Rock damage analysis method and system, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a rock damage analysis method and system, electronic equipment and a storage medium, and belongs to the technical field of rock detection. According to the method, acoustic emission sensors arranged on the surface of rock are used for collecting acoustic wave signals, acoustic emission signals of rock damage are detected based on the acoustic emission signals, and after the acoustic emission signals of rock damage are detected, an approximate rock damage area is determined based on the arrangement positions of the corresponding acoustic emission sensors. Furthermore, the rock damage position is determined according to the target acoustic emission signals of the acoustic emission sensors in the damage range by utilizing a sound source positioning technology in the damage area, so that the rock damage positioning precision is improved.

Description

Technical Field

[0001] The present application relates to the technical field of rock detection, and particularly to a rock damage analysis method, system, electronic device and storage medium. Background Art

[0002] In many fields such as civil engineering, petrochemical industry, and aerospace, the safety monitoring of structures is crucial. Currently, for the damage detection of rocks, fiber Bragg grating sensors or radar are usually used for monitoring. The principle of fiber Bragg grating sensors is based on the linear relationship between the wavelength of fiber Bragg gratings and strain and temperature. By monitoring the wavelength change, the strain and temperature changes of the tunnel surrounding rock are sensed, and then the damage situation of the surrounding rock is inferred. The strain gauge is pasted on the surface of the tunnel surrounding rock. When the surrounding rock deforms, the resistance value of the strain gauge will change. By measuring the change in the resistance value, the strain is calculated, so as to evaluate the stress and damage situation of the surrounding rock. Radar monitoring utilizes the propagation characteristics of electromagnetic waves in the tunnel surrounding rock. When encountering different medium interfaces, reflection and scattering will occur. By analyzing the characteristics of the reflected waves, such as amplitude, phase, frequency, etc., the structure and damage situation of the surrounding rock are inferred.

[0003] The monitoring of fiber Bragg grating sensors is difficult to distinguish the types of damage, can only reflect the strain change, and is easily affected by external environmental temperature, etc. The radar monitoring method has a low resolution for minor damage and limited adaptability to complex geological conditions. To achieve real-time monitoring, continuous radar signals need to be emitted, resulting in high costs. Based on this, in related technologies, acoustic emission sensors can be used to detect rock crack damage. It detects the damage category by analyzing the sound characteristics when the rock cracks, and does not require the emission of radar signals, with low costs. In the actual application process, acoustic emission sensors are arranged on the rock surface for detection. If the acoustic wave characteristics collected by the acoustic emission sensors meet the acoustic wave characteristics of rock rupture, it can be determined that rock damage occurs within a certain range of the position where the acoustic emission sensors are located, but the specific location of the rock damage cannot be determined, thus causing relevant personnel to be unable to comprehensively and accurately understand the internal situation and affecting subsequent related projects. Summary of the Invention

[0004] The main purpose of the embodiments of the present application is to propose a rock damage analysis method, system, electronic device and storage medium, aiming to improve the accuracy of rock damage location.

[0005] To achieve the above purpose, on the one hand, an embodiment of the present application proposes a rock damage analysis method, including the following steps:

[0006] Collect the acoustic wave signals of each acoustic emission sensor;

[0007] Judge whether there are acoustic wave segments in the acoustic wave signals of each acoustic emission sensor that conform to the acoustic wave characteristics of rock damage;

[0008] When there is a sound wave segment in the sound wave signal of the acoustic emission sensor that conforms to the acoustic wave characteristics of rock damage, the target sensor is determined according to the acoustic emission sensor;

[0009] The damage range is determined according to the layout position of the target sensor;

[0010] A plurality of target acoustic emission signals collected by the acoustic emission sensors within the damage range are obtained, where the target acoustic emission signal is a sound wave segment that conforms to the acoustic wave characteristics of rock damage;

[0011] The rock damage position is determined by using the sound source localization technology according to the target acoustic emission signals of the plurality of acoustic emission sensors within the damage range.

[0012] In some embodiments, determining whether there is a sound wave segment in the sound wave signal of each acoustic emission sensor that conforms to the acoustic wave characteristics of rock damage includes the following steps:

[0013] The sound wave signal collected by the acoustic emission sensor is denoised to obtain a denoised sound wave signal;

[0014] Effective sound wave segments are extracted from the denoised sound wave signal according to the signal intensity;

[0015] Feature extraction is performed on the effective sound wave segments to obtain sound wave segment features;

[0016] The feature similarity between the effective sound wave segments and the acoustic wave characteristics of rock damage is calculated;

[0017] When the feature similarity of the effective sound wave segments is greater than the expected similarity value, it is determined that there is a sound wave segment in the sound wave signal of the acoustic emission sensor that conforms to the acoustic wave characteristics of rock damage, and the effective sound wave segments are marked as rock acoustic emission segments.

[0018] In some embodiments, the rock damage analysis method further includes the following steps:

[0019] The ring count, duration, rise time, and signal amplitude are determined according to the waveform of the rock acoustic emission segment;

[0020] A first parameter value is determined according to the ring count and the duration, and a second parameter value is determined according to the rise time and the signal amplitude;

[0021] The coordinate points formed by the first parameter value and the second parameter value are mapped onto a constructed scatter plot, and the damage type of the rock acoustic emission segment is determined according to the classification area in the scatter plot to which the coordinate points belong.

[0022] In some embodiments, when there are acoustic wave segments in the acoustic wave signal of the acoustic emission sensor that conform to the characteristics of acoustic waves of rock damage, determining the target sensor according to the acoustic emission sensor includes the following steps:

[0023] When there are acoustic wave segments in the acoustic wave signal of the acoustic emission sensor that conform to the characteristics of acoustic waves of rock damage, accumulate the number of damage events of the acoustic emission sensor;

[0024] Determine the acoustic emission sensors with the number of damage events greater than the preset number value as the target sensors.

[0025] In some embodiments, obtaining the target acoustic emission signals collected by several acoustic emission sensors within the damage range includes the following steps:

[0026] Obtain multiple rock acoustic emission segments of each acoustic emission sensor within the damage range during the time period when the damage event occurs to obtain the set of segments to be analyzed of the acoustic emission sensor;

[0027] Judge whether two rock acoustic emission segments between the sets of segments to be analyzed of each acoustic emission sensor are the same damage sound;

[0028] Mark the rock acoustic emission segments judged to be the same damage sound in each set of segments to be analyzed as the same damage event;

[0029] Determine the damage acoustic wave segments marked with the target damage event in the set of segments to be analyzed as the target acoustic emission signals.

[0030] In some embodiments, using the sound source localization technology to determine the rock damage position according to the target acoustic emission signals of several acoustic emission sensors within the damage range includes the following steps:

[0031] Obtain the actual time when each acoustic emission sensor within the damage range receives the target acoustic emission signal;

[0032] Determine the actual time difference between each pair of acoustic emission sensors according to the respective actual times;

[0033] Determine the rock damage position according to the respective actual time differences and the layout positions of the acoustic emission sensors.

[0034] In some embodiments, determining the rock damage position according to the respective actual time differences and the layout positions of the acoustic emission sensors includes the following steps:

[0035] According to the layout positions of each acoustic emission sensor and the propagation speed of rock sound, determine the theoretical time difference between each pair of acoustic emission sensors when receiving the target acoustic emission signal;

[0036] Construct an objective function with the goal of minimizing the sum of each time difference error, where the time difference error represents the difference between the actual time difference and the theoretical time difference of two corresponding acoustic emission sensors;

[0037] Use the beetle antennae search algorithm to optimize the rock damage coordinates in the objective function, and determine the optimal rock damage coordinates as the rock damage location.

[0038] To achieve the above object, another aspect of the embodiments of the present application proposes a rock damage analysis system, including:

[0039] A first module for collecting acoustic wave signals of each acoustic emission sensor;

[0040] A second module for determining whether there is an acoustic wave segment that conforms to the acoustic wave characteristics of rock damage in the acoustic wave signals of each acoustic emission sensor;

[0041] A third module for, when there is an acoustic wave segment that conforms to the acoustic wave characteristics of rock damage in the acoustic wave signal of the acoustic emission sensor, determining a target sensor according to the acoustic emission sensor;

[0042] A fourth module for determining the damage range according to the layout position of the target sensor;

[0043] A fifth module for obtaining target acoustic emission signals collected by several acoustic emission sensors within the damage range, where the target acoustic emission signal is an acoustic wave segment that conforms to the acoustic wave characteristics of rock damage;

[0044] A sixth module for using a sound source localization technique to determine the rock damage position according to the target acoustic emission signals of several acoustic emission sensors within the damage range.

[0045] To achieve the above object, another aspect of the embodiments of the present application proposes an electronic device, where the electronic device includes a memory, a processor, a program stored on the memory and executable on the processor, and a data bus for realizing connection communication between the processor and the memory. When the program is executed by the processor, the method described in the above embodiments is realized.

[0046] To achieve the above object, another aspect of the embodiments of the present application proposes a storage medium, where the storage medium is a computer-readable storage medium for computer-readable storage. The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to realize the method described in the above embodiments.

[0047] The rock damage analysis method, system, electronic device and storage medium proposed in this application collect acoustic wave signals through acoustic emission sensors arranged on the rock surface, detect the acoustic emission signals of rock damage based on the acoustic emission signals, determine the approximate rock damage area based on the arrangement positions of the corresponding acoustic emission sensors after detecting the acoustic emission signals of rock damage, and further use the sound source localization technology in this damage area to determine the rock damage position according to the target acoustic emission signals of several acoustic emission sensors within the damage range, improving the accuracy of rock damage localization. Description of the Drawings

[0048] Figure 1 is a flowchart of the rock damage analysis method provided by an embodiment of this application;

[0049] Figure 2 is a schematic diagram showing the relationship between the acoustic emission sensor and the sound source position provided by an embodiment of this application;

[0050] Figure 3 is a schematic diagram of the hardware structure of the electronic device provided by an embodiment of this application. Detailed Embodiments

[0051] In order to make the objectives, technical solutions and advantages of this application clearer, the following further elaborates on this application in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not used to limit this application.

[0052] It should be noted that although functional module division is performed in the system and the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order from the module division in the system or the flowchart. Terms such as "first" and "second" in the specification, claims and the above drawings are used to distinguish similar objects and do not necessarily need to describe a specific order or sequence.

[0053] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0054] Based on this, the embodiments of this application provide a rock damage analysis method, system, electronic device and storage medium, aiming to improve the accuracy of rock damage localization.

[0055] The rock damage analysis method, system, electronic device and storage medium provided by the embodiments of this application are specifically described through the following embodiments. First, the rock damage analysis method in the embodiments of this application is described.

[0056] The rock damage analysis method provided by the embodiments of the present application relates to the technical field of rock detection. The rock damage analysis method provided by the embodiments of the present application can be applied to a terminal, or to a server side, or can also be software running on a terminal or a server side. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc.; the server side can be configured as an independent physical server, or can be configured as a server cluster or a distributed system composed of multiple physical servers, or can also be configured as a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application that implements the rock damage analysis method, etc., but is not limited to the above forms.

[0057] The present application can be used in many general or specific computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multi-processor systems, microprocessor-based systems, set-top boxes, programmable consumer electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and so on. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in a distributed computing environment where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0058] Figure 1 is an optional flowchart of the rock damage analysis method provided by the embodiments of the present application, Figure 1 The method in can include but is not limited to steps S101 to S106.

[0059] Step S101, collect the acoustic wave signals of each acoustic emission sensor;

[0060] Step S102, determine whether there are acoustic wave segments in the acoustic wave signals of each acoustic emission sensor that conform to the acoustic wave characteristics of rock damage;

[0061] Step S103, when there are acoustic wave segments in the acoustic wave signals of the acoustic emission sensor that conform to the acoustic wave characteristics of rock damage, determine the target sensor according to the acoustic emission sensor;

[0062] Step S104, determine the damage range according to the layout position of the target sensor;

[0063] Step S105: Obtain the target acoustic emission signals collected by several acoustic emission sensors within the damage range, where the target acoustic emission signals are acoustic wave segments that conform to the acoustic wave characteristics of rock damage.

[0064] Step S106: Use the sound source localization technology to determine the rock damage location based on the target acoustic emission signals of several acoustic emission sensors within the damage range.

[0065] In step S101 of some embodiments, this embodiment takes the analysis of tunnel surrounding rock damage as an example to illustrate the rock damage analysis method of the embodiments of the present application. Several acoustic emission sensors can be arranged on the surface or inside the surrounding rock along the tunnel direction at a certain distance interval. One row or multiple rows of acoustic emission sensors can be arranged on the surrounding rock in the tunnel direction. The embodiments of the present application can also be arranged in other ways, and the embodiments of the present application do not make specific limitations. After arranging the acoustic emission sensors, store the arrangement positions of each acoustic emission sensor. The arrangement positions of the acoustic emission sensors can be represented by the world coordinate system or the coordinate system of a custom three-dimensional space. Taking the custom three-dimensional space coordinate system as an example, determine the tunnel reference point and three reference directions, measure the three reference direction distances between each acoustic emission sensor and the tunnel reference point, then map the tunnel reference point and the three reference directions into the computer three-dimensional space to construct a three-dimensional space coordinate system, and then determine the arrangement positions of the acoustic emission sensors in the three-dimensional space coordinate system according to the measured distance values.

[0066] Before failure, various physical effects occur in rocks. These phenomena include acoustic emission (AE), wave velocity change, wave velocity anisotropy, and low-frequency radiation. Rock acoustic emission refers to the phenomenon that rocks emit sound waves or ultrasonic waves during the process of stress deformation and fracture. The principle of acoustic emission detection lies in that when an object deforms or is affected by an external force, elastic energy is rapidly released to generate transient stress waves. By collecting and analyzing the acoustic waves of rock acoustic emission, it can be determined whether a rock damage event has occurred. To improve the accuracy of damage detection, this embodiment needs to use high-precision acoustic emission sensing equipment. Based on this, the acoustic emission sensors of the embodiments of the present application can be prepared in a certain way to improve the acquisition accuracy of acoustic wave signals.

[0067] Select a PZT-5H piezoelectric ceramic sheet with a thickness of 30 mm and a diameter of 20 mm. Ultrasonically clean it with acetone or alcohol for 15 - 30 minutes. After rinsing with deionized water, dry it at 80 - 100 °C for 1 - 2 hours. Polarize it at 120 - 150 °C and an electric field of 3 - 5 kV / mm for 30 - 60 minutes, and then cool it to room temperature in the furnace. Screen-print electrode layers with a thickness of 20 - 50 μm on the upper and lower surfaces of the ceramic sheet, and sinter it in a high-temperature furnace at 700 - 850 °C for 30 - 60 minutes to form an ohmic contact. Connect the electrodes with a silver-plated copper wire with a cross-sectional area of 0.2 - 0.5 mm² by low-temperature soldering or conductive adhesive. Mix the A and B components of the epoxy resin, apply a layer on the bottom of the customized shell, place the ceramic sheet with the connected wire, pour it until it reaches 1 / 3 - 1 / 2 of the volume of the shell, prevent air bubbles, and cure it at room temperature or in an oven for 12 - 24 hours. Cut a copper or aluminum shielding net with a mesh size of 0.5 - 2 mm according to the size of the first encapsulated shell, tightly wrap it, process the overlap to ensure electrical continuity, and insulate the wire contact to prevent short circuits. Stick the cut and polished Al₂O₃ ceramic sheet on the shielding net with a high-temperature ceramic binder and cure it in a high-temperature furnace. Measure the impedance with an impedance analyzer, observe the output voltage waveform of the excitation signal with an oscilloscope, calibrate the sensitivity with a standard acoustic emission source, and measure the frequency response with a sweep signal source and plot a graph.

[0068] In step S102 of some embodiments, the acoustic emission sensors continuously collect sound signals at a certain sampling frequency. In this embodiment, it is necessary to continuously analyze the collected acoustic wave signals to determine whether there are acoustic wave segments in the acoustic wave signals of each acoustic emission sensor that conform to the acoustic wave characteristics of rock damage. The judgment method can be the feature library comparison method or the machine learning method. In one example, the feature library comparison method is specifically to store various acoustic wave characteristics of rock fracture in the feature library, and compare the characteristics of each segment of the collected acoustic wave signal with various acoustic wave characteristics in the feature library, so as to determine whether there are acoustic wave segments in the acoustic wave signal that conform to the acoustic wave characteristics of rock damage. In another example, various acoustic wave signals of rock fracture can be used as samples to train a neural network model, and then the trained neural network model is used to determine whether there are acoustic wave segments in the acoustic wave signal that conform to the acoustic wave characteristics of rock damage.

[0069] In step S103 of some embodiments, continuously detect the acoustic wave signals of each acoustic emission sensor. When it is determined that there are acoustic wave segments in the acoustic wave signal of a certain acoustic emission sensor that conform to the acoustic wave characteristics of rock damage, it indicates that the acoustic emission sensor has detected the acoustic wave emitted by rock fracture. At this time, the target sensor can be determined according to this acoustic emission sensor. Specifically, the sensor that monitors the acoustic wave of rock fracture can be directly determined as the target sensor.

[0070] In step S104 of some embodiments, after determining the target sensor, the damage range is determined according to the layout position of the target sensor. The damage range can be specifically determined according to the monitoring range of the acoustic emission sensor. Exemplarily, the rock portion in the space with the target sensor as the center and the monitoring range as the radius is determined as the damage range.

[0071] In step S105 of some embodiments, acoustic wave signals collected by a plurality of acoustic emission sensors arranged within the damage range are acquired, and subsequent positioning analysis is performed based on target acoustic emission signals when the rock is fractured in the acoustic wave signals.

[0072] In step S106 of some embodiments, the sound source positioning technology is used to determine the rock damage position according to the target acoustic emission signals of several acoustic emission sensors within the damage range. The sound source positioning technology calculates the position of the sound source through the time difference and intensity difference of the sound wave signals received by multiple acoustic emission sensors. In this embodiment, the acoustic emission sensors arranged on the rock surface collect the sound wave signals, and detect the acoustic emission signals of the rock damage based on the acoustic emission signals. After the acoustic emission signals when the rock damage is detected, the approximate rock damage area is determined based on the corresponding acoustic emission sensor arrangement position, and the sound source positioning technology is further used in the damage area to determine the rock damage position according to the target acoustic emission signals of several acoustic emission sensors within the damage range, thereby improving the accuracy of rock damage positioning.

[0073] According to some embodiments of the present application, in step S102, the step of determining whether there is an acoustic wave segment that meets the acoustic wave characteristics of rock damage in the acoustic wave signal of each acoustic emission sensor may include, but is not limited to, the following steps:

[0074] Step S201, performing noise reduction processing on the sound wave signal collected by the acoustic emission sensor to obtain a noise-reduced sound wave signal;

[0075] Step S202, extracting effective sound wave segments from the noise-reduced sound wave signal according to signal strength;

[0076] Step S203, extracting features from the effective sound wave segments to obtain sound wave segment features;

[0077] Step S204, calculating the feature similarity between the effective acoustic wave segment and the rock damage acoustic wave feature;

[0078] Step S205: when the feature similarity of the valid sound wave segment is greater than the expected similarity value, it is determined that there is a sound wave segment that meets the rock damage sound wave feature in the sound wave signal of the acoustic emission sensor, and the valid sound wave segment is marked as a rock acoustic emission segment.

[0079] In step S201 of some embodiments, the acoustic wave signals collected by the acoustic emission sensors include, in addition to the rock acoustic emission signals, environmental noises, such as vehicle driving noises and human voices in the tunnel, etc. Therefore, it is necessary to perform noise reduction processing on the acoustic wave signals to remove the environmental noises therein. The noise reduction process can use a digital filter to filter the acoustic wave signals to reduce the intensity of the noise signals within the frequency ranges of vehicle noise, wind noise, and human voices to 0. The filter is designed and adjusted according to the spectral characteristics of the environmental noise. In another example, it is also possible to analyze the spectrum of the acoustic wave signals, compare the noise spectrum with the rock acoustic emission spectrum, and then subtract the noise spectrum to remove the environmental noises therein. Common spectral subtraction algorithms include short-time Fourier transform (STFT) and minimum mean square error estimation (MMSE), etc.

[0080] In step S202 of some embodiments, since the rock fracture is a sudden event and the environment is mostly quiet for most of the time, that is, most of the acoustic wave signals after noise reduction are invalid segments. In order to reduce the computer processing load, it is possible to extract the effective acoustic wave segments from the acoustic wave signals after noise reduction based on the signal intensity. For example, the segments with a signal intensity of 0 or close to 0 are intercepted from the acoustic wave signals after noise reduction to obtain the effective acoustic wave segments.

[0081] In steps S203 to S205 of some embodiments, considering that in step S201, only some vehicle noises and wind noises with far - apart frequency ranges are preliminarily filtered out, and there may be some acoustic waves with similar sound characteristics that cannot be filtered out, such as the sound of hitting the rock externally. Therefore, in this embodiment, after extracting the effective sound segments, the features of the effective acoustic wave segments are extracted to obtain the acoustic wave segment features, and then the feature similarity between the effective acoustic wave segments and the statistically obtained rock damage acoustic wave features is calculated. When the feature similarity of the effective acoustic wave segments is greater than the expected similarity value, it is determined that there are acoustic wave segments in the acoustic wave signals of the acoustic emission sensors that conform to the rock damage acoustic wave features, and the effective acoustic wave segments are marked as rock acoustic emission segments.

[0082] In another example, it is also possible to identify the rock acoustic emission segments based on the machine learning method. Train a rock acoustic emission recognition model, and training data of positive sample data (various rock acoustic emission segments) and negative sample data (other types of sounds outside the rock acoustic emission segments, such as the sound of hitting the rock) can be used to train a model to learn the feature differences between rock acoustic emissions and other sounds. Machine learning algorithms can adopt deep neural network (DNN), convolutional neural network (CNN), and recurrent neural network (RNN), etc.

[0083] According to some embodiments of the present application, the rock damage analysis method of the embodiments of the present application may further include, but is not limited to, the following steps:

[0084] Step S301: Determine the ring count, duration, rise time, and signal amplitude based on the waveform of the rock acoustic emission segment.

[0085] Step S302: Determine the first parameter value based on the ring count and duration, and determine the second parameter value based on the rise time and signal amplitude.

[0086] Step S303: Map the coordinate points formed by the first parameter value and the second parameter value onto the constructed scatter plot, and determine the damage type of the rock acoustic emission segment according to the classification area in the scatter plot where the coordinate points belong.

[0087] In this embodiment, the internal damage of the rock is generally a rock crack. The causes of rock cracks can usually be divided into two categories: tensile cracks and shear cracks. Usually, when concrete generates tensile cracks, it will instantaneously expand and release energy in the form of longitudinal waves (P-waves), while shear failure releases energy through transverse waves (S-waves). During the propagation of the waveform, the propagation speed of the transverse wave (S-wave) is slower than that of the longitudinal wave (P-wave), so it takes longer to reach the peak. When the surrounding rock undergoes tensile cracking, the acoustic emission wave has the characteristics of fast speed, high frequency, short wavelength, and short rise time; while the acoustic emission wave of shear cracking has a long waveform, slow wave speed, low frequency, and long rise time. In this embodiment, a high-precision acoustic emission sensor is used to collect the rock acoustic emission signal in real time. Each detected rock acoustic emission segment is determined as a rock damage event. In order to further analyze the crack type (tensile crack or shear crack) of each damage event, the RA-AF correlation analysis method can be used to analyze the corresponding rock acoustic emission segment to determine the crack type, as follows:

[0088] Determine the ring count, duration, rise time, and signal amplitude based on the waveform of the rock acoustic emission segment. The ring count refers to the number of rectangular pulses formed after the ringing waveform exceeds the threshold voltage; the duration is the duration of a rock acoustic emission signal, that is, the time length of the rock acoustic emission segment; the rise time refers to the time for the rock acoustic emission signal to reach the highest point; the signal amplitude can refer to the maximum amplitude of the signal.

[0089] Divide the ring count by the duration to obtain the first parameter value, that is, the average frequency AF value. Divide the rise time by the signal amplitude to obtain the second parameter value, that is, the RA value.

[0090] Plot the calculated RA value and AF value on the scatter plot, and judge the crack mode of the surrounding rock damage according to the distribution of the scatter points and their relative positions to the preset demarcation line. If the scatter points are mainly distributed above the line, it indicates that there may be more tensile cracks; if the scatter points are concentrated below the line, then shear cracks may be dominant.

[0091] According to some embodiments of the present application, in step S103, when there are acoustic wave segments in the acoustic wave signal of the acoustic emission sensor that conform to the acoustic wave characteristics of rock damage, the steps of determining the target sensor based on the acoustic emission sensor may include, but are not limited to, the following steps:

[0092] Step S401, when there are acoustic wave segments in the acoustic wave signal of the acoustic emission sensor that conform to the acoustic wave characteristics of rock damage, accumulate the number of damage events of the acoustic emission sensor;

[0093] Step S402, determine the acoustic emission sensors with the number of damage events greater than the preset number value as target sensors.

[0094] In this embodiment, each acoustic emission sensor is set with a number of damage events, which is initialized to 0. During the continuous detection of the acoustic wave signals of each acoustic emission sensor, when it is determined that there are acoustic wave segments in the acoustic wave signal of a certain acoustic emission sensor that conform to the acoustic wave characteristics of rock damage, it indicates that the acoustic emission sensor has detected the acoustic waves emitted by rock fracture, and then accumulate the number of damage events of the acoustic emission sensor. Judge whether the number of damage events of each acoustic emission sensor is greater than the preset number value. If so, it indicates that the area where the corresponding acoustic emission sensor is located is a severely damaged area, and then determine the acoustic emission sensor as the target sensor, and then prioritize crack location in the severely damaged area. It should be noted that in addition to determining the degree of damage according to the number of damage events, it can also be determined in combination with the energy of the rock acoustic emission signal in each acoustic emission event (i.e., damage event).

[0095] According to some embodiments of the present application, in step S105, the steps of obtaining the target acoustic emission signals collected by several acoustic emission sensors within the damage range may include, but are not limited to, the following steps:

[0096] Step S501, obtain multiple rock acoustic emission segments of each acoustic emission sensor within the damage range during the time period when the damage event occurs, and obtain the set of segments to be analyzed of the acoustic emission sensor;

[0097] Step S502, judge whether two rock acoustic emission segments between the sets of segments to be analyzed of each acoustic emission sensor are the same damage sound;

[0098] Step S503, mark the rock acoustic emission segments determined to be the same damage sound in each set of segments to be analyzed as the same damage event;

[0099] Step S504, determine the damage acoustic wave segments marked with the target damage event in the set of segments to be analyzed as the target acoustic emission signal.

[0100] In this embodiment, through the analysis process of the above embodiment, multiple rock acoustic emission segments of each acoustic emission sensor in the historical time can be determined. When finely locating the damage position of a certain rock damage event, it is necessary to select appropriate rock acoustic emission segments for analysis based on the time period when the event occurs and the damage area. After determining the target sensor in this embodiment, the damage range is determined according to the layout position of the target sensor, and then a certain rock acoustic emission segment of the target sensor is selected as a damage event for location analysis as needed. The acquisition time of the selected rock acoustic emission segment is the occurrence time of the damage event, and a time interval before and after this time point is determined as the time period when the damage event occurs. Multiple rock acoustic emission segments of each acoustic emission sensor within the damage range during the time period when the damage event occurs are obtained, and a set of segments to be analyzed for each acoustic emission sensor is obtained. Considering that some acoustic emission sensors may receive acoustic emission events during the time period when the damage event occurs when other rocks in the analyzed area or adjacent areas break, it is necessary to determine whether two rock acoustic emission segments from different sets of segments to be analyzed are the same damage sound. If they are the same damage sound, it indicates the same damage event. Since the intensities and phases of the same sound received by acoustic emission sensors at different positions are different, when determining whether two rock acoustic emission segments are the same damage sound, their frequency characteristics are mainly considered. The specific determination method is as follows:

[0101] Extract the spectral features from the rock acoustic emission segments. Usually, methods such as the fast Fourier transform (FFT) are used to convert the time-domain signal into a frequency-domain signal and extract the spectrogram. Compare the spectrograms of different rock acoustic emission segments. Usually, correlation analysis or similarity measurement methods are used to calculate the similarity between them. Specifically, indicators such as the Euclidean distance, cosine similarity, and Pearson correlation coefficient between two spectrograms can be calculated to complete this. Calculate the similarity between a certain rock acoustic emission segment in the first set of segments to be analyzed and all rock acoustic emission segments in the second set of segments to be analyzed, and determine that the rock acoustic emission segment with the maximum similarity in the second set of segments to be analyzed and this rock acoustic emission segment in the first set of segments to be analyzed are the same damage sound.

[0102] By performing pairwise comparison and analysis on the rock acoustic emission segments from different sets of segments to be analyzed, it can be determined which rock acoustic emission segments from different sets of segments to be analyzed are the same damage sound, and the same damage sound is marked. The user inputs a target damage event as needed or the system selects a target damage event according to the set rules. The system determines the damage acoustic wave segments marked with the target damage event in the set of segments to be analyzed as the target acoustic emission signal for damage location.

[0103] According to some embodiments of the present application, in step S106, the step of determining the rock damage position according to the target acoustic emission signals of several acoustic emission sensors within the damage range by using the acoustic source localization technology may include, but is not limited to, the following steps:

[0104] Step S601, obtain the actual time when each acoustic emission sensor within the damage range receives the target acoustic emission signal;

[0105] Step S602, determine the actual time difference between each pair of acoustic emission sensors according to the respective actual times;

[0106] Step S603, determine the rock damage position according to the respective actual time differences and the layout positions of the acoustic emission sensors.

[0107] In this embodiment, this embodiment is based on the fact that the sound arrives at different acoustic emission sensors at different times, and uses the time difference and distance difference between the sensors to calculate the specific position of the rock damage.

[0108] According to some embodiments of the present application, in step S603, the step of determining the rock damage position according to the respective actual time differences and the layout positions of the acoustic emission sensors may include, but is not limited to, the following steps:

[0109] Step S701, determine the theoretical time difference between each pair of acoustic emission sensors receiving the target acoustic emission signal according to the layout positions of the respective acoustic emission sensors and the rock sound propagation speed;

[0110] Step S702, construct an objective function with the goal of minimizing the sum of each time difference error, where the time difference error represents the difference between the actual time difference and the theoretical time difference of the corresponding two acoustic emission sensors;

[0111] Step S703, use the beetle antenna search algorithm to optimize the rock damage coordinates in the objective function, and determine the optimal rock damage coordinates as the rock damage position.

[0112] Specifically, please combine Figure 2 , in three-dimensional acoustic emission positioning, assume that the emission source 100 (i.e., the crack damage) is located at a certain coordinate (x, y, z) inside the tunnel surrounding rock. There are n acoustic emission sensors 200 arranged in the damage area, and the position coordinates of each sensor are (x i , y i , z i ), where i = 1, 2,..., n. Given that the sound speed is v, according to the relationship between the distance difference from the emission source to different sensors and the time difference of the acoustic emission signal arrival:

[0113]

[0114] where, Δd ij is the distance difference between the acoustic emission source and sensors i and j, and its calculation formula is:

[0115]

[0116] And the time difference ΔT of the actually measured acoustic emission signal arriving at different sensors ij (the time when the acoustic emission signal arrives at each sensor can be accurately measured by the time measurement device set inside the sensor). To improve the positioning accuracy, in this embodiment, the theoretical time difference Δt ij and the actually measured time difference ΔT ij are used as the target with the minimum error to find the position (x, y, z) of the acoustic emission source, and the optimization process can be implemented using the beetle antennae search algorithm.

[0117] The beetle antennae search algorithm is a heuristic optimization algorithm based on bionics. In the optimization problem, this algorithm is used to find the variable value that minimizes the objective function, that is, the position (x, y, z) of the acoustic emission source. The three-dimensional time difference positioning problem of acoustic emission is transformed into an optimization problem, and the following objective function is defined

[0118]

[0119] where, Δt ij is calculated according to the position (x, y, z) of the acoustic emission source, the positions of the sensors (x i , y i , z i ) and the sound speed v by the following formula:

[0120]

[0121] where, ΔT ij is the time difference of the actually measured acoustic emission signal arriving at sensors i and j.

[0122] Set the parameters of the beetle antennae search algorithm, including the step size η, the search ranges [x min , x max , [y min , y max , [z min , z max , the maximum number of iterations N, etc. Among them, the search range is determined according to the above damage range. Randomly initialize the initial position (x0, y0, z0) of the beetle, and this position is within the search range. In each iteration, generate the left and right antennae positions (x l , y l , z l ) and (x r , yr , z r ). Calculate the objective function values f corresponding to the left and right whisker positions l = f(x l , y l , z l ) and f r = (x r , y r , z r ). Determine the advancing direction of the longhorn beetle according to the magnitudes of f l and f r , and update the position (x k+1 , y k+1 , z k+1 ) of the longhorn beetle, where k represents the number of iterations. When the number of iterations reaches N or the objective function value f(x, y, z) is less than the set threshold, terminate the search. At this time, the obtained (x, y, z) is the estimated position of the acoustic emission source.

[0123] In this embodiment, the longhorn beetle whisker search algorithm is combined with the acoustic emission three-dimensional time difference location method, effectively solving the positioning problem caused by complex factors such as the change of sound speed, and significantly improving the accuracy and efficiency of damage distribution positioning.

[0124] This application embodiment also proposes a rock damage analysis system, including:

[0125] The first module is used to collect the acoustic wave signals of each acoustic emission sensor;

[0126] The second module is used to judge whether there are acoustic wave segments conforming to the acoustic wave characteristics of rock damage in the acoustic wave signals of each acoustic emission sensor;

[0127] The third module is used to, when there are acoustic wave segments conforming to the acoustic wave characteristics of rock damage in the acoustic wave signals of the acoustic emission sensor, determine the target sensor according to the acoustic emission sensor;

[0128] The fourth module is used to determine the damage range according to the layout position of the target sensor;

[0129] The fifth module is used to obtain the target acoustic emission signals collected by several acoustic emission sensors within the damage range, where the target acoustic emission signal is an acoustic wave segment conforming to the acoustic wave characteristics of rock damage;

[0130] The sixth module is used to adopt the sound source localization technology to determine the rock damage position according to the target acoustic emission signals of several acoustic emission sensors within the damage range.

[0131] It can be understood that the content in the above embodiments of the rock damage analysis method is applicable to the embodiments of this system. The functions specifically implemented by the embodiments of this system are the same as those of the above embodiments of the rock damage analysis method, and the beneficial effects achieved are also the same as those of the above embodiments of the rock damage analysis method.

[0132] An embodiment of this application also provides an electronic device, which includes: a memory, a processor, a program stored on the memory and executable on the processor, and a data bus for realizing the connection and communication between the processor and the memory. When the program is executed by the processor, it realizes the above rock damage analysis method. This electronic device can be any intelligent terminal including a tablet computer, an in-vehicle computer, etc.

[0133] Please refer to Figure 3 , Figure 3 which shows the hardware structure of an electronic device in another embodiment. The electronic device includes:

[0134] A processor 901, which can be implemented in ways such as a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided by the embodiments of this application;

[0135] A memory 902, which can be implemented in forms such as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 902 can store an operating system and other application programs. When implementing the technical solutions provided by the embodiments of this specification through software or firmware, the relevant program codes are stored in the memory 902 and are called by the processor 901 to execute the rock damage analysis method of the embodiments of this application;

[0136] An input / output interface 903, which is used to realize information input and output;

[0137] A communication interface 904, which is used to realize the communication interaction between this device and other devices, and can realize communication through a wired method (such as USB, network cable, etc.) or through a wireless method (such as a mobile network, WIFI, Bluetooth, etc.);

[0138] A bus 905, which transmits information between the various components of the device (such as the processor 901, the memory 902, the input / output interface 903, and the communication interface 904);

[0139] Among them, the processor 901, the memory 902, the input / output interface 903, and the communication interface 904 are communicatively connected to each other inside the device through the bus 905.

[0140] The embodiment of the present application also provides a storage medium, which is a computer-readable storage medium for computer-readable storage. The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the above-mentioned rock damage analysis method.

[0141] As a non-transitory computer-readable storage medium, the memory can be used to store non-transitory software programs and non-transitory computer-executable programs. In addition, the memory can include high-speed random access memory, and can also include non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories can be connected to the processor through a network. Examples of the above networks include, but are not limited to, the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0142] The embodiments described in the embodiments of the present application are for more clearly illustrating the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. Those skilled in the art will know that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of the present application are equally applicable to similar technical problems.

[0143] Those skilled in the art can understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or combine certain steps, or different steps.

[0144] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0145] Those of ordinary skill in the art can understand that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices can be implemented as software, firmware, hardware, and appropriate combinations thereof.

[0146] In the description of this application and the above-mentioned accompanying drawings, terms such as "first", "second", "third", "fourth", etc. (if any) are used to distinguish similar objects and do not necessarily describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances so that the embodiments of this application described here can be implemented in an order other than those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that comprises a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0147] In several embodiments provided by this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the above-mentioned division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of systems or units can be in electrical, mechanical or other forms.

[0148] The units described above as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0149] In addition, in each embodiment of this application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0150] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of various embodiments of this application. The foregoing storage medium includes: various media that can store programs, such as USB flash drives, mobile hard disks, read-only memory (ROM for short), random access memory (RAM for short), magnetic disks, or optical discs.

[0151] The preferred embodiments of the embodiments of this application have been described above with reference to the accompanying drawings, and thus do not limit the scope of the rights of the embodiments of this application. Any modifications, equivalent replacements, and improvements made by those skilled in the art without departing from the scope and essence of the embodiments of this application shall fall within the scope of the rights of the embodiments of this application.

Claims

1. A method for analyzing rock damage, characterized in that, Including the following steps: Collecting acoustic wave signals of each acoustic emission sensor; Judging whether there are acoustic wave segments conforming to the acoustic wave characteristics of rock damage in the acoustic wave signals of each of the acoustic emission sensors; When there are acoustic wave segments conforming to the acoustic wave characteristics of rock damage in the acoustic wave signal of the acoustic emission sensor, determining a target sensor according to the acoustic emission sensor; Determining the damage range according to the layout position of the target sensor; Obtaining target acoustic emission signals collected by a plurality of acoustic emission sensors within the damage range, where the target acoustic emission signal is an acoustic wave segment conforming to the acoustic wave characteristics of rock damage; Adopting a sound source localization technique to determine the rock damage position according to the target acoustic emission signals of a plurality of acoustic emission sensors within the damage range.

2. The rock damage analysis method according to claim 1, wherein The step of judging whether there are acoustic wave segments conforming to the acoustic wave characteristics of rock damage in the acoustic wave signals of each of the acoustic emission sensors includes the following steps: Performing noise reduction processing on the acoustic wave signals collected by the acoustic emission sensor to obtain noise-reduced acoustic wave signals; Extracting effective acoustic wave segments from the noise-reduced acoustic wave signals according to the signal intensity; Performing feature extraction on the effective acoustic wave segments to obtain acoustic wave segment features; Calculating the feature similarity between the effective acoustic wave segments and the acoustic wave characteristics of rock damage; When the feature similarity of the effective acoustic wave segment is greater than the expected similarity value, determining that there are acoustic wave segments conforming to the acoustic wave characteristics of rock damage in the acoustic wave signal of the acoustic emission sensor, and marking the effective acoustic wave segment as a rock acoustic emission segment.

3. The rock damage analysis method according to claim 2, wherein, The rock damage analysis method further includes the following steps: Determining the ring count, duration, rise time, and signal amplitude according to the waveform of the rock acoustic emission segment; Determining a first parameter value according to the ring count and the duration, and determining a second parameter value according to the rise time and the signal amplitude; Mapping the coordinate points formed by the first parameter value and the second parameter value onto a constructed scatter plot, and determining the damage type of the rock acoustic emission segment according to the classification area of the scatter plot where the coordinate points belong.

4. The rock damage analysis method according to claim 1, characterized in that The step of when there are acoustic wave segments conforming to the acoustic wave characteristics of rock damage in the acoustic wave signal of the acoustic emission sensor, determining a target sensor according to the acoustic emission sensor includes the following steps: When there are acoustic wave segments conforming to the acoustic wave characteristics of rock damage in the acoustic wave signal of the acoustic emission sensor, accumulating the number of damage events of the acoustic emission sensor; Determining the acoustic emission sensors with the number of damage events greater than a preset number value as target sensors.

5. The rock damage analysis method according to claim 2, characterized in that The step of obtaining the target acoustic emission signals collected by a plurality of acoustic emission sensors within the damage range includes the following steps: Obtaining multiple rock acoustic emission segments of each acoustic emission sensor within the damage range during the damage event occurrence time period to obtain a set of segments to be analyzed of the acoustic emission sensor; Judging whether two rock acoustic emission segments between the sets of segments to be analyzed of each acoustic emission sensor are the same damage sound; Marking the rock acoustic emission segments judged to be the same damage sound in each of the sets of segments to be analyzed as the same damage event. Determine the damage acoustic wave segments marked with target damage events in the to-be-analyzed segment set as target acoustic emission signals.

6. The rock damage analysis method according to claim 1, characterized in that, Using the sound source localization technology, determining the rock damage position according to the target acoustic emission signals of several acoustic emission sensors within the damage range includes the following steps: Obtain the actual time when each acoustic emission sensor within the damage range receives the target acoustic emission signal; Determine the actual time difference between every two acoustic emission sensors according to each of the actual times; Determine the rock damage position according to each of the actual time differences and the layout positions of the acoustic emission sensors.

7. The rock damage analysis method according to claim 6, characterized in that, The determining the rock damage position according to each of the actual time differences and the layout positions of the acoustic emission sensors includes the following steps: Determine the theoretical time difference between every two acoustic emission sensors receiving the target acoustic emission signal according to the layout positions of each acoustic emission sensor and the rock sound propagation speed; Construct an objective function with the goal of minimizing the sum of each time difference error, where the time difference error represents the difference between the actual time difference and the theoretical time difference of the corresponding two acoustic emission sensors; Use the beetle antennae search algorithm to optimize the rock damage coordinates in the objective function, and determine the optimal rock damage coordinates as the rock damage position.

8. A rock damage analysis system, characterized in that, Including: The first module is used to collect the acoustic wave signals of each acoustic emission sensor; The second module is used to judge whether there are acoustic wave segments conforming to the characteristics of rock damage acoustic waves in the acoustic wave signals of each acoustic emission sensor; The third module is used to, when there are acoustic wave segments conforming to the characteristics of rock damage acoustic waves in the acoustic wave signal of the acoustic emission sensor, determine the target sensor according to the acoustic emission sensor; The fourth module is used to determine the damage range according to the layout position of the target sensor; The fifth module is used to obtain the target acoustic emission signals collected by several acoustic emission sensors within the damage range, where the target acoustic emission signal is an acoustic wave segment conforming to the characteristics of rock damage acoustic waves; The sixth module is used to use the sound source localization technology to determine the rock damage position according to the target acoustic emission signals of several acoustic emission sensors within the damage range.

9. An electronic device, characterized in that, The electronic device includes a memory, a processor, a program stored on the memory and executable on the processor, and a data bus for realizing the connection and communication between the processor and the memory. When the program is executed by the processor, the steps of the method according to any one of claims 1 to 7 are realized.

10. A storage medium, the storage medium being a computer-readable storage medium for computer-readable storage, characterized in that, The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to realize the steps of the method according to any one of claims 1 to 7.

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