WO2023123844A1 - 一种基于nb-iot的岩体破裂失稳微震信号无线监测方法与装置 - Google Patents

一种基于nb-iot的岩体破裂失稳微震信号无线监测方法与装置 Download PDF

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WO2023123844A1
WO2023123844A1 PCT/CN2022/095165 CN2022095165W WO2023123844A1 WO 2023123844 A1 WO2023123844 A1 WO 2023123844A1 CN 2022095165 W CN2022095165 W CN 2022095165W WO 2023123844 A1 WO2023123844 A1 WO 2023123844A1
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microseismic
data
iot
time window
module
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PCT/CN2022/095165
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French (fr)
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许华杰
苏国韶
陈育
蓝兰
蓝日彦
李建合
刘宗辉
覃子秀
严远方
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广西大学
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    • 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
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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  • the invention relates to the technical field of prevention and control of geological disasters, in particular to a method and device for wireless monitoring of microseismic signals of rock mass rupture instability based on NB-IOT.
  • Microseism is a low-frequency acoustic signal with a frequency less than 100 Hz. It is the stress concentration inside the rock mass under the influence of external disturbance stress and temperature, which causes the generation, expansion and penetration of microscopic cracks in the rock mass. The process is accompanied by low-energy elastic waves or stress waves.
  • microseismic signal monitoring equipment can effectively detect The size and location of the elastic wave, and through the analysis of the microseismic signal of the rupture of the dangerous rock mass, reveal the possibility of the collapse and the severity of the damage, and take effective prevention or early avoidance measures to reduce the damage caused by it. So far, microseismic monitoring technology has become an important means of disaster monitoring and forecasting in many demonstration projects, such as coal mine mining, hydropower station construction, and monitoring of dangerous rock masses beside highways.
  • the traditional microseismic monitoring technology mainly adopts wired methods.
  • the sensors need to be connected with equipment such as collectors with cables, and the data collectors and servers are mainly transmitted through wired optical cables.
  • equipment such as collectors with cables
  • the data collectors and servers are mainly transmitted through wired optical cables.
  • the traditional wireless microseismic monitoring method is not only limited by the speed and delay of wireless communication technology, it cannot achieve real-time transmission and detection; at the same time, due to the excessive power consumption of wireless transmission equipment, the working time is too short, which is not conducive to use in outdoor environments .
  • NB-IOT Near Band Internet of Things
  • LPWAN low-power wide area networks
  • IoT wireless transmission technologies such as LoRa, ZigBee, etc.
  • its advantage is that it can be directly deployed on GSM network, UMTS network or LTE network, and can achieve smooth upgrades, so it has the advantage of wide coverage.
  • NB-IOT has the advantage of low power consumption, especially suitable for some occasions where the battery cannot be replaced frequently, such as being placed in remote areas in alpine wilderness; in addition, NB-IOT also has the advantage of low cost, It is conducive to large-scale application in the production environment.
  • the existing NB-IOT technology combined with the specific task of wireless monitoring of rock mass rupture microseismic signals has not yet formed an effective solution, and there are still many problems to be solved.
  • the first thing to bear is the power consumption of the communication module. Since it is installed in a remote field area, it is impractical to replace the battery frequently, so a communication module with low power consumption can only be used.
  • the frequency of data transmission presents the characteristics of short-term high-frequency, which brings difficulties to the long-term work of the communication module. No small challenge.
  • microseismic signals generated when the rock mass ruptures are complex and diverse, and there are some microseismic signals worthy of further analysis. How to transmit the microseismic signals with analytical value to the cloud platform is also a problem of practical significance. Due to the narrow bandwidth characteristics of NB-IOT, when sending large-capacity data packets, there is a phenomenon of high delay, blocked channel or even sending failure.
  • the purpose of the present invention is to provide a NB-IOT-based wireless monitoring method and device for microseismic signals of rock mass rupture and instability, so as to solve the problem of limited use occasions caused by communication cables in the existing wired monitoring scheme for rock mass rupture and instability microseismic signals technical problem.
  • the microseismic signal generated by rock mass rupture and instability is remotely sent to the cloud through NB-IOT technology, which ensures the timeliness of signal transmission and prolongs the working time of the NB-IOT module.
  • a method for wireless monitoring of microseismic signals of rock mass rupture and instability based on NB-IOT comprising the following steps:
  • Step 1 Install one or more data acquisition modules on the rock mass to be monitored, collect microseismic signals generated by rock mass rupture, and use the long and short time window amplitude ratio method to pick up effective microseismic waveform data;
  • Step 2 Create a data sending buffer queue, extract the microseismic feature vector from the effective microseismic waveform data, execute different compression strategies according to the microseismic feature vector to obtain compressed data packets, place the compressed data packets at the end of the data sending buffer queue, and send a The semaphore of the compressed data packet information;
  • Step 3 Use the dormancy wake-up algorithm to schedule the NB-IOT module so that it is woken up when it needs to send data, and sleeps when it does not need to send data, saving power and extending working hours;
  • Step 4 When the NB-IOT module is in the wake-up state, establish a communication link with the cloud platform module, and send the compressed data packet to the cloud platform module;
  • Step 5 The cloud platform module analyzes the received data packets, and sends an early warning message if the early warning condition is met.
  • step 1 the specific process of collecting microseismic signals generated by rock mass rupture is as follows:
  • Step 1.1.1 When the rock mass produces microscopic cracks, it will release low-energy elastic waves and propagate to the surroundings, causing micro-vibrations of the rock mass.
  • the acceleration sensor of the data acquisition module can convert the acceleration value of the micro-vibration of the rock mass into a voltage
  • the value of the microseismic signal is obtained, and the conversion formula is shown in formula (1):
  • d represents the piezoelectric constant
  • m represents the mass of the piezoelectric element inside the acceleration sensor
  • C represents the capacitance at both ends of the piezoelectric element.
  • Step 1.1.2 Use the A/D conversion unit of the data acquisition module to convert the analog signal output by the acceleration sensor into a digitized amplitude and transmit it to the data processing module for further processing.
  • step 1 the specific process of using the long-short time window amplitude ratio method to pick up effective microseismic waveform data is as follows:
  • Step 1.2.1 Create a microseismic data packet temporary storage queue, an effective waveform temporary storage queue, a short time window array and a long time window array.
  • the maximum lengths of the short time window array and the long time window array are M and N respectively,
  • the effective signal extraction threshold is set to be R; the M, N and R are determined according to the monitoring site environment;
  • Step 1.2.2 Initialize the long-time window array, read the amplitudes transmitted from the data acquisition module one by one, and store them in the long-time window array in order until the number of elements in the long-time window array reaches N;
  • Step 1.2.5 Add the elements in the short-time window array to the tail of the effective waveform temporary storage queue in order, obtain the current time stamp, and pack all the elements and time stamps of the effective waveform temporary storage queue into a microseismic data packet, And put it at the end of the microseismic data packet temporary storage queue, indicating that a valid microseismic waveform data is currently picked up, then clear the valid waveform temporary storage queue, and then repeat step 1.2.3 to start picking the next valid microseismic waveform data.
  • step 2 the specific process of extracting the microseismic feature vector from the effective microseismic waveform data is:
  • a microseismic waveform data processing array take out a microseismic data packet from the head of the microseismic data packet temporary storage queue, and copy the effective microseismic waveform data therein to the microseismic waveform data processing array element by element; from the microseismic waveform data
  • the first element of the processing array starts traversing, and the traversal ends at the last element, and a total of six eigenvalues of the trigger position, end position, signal duration, rise time, maximum amplitude, and maximum amplitude position are calculated, and these six
  • the eigenvalues form the microseismic eigenvector, and the specific definitions of the six eigenvalues are:
  • Trigger position indicates the array subscript corresponding to the first amplitude greater than the threshold in the array
  • End position indicates the array subscript corresponding to the minimum amplitude in the array
  • Signal duration Indicates the difference between the end position and the trigger position
  • Maximum amplitude Indicates the largest amplitude among all the amplitudes of the array
  • the position of the maximum magnitude indicates the array subscript corresponding to the maximum magnitude in the array
  • step 2 the specific process of executing different compression strategies according to the microseismic feature vector to obtain the compressed data package is:
  • the maximum amplitude of the microseismic feature vector is greater than or equal to the set threshold V threshold , it means that the effective microseismic waveform data needs to be sent to the cloud platform for backup, and the effective microseismic waveform data is compressed to adapt to the low bandwidth of NB-IOT , first write all the floating-point numbers of the microseismic waveform data processing array into a string separated by commas end to end, and then use the gzip algorithm to compress the string to obtain a compressed string; then the microseismic feature vector, compressed string and Boolean flag bit Flag is encoded into data in JSON format, and then compressed using the Hpack algorithm to obtain a compressed data packet; the value of the Boolean flag bit Flag is set to true, indicating that the compressed data contains valid microseismic waveform data and microseismic features vector;
  • the maximum amplitude in the microseismic feature vector is less than the set threshold V threshold , it means that there is no need to send valid microseismic waveform data to the cloud platform for backup, and only need to send the microseismic feature vector to the cloud platform for storage; first, the microseismic feature vector and Boolean The value flag bit Flag is encoded into data in JSON format, and then it is compressed using the Hpack algorithm to obtain a compressed data packet; the value of the Boolean flag bit Flag, whose value is set to false, indicates that the compressed data packet only contains the microseismic feature vector .
  • step 3 the specific process of scheduling the NB-IOT module using the dormancy wake-up algorithm is:
  • Step 3.1 When the system is initialized, the dormancy wake-up control unit of the data processing module sends the activation AT command, network injection AT command and dormancy AT command to the NB-IOT module in sequence, so that the NB-IOT module performs network injection after being activated. operation, then switch to low power consumption mode and enter sleep state;
  • Step 3.2 Create a counter Counter and a timer Timer, the overflow condition of the counter Counter is that its value reaches C m , and the overflow condition of the timer Timer is that its time reaches T m ;
  • Step 3.3 reset the counter Counter and the timer Timer; the dormant wake-up control unit waits to receive the semaphore, when it receives the semaphore for the first time, if the Boolean flag bit Flag of the semaphore is false, the value of the counter Counter is increased by 1, And the timer Timer is started synchronously, then go to step 3.4, otherwise, go to step 3.5;
  • Step 3.4 The dormant wake-up control unit continues to wait for the received semaphore.
  • the semaphore is received each time, if the Boolean flag bit Flag of the semaphore is true, then enter step 3.5. Otherwise, the value of the counter Counter is increased by 1. If the counter Counter When the overflow condition is met or the timer Timer meets the overflow condition, go to step 3.5; otherwise, repeat step 3.4;
  • Step 3.5 First, the dormant wake-up control unit sends a wake-up AT command to the NB-IOT module to wake up the NB-IOT module, and then executes the data sending process to take out the compressed data packets one by one from the data sending buffer queue and send the compressed data packets To the cloud platform, when the data transmission buffer queue is empty, the sleep wakeup control unit sends a sleep AT command to the NB-IOT module to enter the sleep state, and finally, enter step 3.3.
  • a wireless monitoring device for microseismic signals of rock mass rupture and instability based on NB-IOT including one or more data acquisition modules, data processing modules, NB-IOT modules and cloud platform modules, one or more data acquisition modules and The data processing module is wired or wirelessly connected, and the data processing module is wirelessly connected to the cloud platform module through the NB-IOT module;
  • One or more data acquisition modules are used to obtain microseismic signals generated by rock mass rupture, and convert the microseismic signals into digital voltage signals that need to be processed.
  • the data processing module is used to pick up effective microseismic waveform data, and from them Extract microseismic eigenvectors, compress microseismic eigenvectors and effective microseismic waveform data to meet the characteristics of NB-IOT low bandwidth, and at the same time schedule between the sleep and wake-up states of NB-IOT module, NB-IOT module is used to realize and
  • the cloud platform module establishes a communication link, and sends the compressed data packet to the cloud platform module, and the cloud platform module is used to remotely connect and establish a communication link with the NB-IOT module, and receive and store data from the NB-IOT module , analyze the data, and send an early warning message if the early warning conditions are met.
  • the data acquisition module includes an acceleration sensor unit, an amplification circuit unit, and an A/D conversion unit.
  • the acceleration sensor unit is connected to the A/D conversion unit through the amplification circuit unit.
  • the signal amplifying circuit unit is used to amplify the microseismic signal collected by the acceleration sensor unit, and the A/D conversion unit is used to convert the microseismic signal output by the amplifying circuit unit into a digitized voltage signal.
  • the data processing module includes an effective waveform pickup unit, a feature extraction unit, a data compression unit, and a dormancy wake-up control unit, the input of the effective waveform pickup unit is connected to the A/D conversion unit, and the output of the effective waveform pickup unit is connected to the feature extraction unit.
  • the unit is connected, the output end of the feature extraction unit is connected with the data compression unit, and the dormant wake-up control unit is connected with the NB-IOT module;
  • the effective waveform picking unit is used to extract effective microseismic waveform data from the data transmitted by the A/D conversion unit using the long and short time window amplitude ratio method
  • the feature extraction unit is used to extract microseismic feature vectors from the effective microseismic waveform data
  • the compression unit is used to compress the microseismic feature vector and the effective microseismic waveform data, and reduce the storage space occupied by it so that data transmission can be performed in the narrow bandwidth environment of NB-IOT.
  • the sleep wakeup control unit is used to use the sleep wakeup algorithm to update the NB -
  • the IOT module schedules to wake up when it needs to send data, and sleeps when it does not need to send data, saving power to extend the working time of the NB-IOT module.
  • the present invention combines NB-IOT technology to construct a method and device for wireless monitoring of rock mass rupture microseismic signals, and fully utilizes the advantages of NB-IOT technology in low cost, wide coverage, and low power consumption to make up for existing microseismic signal monitoring
  • the shortcomings of the system's short working time, low communication efficiency and difficulty in long-distance transmission overcome the problems of limited usage scenarios of traditional wired monitoring methods and the problems of low communication efficiency, high delay and inability to achieve real-time monitoring in traditional wireless monitoring methods, and realize Efficient transmission and real-time monitoring of microseismic monitoring data.
  • the NB-IOT module sleep wake-up algorithm proposed by the present invention further prolongs the working time of the NB-IOT module, and is especially suitable for the scene of short-term high-frequency transmission of microseismic signals, so that the NB-IOT module can be installed in remote In mountainous areas, there is no need to replace batteries frequently.
  • microseismic data compression method proposed in the present invention enables the compressed microseismic data to be transmitted to the cloud platform in the narrow bandwidth environment of NB-IOT, which helps to preserve and analyze information related to rock mass fracture instability.
  • Valuable microseismic data create conditions for subsequent processing and analysis of microseismic data.
  • Fig. 1 is the flowchart of the wireless monitoring method for microseismic signal of rock mass rupture based on NB-IOT in the embodiment of the present invention
  • Fig. 2 is the flow chart of using the long and short time window amplitude ratio method to pick up effective microseismic waveform data in the embodiment of the present invention
  • Fig. 3 is the waveform diagram of the effective microseismic waveform data picked up using the long and short time window amplitude ratio method in the embodiment of the present invention
  • Fig. 4 is a flow chart of scheduling the NB-IOT module using the dormancy wake-up algorithm in the embodiment of the present invention
  • Fig. 5 is a circuit schematic diagram of an NB-IOT-based wireless monitoring device for rock mass rupture microseismic signals in an embodiment of the present invention.
  • Figure 1 is a flow chart of the method, specifically including steps 101-105:
  • Step 101 Install data acquisition modules at different positions of the rock mass to be monitored, collect microseismic signals generated by rock mass rupture and instability, and use the long and short time window amplitude ratio method to pick up effective microseismic waveform data.
  • the data acquisition module is installed on the rock mass to be monitored, and the rock mass to be monitored is monitored in real time; first, the installation hole of the acceleration sensor is drilled on the surface of the rock mass to be monitored, and the diameter is slightly larger than the diameter of the acceleration sensor, and then Bury the acceleration sensor deeply into the installation hole, and use an appropriate couplant to embed the rock mass to be monitored and the acceleration sensor as a whole. Achieving direct contact of the sensor with the rock wall is excluded.
  • the acceleration sensor of the data acquisition module can convert the acceleration value of the microscopic vibration of the rock mass to is the voltage value, the conversion formula is shown in formula (1):
  • d represents the piezoelectric constant
  • m represents the mass of the piezoelectric element inside the acceleration sensor
  • C represents the capacitance at both ends of the piezoelectric element.
  • the acceleration sensor of the data acquisition module is connected with the A/D conversion unit of the data acquisition module using wires, and the analog signal output by the acceleration sensor is converted into a digital amplitude by the A/D conversion unit and transmitted to Data processing module for further processing.
  • the effective microseismic waveform data is picked up by using the long-short time window amplitude ratio method.
  • Fig. 2 is a specific flow chart of the method, including steps A1 to A10;
  • Fig. 3 is the effective microseismic data picked up by this method Waveform plot of wave data:
  • A1 Create microseismic data packet temporary storage queue, effective waveform temporary storage queue, short time window array and long time window array.
  • the maximum lengths of the short time window array and the long time window array are M and N respectively, preferably, M is set to 50, and N is set to 1000; the effective signal extraction threshold is set to R, preferably, R is set to 1.5.
  • A2 Initialize the long time window array.
  • the voltage amplitudes transmitted from the data acquisition module are read one by one, and these voltage amplitudes are stored in the long time window array in order, and when the number of elements in the long time window array reaches N, the initialization process ends.
  • A3 Fill the array of short time windows.
  • first clear all the elements of the short-time window array and then read the voltage amplitudes transmitted from the data acquisition module one by one, and store these voltage amplitudes in the short-time window array in order.
  • the elements of the short-time window array When the number reaches M, the process of filling the short-time window array ends.
  • A4 Calculate the ratio r of the average voltage amplitudes of the short time window array and the long time window array.
  • A5 Judging whether the ratio r is greater than the signal extraction threshold R, and jumping according to the judgment result.
  • step A6 it means that it is necessary to start picking up effective microseismic waveforms, and go to step A6; if r ⁇ R, it means that it is not necessary to pick up effective microseismic waveforms, and then go to step A3;
  • A6 Pick up effective microseismic waveform data.
  • the elements in the short-time window array are sequentially added to the tail of the effective waveform temporary storage queue, and then all elements in the short-time window array are cleared.
  • A7 Fill the array of short time windows.
  • A8 Calculate the ratio r of the average voltage amplitudes of the short time window array and the long time window array.
  • A9 Judging whether the ratio r is greater than or equal to R, and jumping according to the judgment result.
  • step A6 it means that the process of picking up valid microseismic waveform data is over, and go to step A6 A10.
  • A10 End the process of picking up valid microseismic waveform data.
  • step A3 add the elements in the short-time window array to the tail of the effective waveform temporary storage queue in order, obtain the current time stamp, pack all the elements and time stamps of the effective waveform temporary storage queue into a microseismic data packet, and It is placed at the end of the microseismic data packet temporary storage queue, indicating that a valid microseismic waveform data is currently picked up; then clear the valid waveform temporary storage queue, and then go to step A3 to start picking the next valid microseismic waveform data.
  • Step 102 Create a data sending buffer queue, extract microseismic feature vectors from valid microseismic waveform data, execute different compression strategies according to the microseismic feature vectors to obtain compressed data packets, place the compressed data packets at the end of the data sending buffer queue, and simultaneously send a A semaphore that compresses packet information.
  • the microseismic feature vector is extracted from the effective microseismic waveform data; first, a microseismic waveform data processing array is created; secondly, a microseismic data packet is taken out from the head of the microseismic data packet temporary storage queue; then , copy the effective microseismic waveform data element by element to the microseismic waveform data processing array; then, traverse from the first element of the microseismic waveform data processing array to the last element, and calculate the trigger position, end position, There are six eigenvalues of signal duration, rise time, maximum amplitude and position of maximum amplitude; finally, these six eigenvalues are composed of microseismic eigenvectors.
  • the trigger position in the microseismic feature vector represents the array subscript corresponding to the first amplitude greater than the threshold in the array;
  • the end position represents the array subscript corresponding to the minimum amplitude in the array;
  • the signal duration represents the end The difference between the position and the trigger position;
  • the maximum amplitude indicates the maximum amplitude among all the amplitudes of the array;
  • the position of the maximum amplitude indicates the array subscript corresponding to the maximum amplitude in the array;
  • the rise time indicates the position of the maximum amplitude and the trigger difference in position.
  • the maximum magnitude in the microseismic feature vector is greater than the set threshold V threshold , if it is greater than or equal to the threshold, it means that the effective microseismic waveform data needs to be sent to the cloud for backup at the same time, and the effective microseismic waveform data needs to be sent to the cloud for backup.
  • Data compression to adapt to NB-IOT low-bandwidth occasions First, all the floating-point numbers in the microseismic waveform data processing array are connected end-to-end with commas and written into a string, and then the gzip algorithm is used to compress the string to obtain a compressed string; then the Microseismic feature vectors, compressed strings and Boolean value flags are encoded into data in JSON format, and then the data in JSON format is compressed using the Hpack algorithm to obtain compressed data packets containing effective microseismic waveform data and microseismic feature vectors; The Boolean flag bit Flag, whose value is set to true, indicates that the compressed data contains valid microseismic waveform data and microseismic feature vectors;
  • the maximum magnitude of the microseismic feature vector is less than the set threshold V threshold , then there is no need to send valid microseismic waveform data to the cloud for backup, just send the microseismic feature vector to the cloud platform for storage; first set the microseismic feature vector and the Boolean flag Flag is encoded into a data packet in JSON format, and then the data packet in JSON format is compressed using the Hpack algorithm to obtain a compressed data packet that only contains the microseismic feature vector; the Boolean flag bit Flag, whose value is set to false, Indicates that the compressed data package only contains microseismic feature vectors.
  • Step 103 In order to prolong the working time of the NB-IOT module and meet the requirement of real-time transmission of microseismic data, use the dormancy wake-up algorithm to schedule the NB-IOT module.
  • FIG. 4 is a specific flow chart of the method, including steps B1 to B11:
  • B1 NB-IOT module initialization.
  • the dormancy wake-up control unit of the data processing module sends an activation AT command to the NB-IOT module through the serial port.
  • the overflow condition of the counter is that its value reaches C m ; and the overflow condition of the timer Timer is that its time reaches T m .
  • B3 Reset counters and timers.
  • the value of the counter Counter is set to 0; the time of the timer Timer is set to 0 seconds, and the time will be incremented by one second every second.
  • the dormancy wake-up control unit waits to receive a semaphore.
  • the Boolean value Flag is false, it means that a compressed data packet containing only the microseismic feature vector is generated, and the compressed data packet does not need to be sent to the cloud platform for analysis immediately, so the NB-IOT module will not be awakened temporarily at this time.
  • step B6 use the idea of batch processing to wait for the arrival of more compressed data packets containing only microseismic feature vectors, and then send the data to the cloud platform in a centralized manner, and then go to step B6; if the Boolean value Flag is true, it means that a message containing Compressed data packets of effective microseismic waveform data and microseismic feature vectors, the compressed data packets need to be sent to the cloud platform for analysis immediately, go to step B11.
  • B6 Increase the value of the counter by 1, and start the timer at the same time.
  • B7 The dormancy wake-up control unit waits to receive the semaphore.
  • step B11 if the Boolean flag bit Flag is true, go to step B11; if the Boolean flag bit Flag is false, go to step B9.
  • the value of the counter Counter is equal to C m or the time of the timer Timer is equal to T m , it means that the compressed data packets in the current data transmission buffer queue need to be sent to the cloud platform in batches, and go to step B11; otherwise, go to step B7.
  • B11 Wake up the NB-IOT module and execute the data sending process to send data.
  • the dormancy wake-up control unit sends a wake-up AT command to the NB-IOT module to wake up the NB-IOT module; then, executes the data sending process to extract compressed data packets from the data sending buffer queue one by one, and sends the compressed data packets To the cloud platform, when the data transmission buffer queue is empty, the sleep wakeup control unit sends a sleep AT command to the NB-IOT module to enter the sleep state; finally, enter step B3.
  • Step 104 When the NB-IOT module is in the wake-up state, establish a communication link with the cloud platform module, and send the compressed data packet to the cloud platform.
  • step 104 specifically includes sub-steps C1 and C2:
  • the dormant wake-up control unit sends an AT command to connect to the cloud platform to the NB-IOT module through the serial port.
  • the NB-IOT module receives the instruction, it will initiate a connection request based on the MQTT protocol to the cloud platform, and the cloud platform takes out the identity information and The key is verified, and if the verification is passed, a stable MQTT connection will be established with the NB-IOT module; finally, when the NB-IOT module establishes a communication link with the cloud platform, the data sending process can be started to send the data to the cloud platform;
  • C2 Take a compressed data packet from the head of the data sending buffer queue and send it to the communication link. After receiving the response data with the success flag returned by the cloud platform, it means that the cloud platform has successfully received the compressed data Then take out the next compressed data packet from the data sending buffer queue, and repeat the sending process until the data sending buffer queue is empty.
  • Step 105 The cloud platform receives the data packets sent by the NB-IOT module in real time, analyzes and warns them, and then saves the data in the database.
  • step 105 includes sub-steps D1 and D2:
  • the cloud platform starts monitoring the communication port. If it receives the handshake protocol packet from the NB-IOT module, it will authenticate its authentication information. If it passes, it will return a response packet with a successful flag and open the communication link. ;Otherwise, return the response data packet carrying the failure flag; when the communication link is opened, read the data packets sent by the NB-IOT module continuously, and put the data packet into the queue after each data packet is read Wait for processing and return to the NB-IOT module a response packet carrying a success flag;
  • D2 Continuously take out data packets from the queue, and analyze, warn and store each data packet
  • the cloud platform module sends an early warning message to the administrator's mobile phone.
  • the early warning information carries the effective microseismic waveform data and time stamp, Monitor the location of the rock mass, etc.; the early warning information is used to assist the administrator to make a judgment on the health status of the monitored rock mass.
  • Boolean flag bit Flag If the value of the Boolean flag bit Flag is false, it means that the compressed data package only has microseismic feature vectors, but does not contain valid microseismic waveform data, so the microseismic feature vectors can be saved in the database.
  • a NB-IOT-based method for wireless monitoring of rock mass rupture and instability microseismic signals has been introduced in detail above. This method can also be realized by a corresponding device. The structure and function of the device will be described in detail below.
  • An embodiment of the present invention provides a device for wireless monitoring of microseismic signals of rock mass rupture and instability based on NB-IOT, including:
  • the data acquisition module is used to obtain the microseismic signal produced by the rock mass rupture, and convert the microseismic signal into a digitized voltage signal that needs to be processed;
  • the data processing module is used to pick up the effective microseismic waveform data and extract the microseismic feature vector from it, which is used to realize the compression of the microseismic feature vector and the effective microseismic waveform data to meet the low bandwidth characteristics of NB-IOT, and also to realize the NB-IOT Scheduling between sleep and wake-up states of the IOT module;
  • the NB-IOT module is used to establish a communication link with the cloud platform module, and send the compressed data packet to the cloud platform module;
  • the cloud platform module is used to remotely connect and establish a communication link with the NB-IOT module, receive and store data from the NB-IOT module, analyze the data, and send early warning information if the early warning conditions are met;
  • the data acquisition module includes:
  • the acceleration sensor unit is used to collect microseismic signals generated by rock mass rupture and instability
  • an amplification circuit unit configured to amplify the microseismic signal collected by the acceleration sensor unit
  • An A/D conversion unit configured to convert the microseismic signal output by the amplifying circuit unit into a digitized voltage signal
  • the data processing module includes:
  • An effective waveform picking unit is used to extract effective microseismic waveform data from the data transmitted by the A/D conversion unit using the long and short time window amplitude ratio method;
  • a feature extraction unit is used to extract a microseismic feature vector from effective microseismic waveform data
  • the data compression unit is used to compress the microseismic eigenvector and effective microseismic waveform data, and reduce the storage space occupied by it so that data transmission can be performed in the narrow bandwidth environment of NB-IOT;
  • the sleep wake-up control unit is used to schedule the NB-IOT module using the sleep wake-up algorithm, so that it is woken up when it needs to send data, and sleeps when it does not need to send data, so as to save power and extend the working time of the NB-IOT module.
  • the embodiment of the present invention provides a hardware implementation circuit of a wireless monitoring device for rock mass rupture and instability microseismic signals based on NB-IOT.
  • the circuit implements the data acquisition module, data processing module and NB-IOT wireless transmission module. Please See Figure 5, specifically:
  • the data acquisition module includes a microseismic sensor SENSOR1, its VCC pin is connected to the power supply, the GND pin is grounded, the signal output terminal OUT is connected to one end of the capacitor C1, the other end of the capacitor C1 is connected to one end of the resistor R1, and the other end of the resistor R1 is connected to the terminal of the capacitor C1.
  • One end of the resistor R2 is connected to the same input end of the operational amplifier AR1, the other end of the resistor R2 is connected to one end of the capacitor C2, the other end of the capacitor C2 is connected to the power supply, and one end of the resistor R3 and the resistor R4 are connected to the op amp.
  • the inverting input terminal of the amplifier AR1 is connected to the ground, the other end of the resistor R4 is connected to the output terminal of the operational amplifier, the resistor R5 is connected to the output terminal of the operational amplifier AR1, and the other end of the resistor R5 is connected to the operational amplifier AR2
  • the non-inverting input terminal of the operational amplifier AR2 is connected to its output terminal, the output terminal of the operational amplifier AR2 is connected to the IN0 pin of the A/D conversion unit;
  • the output terminal of the OR gate NOR1 is connected to the OE pin of ADC1 , the output terminal of NOR gate NOR2 is connected to the START pin and ALE pin of ADC1, the VCC pin and VREF(+) pin of ADC1 are connected to the power supply, and the GND pin and VREF(-) pin of ADC1 are grounded.
  • the A/D conversion unit can use an ADC0809 chip.
  • the data processing module includes a microprocessor MCU1, its VCC pin is connected to the power supply, the GND pin is grounded, and the PC0 to PC7 pins of the MCU1 are respectively connected to the 2-1 to 2-8 pins of the A/D conversion unit ADC1.
  • the PB0 pin of MCU1 is connected to one input end of the NOR gate NOR1 of ADC1
  • the PB1 pin of MCU1 is connected to the other input end of the NOR gate NOR1 of ADC1
  • the PB2 pin of MCU1 is connected to the NOR gate of ADC1
  • An input terminal of NOR2 the PB3 pin, PB4 pin and PB5 pin of MCU1 are respectively connected to the ADDA pin, ADDB pin and ADDC pin of ADC1
  • the PB6 pin of MCU1 is connected to the CLOCK pin of ADC1
  • the PB7 pin is connected to the EOC pin of ADC1.
  • the microprocessor MCU1 can use a chip of the STM32F1 series.
  • the NB-IOT module includes NB-IOT communication module NB1, the VBAT pin of NB1 is connected to one end of capacitor C3, the GND pin of NB1 is connected to the other end of capacitor C3, capacitor C4, capacitor C5, and Zener diode D1 and capacitor C3
  • one end of the Zener diode D1 is connected to the power supply, and the other end of the Zener diode is grounded
  • the RESET pin of NB1 is connected to one end of the Zener diode D2, and the other end of the Zener diode D2 is grounded, and the RESET pin of NB1 is also connected to the button
  • One end of the switch KEY1, the other end of the key switch KEY1 is grounded
  • the SIM_GND pin of NB1 is connected to one end of capacitor C6, the other end of capacitor C6 is connected to the VCC pin of the SIM card connector SCC, and the SIM_GND pin of NB1 is also connected to the SIM card
  • each unit in each embodiment of the present application may be integrated into a module, or a unit may physically exist separately, or two or more units may be integrated into a module.
  • the above-mentioned integrated modules can be implemented in the form of hardware or in the form of software function modules. If the integrated modules are implemented in the form of software function modules and sold or used as independent products, they can also be stored in a computer-readable storage medium.

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Abstract

一种基于NB‑IOT的岩体破裂失稳微震信号无线监测方法与装置，属于地质灾害防治技术领域，监测方法包括：采集岩体破裂产生的微震信号，使用长短时窗幅值比值法拾取有效微震波形数据（101），从有效微震波形数据中提取微震特征向量，根据微震特征向量执行不同的压缩策略得到压缩数据包（102），使用休眠唤醒算法对NB‑IOT模块进行调度，在需要发送数据的时候唤醒，而无需发送数据时进行休眠（103）；在NB‑IOT模块处于唤醒状态时，将数据包发送至云平台（104），云平台对所接收的数据包进行分析，若满足预警条件则发出预警信息（105）。结合NB‑IOT技术解决岩体破裂失稳微震信号无线监测的数据远距离传输问题，同时也延长NB‑IOT模块工作时间，对于地质防灾减灾具有重要的实用价值。

Description

一种基于NB-IOT的岩体破裂失稳微震信号无线监测方法与装置 技术领域
本发明涉及地质灾害防治技术领域，尤其涉及一种基于NB-IOT的岩体破裂失稳微震信号无线监测方法与装置。
背景技术
危岩失稳崩塌具有较高的突发性和较强的破坏性，强大的冲击力直接引起下方建筑物的垮塌、破坏，严重影响公路、铁路交通的正常运营，造成巨大的财产损失，而且近些年，频发旅游景区危岩崩塌和工程施工现场人员伤亡事件，对人民群众的生命造成了严重的威胁。微震(Microseism,MS)是频率小于100赫兹的低频声信号，是岩体在受到外界扰动应力及温度等因素的影响下，岩体内部出现应力集中，引起岩体微观裂隙的产生、扩展、贯通过程中伴随的低能量的弹性波或应力波。同时，在失稳崩塌演变的过程中，无论是从塌方演变初期——微裂纹发育阶段，还是后期——宏观破裂阶段，均包含着丰富的低频段微震弹性波，微震信号监测设备能够有效探测到其弹性波的大小及发生部位，并通过对危岩体破裂微震信号进行分析，揭示塌方发生的可能性及破坏剧烈程度，采取有效的防治或提前规避手段降低其所造成危害大小。到目前为止，微震监测技术已经成为了众多演示工程灾害监测和预报的重要手段，如煤矿的开采、水电站的建设、公路旁危岩体的监测等场景。传统的微震监测技术，主要采用有线的方式，传感器需要和采集仪等设备使用线缆连接起来，采集仪和服务器之间也主要通过有线光缆进行传输，这对一些较为偏远的工程实际来说，不仅需要架设电缆，还需要架设通讯光缆，使其使用代价较大。而传统的无线微震监测方式，不仅受限于无线通讯技术速率和延迟，无法做到实时传输和检测；同时也由于无线传输设备的功耗过大而导致工作时间过短不利于在室外环境使用。
NB-IOT(Narrow Band Internet of Things)是物联网领域一种新兴的技术，支持低功耗设备在广域网的蜂窝数据连接，也被称作低功耗广域网(LPWAN)。相比起其他不同的物联网无线传输技术如LoRa、ZigBee等，其优点在于可直接部署于GSM网络、UMTS网络或LTE网络，能实现平滑升级，因此其具有覆盖范围广阔的优点，在野外、山区等地方均能被覆盖到；NB-IOT具有低功耗的优点，特别适合于一些不能经常更换电池的场合，如安置于高山荒野偏远地区；此外，NB-IOT还具有低成本的优点，有利于在生产环境中大规模应用。
然而，现有的NB-IOT技术结合到岩体破裂微震信号无线监测这一具体的任务上，尚未形成一个有效的解决方案，尚存在诸多待解决的问题。首当其冲的是通信模块的功耗问题，由于其安装在偏远的野外地区，经常更换电池是不切实际的做法，只能选用低功耗的通信模块。然而对于微震信号传输这一任务来说，区别于传统的物联网应用的低频率数据传输场景，其数据传输的频率呈现了短时高频率的特点，这给通信模块的长时间工作带来了不小的挑战。除此之外，岩体破裂时产生的微震信号复杂多样，存在一些值得进一步分析的微震信号，如何将有分析价值的微震信号传输到云平台也是一个具有现实意义的问题。由于NB-IOT的窄带宽的特点，其在发送容量较大的数据包的时候存在延迟较高、阻塞信道 甚至发送失败的现象。
发明内容
本发明的目的在于提供一种基于NB-IOT的岩体破裂失稳微震信号无线监测方法与装置，解决现有岩体破裂失稳微震信号有线监测方案中因通讯线缆导致使用场合受限的技术问题。以及现有无线传输装置因功耗过高而导致无法安装在偏远地区的问题。实现了将岩体破裂失稳产生的微震信号通过NB-IOT技术远程地发送到云端，确保了信号发送的及时性同时延长了NB-IOT模块的工作时间。
为了实现上述目的，本发明采用的技术方案如下：
一种基于NB-IOT的岩体破裂失稳微震信号无线监测方法，所述方法包括如下步骤：
步骤1：在待监测岩体上安装一个或者一个以上的数据采集模块，采集岩体破裂产生的微震信号，使用长短时窗幅值比值法拾取有效微震波形数据；
步骤2：创建数据发送缓冲队列，从有效微震波形数据中提取微震特征向量，根据微震特征向量执行不同的压缩策略得到压缩数据包，将压缩数据包放置于数据发送缓冲队列尾部，同时发出一个携带了压缩数据包信息的信号量；
步骤3：使用休眠唤醒算法对NB-IOT模块进行调度，使其在需要发送数据的时候被唤醒，而不需要发送数据的时候进行休眠，节省电量以延长工作时间；
步骤4：当NB-IOT模块处于唤醒状态时，与云平台模块建立通信链路，将所述的压缩数据包发送至云平台模块；
步骤5：云平台模块对接收到的数据包进行分析，若满足预警条件则发出预警信息。
进一步地，步骤1中，采集岩体破裂产生的微震信号的具体过程为：
步骤1.1.1：当岩体产生微观裂隙时会释放出低能量的弹性波并向四周传播，引发岩体的微小震动，数据采集模块的加速度传感器能够将岩体微小震动的加速度值转换为电压值得到微震信号，转换公式如式子(1)所示：
Figure PCTCN2022095165-appb-000001
式中，d表示压电常数，m表示加速度传感器内部压电元件的质量，C表示压电元件两端的电容，在加速度传感器型号确定的情况下其d、m和C均为确定常量，因此电压值V与加速度a成正比，所采集的微震信号的电压值越大，表示岩体震动的加速度越大；
步骤1.1.2：使用所述数据采集模块的A/D转换单元将加速度传感器输出的模拟信号转换为数字化的幅值并传输至数据处理模块作进一步处理。
进一步地，步骤1中，使用长短时窗幅值比值法拾取有效微震波形数据的具体过程为：
步骤1.2.1：创建微震数据包暂存队列、有效波形暂存队列、短时窗数组和长时窗数组，所述的短时窗数组和长时窗数组的最大长度分别为M和N，设有效信号提取阈值为R；所述的M、N和R根据监测现场环境决定；
步骤1.2.2：初始化长时窗数组，逐个读取从所述数据采集模块传输过来的幅值， 将其按顺序保存于长时窗数组内，直至长时窗数组的元素个数达到N；
步骤1.2.3：逐个读取从所述数据采集模块传输过来的幅值，将其按顺序保存于短时窗数组内，当短时窗数组内的元素达到M时，分别计算短时窗数组和长时窗数组内的平均电压幅值Amplitude 1和Amplitude 2，接着将长时窗数组的元素整体往前搬移M个位置，将短时窗数组内的元素依次添加到长时窗数组末尾的M个位置上，然后求得Amplitude 1和Amplitude 2的比值r＝Amplitude 1/Amplitude 2，若r大于等于R则表示开始拾取有效微震波形数据，接着转步骤1.2.4：；否则，清空短时窗数组内的元素并重复执行步骤1.2.3；
步骤1.2.4：将短时窗数组内的元素依次添加到有效波形暂存队列尾部中；接着清空短时窗数组内的元素，然后继续逐个读取从所述数据采集模块传输过来的幅值，当短时窗数组内的元素达到M后，分别计算短时窗数组和长时窗数组的平均电压幅值Amplitude 1和Amplitude 2并求得二者的比值r＝Amplitude 1/Amplitude 2，若r小于R则表示结束拾取有效的微震波形数据，转步骤1.2.5，否则，将长时窗数组的元素整体往前搬移M个位置，将短时窗数组内的元素依次添加到长时窗数组末尾的M个位置上，重复执行步骤1.2.4；
步骤1.2.5：将短时窗数组内的元素按顺序添加到有效波形暂存队列尾部中，获取当前的时间戳，将有效波形暂存队列的所有元素和时间戳打包成一个微震数据包，并将其放置于微震数据包暂存队列尾部，表示当前拾取了一个有效微震波形数据，接着清空有效波形暂存队列，然后重复执行步骤1.2.3，开始拾取下一个有效微震波形数据。
进一步地，步骤2中，从有效微震波形数据中提取微震特征向量的具体过程为：
创建一个微震波形数据处理数组，从所述的微震数据包暂存队列的头部中取出一个微震数据包，将其中的有效微震波形数据逐元素复制到微震波形数据处理数组中；从微震波形数据处理数组的第一个元素开始遍历，到最后一个元素结束遍历，计算得到触发位置、结束位置、信号持续时间、上升时间、最大幅值和最大幅值的位置共六个特征值，将这六个特征值组成微震特征向量，六个特征值的具体定义为：
触发位置：表示数组中第一个大于阈值的幅值对应的数组下标；
结束位置：表示数组中最小幅值对应的数组下标；
信号持续时间：表示结束位置与触发位置的差值；
最大幅值：表示数组所有幅值中最大的幅值；
最大幅值的位置：表示数组中最大幅值所对应的数组下标；
上升时间：表示最大幅值的位置与触发位置的差值。
进一步地，步骤2中，根据微震特征向量执行不同的压缩策略得到压缩数据包的具体过程为：
若所述微震特征向量的最大幅值大于或等于设定的阈值V threshold，则表示需要将有效微震波形数据发送至云平台备份，将有效微震波形数据进行压缩以适应NB-IOT低带宽的场合，首先将微震波形数据处理数组的所有浮点数以逗号分隔首尾相连写成字符串，其次采用gzip算法对该字符串进行压缩得到压缩字符串；接着将微震特征向量、压缩字符串和布尔值标志位Flag编码成JSON格式的数据，然后用Hpack算法对其进行压缩得到压缩数据包；所述的布尔值标志位Flag，其值被设置为真，表示该压缩数据包含有有效微震波形数据和微震特征向量；
若所述微震特征向量中的最大幅值小于设定的阈值V threshold，则表示无需发送有 效微震波形数据到云平台备份，只需发送微震特征向量到云平台保存；首先将微震特征向量和布尔值标志位Flag编码成JSON格式的数据，然后使用Hpack算法对其进行压缩得到压缩数据包；所述的布尔值标志位Flag，其值被设置为假，表示该压缩数据包仅含有微震特征向量。
进一步地，步骤3中，使用休眠唤醒算法对NB-IOT模块进行调度的具体过程为：
步骤3.1：系统初始化时，所述数据处理模块的休眠唤醒控制单元向NB-IOT模块按顺序发送激活AT指令、注网AT指令和休眠AT指令，使NB-IOT模块在被激活后进行注网操作，随后切换至低功耗模式，进入休眠状态；
步骤3.2：创建一个计数器Counter和一个计时器Timer，所述计数器Counter的溢出条件是其数值达到C m，所述的计时器Timer的溢出条件是其时间达到T m；
步骤3.3：重置计数器Counter和计时器Timer；休眠唤醒控制单元等待接收信号量，当其首次接收到信号量时，若信号量的布尔值标志位Flag为假，则计数器Counter的数值加1，且计时器Timer同步开启，然后进入步骤3.4，否则，进入步骤3.5；
步骤3.4：休眠唤醒控制单元继续等待接收信号量，每次接收到信号量时，若信号量的布尔值标志位Flag为真，则进入步骤3.5，否则，计数器Counter的数值加1，若计数器Counter满足溢出条件或计时器Timer满足溢出条件时，进入步骤3.5；否则重复执行步骤3.4；
步骤3.5：首先，所述休眠唤醒控制单元向NB-IOT模块发送唤醒AT指令以唤醒NB-IOT模块，接着，执行数据发送流程从数据发送缓冲队列中逐个取出压缩数据包，并发送压缩数据包到云平台，当数据发送缓冲队列为空时，所述休眠唤醒控制单元向NB-IOT模块发送休眠AT指令使其进入休眠状态，最后，进入步骤3.3。
一种基于NB-IOT的岩体破裂失稳微震信号无线监测装置，包括一个或者一个以上的数据采集模块、数据处理模块、NB-IOT模块和云平台模块，一个或者一个以上的数据采集模块与数据处理模块有线或者无线连接，数据处理模块经NB-IOT模块与云平台模块无线连接；
一个或者一个以上的数据采集模块用于获取岩体破裂所产生的微震信号，并将所述的微震信号转换成需要处理的数字化的电压信号，数据处理模块用于拾取有效微震波形数据，并从中提取微震特征向量，对微震特征向量和有效微震波形数据的压缩以满足NB-IOT低带宽的特点，同时对NB-IOT模块的休眠和唤醒状态之间的调度，NB-IOT模块用于实现与云平台模块建立通信链路，将压缩数据包发送至云平台模块，云平台模块用于与NB-IOT模块进行远程连接并建立通信链路，接收并存储来自所述的NB-IOT模块的数据，对数据进行分析，若满足预警条件则发送预警信息。
进一步地，数据采集模块包括加速度传感器单元、放大电路单元和A/D转换单元，加速度传感器单元经放大电路单元与A/D转换单元连接，加速度传感器单元用于采集岩体破裂失稳产生的微震信号，放大电路单元用于将所述加速度传感器单元采集到的微震信号进行放大，A/D转换单元用于将所述放大电路单元输出的微震信号转换为数字化的电压信号。
进一步地，数据处理模块包括有效波形拾取单元、特征提取单元、数据压缩单元和休眠唤醒控制单元，有效波形拾取单元的输入端与A/D转换单元连接，有效波形拾取单元的 输出端与特征提取单元连接，特征提取单元的输出端与数据压缩单元连接，休眠唤醒控制单元与NB-IOT模块连接；
有效波形拾取单元用于使用长短时窗幅值比值法从所述A/D转换单元传输过来的数据中提取有效微震波形数据，特征提取单元用于从有效微震波形数据中提取微震特征向量，数据压缩单元用于压缩微震特征向量和有效微震波形数据，减少其所占的存储空间以便能够在NB-IOT的窄带宽环境下进行数据传输，休眠唤醒控制单元用于使用休眠唤醒算法对所述NB-IOT模块进行调度，使其在需要发送数据时被唤醒，而无需发送数据时休眠，节省电量以延长NB-IOT模块的工作时间。
本发明由于采用了上述技术方案，具有以下有益效果：
(1)本发明结合NB-IOT技术构建一个用于岩体破裂微震信号无线监测方法及装置，充分发挥NB-IOT技术的低成本、广覆盖、低功耗的优势来弥补现有微震信号监测系统工作时间过短、通信效率低下以及难以远距离传输的缺点，克服传统有线监测方式使用场景受限的难题和传统无线监测方式通讯效率低、延迟高且无法做到实时监测的难题，实现了微震监测数据的高效传输和实时监测。
(2)本发明提出的NB-IOT模块休眠唤醒算法，进一步延长了NB-IOT模块的工作时长，尤其适用于微震信号的短时高频率发送的场景，使得NB-IOT模块能够安装在偏远的山区地方而不用时常更换电池。
(3)本发明提出的微震数据压缩方法，使得压缩后的微震数据能够在NB-IOT的窄带宽环境下传输到云平台中，这有助于保存与岩体破裂失稳相关的、有分析价值的微震数据，为微震数据的后续处理和分析创造条件。
附图说明
图1是本发明实施例中基于NB-IOT的岩体破裂微震信号无线监测方法的流程图；
图2是本发明实施例中使用长短时窗幅值比值法拾取有效微震波形数据的流程图；
图3是本发明实施例中使用长短时窗幅值比值法拾取的有效微震波形数据的波形图；
图4是本发明实施例中使用休眠唤醒算法对NB-IOT模块进行调度的流程图；
图5是本发明实施例中的基于NB-IOT的岩体破裂微震信号无线监测装置的实现电路原理图。
具体实施方式
为使本发明的目的、技术方案及优点更加清楚明白，以下参照附图并举出优选实施例，对本发明进一步详细说明。然而，需要说明的是，说明书中列出的许多细节仅仅是为了使读者对本发明的一个或多个方面有一个透彻的理解，即便没有这些特定的细节也可以实现本发明的这些方面。
如图1-4所示，一种基于NB-IOT的岩体破裂失稳微震信号无线监测方法，图1为该方法的流程图，具体包括步骤101-105：
步骤101：在待监测的岩体不同位置安装数据采集模块，采集由岩体破裂失稳而产 生的微震信号，使用长短时窗幅值比值法拾取有效微震波形数据。
在本发明实施例中，在待监测的岩体上安装数据采集模块，对待监测岩体进行实时监测；首先在待监测岩体表面钻出加速度传感器的安装孔，直径略大于加速度传感器直径，然后将加速度传感器深埋入安装孔内，并采用适当的耦合剂将待监测岩体与加速度传感器嵌为一体，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。
在本发明实施例中，当岩体产生微观裂隙时会释放出低能量的弹性波并向四周传播，引发岩体的微小震动，数据采集模块的加速度传感器能够将岩体微小震动的加速度值转换为电压值，转换公式如式子(1)所示：
Figure PCTCN2022095165-appb-000002
式中，d表示压电常数，m表示加速度传感器内部压电元件的质量，C表示压电元件两端的电容，在加速度传感器型号确定的情况下其d、m和C均为确定常量，因此电压值V与加速度a成正比，所采集的微震信号的电压值越大，表示岩体震动的加速度越大。
在本发明实施例中，数据采集模块的加速度传感器与数据采集模块的A/D转换单元使用导线相连接，使用A/D转换单元将加速度传感器输出的模拟信号转换为数字化的幅值并传输至数据处理模块作进一步处理。
在本发明实施例中，使用长短时窗幅值比值法拾取有效微震波形数据，具体地，图2为该方法的具体流程图，包括步骤A1～A10；图3为使用该方法拾取的有效微震波形数据的波形图：
A1：创建微震数据包暂存队列、有效波形暂存队列、短时窗数组和长时窗数组。
具体的，短时窗数组和长时窗数组的最大长度分别为M和N，优选的，M取为50，N取为1000；设有效信号提取阈值为R，优选的，R设置为1.5。
A2：初始化长时窗数组。
具体的，逐个读取从数据采集模块传输过来的电压幅值，将这些电压幅值按顺序保存在长时窗数组内，当长时窗数组的元素的个数达到N时，结束初始化过程。
A3：填充短时窗数组。
具体的，首先清空短时窗数组的所有元素，然后逐个读取从数据采集模块传输过来的电压幅值，将这些电压幅值按顺序保存在短时窗数组内，当短时窗数组的元素个数达到M时，结束填充短时窗数组的过程。
A4：计算短时窗数组和长时窗数组的平均电压幅值的比值r。
具体的，累加短时窗数组所有元素的值，然后除以M，得到短时窗数组的平均电压幅值Amplitude 1；累加长时窗数组所有元素的值，然后除以N，得到长时窗数组的平均电压幅值Amplitude 2；将长时窗数组的所有元素整体往前搬移M个位置，将短时窗数组内的元素依次添加到长时窗数组末尾的M个位置上；然后求得Amplitude 1和Amplitude 2的比值r＝Amplitude 1/Amplitude 2。
A5：判断比值r是否大于信号提取阈值R，并根据判断结果进行跳转。
具体的，若r≥R，则表示需要开始拾取有效微震波形，转步骤A6；若r＜R，则表示不需要拾取有效微震波形，转步骤A3；
A6：拾取有效微震波形数据。
具体的，将短时窗数组内的元素依次添加到有效波形暂存队列尾部，然后清空短时窗数组内的所有元素。
A7：填充短时窗数组。
具体的，逐个读取从数据采集模块传输过来的电压幅值，将这些电压幅值按顺序添加到短时窗数组内，当短时窗数组的元素达到M后，停止填充短时窗数组的流程。
A8：计算短时窗数组和长时窗数组的平均电压幅值的比值r。
具体的，累加短时窗数组所有元素的值，然后除以M，得到短时窗数组的平均电压幅值Amplitude 1；累加长时窗数组所有元素的值，然后除以N，得到长时窗数组的平均电压幅值Amplitude 2；将长时窗数组的所有元素整体往前搬移M个位置，将短时窗数组内的元素依次添加到长时窗数组末尾的M个位置上；然后求得Amplitude 1和Amplitude 2的比值r＝Amplitude 1/Amplitude 2。
A9：判断比值r是否大于等于R，并根据判断结果进行跳转。
具体的，若r≥R，则表示当前的微震波形仍属于有效波形，需要继续保持有效波形的拾取流程，转步骤A6；若r＜R，则表示结束拾取有效微震波形数据的流程，转步骤A10。
A10：结束拾取有效微震波形数据的流程。
具体的，将短时窗数组内的元素按顺序添加到有效波形暂存队列尾部中，获取当前的时间戳，将有效波形暂存队列的所有元素和时间戳打包成一个微震数据包，并将其放置于微震数据包暂存队列尾部，表示当前拾取了一个有效微震波形数据；接着清空有效波形暂存队列，然后转步骤A3开始拾取下一个有效微震波形数据。
步骤102：创建数据发送缓冲队列，从有效微震波形数据中提取微震特征向量，根据微震特征向量执行不同的压缩策略得到压缩数据包，将压缩数据包放置于数据发送缓冲队列尾部，同时发出一个携带了压缩数据包信息的信号量。
在本发明实施例中，从有效微震波形数据中提取微震特征向量；首先，创建一个微震波形数据处理数组；其次，从所述的微震数据包暂存队列的头部取出一个微震数据包；接着，将其中的有效微震波形数据逐元素复制到微震波形数据处理数组中；然后，从微震波形数据处理数组的第一个元素开始遍历，到最后一个元素结束遍历，计算得到触发位置、结束位置、信号持续时间、上升时间、最大幅值和最大幅值的位置共六个特征值；最后，将这六个特征值组成微震特征向量。
在本发明实施例中，微震特征向量中的触发位置表示数组中第一个大于阈值的幅值对应的数组下标；结束位置表示数组中最小幅值对应的数组下标；信号持续时间表示结束位置与触发位置的差值；最大幅值表示数组所有幅值中最大的幅值；最大幅值的位置表示数组中最大幅值所对应的数组下标；上升时间表示最大幅值的位置与触发位置的差值。
在本发明实施例中，判断微震特征向量中的最大幅值是否大于设定的阈值V threshold，如果大于或等于该阈值，则表示同时需要将有效微震波形数据发送至云端备份，将有效微震波形数据进行压缩以适应NB-IOT低带宽的场合：首先将微震波形数据处理数组的所有浮点数以逗号相隔首尾相连写成字符串，其次采用gzip算法对该字符串进行压缩得到压缩字符串；接着将微震特征向量、压缩字符串和布尔值标志位Flag编码成JSON格式的数据，然后采用Hpack算法对该JSON格式的数据进行压缩，得到含有有效微震波形数据和微 震特征向量的压缩数据包；所述的布尔值标志位Flag，其值被设置为真，表示该压缩数据包含有有效微震波形数据和微震特征向量；
如果微震特征向量中的最大幅值小于设定的阈值V threshold，那么就无需发送有效微震波形数据到云端备份，只需发送微震特征向量到云平台保存；首先将微震特征向量和布尔值标志位Flag编码成JSON格式的数据包，然后使用Hpack算法对该JSON格式的数据包进行压缩，得到仅含有微震特征向量的压缩数据包；所述的布尔值标志位Flag，其值被设置为假，表示该压缩数据包仅含有微震特征向量。
步骤103：为了延长NB-IOT模块的工作时间并且能够满足实时发送微震数据的需求，使用休眠唤醒算法对NB-IOT模块进行调度。
在本发明实施例中，使用休眠唤醒算法对NB-IOT模块进行调度，具体地，图4为该方法的具体流程图，包括步骤B1～B11：
B1：NB-IOT模块初始化。
具体的，数据处理模块的休眠唤醒控制单元通过串口向NB-IOT模块发送激活AT指令，该AT指令的形式为：“AT+SM＝LOCK”；接着发送注网AT指令，该AT指令的形式为：“AT+CEREG＝1”；然后发送休眠AT指令，该AT指令的形式为：“AT+CFUN＝0”。
B2：分别创建一个计数器Counter和一个计时器Timer。
具体的，计数器Counter的溢出条件是其数值达到C m；而计时器Timer的溢出条件是其时间达到T m。
B3：重置计数器和计时器。
具体的，计数器Counter的数值设置为0；计时器Timer的时间设置为0秒，每过一秒，时间都会自增一秒。
B4：休眠唤醒控制单元等待接收信号量。
B5：判断信号量的布尔值标志位Flag是否为真，并根据判断结果进行跳转。
具体的，若布尔值标志位Flag为假，说明产生了一个仅含有微震特征向量的压缩数据包，该压缩数据包没有必要马上发送到云平台分析，所以此时暂时不唤醒NB-IOT模块，而是利用批处理的思想来等待更多的仅含有微震特征向量的压缩数据包的到来，再集中发送数据到云平台，转步骤B6；若布尔值标志位Flag为真，说明产生了一个包含有效微震波形数据和微震特征向量的压缩数据包，该压缩数据包需要马上发送至云平台进行分析，转步骤B11。
B6：计数器的数值加1，同时开启计时器。
B7：休眠唤醒控制单元等待接收信号量。
B8：判断信号量的布尔值标志位Flag是否为真，并根据判断结果进行跳转。
具体的，若布尔值标志位Flag为真，则转步骤B11；若布尔值标志位Flag为假，转步骤B9。
B9：计数器的数值加1。
B10：判断计数器是否满足溢出条件或计时器是否满足溢出条件，并根据判断结果进行跳转。
具体的，若计数器Counter的数值等于C m或计时器Timer的时间等于T m，则表示需要批量发送目前数据发送缓冲队列存在的压缩数据包到云平台，转步骤B11；否则，转步骤B7。
B11：唤醒NB-IOT模块，执行数据发送流程来发送数据。
具体的，首先，所述休眠唤醒控制单元向NB-IOT模块发送唤醒AT指令以唤醒NB-IOT模块；接着，执行数据发送流程从数据发送缓冲队列中逐个取出压缩数据包，并发送压缩数据包到云平台，当数据发送缓冲队列为空时，所述休眠唤醒控制单元向NB-IOT模块发送休眠AT指令使其进入休眠状态；最后，进入步骤B3。
步骤104：在NB-IOT模块处于唤醒状态时，与云平台模块建立通信链路，将所述压缩数据包发送至云平台。
在本发明实施例中，步骤104具体包括了子步骤C1和C2：
C1：休眠唤醒控制单元通过串口向NB-IOT模块发送连接云平台AT指令，该指令为“AT+QMTOPEN＝0,"iot-as-mqtt.cn-shanghai.aliyuncs.com",1883”，指令包含了云平台的网络域名和端口号；其次，当NB-IOT模块接收到该指令后，会向云平台发起一个基于MQTT协议的连接请求，云平台从请求中取出NB-IOT的身份信息和密钥进行验证，若验证通过则会与NB-IOT模块建立一个稳定的MQTT连接；最后，当NB-IOT模块与云平台建立通信链路后，便可以开始执行数据发送流程将数据发送到云平台；
C2：从数据发送缓冲队列的头部取出一个压缩数据包，将其发送至通信链路中，当接收到云平台返回的携带成功标志位的响应数据后，表示云平台已经成功接收到压缩数据包；然后从数据发送缓冲队列内取出下一份压缩数据包，重复发送过程，直至数据发送缓冲队列为空。
步骤105：云平台实时接收NB-IOT模块发送的数据包，对其进行分析预警操作，然后将数据保存到数据库中。
在本发明实施例中，步骤105包括子步骤D1和D2：
D1：云平台开启通信端口监听，若接收到来自NB-IOT模块的握手协议数据包，则对其鉴权信息进行鉴权，若通过则返回携带成功标志位的响应数据包并打开通信链路；否则，返回携带失败标志位的响应数据包；当通信链路打开后，连续地读取由NB-IOT模块发送过来的数据包，每读取到一个数据包后，将数据包放进队列中等待处理并向NB-IOT模块返回携带成功标志位的响应数据包；
D2：连续地从队列中取出数据包，并对每一个数据包进行分析、预警和存储操作；
首先，使用Hpack算法解压缩得到布尔值标志位Flag和微震特征向量；读取布尔值标志位Flag，若其值为真，说明解压缩还会得到压缩字符串，对其使用gzip算法解压缩得到有效微震波形数据；将微震特征向量和有效微震波形数据都保存到数据库中，同时云平台模块发出一个预警信息推送到管理员的手机中，该预警信息携带了该有效微震波形数据及时间戳、监测岩体所在的位置等；该预警信息用于辅助管理员对监测岩体的健康状态做出判断。
若布尔值标志位Flag的值为假，说明该压缩数据包只有微震特征向量，而不含有有效微震波形数据，因此将有微震特征向量保存到数据库中即可。
以上详细介绍了一种基于NB-IOT的岩体破裂失稳微震信号无线监测的方法流程，该方法也可以通过相应的装置实现，下面详细介绍该装置的结构和功能。
本发明实施例提供一种基于NB-IOT的岩体破裂失稳微震信号无线监测的装置，包括：
数据采集模块，用于获取岩体破裂所产生的微震信号，并将所述的微震信号转换成需要处理的数字化的电压信号；
数据处理模块，用于拾取有效微震波形数据，并从中提取微震特征向量，用于实现对微震特征向量和有效微震波形数据的压缩以满足NB-IOT低带宽的特点，还用于实现对NB-IOT模块的休眠和唤醒状态之间的调度；
NB-IOT模块，用于实现与云平台模块建立通信链路，将压缩数据包发送至云平台模块；
云平台模块，用于与NB-IOT模块进行远程连接并建立通信链路，接收并存储来自所述的NB-IOT模块的数据，对数据进行分析，若满足预警条件则发送预警信息；
在本发明实施例中，所述数据采集模块包括：
加速度传感器单元，用于采集岩体破裂失稳产生的微震信号；
放大电路单元，用于将所述加速度传感器单元采集到的微震信号进行放大；
A/D转换单元，用于将所述放大电路单元输出的微震信号转换为数字化的电压信号；
在本发明实施例中，所述数据处理模块包括：
有效波形拾取单元，用于使用长短时窗幅值比值法从所述A/D转换单元传输过来的数据中提取有效微震波形数据；
特征提取单元，用于从有效微震波形数据中提取微震特征向量；
数据压缩单元，用于压缩微震特征向量和有效微震波形数据，减少其所占的存储空间以便能够在NB-IOT的窄带宽环境下进行数据传输；
休眠唤醒控制单元，用于使用休眠唤醒算法对所述NB-IOT模块进行调度，使其在需要发送数据时被唤醒，而无需发送数据时休眠，节省电量以延长NB-IOT模块的工作时间。
本发明实施例提供一种基于NB-IOT的岩体破裂失稳微震信号无线监测装置的硬件实现电路，该电路实现了所述的数据采集模块、数据处理模块和NB-IOT无线传输模块，请参见图5，具体为：
所述数据采集模块包括微震传感器SENSOR1，其VCC引脚接电源，GND引脚接地，信号输出端OUT接电容C1的一端，电容C1的另一端接电阻R1的一端，电阻R1的另一端接运放器AR1的同相输入端，电阻R2的一端接运放器AR1的同相输入端，电阻R2的另一端接电容C2的一端，电容C2的另一端接电源，电阻R3和电阻R4的一端接运放器AR1的反相输入端，电阻R3的另一端接地，电阻R4的另一端接运放器的输出端，电阻R5接运放器AR1的输出端，电阻R5的另一端接运放器AR2的同相输入端，运放器AR2的反相输入端接其输出端，运放器AR2的输出端接A/D转换单元的IN0引脚；或非门NOR1的输出端接ADC1的OE引脚，或非门NOR2的输出端接ADC1的START引脚和ALE引脚，ADC1的VCC引脚和VREF(+)引脚接电源，ADC1的GND引脚和VREF(-)引脚接地。优选的，A/D转换单元可以使用ADC0809芯片。
所述数据处理模块包括微型处理器MCU1，其VCC引脚接电源，GND引脚接地，MCU1的PC0至PC7引脚分别与所述的A/D转换单元ADC1的2-1至2-8引脚相连接，MCU1的PB0引脚接ADC1的或非门NOR1的一个输入端，MCU1的PB1引脚接ADC1的或非门NOR1的另一个输入端，MCU1的PB2引脚接ADC1的或非门NOR2的一个输入端，MCU1的PB3引脚、PB4引脚和PB5引脚分别接ADC1的ADDA引脚、ADDB引脚和ADDC引脚，MCU1的PB6引脚与ADC1的CLOCK引脚相连，MCU1 的PB7引脚与ADC1的EOC引脚相连。优选的，微型处理器MCU1可以采用STM32F1系列的芯片。
所述NB-IOT模块包括NB-IOT通信模块NB1，NB1的VBAT引脚接电容C3的一端，NB1的GND引脚接电容C3的另一端，电容C4、电容C5和稳压二极管D1与电容C3并联，稳压二极管D1的一端接电源，稳压二极管的另一端接地；NB1的RESET引脚接稳压二极管D2的一端，稳压二极管D2的另一端接地，NB1的RESET引脚还接了按键开关KEY1的一端，按键开关KEY1的另一端接地；NB1的SIM_GND引脚接电容C6的一端，电容C6的另一端接SIM卡连接器SCC的VCC引脚，NB1的SIM_GND引脚还接了SIM卡连接器SCC的GND引脚，NB1的SIM_VDD引脚接了SIM卡连接器SCC的VCC引脚，NB1的SIM_VDD引脚还接了电阻R9的一端，电阻R9的另一端接了NB1的SIM_DATA引脚，电阻R9的另一端还接了电阻R8的一端，电阻R8另一端还接了SIM卡连接器SCC的IO引脚，NB1的SIM_RST引脚接了电阻R6的一端，电阻R6的另一端还接了SIM卡连接器SCC的RST引脚，NB1的SIM_CLK引脚接电阻R7的一端，电阻R7的另一端接SIM卡连接器SCC的CLK引脚；NB1的NETLIGHT引脚接电阻R14的一端，电阻R14的另一端接晶体管Q3的基极，晶体管Q3的发射极接电阻R15的一端，电阻R15的另一端接地以及晶体管Q3的基极，晶体管Q3的集电极接电阻R16的一端，电阻R16的另一端接发光二极管LED1的一端，发光二极管LED1的另一端接NB1的VDD引脚；NB1的TXD引脚接晶体管Q1的发射极，晶体管Q1的集电极接MCU1的PA1引脚，晶体管Q1的集电极还接了电阻R10的一端，电阻R10的另一端接MCU1的VDD引脚，晶体管Q1的基极接电阻R11的一端，电阻R11的另一端接NB1的VDD_EXT引脚，晶体管Q1的基极还接了电容C7的一端，电容C7的另一端接NB1的VDD_EXT引脚，NB1的RXD引脚接电阻R12的一端，电阻R12的另一端接NB1的VDD_EXT引脚，电阻R12的另一端还接了电阻R13和电容C8的一端，电阻R13和电容C8的另一端接晶体管Q2的基极，NB1的RXD引脚还接了晶体管Q2的集电极，晶体管Q2的发射极接MCU1的PA0引脚。
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，所述的方法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。
此外，在本申请各个实施例中的各个单元可以集成在一个模块中，也可以是单元单独物理存在，也可以两个或两个以上单元集成在一个模块中。上述集成的模块既可以采用硬件的形式实现，也可以采用软件功能模块的形式实现。所述集成的模块如果以软件功能模块的形式实现并作为独立的产品销售或使用时，也可以存储在一个计算机可读取存储介质中。
以上所述仅是本发明的优选实施方式，应当指出，对于本技术领域的普通技术人员来说，在不脱离本发明原理的前提下，还可以做出若干改进和润饰，这些改进和润饰也应视为本发明的保护范围。

Claims (9)

  1. 一种基于NB-IOT的岩体破裂失稳微震信号无线监测方法，其特征在于，所述方法包括如下步骤：
    步骤1：在待监测岩体上安装一个或者一个以上的数据采集模块，采集岩体破裂产生的微震信号，使用长短时窗幅值比值法拾取有效微震波形数据；
    步骤2：创建数据发送缓冲队列，从有效微震波形数据中提取微震特征向量，根据微震特征向量执行不同的压缩策略得到压缩数据包，将压缩数据包放置于数据发送缓冲队列尾部，同时发出一个携带压缩数据包信息的信号量；
    步骤3：使用休眠唤醒算法对NB-IOT模块进行调度，使其在需要发送数据的时候被唤醒，而不需要发送数据的时候进行休眠，节省电量以延长工作时间；
    步骤4：当NB-IOT模块处于唤醒状态时，与云平台模块建立通信链路，将所述的压缩数据包发送至云平台模块；
    步骤5：云平台模块对接收到的数据包进行分析，若满足预警条件则发出预警信息。
  2. 根据权利要求1所述的一种基于NB-IOT的岩体破裂失稳微震信号无线监测方法，其特征在于，步骤1中，采集岩体破裂产生的微震信号的具体过程为：
    步骤1.1.1：当岩体产生微观裂隙时会释放出低能量的弹性波并向四周传播，引发岩体的微小震动，数据采集模块的加速度传感器能够将岩体微小震动的加速度值转换为电压值得到微震信号，转换公式如式子(1)所示：
    Figure PCTCN2022095165-appb-100001
    式中，d表示压电常数，m表示加速度传感器内部压电元件的质量，C表示压电元件两端的电容，在加速度传感器型号确定的情况下其d、m和C均为确定常量，因此电压值V与加速度a成正比，所采集的微震信号的电压值越大，表示岩体震动的加速度越大；
    步骤1.1.2：使用所述数据采集模块的A/D转换单元将加速度传感器输出的模拟信号转换为数字化的幅值并传输至数据处理模块作进一步处理。
  3. 根据权利要求1所述的一种基于NB-IOT的岩体破裂失稳微震信号无线监测方法，其特征在于，步骤1中，使用长短时窗幅值比值法拾取有效微震波形数据的具体过程为：
    步骤1.2.1：创建微震数据包暂存队列、有效波形暂存队列、短时窗数组和长时窗数组，所述的短时窗数组和长时窗数组的最大长度分别为M和N，设有效信号提取阈值为R；所述的M、N和R根据监测现场环境决定；
    步骤1.2.2：初始化长时窗数组，逐个读取从所述数据采集模块传输过来的幅值，将其按顺序保存于长时窗数组内，直至长时窗数组的元素个数达到N；
    步骤1.2.3：逐个读取从所述数据采集模块传输过来的幅值，将其按顺序保存于短时窗数组内，当短时窗数组内的元素达到M时，分别计算短时窗数组和长时窗数组内的平均电压幅值Amplitude 1和Amplitude 2，接着将长时窗数组的元素整体往前搬移M个位置，将短时窗数组内的元素依次添加到长时窗数组末尾的M个位置上，然后求得Amplitude 1和Amplitude 2的比值r＝Amplitude 1/Amplitude 2，若r大于等于R则表示开始拾取有效微震波形数据，接着转步骤1.2.4：；否则，清空短时窗数组内的元素并重复执行步骤1.2.3；
    步骤1.2.4：将短时窗数组内的元素依次添加到有效波形暂存队列尾部中；接着清空短时窗数组内的元素，然后继续逐个读取从所述数据采集模块传输过来的幅值，当短时窗数 组内的元素达到M后，分别计算短时窗数组和长时窗数组的平均电压幅值Amplitude 1和Amplitude 2并求得二者的比值r＝Amplitude 1/Amplitude 2，若r小于R则表示结束拾取有效的微震波形数据，转步骤1.2.5，否则，将长时窗数组的元素整体往前搬移M个位置，将短时窗数组内的元素依次添加到长时窗数组末尾的M个位置上，重复执行步骤1.2.4；
    步骤1.2.5：将短时窗数组内的元素按顺序添加到有效波形暂存队列尾部中，获取当前的时间戳，将有效波形暂存队列的所有元素和时间戳打包成一个微震数据包，并将其放置于微震数据包暂存队列尾部，表示当前拾取了一个有效微震波形数据，接着清空有效波形暂存队列，然后重复执行步骤1.2.3，开始拾取下一个有效微震波形数据。
  4. 根据权利要求1所述的一种基于NB-IOT的岩体破裂失稳微震信号无线监测方法，其特征在于，步骤2中，从有效微震波形数据中提取微震特征向量的具体过程为：
    创建一个微震波形数据处理数组，从所述的微震数据包暂存队列的头部中取出一个微震数据包，将其中的有效微震波形数据逐元素复制到微震波形数据处理数组中；从微震波形数据处理数组的第一个元素开始遍历，到最后一个元素结束遍历，计算得到触发位置、结束位置、信号持续时间、上升时间、最大幅值和最大幅值的位置共六个特征值，将这六个特征值组成微震特征向量，六个特征值的具体定义为：
    触发位置：表示数组中第一个大于阈值的幅值对应的数组下标；
    结束位置：表示数组中最小幅值对应的数组下标；
    信号持续时间：表示结束位置与触发位置的差值；
    最大幅值：表示数组所有幅值中最大的幅值；
    最大幅值的位置：表示数组中最大幅值所对应的数组下标；
    上升时间：表示最大幅值的位置与触发位置的差值。
  5. 根据权利要求1所述的一种基于NB-IOT的岩体破裂失稳微震信号无线监测方法，其特征在于，步骤2中，根据微震特征向量执行不同的压缩策略得到压缩数据包的具体过程为：
    若所述微震特征向量的最大幅值大于或等于设定的阈值V threshold，则表示需要将有效微震波形数据发送至云平台备份，将有效微震波形数据进行压缩以适应NB-IOT低带宽的场合，首先将微震波形数据处理数组的所有浮点数以逗号分隔首尾相连写成字符串，其次采用gzip算法对该字符串进行压缩得到压缩字符串；接着将微震特征向量、压缩字符串和布尔值标志位Flag编码成JSON格式的数据，然后用Hpack算法对其进行压缩得到压缩数据包；所述的布尔值标志位Flag，其值被设置为真，表示该压缩数据包含有有效微震波形数据和微震特征向量；
    若所述微震特征向量中的最大幅值小于设定的阈值V threshold，则表示无需发送有效微震波形数据到云平台备份，只需发送微震特征向量到云平台保存；首先将微震特征向量和布尔值标志位Flag编码成JSON格式的数据，然后使用Hpack算法对其进行压缩得到压缩数据包；所述的布尔值标志位Flag，其值被设置为假，表示该压缩数据包仅含有微震特征向量。
  6. 根据权利要求1所述的一种基于NB-IOT的岩体破裂失稳微震信号无线监测方法，其特征在于，步骤3中，使用休眠唤醒算法对NB-IOT模块进行调度的具体过程为：
    步骤3.1：系统初始化时，所述数据处理模块的休眠唤醒控制单元向NB-IOT模块按顺序 发送激活AT指令、注网AT指令和休眠AT指令，使NB-IOT模块在被激活后进行注网操作，随后切换至低功耗模式，进入休眠状态；
    步骤3.2：创建一个计数器Counter和一个计时器Timer，所述计数器Counter的溢出条件是其数值达到C m，所述的计时器Timer的溢出条件是其时间达到T m；
    步骤3.3：重置计数器Counter和计时器Timer；休眠唤醒控制单元等待接收信号量，当其首次接收到信号量时，若信号量的布尔值标志位Flag为假，则计数器Counter的数值加1，且计时器Timer同步开启，然后进入步骤3.4，否则，进入步骤3.5；
    步骤3.4：休眠唤醒控制单元继续等待接收信号量，每次接收到信号量时，若信号量的布尔值标志位Flag为真，则进入步骤3.5，否则，计数器Counter的数值加1，若计数器Counter满足溢出条件或计时器Timer满足溢出条件时，进入步骤3.5；否则重复执行步骤3.4；
    步骤3.5：首先，所述休眠唤醒控制单元向NB-IOT模块发送唤醒AT指令以唤醒NB-IOT模块，接着，执行数据发送流程从数据发送缓冲队列中逐个取出压缩数据包，并发送压缩数据包到云平台，当数据发送缓冲队列为空时，所述休眠唤醒控制单元向NB-IOT模块发送休眠AT指令使其进入休眠状态，最后，进入步骤3.3。
  7. 一种基于NB-IOT的岩体破裂失稳微震信号无线监测装置，其特征在于：包括一个或者一个以上的数据采集模块、数据处理模块、NB-IOT模块和云平台模块，一个或者一个以上的数据采集模块与数据处理模块有线或者无线连接，数据处理模块经NB-IOT模块与云平台模块无线连接；
    一个或者一个以上的数据采集模块用于获取岩体破裂所产生的微震信号，并将所述的微震信号转换成需要处理的数字化的电压信号，数据处理模块用于拾取有效微震波形数据，并从中提取微震特征向量，对微震特征向量和有效微震波形数据的压缩以满足NB-IOT低带宽的特点，同时对NB-IOT模块的休眠和唤醒状态之间的调度，NB-IOT模块用于实现与云平台模块建立通信链路，将压缩数据包发送至云平台模块，云平台模块用于与NB-IOT模块进行远程连接并建立通信链路，接收并存储来自所述的NB-IOT模块的数据，对数据进行分析，若满足预警条件则发送预警信息。
  8. 根据权利要求7所述的一种基于NB-IOT的岩体破裂失稳微震信号无线监测装置，其特征在于：数据采集模块包括加速度传感器单元、放大电路单元和A/D转换单元，加速度传感器单元经放大电路单元与A/D转换单元连接，加速度传感器单元用于采集岩体破裂失稳产生的微震信号，放大电路单元用于将所述加速度传感器单元采集到的微震信号进行放大，A/D转换单元用于将所述放大电路单元输出的微震信号转换为数字化的电压信号。
  9. 根据权利要求8所述的一种基于NB-IOT的岩体破裂失稳微震信号无线监测装置，其特征在于：数据处理模块包括有效波形拾取单元、特征提取单元、数据压缩单元和休眠唤醒控制单元，有效波形拾取单元的输入端与A/D转换单元连接，有效波形拾取单元的输出端与特征提取单元连接，特征提取单元的输出端与数据压缩单元连接，休眠唤醒控制单元与NB-IOT模块连接；
    有效波形拾取单元用于使用长短时窗幅值比值法从所述A/D转换单元传输过来的数据中提取有效微震波形数据，特征提取单元用于从有效微震波形数据中提取微震特征向量，数据压缩单元用于压缩微震特征向量和有效微震波形数据，减少其所占的存储空间以便能 够在NB-IOT的窄带宽环境下进行数据传输，休眠唤醒控制单元用于使用休眠唤醒算法对所述NB-IOT模块进行调度，使其在需要发送数据时被唤醒，而无需发送数据时休眠，节省电量以延长NB-IOT模块的工作时间。
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