatively serious joints in Guangxi Zhuang Autonomous Region.
  • Attached Figure 2 is a layout diagram of a local dangerous rock mass monitoring network. Firstly, calculate the optimal grid layout of the acoustic signal sensors according to the topography and location of the monitoring objects; then, arrange the acquisition units of the three kinds of acoustic signal sensors in the preset positions in sequence, and smear and couple the acoustic emission and microseismic sensors Place the agent at a relatively complete, stable, and easy-to-install part of the dangerous rock mass.
  • the sound sensor can be installed directly at the acquisition unit;
  • the multiple acoustic signal sensor acquisition units that have been arranged are converged into points in a network structure and connected to the acoustic signal acquisition terminal; finally, the data of each acoustic signal sensor acquisition unit recorded and received by the acoustic signal acquisition terminal is wirelessly transmitted to the acoustic signal processing system, the present invention applies the computing module in the cloud server.
  • the acquisition unit of the three kinds of acoustic signal sensors is a minimum unit of acquisition, and its acquisition unit is equipped with an acoustic emission sensor, a sound sensor, and a microseismic sensor, and each sensor is drawn from a closed unit.
  • the coupling agent embeds the monitoring target and the sensor as one; the coupling agent has the characteristics of plasticity, quick setting, and uniformity, and removes the air and moisture in the coupling interface to achieve direct contact between the sensor and the rock wall; however, thanks to the sound signal
  • the sound sensor only needs to be installed in the reserved position around the acquisition unit.
  • the characteristics of the installation site of the acoustic emission and microseismic sensor in Embodiment 1 of the present invention no excessive cracks, good contact between the interface and the sensor, high stability, and easy manual installation and disassembly.
  • the selection of three types of acoustic signals is as follows: the acoustic emission sensor is a relatively low-frequency resonant sensor with high sensitivity, its sampling frequency range is 10-70kHz, and the sensitivity is as high as 121dB; the acoustic sensor is a highly sensitive capacitive sensor , the sampling range is 20Hz-20kHz, the sensitivity is as high as 80-85dB (1kHz); the microseismic sensor is a high-sensitivity piezoelectric acceleration sensor, the sampling frequency range is between 0.6-300Hz, and the voltage sensitivity is as high as 30V/m/s 2 .
  • sampling rate value set the sampling rate value of each acoustic signal through the maximum frequency range parameter of the selected sensor of each frequency band acoustic signal, the low frequency microseismic signal - 1000Hz, the intermediate frequency sound signal - 44.1kHz, the high frequency acoustic emission signal —150kHz.
  • Step S1-2 Perform an automatic noise reduction operation on the multi-band acoustic signal data received from the rupture of the dangerous rock mass, remove the periodic environmental noise signal superimposed in the effective rupture signal, and obtain relatively pure acoustic signal data of the rupture of the dangerous rock mass.
  • the acoustic signal monitoring method for multi-scale fractures of hard rock proposed by the present invention is based on the acoustic signals of multiple different frequency bands of the rupture of dangerous rock masses, so there are certain differences in the denoising methods for the acoustic signals of multiple different frequency bands sex.
  • the three signals are all in the category of acoustic signal science, and the denoising principles are consistent.
  • the present invention adopts the wavelet threshold denoising method, also known as the wavelet shrinkage (Wave Shrink, WS) method.
  • Step (1) select appropriate wavelet function, wavelet basis and wavelet decomposition layer number, carry out discrete wavelet transform to the acoustic signal s(n) that contains noise, obtain corresponding wavelet coefficient D i ;
  • Step (2) using the threshold value to process the wavelet coefficient D i obtained by the discrete wavelet transform, to obtain the corresponding wavelet coefficient estimated value d i ;
  • step (3) the acoustic signal is reconstructed by using the estimated value di of the wavelet coefficient, so as to obtain the estimated value h(n) of the original acoustic signal.
  • the core problem of the wavelet threshold denoising method is to choose an appropriate threshold.
  • thresholds There are three types of thresholds: hard threshold, soft threshold and semi-soft threshold. Since the semi-soft threshold method can take into account the advantages of both soft and hard thresholds, the denoised acoustic signal has the original smoothness and can retain the details of the original acoustic signal. The formula is as follows:
  • the essence of wavelet denoising is to perform multi-strategy processing on different frequency band signals to obtain the most complete and pure original signal; the frequency bands monitored by the three acoustic signals of acoustic emission, sound, and microseismic signals are different, and hard rock fractures The overall distribution of the frequency bands of each sound signal is also different. Therefore, when performing wavelet denoising operations, the wavelet function, wavelet base, and wavelet decomposition layers mentioned in the above process need to be selected according to the three signal characteristics.
  • Step S1-3 According to the activity of acoustic signals in three different frequency bands of acoustic emission, sound, and microseismic signals in the hard rock fracture process, determine the current stage of the hard rock fracture scale.
  • the activity analysis methods of the three acoustic signals adopt waveform analysis.
  • the waveform analysis methods of each acoustic signal are: acoustic emission signal - number of impacts, acoustic signal - —Waveform amplitude, microseismic signal—waveform amplitude.
  • the criterion for judging the stage of the rupture scale can be interpreted as: Criterion 1, the number of acoustic emission impacts presents a low value, an upward trend, or a high value that fluctuates steadily, and the amplitude of the sound or microseismic waveform is at a low level of activity, Hard rock fractures are at the centimeter level and below, and the crack development is in the "stable development" stage (stage I); Criterion 2, the number of acoustic emission impacts occurs in a quiet period, and the amplitude of the sound waveform is obviously active, and the amplitude of the microseismic waveform Still showing low activity, hard rock fractures are below the meter scale, and crack development is in the "unstable development” stage (stage II); criterion 3, the number of acoustic emission impacts occurs in a quiet period, and the waveform amplitudes of sound and microseismic The values are obviously active, the fracture of hard rock is at the meter level and above,
  • the initial stress levels of the hard rock in the "unstable development” and “accelerated expansion” stages of fracture scale are about 80%, 95% and above, respectively, corresponding to the obvious active starting points of intermediate-frequency sound and low-frequency microseismic signals .
  • AE hits is the number of acoustic emission hits
  • AE hit rate is the activity level of acoustic emission hits
  • Sound amplitude rate is the activity level of the sound signal waveform amplitude
  • MS amplitude rate is the activity level of the microseismic signal waveform amplitude
  • HT is the sound emission The high activity level value of the impact number
  • LT is the low activity level value of the acoustic emission impact number, and it can be judged whether there is a quiet period in the acoustic emission signal through AE hits and Sound amplitude rate or/and MS amplitude rate
  • A, B, and C are respectively Acoustic emission, sound, and microseismic activity thresholds, the above values are determined according to the specific environment.
  • Figure 3 is a characteristic evolution diagram of multi-band acoustic signal waveforms for monitoring the entire process of the rupture of dangerous rock mass, specifically the monitoring data from 0:00 to 12:00 on February 16, 2021; , the AE impact number of dangerous rock mass rupture is judged as stage I when it is in a low-active high-increase trend or in a high-active low-increase trend stage, that is, the period from 0:00 to 10:30; further, the AE impact number of dangerous rock mass rupture Low activity, high activity of sound amplitude and low activity of microseismic amplitude are judged as stage II, that is, from 10:30 to 11:06; finally, the acoustic emission of dangerous rock mass rupture is at low activity, the sound is at high activity and When the microseismic amplitude is highly active, it is judged as stage III, that is, from 11:06 to 11:48.
  • Step S1-4 According to the analysis and decision-making of the b value of the acoustic signal at the current stage of the hard rock fracture scale, the b value of the acoustic signal is calculated at a certain interval, and the trend of the b value over time is analyzed to obtain the quantitative evaluation results of the evolution of the hard rock fracture scale.
  • m is the magnitude of the acoustic signal applicable to a certain rupture scale
  • N is the number of rupture events whose magnitude varies within the range of ⁇ m.
  • the b-value analysis of the acoustic signals in each frequency band is carried out based on the signal amplitude, thus, the b-value curve of each acoustic signal in the whole process of the multi-scale rupture of the dangerous rock mass is obtained, as shown in Fig. 4 .
  • the high-frequency acoustic emission signal is used to independently evaluate the scale evolution process of the dangerous rock mass; from 0:00 to 7:27
  • the acoustic emission b value fluctuates steadily between 5 and 6, which indicates that the number of rupture events of the dangerous rock mass and the scale change of the rupture event are in a dynamic stability, but the overall rupture event scale of the dangerous rock mass is at a low level;
  • the acoustic emission b value showed an obvious downward trend, and between 9:19 and 9:56, it dropped to a relatively low value of 2.15, which indicated the rupture of the dangerous rock mass
  • the event scale showed a trend of increasing gradually, and the overall rupture scale of the dangerous rock mass was at a medium level at this time; in addition, after 9:56, the decline rate of the acoustic emission b value slowed down and gradually turned into a steady fluctuation, and the
  • the stress level of the rock mass is about 80%
  • the medium-frequency sound signal and the high-frequency acoustic emission signal are used to monitor at the same time, so as to achieve micron cracks in the dangerous rock mass.
  • Assessment of the evolution process of fracture scales ranging from the level to the meter level. It can be found that from 10:30 to 11:11, the overall value of the sound b value showed a steady fluctuation trend between 4.18 and 5.14, and slightly decreased, which indicated that the scale of the rupture event of the dangerous rock mass showed a slow increase. Trend; further, according to the judgment results of the above-mentioned rupture scale stage of the dangerous rock mass, after 11:11, the rupture scale stage of the dangerous rock mass has turned into stage III.
  • the stress level of the rock mass is about 95% or above
  • the low-frequency microseismic signal, the medium-frequency sound signal and the high-frequency acoustic emission signal are used to simultaneously monitor, so as to realize Evaluation of the fracture scale evolution process of the dangerous rock mass ranging from micron to meter above. It can be found that after 11:11, the acoustic emission b-value presents a calm period with low values and stable fluctuations, while the sound b-value presents a high-value and rapid decline trend, and the microseismic b-value presents a high-value stable fluctuation between 4.15 and 4.87.
  • Step S1-5 According to the early warning standard of hard rock instability, that is, the current stage of hard rock fracture scale and the time evolution trend of b value, an early warning of instability and damage is carried out for the monitored hard rock.
  • the b-value characteristics of multi-band acoustic signals all show a significant downward trend at different fracture scale stages, so as to reveal the scale evolution process of hard rock fracture events at different fracture scale stages.
  • the rupture of the dangerous rock mass is in the "accelerated expansion" stage III
  • the stress level of the rock mass is about 95% and above
  • the rupture of the dangerous rock mass is in a meter-scale rupture stage, with a certain failure.
  • the b-value of acoustic emission presents a low-value stable fluctuation trend, while the b-value of sound and microseismic both show a significant downward trend, and the two have a large and sudden increase at 11:35 and 11:40 respectively.
  • the monitored dangerous rock mass experienced a short-term shear slip phenomenon along the plane of the main control structure, and occurred downward from the mountainside at an altitude of 27m caused by its own weight.
  • the multi-track rolling eventually piled up at the foot of the mountain, causing no casualties.
  • the sampling time of the samples sampled in Example 1 of the present invention is not fixed, according to the threshold values of the three acoustic signals To define, if the threshold value is exceeded, continuous sampling will be performed, otherwise it will be in a stagnant sampling state. This sampling method effectively reduces useless data and provides feasibility for data analysis and data wireless transmission.
  • Implementation 2 of the present invention is in the field of deep hard rock engineering.
  • the process flow of the multi-frequency band acoustic signal monitoring method for multi-scale fracture of hard rock is similar to that of implementation 1, and will not be described in detail.
  • the method specifically includes the following:
  • Step S2-1 Embodiment 2 of the present invention carried out real-time monitoring on the excavation process of a tunnel with a depth of 570m from the surface and a diameter of 10m in a certain city in Yunnan province.
  • Attached drawing 5 is a layout diagram of the monitoring network of the tunnel. Considering that during the excavation process of the tunnel, not only the tunnel face will experience high-intensity damage caused by the rapid release of elastic strain energy of the hard rock, but the tunnel section after excavation will also be affected by the disturbance caused by excavation and blasting, resulting in relatively serious static damage. , Power damage.
  • strain-type rockburst disasters are mainly concentrated around 2.3 times the tunnel diameter, and there is little distribution beyond this range.
  • 75m at the back of the face it is divided into 5 sections of 5m, 15m, 25m, 50m, and 75m; then, apply coupling agent to the acoustic emission and microseismic sensors, and install them in suitable holes on both sides of the excavated section.
  • the sound sensor can be directly installed at the acquisition unit; then, the multiple acoustic signal sensor acquisition units that have been arranged in the tunnel are connected with multiple wireless relay bridges and a total wireless
  • the network bridge transmits to the acoustic signal acquisition terminal; finally, the data of each acoustic signal sensor acquisition unit recorded and received by the acoustic signal acquisition terminal is transmitted to the acoustic signal processing system, and the present invention applies the computing module in the cloud server.
  • the connection sensors of the acquisition units arranged in the above five tunnel sections are located at 2-5m from the monitoring section; and the deep tunnel is in a highly airtight environment , the data signal is weak, the transmission efficiency is low, and the huge data volume of the three acoustic signals cannot be transmitted in real time; therefore, a wireless bridge component is introduced, and each acquisition unit at the tunnel section is equipped with a transmission sub-wireless bridge, and then A general receiving wireless network bridge is arranged 500m away from the tunnel face, and then a point-to-point, repeater wireless network bridge is arranged at an equal distance of 500m to transfer the collected hard rock cracking sound signals.
  • the total number of wireless network bridges is determined according to the excavation length of the tunnel , finally deploy a final receiving general wireless network bridge N at the entrance of the excavated tunnel, connect this wireless network to an acoustic signal acquisition terminal central processing unit, and be responsible for integrating all the data collected in the tunnel, extracting valid data and wirelessly transmitting to the acoustic signal processing system.
  • monitoring ends may be in a relatively active period of macro cracks, while another monitoring section may be in a period of micro cracks. crack development period.
  • the specific parameters of the acoustic signal in each frequency band are: acoustic emission sensor, which is a relatively wide-band resonant sensor with high sensitivity, and its sampling frequency range is 20-800kHz, and its sensitivity is as high as 110dB
  • the sound sensor is a highly sensitive capacitive sensor with a sampling range of 20Hz-20kHz and a sensitivity of 80-85dB (1kHz);
  • the microseismic sensor is a high-sensitivity piezoelectric acceleration sensor with a sampling frequency range of 0.8-450Hz
  • the voltage sensitivity is as high as 25V/m/s 2 ; further, based on the signal Nyquist sampling theorem (if you need to obtain relatively complete information of the original signal, generally you need to ensure that the sampling frequency is twice the highest frequency of the signal), the acquisition device
  • the sampling rate value setting is comprehensively considered in many aspects such as power consumption and signal data validity.
  • the sampling rate value of each acoustic signal is set separately through the maximum frequency range parameters of the selected sensor for each frequency band acoustic signal, and the low frequency microseismic signal—1000Hz , Intermediate frequency sound signal - 44.1kHz, high frequency acoustic emission signal - 1.6MHz.
  • the entire process of this embodiment monitors the surrounding rock rupture process near a total of 5 tunnel sections, among which there are 3 tunnel section points such as 5m, 15m, and 50m where the surrounding rock cracks Dynamic damage rockburst phenomenon; due to limited space, only the multi-band acoustic signal monitoring process of the surrounding rock collapse at the 15m section with the highest destructive intensity is shown.
  • Step S2-2 Similar to step S1-2, the environmental noise superimposed in the three acoustic signals of tunnel surrounding rock rupture is filtered out by formula (1).
  • Step S2-3 Similar to step S1-3, the waveform analysis of the multi-band acoustic signal of the tunnel surrounding rock rupture is carried out through formula (2), and then the current stage of the surrounding rock rupture scale is judged.
  • Figure 6 is a graph showing the characteristic change curve of the multi-band acoustic signal waveform for monitoring the whole process of surrounding rock rupture, specifically the monitoring data from 0:00 to 15:00 on February 16, 2021; through the number of acoustic emission impacts and sound, Analysis of the amplitude characteristics of microseismic waveforms, and distinguish the stages of rupture scales such as "stable development” stage I, "unstable development” stage II, and "accelerated expansion” stage III of the surrounding rock of the tunnel. 42 and from 13:42 to 14:56.
  • Step S2-4 Similar to step S1-4, calculate the b-value characteristics of the acoustic signal in different frequency bands of the surrounding rock rupture through formula (3), and based on the stage discrimination results of the rupture scale in step S1-3, the current The b-value analysis and decision-making of the stage acoustic signal realizes the quantitative evaluation of the evolution of hard rock fracture scale.
  • Figure 7 shows the b-value change curves of the various acoustic signals in the whole process of multi-scale rupture of the surrounding rock at the 15m section of the tunnel.
  • the scale evolution process of the surrounding rock fracture is independently evaluated by using high-frequency acoustic emission signals from 0:00 to 13:00; between 0:00 and 11:48,
  • the acoustic emission b value fluctuates steadily between 5.6 and 8.1, which indicates that the number of rupture events and the scale of rupture events in the surrounding rock are in a dynamic stability, but the overall rupture event scale of the surrounding rock is at a low level; when it exceeds 11:48 Afterwards, the acoustic emission b value showed an obvious downward trend, and between 12:42 and 13:02, it dropped to a relatively low value of 2.75, which implied that the scale of the surrounding rock rupture event gradually increased.
  • stage II and stage III cannot reflect the evolution process of surrounding rock rupture events well only through acoustic emission signals, and need to be evaluated in combination with intermediate-frequency sound and low-frequency microseismic signals suitable for centimeter scales and above.
  • the stress level of the surrounding rock is about 80%, and the intermediate frequency sound signal and the high frequency acoustic emission signal are used to monitor at the same time, so as to realize the Assessment of the evolution process of fracture scales in the meter range. It can be found that from 13:00 to 13:42, the overall value of the sound b value showed a steady fluctuation trend between 5.57 and 7.01, and slightly decreased, which indicated that the scale of the surrounding rock rupture event showed a slow increase trend; further , according to the above judgment results of the scale stage of the surrounding rock rupture, after 13:42, the stage of the surrounding rock rupture has turned into stage III. Therefore, it is necessary to comprehensively evaluate the evolution process of the surrounding rock rupture scale in combination with low-frequency microseismic signals.
  • the stress level of the surrounding rock is about 95% or above
  • the low-frequency microseismic signal, the medium-frequency sound signal and the high-frequency acoustic emission signal are used to monitor simultaneously, so as to realize the surrounding rock Evaluation of the evolution process of fracture scales ranging from micron to meter above. It can be found that after 13:42, the b-value of acoustic emission presents a calm period with low values and steady fluctuations, while the b-value of sound presents a trend of rapid decline at high values, and the b-value of microseisms presents a high and stable fluctuation between 5.74 and 6.47.
  • Step S2-5 According to the hard rock instability early warning standard, that is, the current stage of the hard rock fracture scale and the time evolution trend of the b value, the monitored hard rock is subjected to an early warning of instability and damage.
  • the surrounding rock rupture of the tunnel is in the "accelerated expansion" stage III, the stress level of the surrounding rock is about 95% and above, and the surrounding rock rupture is in a meter-scale rupture stage, with certain instability Risk of damage; moreover, the b-value of acoustic emission showed a steady fluctuation trend of low values, while the b-values of sound and microseismic both showed a significant downward trend, and the two showed a sharp drop at 14:26 and 14:39 respectively This shows that the meter-scale fracture of surrounding rock continues to grow, and there is a very high risk of instability and damage. That is, at 14:39, an early warning of surrounding rock collapse will be carried out.
  • the early warning method is multi-channel early warning such as on-site, mobile terminal, and cloud.
  • the surrounding rock mass of about 9m 2 at the upper right of the 15m section of the tunnel broke away from the parent rock and collapsed, and fell vertically around the tunnel.
  • the evaluation results of the surrounding rock rupture state provided early warning of landslide disasters, and all construction equipment and personnel inside the tunnel have been evacuated without causing any economic losses and casualties.
  • the sampling time of the samples sampled in Embodiment 2 of the present invention is not fixed, and is defined according to the threshold values of the three acoustic signals. If If the threshold value is exceeded, continuous sampling will be performed, otherwise it will be in a stagnant sampling state. This sampling method effectively reduces useless data and provides feasibility for data analysis and data wireless transmission.
  • Figure 8 is a schematic structural diagram of a multi-band acoustic signal monitoring device for multi-scale fracture of hard rock provided by Embodiment 3 of the present invention.
  • the device of this embodiment can be used to implement the above-mentioned method embodiments of the present application, and the device of this embodiment includes:
  • Acoustic signal acquisition unit 3-1 used for real-time acquisition of acoustic emission, sound, and microseismic multi-band acoustic signals in the process of hard rock fracture;
  • Acoustic signal transmission unit 3-2 used for wireless transmission of effective data of three acoustic signals for hard rock fracture;
  • Acoustic signal processing unit 3-3 used for real-time preprocessing and noise reduction of hard rock fracture acoustic signals, and activity analysis of the three processed signals, so as to determine the current stage of hard rock fracture scale;
  • Acoustic signal evaluation unit 3-4 used to analyze and make decisions based on the b value of the acoustic signal at the current stage of the hard rock fracture scale, calculate the b value of the acoustic signal at a certain interval, analyze the trend of the b value over time, and obtain the evolution of the hard rock fracture scale Quantitative evaluation results;
  • Disaster early warning unit 3-5 used for early warning of instability and failure of the monitored hard rock according to the hard rock instability early warning standard, that is, the current stage of the hard rock fracture scale and the time evolution trend of b value.
  • acoustic signal acquisition unit 3-1 comprises:
  • Acoustic signal acquisition sub-unit 3-1-1 used to collect multi-band acoustic signal data of the whole process of multi-scale fracture at each monitoring position of hard rock;
  • Acoustic signal acquisition control subunit 3-1-2 used to send commands to the acquisition subunits to control the acquisition, storage and deletion of acoustic signal data of each acquisition subunit. Its control features are: in terms of acquisition function, when the acquisition subunit signal When the activity does not exceed the set threshold value, it is in sleep mode. If it exceeds the threshold value, the acquisition mode of each acquisition sub-unit is activated and turned into a normal mode; in terms of storage function, the storage acquisition sub-unit collects effective microseismic signals ; In terms of deletion function, when the amount of stored data is greater than the total amount of single storage of the acquisition sub-unit, the previous segment of data stored in it will be gradually deleted one by one.
  • the acoustic signal transmission unit 3-2 includes:
  • Acoustic signal transmission subunit 3-2-1 used for real-time transmission of rupture event acoustic signal data with obvious changing characteristics
  • Acoustic signal transmission control subunit 3-2-2 used to send commands to the transmission subunit to control the transmission of acoustic signal data of the transmission subunit. Specifically, it can be interpreted as: when the microseismic signal data storage capacity is greater than or equal to a complete sampling time period , the transmission function of the signal transmission subunit is turned on, and the data stored in it is transmitted to the cloud server in real time through wireless transmission.
  • described acoustic signal processing unit 3-3 comprises:
  • Acoustic signal preprocessing subunit 3-3-1 used for noise reduction processing of acoustic emission, sound, and microseismic signal data received from hard rock fractures, so as to obtain relatively pure and high-quality signals to be analyzed;
  • Fracture Scale Stage Discrimination Subunit 3-3-2 Used to analyze the activity of the three processed signals and judge the current stage of the hard rock fracture scale.
  • the judgment criterion is: Criterion 1, the crack "stable development" stage , that is, the cracking of hard rock is at the scale of centimeters or below, the number of acoustic emission impacts presents a low value, an upward trend, or a high value that fluctuates steadily, and the amplitude of the sound or microseismic waveform is at a low level of activity; Criterion 2, the crack In the "unstable development” stage, the hard rock fracture is below the meter scale, the number of acoustic emission impacts has a quiet period, and the amplitude of the sound waveform is obviously active, and the amplitude of the microseismic waveform is still relatively active; Criterion 3, In the "accelerated expansion" stage of cracks, that is, the hard rock fractures are at the scale of meters or above, the number of acoustic emission impacts
  • described acoustic signal evaluation unit 3-4 comprises:
  • Acoustic signal first evaluation subunit 3-4-1 used to evaluate the evolution process of the "stable development" stage of the hard rock fracture scale through the characteristic change trend of the b-value of the high-frequency acoustic emission signal;
  • Acoustic signal second evaluation subunit 3-4-2 used to evaluate the evolution process of the "unstable development" stage of the hard rock fracture scale through the characteristic change trend of b value of intermediate frequency sound and high frequency acoustic emission signal;
  • Acoustic signal third evaluation subunit 3-4-3 used to evaluate the evolution process of the "accelerated expansion" stage of the hard rock fracture scale through the characteristic change trend of low-frequency microseisms, medium-frequency sounds, and high-frequency acoustic emission b-values.
  • this embodiment also provides a multi-band acoustic signal monitoring device for multi-scale fracture of hard rock.
  • the multi-band acoustic signal monitoring equipment for multi-scale fractures of hard rock described below and the multi-band acoustic signal monitoring method for multi-scale fractures of hard rock described above can be referred to each other.
  • Field device 4-1 may include: signal collector 4-1-1, power supply 4-1-2, high-speed AD converter 4-1-3, storage 4-1-4, clock 4-1-5, FGPA Microcontroller 4-1-6, and communication components 4-1-7.
  • the signal collector 4-1-1 is used to collect multi-band acoustic signals of multi-scale fractures of hard rock.
  • the signal collector 4-1-1 includes: an acoustic signal analog signal sensor and a signal conditioner; the acoustic signal analog signal sensor is used to measure the energy or vibration physical quantity produced by the fracture of hard rock through the sensing element;
  • the acoustic signal analog signal sensor includes: an acoustic emission sensor, a sound sensor and a microseismic sensor.
  • the acoustic emission sensor can be a resonant/differential type acoustic emission sensor, the resonant type can be used in general environment, and the differential type can be used in the environment with partial discharge detection or strong electrical interference; optional, the acoustic sensor can be It is a capacitive/electret type sound sensor; optionally, according to the direction of collecting vibration physical quantities, the microseismic sensor can be a one-way/three-way acceleration microseismic sensor, and according to the collection principle, the microseismic sensor can be a charge output type/voltage output type Acceleration sensor; as mentioned above, the signal conditioner is a double-integral conditioner that can gain the acoustic emission/sound/microseismic analog signal input from the sensor end, and also includes high- and low-pass filtering functions.
  • the power supply 4-1-2 is used to provide power for other subcomponents of the field device 4-1 to operate normally.
  • the power supply 4-1-2 can be a lithium battery, a storage battery, or a solar battery, and the specific type depends on the environment of the project site.
  • the high-speed AD converter 4-1-3 is used to convert the analog signal acquired by the sensor into a digital signal recognizable by the computer.
  • the high-speed AD converter needs to meet technical requirements such as sampling theorem, wideband, signal dynamic characteristics, and less quantization noise, and it also needs to be a type with more than 3 channels, a sampling rate of more than 1MSPS, and a quantization accuracy of 16 Bit high-performance AD.
  • the memory 4-1-4 is used to store the digital signal data converted by the high-speed AD converter 4-1-3, and is also used to store pre-designed computer program codes for the FGPA microcontroller 4-1-6 Call run.
  • the memory 4-1-4 can be a static random access memory (Static Random Access Memory, SRAM) or a synchronous dynamic random access memory (Synchronous Dynamic Random Access Memory, SDRAM), and can also be a pseudo-static random access memory (Pseudo Static Random Access Memory, PSRAM) memory, but it can also store a combination of two or three for the above three types.
  • the clock 4-1-5 is used to provide clock services for other sub-assemblies of the field device 4-1, specifically to enable other sub-assemblies to work synchronously, and to achieve synchronous timing when communicating with external devices.
  • the clock 4-1-5 may include a clock source component that provides clock information, and may also include a synchronous timing component that provides synchronous timing services.
  • the clock source component can be a low-frequency/high-frequency time source LFXTICLK or a high-frequency clock source XTCLK, or a voltage-controlled oscillator clock DCOCLK, or even a combination of two clock sources or three clock sources Combination; as mentioned, if the above three clock sources are combined, the clock component can provide the auxiliary clock signal ACLK, the main clock signal MCLK and the subsystem clock signal SMCLK; as described, the auxiliary clock signal ACLK is generated by the FLXT1CLK clock source , can be used to provide CPU peripheral function module clock signal in FPGA microcontroller 4-1-6; Described, main clock signal MCLK is produced by above-mentioned three kinds of clocks, can be used to provide FPGA microcontroller 4-1-6 and Relevant system module clock signals; as mentioned above, the subsystem clock signal SMCLK is generated by any two of the above three clock sources, and can be used to provide clock signals for peripheral components.
  • main clock signal MCLK is produced by above-mentioned three kinds of clock
  • the synchronous timing component can be a precise time protocol PTP timing system, a GPS timing system or a Beidou timing system, or even an ultra-high-precision rubidium clock timing system; optionally, the The synchronous timing component can also be a combination of the above-mentioned multiple timing systems, specifically: PTP+Beidou, GPS+Beidou, and PTP+rubidium clock three time synchronization modes.
  • PTP+Beidou and GPS+Beidou timing systems can only be used in the monitoring of surface hard rock engineering with better signals, while the PTP+rubidium clock timing system can be used in all rock mass engineering monitoring.
  • the FPGA microcontroller 4-1-6 is used to call the computer program in the memory 4-1-4 to control other components in the field device 4-1 to perform desired functions.
  • the FGPA microcontroller 4-1-6 can be designed under any language environment in VHDL, Verilog HDL, System Verilog and System C;
  • the FGPA microcontroller 4-1 -6 may include: input and output units, programmable logic blocks, underlying embedded functional units, Block RAM and programmable wiring matrix; optional, the input and output units are the interface part between the chip and external circuits, and complete different electrical characteristics
  • the drive and matching requirements for input/output signals can be HP I/O units or HD I/O units; optionally, the programmable logic block can include look-up tables and registers; the look-up table Complete pure combinational logic functions; as mentioned above, the registers can be configured as flip-flops or latches; optionally, the underlying embedded functional units can be DLL, PLL, DSP and CPU, which are used to realize high-precision clock distribution, Low
  • the communication component 4-1-7 is used to realize wired or wireless communication between the field device 4-1 and other external devices.
  • the communication component 4-1-7 can be an independent router, or a combination component constructed by a fiber optic box, an optical fiber and a router, or even a combination component constructed by a wireless bridge, an optical fiber and a router;
  • the above-mentioned optical fiber box, router and wireless bridge can be one or more; as mentioned above, the final communication mode of the above-mentioned single component or multiple components adopts 5G, and 5G communication can be operated by one of China Mobile, China Unicom or China Telecom Provider-owned SIM cards.
  • the embodiment also provides a structure diagram of a multi-band acoustic signal monitoring cloud device for multi-scale fracture of hard rock, such as a mobile terminal, a personal computer, a tablet computer, a server, and the like.
  • cloud device 4-2 comprises: memory 4-2-1, multimedia component 4-2-2, I/O interface 4-2-3, communication component 4-2-4, and processor 4- 2-5 and so on for one or more subs.
  • the components and structure of the cloud device shown in FIG. 14 are only exemplary rather than limiting, and the cloud device 4-2 may also have other components and structures as required.
  • the memory 4-2-1 may include one or more computer program products, and the computer program products may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory .
  • the volatile memory may include, for example, a random access memory (RAM) and/or a cache memory (Cache).
  • the non-volatile memory may include, for example, a read-only memory (ROM), a hard disk, a flash memory, and the like.
  • One or more computer program instructions can be stored on the computer-readable storage medium, and the processor 4-2-5 can execute the program instructions to realize the embodiments of the present invention described below (implemented by the processor) computer functions and/or other desired functions.
  • Various application programs and various data such as various data used and/or generated by the application programs, may also be stored in the computer-readable storage medium.
  • the multimedia component 4-2-2 can be used to receive instructions input by the user and collect data, and can also output various information (such as data, images or sounds) to the outside (such as the user), and can include a display , speakers, etc.
  • the I/O interface 4-2-3 provides an interface between the processor 4-2-5 and other interface modules.
  • the above-mentioned other interface modules can be keyboards, mice, buttons, etc., and these buttons can be virtual buttons or Physical button.
  • the communication component 4-2-4 is used for wired or wireless communication between the cloud device 4-2 and other devices.
  • Wireless communication can be short-range communication Wi-Fi, Bluetooth, or NFC, or long-distance 5G communication, which can be one or more combinations.
  • the processor 4-2-5 can be a central processing unit (CPU) or other forms of processing units with data processing capabilities and/or instruction execution capabilities, and can control other processes in the cloud device 4-2.
  • the components are used to perform expected functions, so as to complete some steps in the above-mentioned multi-frequency band acoustic signal monitoring method for multi-scale fractures in hard rock.
  • this embodiment also provides a readable storage medium, a readable storage medium described below and a multi-band acoustic signal monitoring method for multi-scale fracture of hard rock described above can be referred to each other.
  • a readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the steps of the multi-frequency band acoustic signal monitoring method for multi-scale fracture of hard rock in the above method embodiment are realized.
  • the readable storage medium can be a readable storage medium that can store program codes such as a flash memory, a hard disk, a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a magnetic disk, or an optical disk. storage medium.
  • program codes such as a flash memory, a hard disk, a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a magnetic disk, or an optical disk.

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Abstract

一种硬岩多尺度破裂的多频段声信号监测方法、装置、设备以及存储介质，方法包括：实时采集硬岩破裂过程的声发射、声音、微震三种频段声信号，并对三种声信号降噪；根据硬岩破裂过程的声发射、声音、微震三种不同频段声信号的活跃度，判别硬岩破裂尺度所处当前阶段；根据当前硬岩破裂尺度阶段声信号b值分析决策，分析b值随时间变化趋势，获得硬岩破裂尺度演化的定量化评估结果；根据硬岩失稳预警标准，即硬岩破裂尺度当前阶段与b值时间演化趋势，对所监测的硬岩进行失稳预警。解决基于单频段声信号无法实现硬岩失稳破坏过程中多尺度裂纹信息监测的不足，有利于提高硬岩破裂失稳预警的准确性。

Description

硬岩多尺度破裂的多频段声信号监测方法、装置、设备以及存储介质 技术领域
本发明属于地质灾害防治工程技术领域，涉及一种利用多频段声信号监测硬岩多尺度破裂全过程的方法、装置、设备以及存储介质，适用于地表与地下硬岩灾变孕育全过程实时预警。
背景技术
岩质边坡失稳、危岩体崩塌、岩溶地面塌陷、隧道塌方与岩爆等硬岩(标准岩样单轴抗压强度大于等于30MPa的岩石)地质灾害直接或间接危害人类安全，并给社会和经济建设造成损失。硬岩地质灾害的有效监测是防范地质灾害的重要技术手段。硬岩地质灾害的孕育过程其本质是硬岩的破裂过程，即硬岩的微裂纹萌生、裂纹发育与扩展、裂纹贯通直至失稳的贯序进程。因此，对硬岩破裂过程监测是硬岩地质灾害有效监测的重要途径。硬脆性硬岩破裂过程中内部积聚的应变能以弹性波、振动波、应力波等形式向外释放多种声信号物理信号。借助声信号仪器设备监听这些声信号物理信号，从而实现硬岩破裂过程的有效监测。
根据频段高低的不同，一般将岩体声信号分为声发射(10 4Hz～10 6kHz，高频，适用于表征微米至厘米尺度的硬岩破裂)、声音(20Hz～20kHz，中频，适用于表征厘米至米级尺度的硬岩破裂)和微震(1Hz～100Hz，低频，适用于米级尺度的硬岩破裂)等三个频段声信号。目前，国内外工程实践中，声信号监测一般采用单一频段信号监测的技术方案，不能对硬岩地质灾害孕育过程硬岩小尺度破裂发展至中尺度乃至发展为大尺度破裂的全过程进行有效监测。
本发明将三种不同频段的声信号引入硬岩破裂监测中，提出一种硬岩多尺度破裂的多频段声信号监测方法、装置、设备以及存储介质，实现硬岩的微裂纹萌生、裂纹发育与扩展、裂纹贯通直至失稳的全过程精细监测，并实时评估硬岩的破裂阶段及状态，对硬岩地质灾害的防灾减灾具有重要应用价值。
发明内容
本发明目的在于，针对现有硬岩破裂过程声信号监测频段缺失、破裂尺度信息不足等问题，提出一种可监测硬岩多尺度破裂全过程的多频段声信号监测方法、装置、设备以及存储介质，以有效获取硬岩微米级至米级以上多尺度破裂的声信号，从而实现硬岩地质灾害的有效预警。
本发明为实现上述目的，采用技术方案如下：
第一方面，本发明提供一种硬岩多尺度破裂的多频段声信号监测方法，包括以下步骤：
步骤S1：实时采集硬岩破裂过程的声发射、声音、微震三种频段声信号，并对三种声信号降噪；
步骤S2：根据硬岩破裂过程的声发射、声音、微震三种不同频段声信号的活跃度，判别硬岩破裂尺度所处当前阶段；
步骤S3：根据硬岩破裂尺度当前阶段声信号b值分析决策，每间隔一定时间计算声信号的b值，分析b值随时间变化趋势，获得硬岩破裂尺度演化的定量化评估结果；
步骤S4：根据硬岩失稳预警标准，即硬岩破裂尺度当前阶段与b值时间演化趋势，对所监测的硬岩进行失稳破坏预警。
对于步骤2，具体说明如下：
优选的，所述三种声信号的活跃度分析方法采用波形分析，根据各声信号对于硬岩破裂尺度敏感的差异性，各声信号波形分析手段分别为：声发射信号—撞击数，声音信号——波形幅值，微震信号—波形幅值；
优选的，所述判别破裂尺度阶段准则可解释为：判据一，声发射撞击数呈现低值、上升趋势，或高值平稳波动，且声音或微震波形幅值均处于一个较低活跃性，硬岩破裂处于厘米级及其以下尺度，裂纹发育处于“稳定发展”阶段；判据二，声发射撞击数发生平静期现象，且声音波形幅值出现明显活跃，微震波形幅值仍呈现较低活跃性，硬岩破裂处于米级尺度以下，裂纹发育处于“非稳定发展”阶段；判据三，声发射撞击数发生平静期现象，且声音与微震的波形幅值均呈现明显活跃，硬岩破裂处于米级及其以上尺度，裂纹发育处于“加速扩展”阶段；
优选的，经大量已有研究硬岩发现，三种声信号对应的硬岩破裂尺度所存在的差异性，各声信号在硬岩破裂过程中也具有明显的时序特征。具体可表述为：当硬岩的裂纹发育处于“稳定破裂”阶段，高频的声发射信号较为活跃，对应的硬岩应力水平较低，一般约小于岩体峰值应力的80％；当硬岩的裂纹发育进入“非稳定发展”阶段，中频的声音信号开始活跃时，对应的硬岩应力水平较高，一般约为岩体峰值应力的80％；当硬岩的裂纹发育进入“加速扩展”阶段，低频的微震信号开始活跃时，对应的硬岩应力水平高，一般约为岩体峰值应力的95％及以上。
对于步骤3，具体说明如下：
优选的，所述声信号b值是由基于地震震级与频度之间统计关系得到的一种相关参数，声发射、声音以及微震多频段声信号均与地震活动具有高度的相关性，因此均可通过地震学b值方法来分析硬岩各尺度破裂演变过程；
优选的，声信号b值的变化与硬岩内部裂纹的演化过程密切相关，b值增大意味着小事件所占比例增加，以小尺度微破裂为主；b值减小，意味着大事件比例增加，大尺度微破裂增多，b值大幅减小表示裂纹发展变化剧烈，预示着硬岩可能发生失稳破坏；
优选的，所述声信号b值分析决策为：决策一，若硬岩破裂尺度处于“稳定发展”阶段，即厘米级尺度及以下阶段时，对间隔一定相同时间的声发射信号进行b值计算；决策二，若硬岩破裂尺度处于“非稳定发展”阶段，即厘米级尺度至米级阶段时，对间隔一定相同时间的声发射和声音等两种声信号进行b值计算；决策三，若硬岩破裂尺度处于“加速扩展”阶段，即米级尺度及以上阶段时，对间隔一定相同时间的声发射、声音和微震三种声信号进行b值计算；
优选的，所述三种频段声信号对于不同硬岩破裂尺度表征性能有所区别，进而导致了各信号b值特征变化趋势的差异。具体可解释为：声发射信号对于小尺度破裂敏感，最 先发生下降，且下降速率相对较慢；声音信号对于中等尺度破裂敏感，下降时间稍有滞后，且下降速率略有加快；而微震信号对于大尺度破裂敏感，表现为最晚的下降时间以及最快的下降速率；因此，结合三种声信号b值变化趋势可对硬岩各破裂尺度阶段演化较好地评估；
优选的，所述硬岩破裂尺度若处于“加速扩展”阶段时，表明硬岩破裂处于一个米级尺度以上的破裂阶段，并且硬岩应力水平约为岩体峰值应力的95％，具有高失稳破坏风险；此外，若三种声信号b值均呈现下降趋势，且声音、微震信号的b值下降速率不断的增大，这表明硬岩米级尺度破裂持续性增长，具有极高的失稳破坏风险，即刻进行预警。
第二方面，本发明还提供一种硬岩多尺度破裂的多频段声信号监测装置，包括：
声信号采集单元：用于实时采集硬岩破裂过程的声发射、声音、微震多频段声信号；
声信号传输单元：用于无线传输硬岩破裂的三种声信号有效数据；
声信号处理单元：用于对硬岩破裂声信号进行实时预处理降噪，并对处理后的三种信号进行活跃度分析，进而判别硬岩破裂尺度所处当前阶段；
声音信号评估单元：用于根据硬岩破裂尺度当前阶段声信号b值分析决策，每间隔一定时间计算声信号的b值，分析b值随时间变化趋势，获得硬岩破裂尺度演化的定量化评估结果；
灾害预警单元：用于根据硬岩失稳预警标准，即硬岩破裂尺度当前阶段与b值时间演化趋势，对所监测的硬岩进行失稳破坏预警。
优选的，所述声信号处理单元包括：
声信号预处理子单元：用于将接收硬岩破裂的声发射、声音、微震信号数据进行降噪处理，以得到较纯净、质量较高的待分析信号；
破裂尺度阶段判别子单元：用于对处理后的三种信号进行活跃度分析，判别硬岩破裂尺度所处当前阶段，判别准则为：判据一，裂纹“稳定发展”阶段，即硬岩破裂处于厘米级及其以下尺度，声发射撞击数呈现低值、上升趋势，或高值平稳波动，且声音或微震波形幅值均处于一个较低活跃性；判据二，裂纹“非稳定发展”阶段，硬岩破裂即处于米级尺度以下，声发射撞击数发生平静期现象，且声音波形幅值出现明显活跃，微震波形幅值仍呈现较低活跃性；判据三，裂纹“加速扩展”阶段，即硬岩破裂处于米级及其以上尺度，声发射撞击数发生平静期现象，且声音与微震波形幅值均呈现明显活跃。
优选的，所述声信号评估单元包括：
声信号第一评估子单元：用于通过高频声发射信号b值特征变化趋势，评估硬岩破裂尺度的“稳定发展”阶段演化过程；
声信号第二评估子单元：用于通过中频声音与高频声发射信号b值特征变化趋势，评估硬岩破裂尺度的“非稳定发展”阶段演化过程；
声信号第三评估子单元：用于通过低频微震、中频声音以及高频声发射b值特征变化趋势，评估硬岩破裂尺度的“加速扩展”阶段演化过程。
第三方面，本发明还提供一种硬岩多尺度破裂的多频段声信号监测设备，包括：
现场设备以及云端设备。
优选的，所述现场设备用于实时监测工程岩体破裂的声信号，并将通过5G无线传 输至云端设备。可以包括信号采集器，电源，高速AD转换器，储存器，时钟，FGPA微控制器，以及通讯组件一个或多个。可以完成上述的硬岩多尺度破裂的多频段声信号监测方法中的步骤1部分。
优选的，所述云端设备用于接收现场设备所获取的岩体破裂的声信号数据，通过声信号的滤噪、波形分析以及b值分析，进一步完成岩体破裂阶段判别以及破裂状态评估，最终实现岩体失稳破坏风险预警。可以包括存储器，多媒体组件，I/O接口，通讯组件，以及处理器一个或多个。可以完成上述的硬岩多尺度破裂的多频段声信号监测方法中的步骤1部分以及步骤2至步骤4。
第四方面，本申请还提供了一种可读存储介质，所述可读存储介质上存储有计算机程序，所述计算机程序被处理器执行时实现上述硬岩多尺度破裂的多频段声信号监测方法的步骤。
与现有技术相比，本发明的有益效果是：
(1)本发明为硬岩工程提供了一种硬岩多尺度破裂的有效监测手段，能有效解决单一的声信号监测方法及其装置不能有效表征硬岩的微裂纹萌生、裂纹扩展、裂纹贯通直至失稳破坏，即小尺度(微米级)向大尺度(米级)演化的多尺度破裂全过程的不足，有利于显著提升硬岩失稳预警的准确性；
(2)本发明不仅可用于判别硬岩当前所处的破裂尺度阶段，还可以定量化评价硬岩破裂尺度随时间的演化趋势，有利于实现硬岩失稳诱发地质灾害预警的超前预测与预警，进而有利于延长灾害规避时间，降低灾害所导致的安全事故风险；
(3)本发明提出了一种适用于硬岩失稳地质灾害的多方位、网格化的智能监测系统，该系统自动采集硬岩破裂的多频段声信号，通过传感器有线传输至汇聚节点，通过汇聚节点中处理模块以有效的处理方式滤除无效数据，然后将某一段采样时间内的有效数据传输至云服务器，并在云服务器中进行数据的储存、处理、分析，能实时预警硬岩失稳风险，与传统的硬岩声信号自动监测系统相比，该系统的感知能力更强，自动化与智能化水平较高，对于硬岩破裂失稳所导致的地质灾害防范具有重要实用价值。
附图说明
图1为本发明实施例1提供的硬岩多尺度破裂的多频段声信号监测方法流程图。
图2为本发明实施例1提供的地面硬岩工程——危岩体的多频段声信号监测网的布置图。
图3为本发明实施例1提供的危岩崩塌失稳全过程的多频段声信号波形特征变化曲线图。
图4为本发明实施例1提供的危岩崩塌失稳全过程的多频段声信号b值特征变化曲线图。
图5为本发明实施例2提供的地下硬岩工程——隧洞围岩的多频段声信号监测网的布置图。
图6为本发明实施例2提供的隧洞围岩塌方全过程的多频段声信号波形特征变化曲线图。
图7为本发明实施例2提供的隧洞围岩塌方全过程的多频段声信号b值特征变化曲 线图。
图8为本发明实施例3提供的一种硬岩多尺度破裂的多频段声信号监测装置结构示意图。
图9为本发明实施例3提供的一种声信号采集单元结构示意图。
图10为本发明实施例3提供的一种声信号传输单元结构示意图。
图11为本发明实施例3提供的一种声信号处理单元结构示意图。
图12为本发明实施例3提供的一种声信号评估单元结构示意图。
图13为本发明实施例4提供的一种硬岩多尺度破裂的多频段声信号监测现场设备示意图。
图14为本发明实施例4提供的一种硬岩多尺度破裂的多频段声信号云端设备示意图。
具体实施方式
下面结合附图和实例对本发明的具体实施方式进一步进行说明阐述。需要指出的是，附图中仅示出了与本发明相关的部分，并非全部结果。并且具体实例仅为解释本发明，而非限制发明的范围。
实施例1
附图1为本发明实施1的硬岩多尺度破裂的多频段声信号监测方法流程图，其方法具体包括如下：
步骤S1-1：本发明实施例1针对广西壮族自治区某石灰岩山体的节理较为严重局部部位进行实时监测，附图2为局部危岩体监测网络布置图。首先，根据地形地貌及监测对象所处方位计算出声信号传感器最优网格布置图；然后，将三种声信号传感器封装后的采集单元依次布设预设位置，将声发射、微震传感器涂抹耦合剂，放置至危岩体较为完整的、稳定性、易安装的部位，鉴于声音传感器的非接触式、远程采集原理，直接将声音传感器安装于采集单元处即可；随后，将危岩体上已布置的多个声信号传感器采集单元以网状结构汇聚成点连接至声信号采集终端；最后，通过声信号采集终端所记录及接收的各声信号传感器采集单元的数据无线传输至声信号处理系统，本发明应用云服务器中计算模块。
示例性的，本发明实施例1，三种声信号传感器的采集单元是一种采集的最小单元，其采集单元配有声发射、声音、微震传感器各一个，并且各传感器都由封闭单元内引出一定长度的信号线；声发射、微震传感器由于是接触式采集，需要将两种探头埋设于岩体内的预留孔内，将传感器深埋入直径略大的预留孔中，并采用合适的耦合剂将监测目标与传感器嵌为一体；耦合剂具有可塑性、速凝性、均一性等特点，将耦合界面内的空气、水分排除实现传感器与岩壁的直接接触；然而，得益于声音信号采集方式的便捷性，声音传感器仅需要安装至采集单元的四周预留部位即可。
示例性的，本发明实施例1，声发射、微震传感器安装部位特点：没有过大的裂缝，界面与传感器接触较好、稳定程度高，以及便于人工安装及拆卸。
示例性的，本实施例鉴于此危岩体风化程度高、节理丰富，且主控结构面具有较大的断层裂缝，若在其结构上施加额外的荷载作用，可能会导致此危岩快速失稳崩塌；因此，在对于此危岩体进行监测之前，对危岩体的薄弱处进行了预加固措施，具体包括危主控结 构关键部位灌浆、钢筋网范围性加固。
示例性的，三种声信号的选型如下：声发射传感器，是高敏度的相对低频的谐振传感器，其采样频率范围为10-70kHz，灵敏度高达121dB；声音传感器，是高灵敏的电容式传感器，其采样范围为20Hz-20kHz，灵敏度高达80-85dB(1kHz)；微震传感器，是高敏度的压电型加速度传感器，其采样频率范围在0.6-300Hz之间，电压灵敏度高达30V/m/s 2。
示例性的，基于信号奈奎斯特采样定理(若需要获取较为完整原始信号的信息，一般需保证采样频率为信号最高频率2倍)、采集装置的功耗以及信号数据有效性等多方面综合考虑采样率值设定，因此，通过各频段声信号的选定传感器最大频率范围参数，分别设定各声信号的采样率值，低频微震信号—1000Hz，中频声音信号—44.1kHz，高频声发射信号—150kHz。
步骤S1-2：将接收危岩体破裂的多频段声信号的数据进行自动降噪操作，剔除有效破裂信号中叠加的周期性环境噪声信号，得到较为纯净的危岩体破裂声信号数据。
示例性的，本发明提出的硬岩多尺度破裂的声信号监测方法是基于危岩体破裂的多种不同频段的声信号，因此对于多种不同频带的声信号的去噪方法具有一定的差异性。但是，三种信号都是声信号学的范畴，去噪原理是一致的，本发明采用小波阈值去噪法也称为小波收缩(Wave Shrink，WS)方法。
其步骤如下：
步骤(1)，选择合适的小波函数、小波基以及小波分解层数，对包含有噪声的声信号s(n)进行离散小波变换，得到相应的小波系数D i；
步骤(2)，利用阈值对离散小波变换得到的小波系数D i进行处理，得到相应的小波系数估计值d i；
步骤(3)，利用小波系数估计值di重构声响信号，从而得到原始声信号的估计值h(n)。
显然，小波阈值去噪方法的核心问题是选择合适的阈值。阈值包括硬阈值、软阈值及半软阈值3种，由于半软阈值法能兼顾软、硬阈值的优点，使得去噪过的声信号既具有原来的光滑型又可以保留原声信号的细节，其公式如下：
Figure PCTCN2022095164-appb-000001
式中，当λ 1＜|w|＜λ 2时，接近软阈值情况；当λ 2＜|w|时，接近于硬阈值情况式，当λ 2＝∞时，接近软阈值的情况。
示例性的，小波去噪的本质是针对不同的频段信号进行多策略处理，以得到最完整、纯净的原始信号；声发射、声音、微震三种声信号所监测的频段不同，并且硬岩破裂的各声信号频段总体分布也是具有区别的。因此在进行小波除噪操作时，上述过程中所提及的小波函数、小波基及小波分解层数需要根据三种信号特征而选定。
步骤S1-3：根据硬岩破裂过程的声发射、声音、微震三种不同频段声信号的活跃 度，判别硬岩破裂尺度所处当前阶段。
示例性的，三种声信号的活跃度分析方法采用波形分析，根据各声信号对于硬岩破裂尺度敏感的差异性，各声信号波形分析手段分别为：声发射信号—撞击数，声音信号——波形幅值，微震信号—波形幅值。
优选的，所述判别破裂尺度阶段准则可解释为：判据一，声发射撞击数呈现低值、上升趋势，或高值平稳波动，且声音或微震波形幅值均处于一个较低活跃性，硬岩破裂处于厘米级及其以下尺度，裂纹发育处于“稳定发展”阶段(阶段Ⅰ)；判据二，声发射撞击数发生平静期现象，且声音波形幅值出现明显活跃，微震波形幅值仍呈现较低活跃性，硬岩破裂处于米级尺度以下，裂纹发育处于“非稳定发展”阶段(阶段Ⅱ)；判据三，声发射撞击数发生平静期现象，且声音与微震的波形幅值均呈现明显活跃，硬岩破裂处于米级及其以上尺度，裂纹发育处于“加速扩展”阶段(阶段Ⅲ)。
示例性的，硬岩破裂尺度处于“非稳定发展”以及“加速扩展”阶段的硬岩起始应力水平分别约为80％、95％及以上，各对应中频声音以及低频微震信号明显活跃起始点。
示例性的，依据上述所述硬岩破裂尺度阶段三种声信号综合性评估手段，现提出一种硬岩破裂尺度阶段判别公式，如下：
Figure PCTCN2022095164-appb-000002
式中，AE hits为声发射撞击数，AE hit rate为声发射撞击数活跃程度，Sound amplitude rate为声音信号波形幅值活跃程度，MS amplitude rate为微震信号波形幅值活跃程度，HT为声发射撞击数的高活跃水平值，LT为声发射撞击数的低活跃水平值，可通过AE hits与Sound amplitude rate或/和MS amplitude rate判别声发射信号是否出现平静期，A、B、C分别为声发射、声音、微震活跃程度门槛值，上述数值根据特定环境而定。
示例性的，附图3为监测危岩体破裂全过程的多频段声信号波形特征演化图，具体为2021年2月16日0时至12时的监测数据；根据所述破裂尺度阶段判别准则，将危岩体破裂声发射撞击数处于低活跃高增长趋势或处于高活跃低增长趋势阶段判定为阶段Ⅰ，即0时至10时30分时段；进一步，将危岩体破裂声发射撞击数低活跃、声音幅值高活跃以及微震幅值低活跃等特征判定为阶段Ⅱ，即10时30分至11时06分；最终，将危岩体破裂声发射处于低活跃、声音处于高活跃以及微震幅值处于高活跃特征判定为阶段Ⅲ，即11时06分至11时48分。
步骤S1-4：根据硬岩破裂尺度当前阶段声信号b值分析决策，每间隔一定时间计算声信号的b值，分析b值随时间变化趋势，获得硬岩破裂尺度演化的定量化评估结果。
示例性的，大量现场以及试验观测数据的分析表明硬岩破坏的破裂事件都服从震级-频率(G-R)关系式，通过研究各频段声信号活动性，震级-频率关系对所有的破裂尺度范围内的声信号都是适用的，在一定时间范围内，声信号监测区域内的破裂事件频率与震级遵从公式：
lg N＝a-bm                  (3)
式中，m为适用于某破裂尺度的声信号震级，N为震级在Δm范围内变化的破裂事件次数。
示例性的，各频段声信号均采用基于信号幅值大小进行b值分析，由此，得到危岩体多尺度破裂全过程的各声信号b值随时间变化曲线，见附图4。
示例性的，当危岩体破裂处于厘米级以下尺度微裂纹发育阶段Ⅰ时，0时至10时30分时段，利用高频声发射信号独立评估危岩体破裂尺度演化过程；0时至7时27分之间，声发射b值在5～6之间平稳波动，这表明危岩体的破裂事件数量以及破裂事件尺度变化处于一个动态平稳，但危岩体整体破裂事件尺度处于一个较低水平；当超过7时27分之后，声发射b值出现明显下降趋势，并在9时19分至9时56分之间，以一个较大幅度下降至较低值2.15，这暗示危岩体的破裂事件尺度呈现逐渐增大趋势，此时危岩体整体破裂尺度处于一个中等水平；此外，在9时56分后，声发射b值下降速率变缓并逐渐转为平稳波动，声发射信号出现平静期，这表明危岩体破裂尺度进一步扩大，进入危岩体破裂尺度阶段Ⅱ以及阶段Ⅲ。但是，阶段Ⅱ及阶段Ⅲ仅通过声发射信号不能很好反映危岩体破裂事件尺度演变过程，需结合适用于厘米级尺度以上的中频声音、低频微震信号进行评估。
示例性的，当危岩体破裂出现厘米级至米级尺度宏观裂纹阶段Ⅱ时，岩体应力水平约为80％，利用中频声音信号以及高频声发射信号同时进行监测，以此实现危岩体微米级至米级范围破裂尺度演化过程的评估。可发现，10时30分至11时11分之间，声音b值整体数值在4.18～5.14之间呈现平稳波动趋势，且略有下降，这表明危岩体的破裂事件尺度呈现一个缓慢增大趋势；进一步，根据上述危岩体破裂尺度阶段判定结果，11时11分之后，危岩体破裂尺度阶段已转为阶段Ⅲ，因此，需结合低频微震信号综合评估危岩体破裂尺度演变过程。
示例性的，当危岩体破裂出现米级以上尺度宏观裂纹阶段Ⅲ时，岩体应力水平约为95％及以上，利用低频微震信号、中频声音信号以及高频声发射信号同时进行监测，以此实现危岩体微米级至米级以上范围破裂尺度演化过程的评估。可发现，11时11分之后，声发射b值呈现低值平稳波动的平静期状态，而声音b值呈现为高值快速下降趋势，微震b值在4.15～4.87之间呈现高值平稳波动，并略有下降趋势，并进一步在11时25分后转而快速下降，这暗示危岩体的破裂事件尺度增大趋势明显加快，特别是处于米级尺度以上的硬岩破裂事件；最终，对于较大尺度敏感性较高的声音及微震信号分别在11时35分及11时40分之后出现了一个显著下降现象，这暗示危岩体大尺度破裂事件已达到了一个极高活跃程度。
步骤S1-5：根据硬岩失稳预警标准，即硬岩破裂尺度当前阶段与b值时间演化趋势，对所监测的硬岩进行失稳破坏预警。
示例性的，在危岩体多尺度破裂全过程中，多频段声信号b值特征均在不同破裂尺度阶段呈现了显著下降趋势，以此揭示不同破裂尺度阶段的硬岩破裂事件尺度演变过程。
示例性的，在11时11分之后，危岩体破裂处于“加速扩展”阶段Ⅲ，岩体应力水平约为95％及以上，危岩体破裂处于一个米级尺度的破裂阶段，具有一定失稳破坏风险；并且，声发射b值呈现出一个低值平稳波动趋势，而声音以及微震b值均呈现显著下降趋势，并且二者分别在11时35分及11时40分先后出现大幅度突降现象，这表明危岩体米级尺度破裂持续性增长，具有极高的失稳破坏风险，即在11时40分钟进行危岩崩塌失稳预警，预警方式为现场、移动端以及云端等多渠道预警。
示例性的，在2021年2月16日11时48分，监测危岩体沿着主控结构面平面发生短暂的剪切滑移现象，并从所处海拔27m山腰方位向下发生由自重导致的多轨迹滚动，最终堆积 于山脚部位，未造成任何人员伤亡。
示例性的，考虑到计算代价比较大及天然危岩体的失稳崩塌发育是一个较为缓慢的过程，本发明实施例1所采样样本的采样时间不固定，依据其三种声信号的门槛值来定义，若超过其门槛值，则进行连续采样，否则处于停滞采样状态，此采样方式有效减少了无用数据，为数据分析以及数据无线传输提供了可行性。
实施例2
本发明实施2深部硬岩工程领域中的硬岩多尺度破裂的多频段声信号监测方法流程与实施1类似，不再赘述，其方法具体包括如下：
步骤S2-1：本发明实施例2针对云南省某市距地表570m深、10m洞径隧道开挖过程进行了实时监测，附图5为此隧洞的监测网络布置图。考虑到隧洞开挖过程中，并非仅掌子面会出现硬岩弹性应变能急剧释放而导致的高烈度破坏现象，开挖后的隧道断面也会受到开挖、爆破产生的扰动影响产生较为严重静、动力破坏。参考国内外文献及报道，深部地下隧道开挖过程中应变型岩爆灾害主要集中于2.3倍洞径附近，超过其范围后鲜有分布，因此将三种声信号采集单元非等间隔布置于距掌子面后部范围75m内，具体分为5m、15m、25m、50m、75m等5段；然后，将声发射、微震传感器涂抹耦合剂，安装至开挖后断面两侧合适的孔洞部位，鉴于声音传感器的非接触式、远程采集原理，直接将声音传感器安装于采集单元处即可；随后，将隧洞已布置的多个声信号传感器采集单元以多个无线中继网桥及一个总无线网桥传输至声信号采集终端；最后，通过声信号采集终端所记录及接收的各声信号传感器采集单元的数据传输至声信号处理系统，本发明应用云服务器中计算模块。
示例性的，本发明实施例1，为了降低信号线过长带来的衰减，上述5个隧洞断面所布设采集单元连接传感器位于监测断面处2-5m处；并且，深部隧洞处于一个高密闭环境，数据信号较弱、传输效率低，不能实现三种声信号庞大的数据量实时传输；因此，引入无线网桥元件，将每个隧道断面处的采集单元都配备一个传输子无线网桥，然后距离掌子面处500m布设一个接收总无线网桥，再以500m等距离布设点对点、中继式无线网桥转接采集的硬岩破裂声信号，其无线网桥总数根据隧洞开挖长度而决定，最终在开挖隧洞口布设一个最终接收总无线网桥N，将此无线网络连接至一个声信号采集终端中央处理单元，负责将隧洞所有采集的数据集成、提取有效数据及无线传输至声信号处理系统。
优选的，本实施例中考虑到深部隧洞危险段较多，可能存在多个不均衡发育的硬岩破裂阶段，某些监测端可能处于宏观裂纹较为活跃期，而另一监测段可能处于一个微裂纹发育期。因此，为了获取更宽频段的硬岩破裂声信号，其各频段声信号的具体参数为：声发射传感器，是高敏度的相对宽频的谐振传感器，其采样频率范围为20-800kHz，灵敏度高达110dB；声音传感器，是高灵敏的电容式传感器，其采样范围为20Hz-20kHz，灵敏度高达80-85dB(1kHz)；微震传感器，是高敏度的压电型加速度传感器，其采样频率范围在0.8-450Hz之间，电压灵敏度高达25V/m/s 2；进一步，基于信号奈奎斯特采样定理(若需要获取较为完整原始信号的信息，一般需保证采样频率为信号最高频率2倍)、采集装置的功耗以及信号数据有效性等多方面综合考虑采样率值设定，因此，通过各频段声信号的选定传感器最大频率范围参数，分别设定各声信号的采样率值，低频微震信号—1000Hz，中频声音信号—44.1kHz，高频声发射信号—1.6MHz。
示例性的，由于本发明实施例2篇幅有限，此实施例全过程监测了共5个隧洞断面 附近的围岩破裂过程，其中存在5m、15m、50m等3个隧洞断面点出现了围岩的动力破坏岩爆现象；由于篇幅有限，仅展示破坏强度最大的15m断面处的围岩崩塌的多频段声信号监测过程。
步骤S2-2：与步骤S1-2类似，通过式(1)滤除隧道围岩破裂的三种声信号中叠加的环境噪声。
步骤S2-3：与步骤S1-3类似，通过式(2)进行隧道围岩破裂多频段声信号的波形分析，进而判别围岩破裂尺度所处当前阶段。
示例性的，附图6为监测围岩破裂全过程的多频段声信号波形特征变化曲线图，具体为2021年2月16日0时至15时的监测数据；通过声发射撞击数以及声音、微震波形幅值特征分析，判别隧道围岩“稳定发展”阶段Ⅰ、“非稳定发展”阶段Ⅱ以及“加速扩展”阶段Ⅲ等破裂尺度阶段分为别0时至13时、13时至13时42分以及13时42分至14时56分。
步骤S2-4：与步骤S1-4类似，通过式(3)计算出围岩破裂不同频段声信号b值特征，并基于步骤S1-3破裂尺度阶段判别结果，通过围岩破裂尺度所处当前阶段声信号b值分析决策，实现硬岩破裂尺度演化的定量化评估。
示例性的，为了便于读者进一步理解本发明专利实施过程，附图7展现了隧道15m断面处围岩多尺度破裂全过程的各声信号b值变化曲线图。
示例性的，当围岩破裂处于厘米级以下尺度微裂纹发育阶段Ⅰ时，0时至13时时段，利用高频声发射信号独立评估围岩破裂尺度演化过程；0时至11时48分之间，声发射b值在5.6～8.1之间平稳波动，这表明围岩的破裂事件数量以及破裂事件尺度变化处于一个动态平稳，但围岩整体破裂事件尺度处于一个较低水平；当超过11时48时之后，声发射b值出现明显下降趋势，并在12时42分至13时02分之间，以一个较大幅度下降至较低值2.75，这暗示围岩的破裂事件尺度呈现逐渐增大趋势，此时围岩整体破裂尺度处于一个中等水平；此外，在13时02分后，声发射b值下降速率变缓并逐渐转为平稳波动，声发射信号出现平静期，这表明围岩破裂尺度进一步扩大，进入围岩破裂尺度阶段Ⅱ以及阶段Ⅲ。但是，阶段Ⅱ及阶段Ⅲ仅通过声发射信号不能很好反映围岩破裂事件演变过程，需结合适用于厘米级尺度以上的中频声音、低频微震信号进行评估。
示例性的，当围岩破裂出现厘米级至米级尺度宏观裂纹阶段Ⅱ时，围岩应力水平约为80％，利用中频声音信号以及高频声发射信号同时进行监测，以此实现围岩微米级至米级范围破裂尺度演化过程的评估。可发现，13时至13时42分之间，声音b值整体数值在5.57～7.01之间呈现平稳波动趋势，且略有下降，这表明围岩的破裂事件尺度呈现一个缓慢增大趋势；进一步，根据上述围岩破裂尺度阶段判定结果，13时42分之后，围岩破裂阶段已转为阶段Ⅲ，因此，需结合低频微震信号综合评估围岩破裂尺度演变过程。
示例性的，当围岩破裂出现米级尺度宏观裂纹阶段Ⅲ时，围岩应力水平约为95％及以上，利用低频微震信号、中频声音信号以及高频声发射信号同时进行监测，以此实现围岩微米级至米级以上范围破裂尺度演化过程的评估。可发现，13时42分之后，声发射b值呈现低值平稳波动的平静期状态，而声音b值呈现为高值快速下降趋势，微震b值在5.74～6.47之间呈现高值平稳波动，并略有下降趋势，并进一步在14时11分后转而快速下降，这暗示围岩的破裂事件尺度增大趋势明显加快，特别是处于米级尺度以上的硬岩破裂事件；最终，对于较大尺度敏感性较高的声音及微震信号分别在14时26分及14时39分之后出现了一个显著 下降现象，这暗示围岩大尺度破裂事件已达到了一个极高活跃程度。
步骤S2-5：根据硬岩失稳预警标准，即硬岩破裂尺度当前阶段与b值时间演化趋势，对所监测的硬岩进行失稳破坏预警。
示例性的，在13时02分之后，隧道围岩破裂处于“加速扩展”阶段Ⅲ，围岩应力水平约为95％及以上，围岩破裂处于一个米级尺度的破裂阶段，具有一定失稳破坏风险；并且，声发射b值呈现出一个低值平稳波动趋势，而声音以及微震b值均呈现显著下降趋势，并且二者分别在14时26分及14时39分先后出现大幅度突降现象，这表明围岩米级尺度破裂持续性增长，具有极高的失稳破坏风险，即在14时39分进行围岩塌方预警，预警方式为现场、移动端以及云端等多渠道预警。
示例性的，在2021年2月16日11时56分，隧道断面15m处右上方约9m 2围岩体脱离于母岩发生塌方，沿着垂直方向垂落于隧洞四周，事先已根据较高风险的围岩破裂状态评估结果对塌方灾害超前预警，隧洞内部施工设备及人员已全部撤离，并未造成任何经济损失及人员伤亡。
示例性的，考虑到计算代价比较大及隧洞围岩塌方发育是一个较为缓慢的过程，本发明实施例2所采样样本的采样时间不固定，依据其三种声信号的门槛值来定义，若超过其门槛值，则进行连续采样，否则处于停滞采样状态，此采样方式有效减少了无用数据，为数据分析以及数据无线传输提供了可行性。
实施例3
附图8为本发明实施例3提供的一种硬岩多尺度破裂的多频段声信号监测设备的结构示意图。该实施例的装置可用于实现本申请上述各方法实施例，该实施例的装置包括：
声信号采集单元3-1：用于实时采集硬岩破裂过程的声发射、声音、微震多频段声信号；
声信号传输单元3-2：用于无线传输硬岩破裂的三种声信号有效数据；
声信号处理单元3-3：用于对硬岩破裂声信号进行实时预处理降噪，并对处理后的三种信号进行活跃度分析，进而判别硬岩破裂尺度所处当前阶段；
声音信号评估单元3-4：用于根据硬岩破裂尺度当前阶段声信号b值分析决策，每间隔一定时间计算声信号的b值，分析b值随时间变化趋势，获得硬岩破裂尺度演化的定量化评估结果；
灾害预警单元3-5：用于根据硬岩失稳预警标准，即硬岩破裂尺度当前阶段与b值时间演化趋势，对所监测的硬岩进行失稳破坏预警。
示例性的，见附图9，所述声信号采集单元3-1包括：
声信号采集子单元3-1-1：用于采集硬岩各监测部位多尺度破裂全过程的多频段声信号数据；
声信号采集控制子单元3-1-2：用于对采集子单元发送命令，控制各采集子单元的声信号数据采集、存储以及删除，其控制特征为：采集功能方面，当采集子单元信号活跃度未超过设定的门槛值时，处于休眠模式，若当其超过门槛值时，则激活各采集子单元的采集方式，转为正常模式；存储功能方面，存储采集子单元采集有效微震信号；删除功能方面，当存储的数据量大于采集子单元单次储存总量时，将其存储的前一段数据逐步一一删除。
示例性的，见附图10，所述声信号传输单元3-2包括：
声信号传输子单元3-2-1：用于实时传输具有明显变化特征的破裂事件声信号数据；
声信号传输控制子单元3-2-2：用于对传输子单元发送命令，控制传输子单元的声信号数据传输，具体可解释为：当微震信号数据存储量大于或等于一个完整采样时间段时，开启信号传输子单元的传输功能，将其存储的数据通过无线传输方式实时传输至云服务器。
示例性的，见附图11，所述声信号处理单元3-3包括：
声信号预处理子单元3-3-1：用于将接收硬岩破裂的声发射、声音、微震信号数据进行降噪处理，以得到较纯净、质量较高的待分析信号；
破裂尺度阶段判别子单元3-3-2：用于对处理后的三种信号进行活跃度分析，判别硬岩破裂尺度所处当前阶段，判别准则为：判据一，裂纹“稳定发展”阶段，即硬岩破裂处于厘米级及其以下尺度，声发射撞击数呈现低值、上升趋势，或高值平稳波动，且声音或微震波形幅值均处于一个较低活跃性；判据二，裂纹“非稳定发展”阶段，硬岩破裂即处于米级尺度以下，声发射撞击数发生平静期现象，且声音波形幅值出现明显活跃，微震波形幅值仍呈现较低活跃性；判据三，裂纹“加速扩展”阶段，即硬岩破裂处于米级及其以上尺度，声发射撞击数发生平静期现象，且声音与微震波形幅值均呈现明显活跃。
示例性的，见附图12，所述声信号评估单元3-4包括：
声信号第一评估子单元3-4-1：用于通过高频声发射信号b值特征变化趋势，评估硬岩破裂尺度的“稳定发展”阶段演化过程；
声信号第二评估子单元3-4-2：用于通过中频声音与高频声发射信号b值特征变化趋势，评估硬岩破裂尺度的“非稳定发展”阶段演化过程；
声信号第三评估子单元3-4-3：用于通过低频微震、中频声音以及高频声发射b值特征变化趋势，评估硬岩破裂尺度的“加速扩展”阶段演化过程。
需要说明的是，关于上述实施例中的装置，其中各个模块执行操作的具体方式已经在有关该方法的实施例中进行了详细描述，此处将不做详细阐述说明。
实施例4
相应于上面的方法实施例，本实施例中还提供了一种硬岩多尺度破裂的多频段声信号监测设备。下文描述的一种硬岩多尺度破裂的多频段声信号监测设备与上文描述的一种硬岩多尺度破裂的多频段声信号监测方法可相互对应参照。
附图13为本实施例提供了一种硬岩多尺度破裂的多频段声信号监测现场设备结构图，可以完成上述的硬岩多尺度破裂的多频段声信号监测方法中的步骤1部分。现场设备4-1可以包括：信号采集器4-1-1，电源4-1-2，高速AD转换器4-1-3，储存器4-1-4，时钟4-1-5，FGPA微控制器4-1-6，以及通讯组件4-1-7。
所述的，信号采集器4-1-1用于采集硬岩多尺度破裂的多频段声信号。可选的，信号采集器4-1-1包括：声信号模拟信号传感器以及信号调理器；所述的，声信号模拟信号传感器用于通过感应元件测量硬岩破裂所产生的能量或振动物理量；所述的，声信号模拟信号传感器包括：声发射传感器、声音传感器以及微震传感器。可选的，声发射传感器可为谐振式/差分型的声发射传感器，谐振式可用于一般环境，而差分型可用于局部放电检测或电气干扰较强的环境中；可选的，声音传感器可为电容式/驻极体型的声音传感器；可选的，根 据采集振动物理量方向，微震传感器可为单向/三向加速度微震传感器，而根据采集原理，微震传感器可为电荷输出型/电压输出型加速度传感器；所述的，信号调理器为可增益传感器端输入的声发射/声音/微震模拟信号的双积分调理器，还包括高、低通滤波功能。
所述的，电源4-1-2用于提供现场设备4-1其他子组件正常运行的电量。可选的，所述电源4-1-2可以为锂电池、蓄电池以及太阳能电池，具体类型依据工程现场使用环境而定。
所述的，高速AD转换器4-1-3用于将传感器获取的模拟信号转换为计算机可识别的数字信号。可选的，所述高速AD转换器需满足采样定理、宽带化、信号动态特性以及较少量化噪声等技术要求，并且还需是一种具有3通道以上、采样速率达1MSPS以上、量化精度16位的高性能AD。
所述的，储存器4-1-4用于存储高速AD转换器4-1-3转换的数字信号数据，还用于存储预先设计的计算机程序代码，供FGPA微控制器4-1-6调用运行。可选的，所述存储器4-1-4可为静态随机存取存储器(Static Random Access Memory，SRAM)或同步动态随机存取内存(Synchronous DynamicRandom Access Memory，SDRAM)，还可以为伪静态随机存储器(Pseudo Static Random Access Memory，PSRAM)存储器，但也可以为上述三种类型存储二者两两组合或是三者组合形式。
所述的，时钟4-1-5用于为现场设备4-1其他子组件提供时钟服务，具体是指使其他子组件同步工作，还可以与外部设备通讯时达到同步授时作用。可选的，所述时钟4-1-5可以包括一种提供时钟信息的时钟源组件，还可以包括一种提供同步授时服务的同步授时组件。可选的，所述时钟源组件可以为低频/高频时间源LFXTICLK或是高频时钟源XTCLK，还可以为压控振荡器时钟DCOCLK，甚至可以为其中两种时钟源组合或是三种时钟组合；所述的，若在上述三种时钟源组合情况下，时钟组件可提供辅助时钟信号ACLK、主时钟信号MCLK和子系统时钟信号SMCLK；所述的，辅助时钟信号ACLK是由FLXT1CLK时钟源产生，可用于提供FGPA微控制器4-1-6中CPU外围功能模块时钟信号；所述的，主时钟信号MCLK是由上述三种时钟产生，可用于提供FGPA微控制器4-1-6和相关系统模块时钟信号；所述的，子系统时钟信号SMCLK是由上述三种时钟源任意两种产生，可用于提供外围组件时钟信号。可选的，所述同步授时组件可以为精确时间协议PTP授时系统，还可以为GPS授时系统或是北斗授时系统，甚至还可以为一种超高精度铷钟授时系统；可选的，所述同步授时组件也可以为上述多种授时系统组合模式，具体为：PTP+北斗、GPS+北斗以及PTP+铷钟三种时间同步模式。所述的，PTP+北斗以及GPS+北斗授时系统均仅能在信号较好的地表硬岩工程监测中应用，而PTP+铷钟授时系统可用于所有岩体工程监测。
所述的，FGPA微控制器4-1-6用于调用存储器4-1-4中计算机程序，控制现场设备4-1中其他组件以执行期望的功能。可选的，所述FGPA微控制器4-1-6可在VHDL、Verilog HDL、System Verilog和System C中任意一种语言环境下设计；可选的，所述的FGPA微控制器4-1-6可以包括：输入输出单元，可编程逻辑块，底层内嵌功能单元、Block RAM以及可编程布线矩阵；可选的，所述输入输出单元是芯片与外界电路的接口部分，完成不同电气特性下对输入/输出信号的驱动与匹配要求，可以为HP I/O单元或是HD I/O单元；可选的，所述可编程逻辑块可以包括查找表和寄存器；所述的，查找表完成纯组合逻辑功能；所述的，寄存器可以配置成触发器或锁存器；可选的，所述底层内嵌功能单元可以为DLL、PLL、DSP以 及CPU，用于实现高精度时钟分配、低抖动的倍频和分频，以及占空比调整和移相等功能；所述的，CPU可以为双核ARM Cortex-R5 CPU或是四核ARM Cortex-A53 CPU，还可以为二者CPU组合；可选的，所述Block RAM可以为单端口RAM、双端口RAM以及内容地址存储器(CAM)，还可以为FIFO存储结构；可选的，所述可编程布线矩阵用于连通FPGA内部的所有单元，可以为全局布线、长线布线、短线布线以及分布式布线。
所述的，通讯组件4-1-7用于实现现场设备4-1与外部其他设备进行有线或无线通讯。可选的，所述通讯组件4-1-7可以为独立路由器，或是光纤盒、光纤及路由器构建组合组件，甚至还可以是无线网桥、光纤以及路由器所构建的组合组件；所述的，上述光纤盒、路由器以及无线网桥可以为一个或多个；所述的，上述单个组件或是多个组件最终通讯方式均采用5G，5G通讯可以通过移动、联通或是电信其中之一运营商所属SIM卡实现。
需要注意的是，所述现场设备4-1内置的所有子组件的命名没有绝对性的主、次逻辑先后顺序，各组件之间的逻辑结构主要参考附图13所绘制逻辑线路决定。
另一方面，实施例还提供了一种硬岩多尺度破裂的多频段声信号监测云端设备结构图，例如可以是移动终端、个人电脑、平板电脑、服务器等。可以完成上述的硬岩多尺度破裂的多频段声信号监测方法中的步骤1部分以及步骤2至步骤4。见附图14，云端设备4-2包括：存储器4-2-1，多媒体组件4-2-2，I/O接口4-2-3，通讯组件4-2-4，以及处理器4-2-5等一个或多个子。应当注意，图14所示的云端设备的组件和结构只是示例性的，而非限制性的，根据需要，所述云端设备4-2也可以具有其他组件和结构。
所述的，存储器4-2-1可以包括一个或多个计算机程序产品，所述计算机程序产品可以包括各种形式的计算机可读存储介质，例如易失性存储器和/或非易失性存储器。所述易失性存储器例如可以包括随机存取存储器(RAM)和/或高速缓冲存储器(Cache)等。所述非易失性存储器例如可以包括只读存储器(ROM)、硬盘、闪存等。在所述计算机可读存储介质上可以存储一个或多个计算机程序指令，处理器4-2-5可以运行所述程序指令，以实现下文所述的本发明实施例中(由处理器实现)的计算机功能以及/或者其它期望的功能。在所述计算机可读存储介质中还可以存储各种应用程序和各种数据，例如所述应用程序使用和/或产生的各种数据等。
所述的，多媒体组件4-2-2可以用来接收用户所输入的指令以及采集数据，还可以向外部(例如用户)输出各种信息(例如本文数据、图像或声音)，并且可以包括显示器、扬声器等中的一个或多个。
所述的，I/O接口4-2-3为处理器4-2-5和其他接口模块之间提供接口，上述其他接口模块可以是键盘，鼠标，按钮等，这些按钮可以是虚拟按钮或者实体按钮。
所述的，通讯组件4-2-4用于云端设备4-2与其他设备之间进行有线或无线通信。无线通讯可以为近距离通讯Wi-Fi、蓝牙或是NFC，还可以通过远距离5G通讯，可以为其中一种或是多种组合。
所述的，处理器4-2-5可以是中央处理单元(CPU)或者具有数据处理能力和/或指令执行能力的其它形式的处理单元，并且可以控制所述云端设备4-2中的其它组件以执行期望的功能，以完成上述的硬岩多尺度破裂的多频段声信号监测方法中的部分步骤。
需要注意的是，所述云端设备4-2内置的所有子组件的命名没有绝对性的主、次逻辑先后顺序，各组件之间的逻辑结构主要参考附图14所绘制逻辑线路决定。
实施例5
相应于上面的方法实施例，本实施例中还提供了一种可读存储介质，下文描述的一种可读存储介质与上文描述的一种硬岩多尺度破裂的多频段声信号监测方法可相互对应参照。
一种可读存储介质，可读存储介质上存储有计算机程序，计算机程序被处理器执行时实现上述方法实施例的硬岩多尺度破裂的多频段声信号监测方法的步骤。
该可读存储介质具体可以为闪存、硬盘、只读存储器(Read-Only Memory，ROM)、随机存取存储器(Random Access Memory，RAM)、磁碟或者光盘等各种可存储程序代码的可读存储介质。
本技术领域的普通技术人员可以理解实现上述实施例方法携带的全部或部分步骤是可以通过程序来指令相关的硬件完成，所述的程序可以存储于一种计算机可读存储介质中，该程序在执行时，包括方法实施例的步骤之一或其组合。
需要注意的是，公布上述实例的目的在于帮助进一步理解本发明，但是本领域的技术人员可以理解：若对本发明进行各种明显变化、重新调整和替代手段，并不会脱离本发明的保护范围。因此，本发明不局限与实例所公开的内容，本发明要求保护的范围以权利要求书界定的范围为准。

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  1. 一种硬岩多尺度破裂的多频段声信号监测方法，其特征在于，包括如下步骤：
    步骤S1：实时采集硬岩破裂过程的声发射、声音、微震三种频段声信号，并对三种声信号降噪；
    步骤S2：根据硬岩破裂过程的声发射、声音、微震三种不同频段声信号的活跃度，判别硬岩破裂尺度所处当前阶段；
    步骤S3：根据硬岩破裂尺度当前阶段声信号b值分析决策，每间隔一定时间计算声信号的b值，分析b值随时间变化趋势，获得硬岩破裂尺度演化的定量化评估结果；
    步骤S4：根据硬岩失稳预警标准，即硬岩破裂尺度当前阶段与b值时间演化趋势，对所监测的硬岩进行失稳破坏预警。
  2. 根据权利要求1所述的一种硬岩多尺度破裂的多频段声信号监测方法，其特征在于，所述步骤2中硬岩破裂阶段判别方法特征为：判据一，声发射撞击数呈现低值、上升趋势，或高值平稳波动，且声音或微震波形幅值均处于一个低活跃期，硬岩破裂处于厘米级尺度及以下的“稳定发展”阶段(阶段Ⅰ)；判据二，声发射撞击数发生平静期现象，且声音波形幅值出现明显活跃，微震波形幅值仍呈现较低活跃期，硬岩破裂处于微米级至米级尺度“非稳定发展”阶段(阶段Ⅱ)；判据三，声发射撞击数发生平静期现象，且声音与微震波形幅值均呈现明显活跃，硬岩破裂处于微米级至米级尺度“加速扩展”阶段(阶段Ⅲ)，破裂尺度阶段的判别式为：
    Figure PCTCN2022095164-appb-100001
    式中，AE hits为声发射撞击数，AE hit rate为声发射撞击数活跃程度，Sound amplitude rate为声音信号波形幅值活跃程度，MS amplitude rate为微震信号波形幅值活跃程度，HT为声发射撞击数的高活跃水平值，LT为声发射撞击数的低活跃水平值，可通过AE hits与Sound amplitude rate或/和MS amplitude rate判别声发射信号是否出现平静期，A、B、C分别为声发射、声音、微震活跃程度门槛值，上述数值根据特定环境而定。
  3. 根据权利要求1所述的一种硬岩多尺度破裂的多频段声信号监测方法，其特征在于，所述的步骤3中声信号b值分析决策为：决策一，若硬岩破裂尺度处于阶段Ⅰ，即厘米级尺度及以下阶段时，对间隔一定相同时间的声发射信号进行b值计算；决策二，若硬岩破裂尺度处于阶段Ⅱ，即厘米级尺度至米级阶段时，对间隔一定相同时间的声发射和声音等两种声信号进行b值计算；决策三，若硬岩破裂尺度处于阶段Ⅲ，即米级尺度及以上阶段时，对间隔一定相同时间的声发射、声音和微震等三种声信号进行b值计算。
  4. 根据权利要求1所述的一种硬岩多尺度破裂的多频段声信号监测方法，其特征在于，所述的步骤4中的硬岩失稳预警标准为：若硬岩破裂尺度处于阶段Ⅲ，即米级尺度时，硬岩具有高失稳风险，宜进行相应等级预警；若硬岩破裂尺度处于阶段Ⅲ，且声发射、声音和微震等三种声信号的b值均随时间呈现下降趋势，其中声音与微震信号的b值下降速率不断增大，硬岩具有极高失稳风险，立即进行风险预警。
  5. 一种硬岩多尺度破裂的多频段声信号监测装置，其特征在于，包括：
    声信号采集单元：用于实时采集硬岩破裂过程的声发射、声音以及微震多频段声信号；
    声信号传输单元：用于无线传输硬岩破裂的三种声信号有效数据；
    声信号处理单元：用于对硬岩破裂声信号进行实时预处理降噪，并对处理后的三种信号进行活跃度分析，进而判别硬岩破裂尺度所处当前阶段；
    声音信号分析单元：用于根据硬岩破裂尺度当前阶段声信号b值分析决策，每间隔一定时间计算声信号的b值，分析b值随时间变化趋势，获得硬岩破裂尺度演化的定量化评估结果；
    预警单元：用于根据硬岩失稳预警标准，即硬岩破裂尺度当前阶段与b值时间演化趋势，对所监测的硬岩进行失稳破坏预警。
  6. 根据权利要求5所述的一种硬岩多尺度破裂的多频段声信号监测装置，其特征在于，所述声信号处理单元包括：
    声信号预处理子单元：用于将接收硬岩破裂的声发射、声音、微震信号数据进行降噪处理，以得到较纯净、质量较高的待分析信号；
    破裂尺度阶段判别子单元：用于对处理后的三种信号进行活跃度分析，判别硬岩破裂所处特定阶段，判别准则为：判据一，“稳定发展”阶段，声发射撞击数呈现低值、上升趋势，或高值平稳波动，且声音或微震波形幅值均处于一个低活跃期；判据二，“非稳定发展”阶段，声发射撞击数发生平静期现象，且声音波形幅值出现明显活跃，微震波形幅值仍呈现较低活跃期；判据三，“加速扩展”阶段，声发射撞击数发生平静期现象，且声音与微震波形幅值均呈现明显活跃。
  7. 根据权利要求5所述的一种硬岩多尺度破裂的多频段声信号监测装置，其特征在于，所述声信号评估单元包括：
    声信号第一评估子单元：用于通过高频声发射信号b值特征变化趋势，评估硬岩破裂尺度的“稳定发展”阶段演化过程；
    声信号第二评估子单元：用于通过中频声音与高频声发射信号b值特征变化趋势，评估硬岩破裂尺度的“非稳定发展”阶段演化过程；
    声信号第三评估子单元：用于通过低频微震、中频声音以及高频声发射b值特征变化趋势，评估硬岩破裂尺度的“加速扩展”阶段演化过程。
  8. 一种硬岩多尺度破裂的多频段声信号监测设备，其特征在于，包括：
    现场设备，用于实时监测工程岩体破裂的声信号，并将通过5G无线传输至云端设备；可以包括信号采集器，电源，高速AD转换器，储存器，时钟，FGPA微控制器，以及通讯组件一个或多个；可以完成权利要求1所述的硬岩多尺度破裂的多频段声信号监测方法中的步骤1部分；
    云端设备，用于接收现场设备所获取的岩体破裂的声信号数据，通过声信号的滤噪、波形分析以及b值分析，进一步完成岩体破裂阶段判别以及破裂状态评估，最终实现岩体失稳破坏风险预警；可以包括存储器，多媒体组件，I/O接口，通讯组件，以及处理器一个或多个；可以完成权利要求1所述的硬岩多尺度破裂的多频段声信号监测方法中的步骤1部分以及步骤2至步骤4。
  9. 一种可读存储介质，其特征在于，所述可读存储介质上存储有计算机程序，所述计算机程序被处理器执行时实现所述权利要求1至4任一项所述的硬岩多尺度破裂的多频段声 信号监测方法的步骤。
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