A node-type slope monitoring system and method

Abstract

The present invention discloses a node-type slope monitoring system and method, which belongs to the field of slope monitoring and protection technology. The present invention uses optical fiber sensors that constitute each monitoring node in the monitoring node array to sense the vibration signal before the slope disaster occurs in real time, combines the satellite timing module and the data processing module to realize the real-time and high-precision collection and processing of the micro-vibration signal of the slope disaster, and performs subsequent effective event identification, source location, magnitude assessment and disaster warning through the cloud server, thereby realizing high-precision, low false alarm rate and accurate warning of slope disasters; the data preliminary screening module performs preliminary screening of the data before uploading through the STA / LTA algorithm, reduces the transmission pressure of the wireless transmission module, reduces the battery power consumption of the equipment, and reduces the storage of invalid data by the cloud server.

Description

Technical Field

[0001] The present invention relates to the technical field of slope monitoring and protection, and in particular to a node-type slope monitoring system and method. Background Art

[0002] In recent years, with the increasing number of slope disasters, higher requirements and demands have been put forward for slope safety. Therefore, carrying out slope structural health monitoring, timely warning and identification of slope instability and landslide, and preventing the occurrence of slope disasters are the core links of current slope health. The existing slope monitoring technologies mainly include: image recognition and processing method, groundwater level monitoring method, slope slip prediction method and distributed optical fiber monitoring method, among which the distributed optical fiber monitoring method uses optical fiber to sense the displacement change of the slope for alarm. Due to the unique sensitive characteristics of optical fiber, there are more and more application cases of using distributed optical fiber for monitoring in recent years. However, there are still some shortcomings in using distributed optical fiber for slope monitoring. For example, the installation hole of distributed optical fiber in slope monitoring construction is generally more than 2 meters or even deeper, the construction process is relatively complicated, and it is easy to cause safety hazards during the construction process.

[0003] Distributed optical fiber can generally only provide an alert when there is a large displacement change in the slope, that is, the distributed optical fiber will only be detected after the slope has a slight deformation, displacement, tilt or crack, and touches the sensor that transmits the signal through the optical fiber. There are technical problems such as timely warning, inaccurate evaluation, and sensor coverage limited by the cable laying distance. At the same time, the construction of the traditional distributed optical fiber sensor slope monitoring system is complex and difficult to maintain. It usually requires full excavation of the slope surface. And because the sensors are connected by optical fiber, under maintenance, cable disconnection, damage to individual sensors, etc., it will lead to an increase in the false alarm rate of the microseismic monitoring signal on the entire slope, data loss, and even inability to monitor.

[0004] In addition, the existing technology usually uploads the data collected by the sensor directly to the cloud server for further calculation of slope disaster warning judgment. However, due to the large amount of original data, it will cause a certain transmission pressure on the low-power wireless transmission module, and consume a lot of device battery power, causing the cloud server to store too much invalid data. Summary of the invention

[0005] In view of the above problems, a node-type slope monitoring system and method are provided. The present invention uses optical fiber sensors to perceive vibration signals before slope disasters occur in real time, and uses satellite timing modules and data processing modules to realize real-time and high-precision collection and processing of micro-vibration signals of slope disasters. The cloud server performs subsequent effective event identification, source location, magnitude assessment and disaster warning, thereby realizing high-precision, low false alarm rate and accurate warning of slope disasters. The data preliminary screening module uses the STA / LTA algorithm to perform preliminary screening of data before uploading, thereby reducing the transmission pressure of the wireless transmission module, reducing the battery power consumption of the equipment and reducing the storage of invalid data on the cloud server.

[0006] To achieve the above object, the technical solution adopted by the present invention is.

[0007] A node-type slope monitoring method comprises the following steps: Step 1: monitoring nodes are evenly arranged at a position ≥0.5 m below the slope surface to form a monitoring node array, wherein the optical fiber sensor in the monitoring node senses the vibration signal before the slope disaster occurs in real time and outputs two optical signals to a photoelectric detector, which are converted into two electrical signals by the photoelectric detector and then output to an ADC;

[0008] Step 2: The ADC triggers a DMA interrupt every time it collects a frame of data, and in the interrupt service, the two electrical signals synchronously collected by the ADC actively carried by the DMA are packaged and output to the data acquisition module;

[0009] Step 3: The satellite timing module obtains the time information TOD and the pulse per second signal PPS from the satellite in real time and outputs them to the time calibration module. When the pulse per second signal PPS arrives, the satellite timing module triggers the external interrupt EXTI of the time calibration module, and queries whether the ADC is started in the interrupt service of the external interrupt EXTI. If not, the ADC is started to perform synchronous acquisition of two electrical signals;

[0010] Step 4: If the ADC is started, query the data point of the two electrical signals actively transferred by the DMA to the current frame, record the index value of the data point at the arrival time of the pulse per second signal PPS, and query the current time information TOD at the same time;

[0011] Step 5: Output the time information TOD and index value in step 4 to the data acquisition module, and the data acquisition module packages the index value, time information TOD and two electrical signals of the current frame actively transported and input by DMA and outputs them to the data demodulation module;

[0012] Step 6: The data demodulation module outputs the real-time vibration signal to the data screening module through the data demodulation algorithm. The data screening module determines the presence of microseismic events in the real-time vibration signal exceeding the set threshold through the STA / LTA algorithm, and uploads the microseismic events to the cloud server via the 4G module. The cloud server determines whether the microseismic event involves a slope disaster and issues a disaster warning.

[0013] Preferably, the sampling rate of the ADC is 24Ksps, the sampling depth is 16 bits, and the length of one frame of data is 10ms.

[0014] Preferably, the satellite timing module adopts UART communication mode with a baud rate of 115200bps, and the satellite timing module sends time information TOD to the time calibration module through the NMEA-0183 protocol.

[0015] Preferably, the data demodulation algorithm in step 6 includes the following steps: Step S1: The optical fiber sensor outputs two optical signals with a fixed phase difference, which are converted into two electrical signals with a fixed phase difference by the photoelectric detector and then output to the ADC. The two electrical signals can be expressed as:

[0016]

[0017] in a 1 and a 2 represents the DC bias of the two signals; b 1 and b 2 is the AC amplitude; i S is the phase to be measured, indicating the phase change caused by external vibration; β is a fixed phase difference.

[0018] Step S2: In step 1 V 1 and V 2 satisfies the ellipse fitting equation:

[0019] .

[0020] Step S3: The ADC module synchronously collects two electrical signals and then demodulates them through the data demodulation module to output the parameters in step 1. a 1. a 2. b 1. b 2. β , and construct a phase i S The two orthogonal signals can be expressed as:

[0021] .

[0022] Step S4: The two orthogonal signals are demodulated by a differential cross-multiplication algorithm and then output as the phase to be measured i S That is, real-time vibration signal to the data initial screening module.

[0023] Preferably, the fixed phase difference β= 2 π / 3.

[0024] Preferably, the STA / LTA algorithm in step 6 comprises the following steps:

[0025] Step S1: Assume that the length of the long time window is nl , a short window is set within the long window, and the length of the short window is n.s. The data demodulation module continuously buffers 350 frames of the real-time vibration signal to the data preliminary screening module.

[0026] Step S2: The end points of the long window and the short window coincide with each other, and the long window and the short window are synchronously slid data point by data point to calculate the value of STA / LTA. The STA / LTA can be expressed as:

[0027]

[0028]

[0029]

[0030] in, i is the sampling time, j is the starting point of the time window, n.s. is the short-time window length, nl is the long time window length, l is the trigger threshold set. CF ( i ) is in i The characteristic function value of the vibration signal at a certain moment represents the amplitude or energy change of the vibration signal.

[0031] Step S3: When the value of STA / LTA exceeds the set trigger threshold, it is determined that a microseismic event exists and the index value of the data point position is recorded.

[0032] Step S4: Starting from the time when the microseismic event occurs, search the positions of the two second pulse signals PPS forward and backward, and calculate the time difference between the time when the microseismic event occurs and the positions of the two second pulse signals PPS before and after the time through the position index value. and .

[0033] Step S5: If , then the real-time vibration signal between the second pulse signal PPS2 and the second pulse signal PPS4 is intercepted; if , then the real-time vibration signal between the second pulse signal PPS1 and the second pulse signal PPS3 is intercepted.

[0034] Step S6: The intercepted real-time vibration signal, combined with the index value of the microseismic event occurrence time and the corresponding time information TOD and the pulse per second signal PPS are all packaged as a microseismic event and output to the 4G module.

[0035] Preferably, the long time window is 120 ms, the short time window is 65 ms, and the threshold is set to 1.6.

[0036] A node-type monitoring system comprises a monitoring node, wherein the monitoring node comprises an optical fiber sensor, a photoelectric detector, a satellite timing module, a data processing module and a 4G module; the monitoring nodes are evenly arranged at a position ≥0.5 m below the slope surface to form a monitoring node array; the optical fiber sensor senses the vibration signal before the slope disaster occurs in real time and outputs two optical signals to the photoelectric detector, which are converted into two electrical signals by the photoelectric detector and then output to the data processing module; the data processing module collects, demodulates and preliminarily screens the two electrical signals and then outputs microseismic events, which are uploaded to a cloud server via a 4G module; the microseismic events are successively subjected to effective event recognition, source location, magnitude assessment and disaster warning by an effective event recognition module, a source location module, a magnitude assessment module and a disaster warning module of the cloud server, thereby determining whether there is a slope disaster and issuing a warning.

[0037] Preferably, the data processing module includes a time calibration module, a data acquisition module, a data demodulation module, a data preliminary screening module, ADC, DMA, UART and an external interrupt EXTI.

[0038] Preferably, the monitoring node also includes a cable and a packaging shell.

[0039] Due to the adoption of the above technical solution, the present invention has the following beneficial effects.

[0040] (1) The present invention uses optical fiber sensors to perceive the vibration signals before a slope disaster occurs in real time, and uses a satellite timing module and a data processing module to achieve real-time, high-precision collection and processing of micro-vibration signals of slope disasters. It also uses a cloud server to perform subsequent effective event identification, earthquake source location, earthquake magnitude assessment, and disaster warning, thereby achieving high-precision, low-false-alarm-rate accurate warning of slope disasters.

[0041] (2) The data processing module of the present invention performs data demodulation, preliminary screening and data processing on the vibration signals collected by the optical fiber sensor through a data demodulation algorithm, thereby improving the collection accuracy of the vibration signal and the accuracy of data processing; the satellite timing module provides high-precision time calibration and time synchronization, thereby improving the time accuracy of the monitoring data and the accuracy of monitoring. Compared with the traditional distributed optical fiber sensing system, the node-based slope monitoring of the present invention can perceive and warn of the precursory tiny vibration signals generated before the occurrence of slope disasters in advance, and the warning is more timely.

[0042] (3) The present invention uses the STA / LTA algorithm through the data preliminary screening module to determine whether a real-time vibration signal that exceeds a set threshold has a microseismic event, and uploads the microseismic event to the cloud server via the 4G module. The preliminary screening of real-time vibration signals at the front end of the cloud server achieves the technical effects of reducing the transmission pressure of the wireless transmission module, reducing the battery power consumption of the device, and reducing the storage of invalid data on the cloud server. Compared with the traditional direct transmission of raw data solution, it solves the problem of low transmission and storage efficiency caused by large amounts of raw data.

[0043] (4) The present invention forms a monitoring node array through monitoring nodes, combines a satellite timing module and a data processing module, realizes node-based collection of microvibration signals that are precursors of slope disasters, demodulates and initially screens wireless transmission data, and realizes effective event recognition, earthquake source location, earthquake magnitude assessment and disaster warning of the data collected by the slope surface monitoring node array through a cloud server, monitors and identifies microvibration signals that are precursors of slope disasters in advance, and provides timely warnings and accurate assessments of microseismic events.

[0044] (5) The present invention further analyzes and processes the uploaded microseismic events through the effective event recognition module, earthquake source location module, earthquake magnitude assessment module and disaster warning module of the cloud server, and performs effective event recognition, earthquake source location, earthquake magnitude assessment and disaster warning analysis in sequence, thereby playing a role in accurately warning and assessing slope disasters, and solving the technical problems of untimely warning and inaccurate assessment in traditional distributed monitoring methods.

[0045] (6) The present invention realizes remote data transmission and node-type independent operation of monitoring nodes by combining 4G modules, time calibration modules and satellite timing modules through rapid installation and disassembly of node-type monitoring nodes, thereby solving the technical problems of complex construction and difficult maintenance of traditional distributed optical fiber sensors in slope monitoring, and achieving the technical effects of simple construction, rapid deployment and flexible maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The following is a detailed discussion of the making and application of the preferred embodiments of the present invention. However, it should be understood that the present invention provides many applicable inventive concepts that can be embodied in various specific environments. The specific embodiments discussed are only for the purpose of illustrating the specific ways of making and using the present invention, and do not limit the scope of the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative work.

[0047] Figure 1 This is a flow chart of slope monitoring of the present invention.

[0048] Figure 2 This is a schematic diagram of the deployment of monitoring nodes of the present invention.

[0049] Figure 3 This is a schematic diagram of the initial screening of data in the present invention. DETAILED DESCRIPTION

[0050] The following is a detailed discussion of the making and application of the preferred embodiments of the present invention. However, it should be understood that the present invention provides many applicable inventive concepts that can be embodied in various specific environments. The specific embodiments discussed are only intended to illustrate specific ways to make and use the present invention and do not limit the scope of the present invention.

[0051] The present invention uses optical fiber sensors to perceive vibration signals before slope disasters occur in real time, realizes real-time, high-precision collection and processing of micro-vibration signals of slope disasters through satellite timing modules and data processing modules, and performs subsequent effective event identification, source location, magnitude assessment and disaster warning through cloud servers, thereby realizing accurate warning of slope disasters with high precision and low false alarm rate.

[0052] The following is combined with Figure 1-3 Further elaboration. Example 1

[0053] The data processing module of the present invention performs data demodulation, preliminary screening and data processing on the vibration signal collected by the optical fiber sensor through a data demodulation algorithm, thereby improving the collection accuracy of the vibration signal and the accuracy of data processing; and provides high-precision time calibration and time synchronization through a satellite timing module, thereby improving the time accuracy of the monitoring data.

[0054] like Figure 1The slope monitoring flow chart shown. A node-based slope monitoring method comprises the following steps: Step 1: The monitoring nodes are evenly arranged at ≥0.5m below the slope surface to form a monitoring node array, and the optical fiber sensor in the monitoring node senses the vibration signal before the slope disaster occurs in real time and outputs two optical signals to the photoelectric detector, which are converted into two electrical signals by the photoelectric detector and then output to the ADC, the sampling rate of the ADC is 24Ksps, the sampling depth is 16bit, and the length of one frame of data is 10ms.

[0055] Step 2: The ADC triggers a DMA interrupt every time it collects a frame of data, and in the interrupt service, the two electrical signals synchronously collected by the ADC actively carried by the DMA are packaged and output to the data acquisition module.

[0056] Step 3: The satellite timing module obtains the time information TOD and the pulse per second signal PPS from the satellite in real time and outputs them to the time calibration module. When the pulse per second signal PPS arrives, the satellite timing module triggers the external interrupt EXTI of the time calibration module, and queries whether the ADC is started in the interrupt service of the external interrupt EXTI. If not, the ADC is started to perform synchronous acquisition of the two electrical signals.

[0057] The satellite timing module adopts UART communication mode with a baud rate of 115200bps. The satellite timing module sends time information TOD to the time calibration module through the NMEA-0183 protocol.

[0058] Step 4: If the ADC is started, query the data point of the two electrical signals actively transferred by the DMA to the current frame, record the index value of the data point at the arrival time of the pulse per second signal PPS, and query the current time information TOD at the same time;

[0059] Step 5: Output the time information TOD and index value in step 4 to the data acquisition module, and the data acquisition module packages the index value, time information TOD and two electrical signals of the current frame actively transported and input by DMA and outputs them to the data demodulation module.

[0060] Step 6: The data demodulation module outputs the real-time vibration signal to the data preliminary screening module through the data demodulation algorithm.

[0061] The data demodulation algorithm comprises the following steps: Step S1: The optical fiber sensor outputs two optical signals with a fixed phase difference, which are converted into two electrical signals with a fixed phase difference by the photoelectric detector and then output to the ADC. The two electrical signals can be expressed as:

[0062]

[0063] in a1 and a 2 represents the DC bias of the two signals; b 1 and b 2 is the AC amplitude; i S is the phase to be measured, indicating the phase change caused by external vibration; β is a fixed phase difference, the fixed phase difference β= 2 π / 3.

[0064] Step S2: In step 1 V 1 and V 2 satisfies the ellipse fitting equation:

[0065] .

[0066] Step S3: The ADC module synchronously collects two electrical signals and then demodulates them through the data demodulation module to output the parameters in step 1. a 1. a 2. b 1. b 2. β , and construct a phase i S The two orthogonal signals can be expressed as:

[0067] .

[0068] Step S4: The two orthogonal signals are demodulated by a differential cross-multiplication algorithm and then output as the phase to be measured i S That is, real-time vibration signal to the data initial screening module.

[0069] Step 7: The data screening module determines that a real-time vibration signal exceeding a set threshold value has a microseismic event through the STA / LTA algorithm, and uploads the microseismic event to the cloud server via the 4G module.

[0070] The STA / LTA algorithm in step 7 includes the following steps: Step S1: Assume that the length of the long time window is nl , a short window is set within the long window, and the length of the short window is n.s. The data demodulation module continuously buffers 350 frames of the real-time vibration signal to the data preliminary screening module. The long time window is 120ms, the short time window is 65ms, and the threshold is set to 1.6.

[0071] Step S2: The end points of the long window and the short window coincide with each other, and the long window and the short window are synchronously slid data point by data point to calculate the value of STA / LTA. The STA / LTA can be expressed as:

[0072]

[0073]

[0074]

[0075] in, i is the sampling time, j is the starting point of the time window, n.s. is the short-time window length, nl is the long time window length, l is the trigger threshold set. CF ( i ) is in i The characteristic function value of the vibration signal at a certain moment represents the amplitude or energy change of the vibration signal.

[0076] Step S3: When the value of STA / LTA exceeds the set trigger threshold, it is determined that a microseismic event exists and the index value of the data point position is recorded.

[0077] Step S4: Figure 3 As shown in the figure, the positions of the two second pulse signals PPS are searched forward and backward from the time when the microseismic event occurs, and the time difference between the time when the microseismic event occurs and the positions of the two second pulse signals PPS before and after the time is calculated by the position index value. and .

[0078] Step S5: If , then the real-time vibration signal between the second pulse signal PPS2 and the second pulse signal PPS4 is intercepted; if , then the real-time vibration signal between the second pulse signal PPS1 and the second pulse signal PPS3 is intercepted.

[0079] Step S6: The intercepted real-time vibration signal, combined with the index value of the microseismic event occurrence time and the corresponding time information TOD and the pulse per second signal PPS are all packaged as a microseismic event and output to the 4G module.

[0080] Step 8: The microseismic event is sequentially determined by the effective event recognition module, earthquake source location module, earthquake magnitude assessment module and disaster warning module of the cloud server to determine whether there is a slope disaster and issue a disaster warning.

[0081] like Figure 2A node-type monitoring system shown includes a monitoring node, which includes an optical fiber sensor, a photoelectric detector, a satellite timing module, a data processing module and a 4G module; the monitoring nodes are evenly arranged at ≥0.5m below the slope surface to form a monitoring node array; the optical fiber sensor senses the vibration signal before the slope disaster occurs in real time and outputs two optical signals to the photoelectric detector, which are converted into two electrical signals by the photoelectric detector and then output to the data processing module, the data processing module collects, demodulates and preliminarily screens the two electrical signals and then outputs microseismic events, which are uploaded to the cloud server through the 4G module, and the microseismic events are sequentially identified by the effective event recognition module, the source location module, the magnitude assessment module and the disaster warning module of the cloud server for effective event recognition, source location, magnitude assessment and disaster warning, and then determine whether there is a slope disaster and issue a warning. The data processing module includes a time calibration module, a data acquisition module, a data demodulation module, a data preliminary screening module, an ADC, a DMA, a UART and an external interrupt EXTI. The monitoring node also includes a cable and a packaging shell.

[0082] The present invention forms a monitoring node array through monitoring nodes, combines a satellite timing module and a data processing module, realizes node-based collection of tiny vibration signals that are precursors to slope disasters, demodulates and initially screens wirelessly transmitted data, and realizes effective event recognition, source location, magnitude assessment and disaster warning of the data collected by the slope surface monitoring node array through a cloud server, monitors and identifies microvibration signals that are precursors to slope disasters in advance, ensures timely warning and accurate assessment of microseismic events. Example 2

[0083] The present invention uses the STA / LTA algorithm through the data preliminary screening module to determine whether there is a microseismic event in the real-time vibration signal that exceeds the set threshold, and uploads the microseismic event to the cloud server via the 4G module. The preliminary screening of the real-time vibration signal is performed at the front end of the cloud server to achieve the technical effects of reducing the transmission pressure of the wireless transmission module, reducing the battery power consumption of the device, and reducing the storage of invalid data in the cloud server. Compared with the traditional direct transmission of raw data solution, it solves the problem of low transmission and storage efficiency caused by the large amount of raw data.

[0084] like Figure 1 The slope monitoring flow chart is shown.

[0085] A node-type slope monitoring method comprises the following steps: Step 1: Monitoring nodes are evenly arranged at a position ≥0.5 m below the slope surface to form a monitoring node array, wherein the optical fiber sensor in the monitoring node senses the vibration signal before the slope disaster occurs in real time and outputs two optical signals to the photoelectric detector, which are converted into two electrical signals by the photoelectric detector and then output to an ADC, wherein the sampling rate of the ADC is 24Ksps, the sampling depth is 16 bits, and the duration of one frame of data is 10 ms.

[0086] Step 2: The ADC triggers a DMA interrupt every time it collects a frame of data, and in the interrupt service, the two electrical signals synchronously collected by the ADC actively carried by the DMA are packaged and output to the data acquisition module.

[0087] Step 3: The satellite timing module obtains the time information TOD and the pulse per second signal PPS from the satellite in real time and outputs them to the time calibration module. When the pulse per second signal PPS arrives, the satellite timing module triggers the external interrupt EXTI of the time calibration module, and queries whether the ADC is started in the interrupt service of the external interrupt EXTI. If not, the ADC is started to perform synchronous acquisition of the two electrical signals.

[0088] The satellite timing module adopts UART communication mode with a baud rate of 115200bps. The satellite timing module sends time information TOD to the time calibration module through the NMEA-0183 protocol.

[0089] Step 4: If the ADC is started, query the data point of the two electrical signals actively transferred by the DMA to the current frame, record the index value of the data point when the pulse per second signal PPS arrives, and query the current time information TOD at the same time.

[0090] Step 5: Output the time information TOD and index value in step 4 to the data acquisition module, and the data acquisition module packages the index value, time information TOD and two electrical signals of the current frame actively transported and input by DMA and outputs them to the data demodulation module.

[0091] Step 6: The data demodulation module outputs the real-time vibration signal to the data preliminary screening module through the data demodulation algorithm.

[0092] The data demodulation algorithm comprises the following steps: Step S1: The optical fiber sensor outputs two optical signals with a fixed phase difference, which are converted into two electrical signals with a fixed phase difference by the photoelectric detector and then output to the ADC. The two electrical signals can be expressed as:

[0093]

[0094] in a 1 and a 2 represents the DC bias of the two signals; b 1 and b 2 is the AC amplitude; i S is the phase to be measured, indicating the phase change caused by external vibration; β is a fixed phase difference, the fixed phase difference β= 2 π / 3.

[0095] Step S2: In step 1 V 1 and V 2 satisfies the ellipse fitting equation:

[0096] .

[0097] Step S3: The ADC module synchronously collects two electrical signals and then demodulates them through the data demodulation module to output the parameters in step 1. a 1. a 2. b 1. b 2. β , and construct a phase i S The two orthogonal signals can be expressed as:

[0098] .

[0099] Step S4: The two orthogonal signals are demodulated by a differential cross-multiplication algorithm and then output as the phase to be measured i S That is, real-time vibration signal to the data initial screening module.

[0100] Step 7: The data screening module determines that a real-time vibration signal exceeding a set threshold value has a microseismic event through the STA / LTA algorithm, and uploads the microseismic event to the cloud server via the 4G module.

[0101] The data screening module adopts the STA / LTA algorithm to monitor in real time whether there is a microseismic event in the vibration signal, and then extracts a 2-second vibration signal as a microseismic event based on the second pulse signal PPS in the data frame and uploads it to the cloud server. It can effectively filter out useless noise signals to reduce the amount of uploaded data. The STA / LTA algorithm is to give a sliding long-time window, and at the same time take a short-time window in this window. The starting point or end point of the two windows coincides, and the ratio of the characteristic value of the short-time window signal (STA) to the characteristic value of the long-time window signal (LTA) is used to reflect the change in signal amplitude or energy. At the arrival time of the microseismic event, STA changes faster than LTA, and the corresponding STA / LTA value will have a significant increase. When the ratio exceeds the set threshold, it can be determined that a microseismic event has occurred.

[0102] The STA / LTA algorithm comprises the following steps: Step S1: Assume that the length of the long time window is nl , a short window is set within the long window, and the length of the short window is n.s.The data demodulation module continuously buffers 350 frames of the real-time vibration signal to the data preliminary screening module. The long time window is 120ms, the short time window is 65ms, and the threshold is set to 1.6.

[0103] Step S2: The end points of the long window and the short window coincide with each other, and the long window and the short window are synchronously slid data point by data point to calculate the value of STA / LTA. The STA / LTA can be expressed as:

[0104]

[0105]

[0106]

[0107] in, i is the sampling time, j is the starting point of the time window, n.s. is the short-time window length, nl is the long time window length, l is the trigger threshold set. CF ( i ) is in i The characteristic function value of the vibration signal at the moment represents the amplitude or energy change of the vibration signal. The main influencing factors of this algorithm include the length of the two time windows, the trigger threshold, the selection of characteristic functions, etc., which will affect the recognition and picking effect of microseismic events.

[0108] Step S3: When the value of STA / LTA exceeds the set trigger threshold, it is determined that a microseismic event exists and the index value of the data point position is recorded.

[0109] Step S4: Figure 3 As shown in the figure, the positions of the two second pulse signals PPS are searched forward and backward from the time when the microseismic event occurs, and the time difference between the time when the microseismic event occurs and the positions of the two second pulse signals PPS before and after the time is calculated by the position index value. and .

[0110] Step S5: If , then the real-time vibration signal between the second pulse signal PPS2 and the second pulse signal PPS4 is intercepted; if , then the real-time vibration signal between the second pulse signal PPS1 and the second pulse signal PPS3 is intercepted.

[0111] Step S6: The intercepted real-time vibration signal, combined with the index value of the microseismic event occurrence time and the corresponding time information TOD and the pulse per second signal PPS are all packaged as a microseismic event and output to the 4G module.

[0112] Step 8: The microseismic event is sequentially determined by the effective event recognition module, earthquake source location module, earthquake magnitude assessment module and disaster warning module of the cloud server to determine whether there is a slope disaster and issue a disaster warning.

[0113] The effective event identification module is a software module running on the cloud server. The module receives microseismic events uploaded by all monitoring nodes in the same slope monitoring area in real time, and arranges the microseismic events uploaded by all monitoring nodes into a two-dimensional matrix according to the TOD and pulse-per-second signal PPS information calibrated in the microseismic events. When more than 4 monitoring nodes upload microseismic events in the same time period (1s duration), the microseismic event data of all monitoring nodes are intercepted based on the arrival time of the pulse-per-second signal PPS as the starting point, and combined together to generate effective microseismic events and stored in the cloud server, and the interception length is 1 second.

[0114] The earthquake source location module retrieves the identified effective microseismic events from the cloud server and locates them using the earthquake source location algorithm. First, the location of the effective microseismic event is defined as ( x 0, y 0, z 0), the occurrence time is t 0. For i The sensors are located at ( x i , y i , z i ). At a uniform speed v Under the assumption that the microseismic wave propagates from the time of occurrence to the i The time of the sensor t i It can be given by the following formula:

[0115]

[0116] Assume i The P wave arrival time recorded by each sensor is T i , then the residual It can be defined as the theoretical time t i The actual time T i Difference:

[0117]

[0118] In order to find the best event location, it is necessary to find the minimum sum of squares of the arrival time residuals of all monitoring nodes of effective microseismic events, that is, to solve the minimum value of the following objective function:

[0119]

[0120] in, n is the number of fiber optic sensors that record the arrival of a P wave.

[0121] Usually, the grid search method can be used for microseismic location. The principle of the grid search method is to first divide the target monitoring area into multiple grid areas in three-dimensional space, and then bring each grid point into the objective function as the source location, compare the calculated values ​​of the objective function of all grid points, and the coordinate point corresponding to the minimum value point is the source location. In fact, in order to improve efficiency, a larger grid step size will be used for a rough search to determine a rough source location range, and then a smaller grid step size will be used within the range for a fine search to further narrow the source location range and ultimately determine the specific location of the source.

[0122] The magnitude assessment module is used to assess the moment magnitude of the current effective microseismic event after the source location of the effective microseismic event is completed. M w When calculating moment magnitude, first evaluate the earthquake moment M 0. Its expression is as follows:

[0123]

[0124] in, r represents the rock mass density, c represents the P-wave or S-wave velocity, R represents the distance between the earthquake source and the monitoring node, Oh 0 represents the low frequency amplitude, F c represents the empirical radiation coefficient. The expression of moment magnitude is:

[0125]

[0126] Within a certain time range, the event frequency and moment magnitude in the earthquake monitoring area follow the following formula:

[0127]

[0128] in, M w represents moment magnitude; n ( M w ) represents the number of microseismic events within a certain period of time; a , b is a constant; b The value is an important indicator for early warning of rock mass dynamic disasters.

[0129] Slope instability and destruction is a progressive development process from gradual change to sudden change, accompanied by certain precursors of destruction. The node-type slope monitoring system is used to conduct long-term and careful monitoring of the slope to timely understand the state of the slope. The disaster warning is based on the statistical monitoring data to make a reasonable evaluation of the slope state, analyze the crisis and impact caused by it, and make predictions and alarms for its aftereffects, so as to make preparations and plans for contingency. The disaster warning in the present invention mainly sends out warning signals in the following four ways.

[0130] 1. Time period identification: If more than 5 effective microseismic events occur within 60 seconds, an alarm will be issued.

[0131] 2. Zone identification: If more than 3 events occur within 10 seconds in a specific area, an alarm will be issued.

[0132] 3. Magnitude determination: If two events with a magnitude greater than -1.0 occur consecutively within 5 minutes, an alarm will be issued.

[0133] 4. b value determination: If the value in the microseismic active range drops significantly, an alarm will be issued.

[0134] like Figure 2 A node-type monitoring system shown includes a monitoring node, which includes an optical fiber sensor, a photoelectric detector, a satellite timing module, a data processing module and a 4G module; the monitoring nodes are evenly arranged at ≥0.5m below the slope surface to form a monitoring node array; the optical fiber sensor senses the vibration signal before the slope disaster occurs in real time and outputs two optical signals to the photoelectric detector, which are converted into two electrical signals by the photoelectric detector and then output to the data processing module, the data processing module collects, demodulates and preliminarily screens the two electrical signals and then outputs microseismic events, which are uploaded to the cloud server through the 4G module, and the microseismic events are sequentially identified by the effective event recognition module, the source location module, the magnitude assessment module and the disaster warning module of the cloud server for effective event recognition, source location, magnitude assessment and disaster warning, and then determine whether there is a slope disaster and issue a warning. The data processing module includes a time calibration module, a data acquisition module, a data demodulation module, a data preliminary screening module, an ADC, a DMA, a UART and an external interrupt EXTI. The monitoring node also includes a cable and a packaging shell.

[0135] A node-type slope monitoring system and method include multiple independently constructed but mutually related monitoring nodes, and the maximum distance between adjacent monitoring nodes is 200 meters; the node-type slope monitoring system includes multiple independently arranged monitoring nodes, and each node communicates with a cloud server using a 4G module. The node-type monitoring system includes an independently constructed monitoring device, and the monitoring device includes the following basic components: an optical fiber sensor, a cable, a data processing module, a 4G module, a satellite timing module, and a packaging shell.

[0136] The optical fiber sensor is used to sense external vibration signals. A semiconductor laser is used as a light source in the optical path. A balanced Michelson interferometer is formed by a 3×3 coupler and a Faraday rotating mirror. The sensing arm and the reference arm of the interferometer are respectively wound around the elastic body and the mass block. When it senses external vibration, the optical path difference of the two arms will change. After the two paths of light are reflected by the Faraday rotating mirror, they return to the coupler to merge and interfere. The vibration signal will be modulated into the phase of the interference light. The two paths of light signals with a fixed phase difference output from the 3×3 coupler are converted into electrical signals through two photodetectors and then amplified by the circuit and synchronously collected by the ADC into the data processing module for subsequent data processing.

[0137] The fiber optic sensor is buried below the slope surface, which can effectively reduce the impact of external noise; the cable is used for optical signal transmission between the fiber optic sensor and the data processing module; the data processing module is used to collect, demodulate and process the vibration signal picked up by the fiber optic sensor; the 4G module is used to transmit the microseismic events output by the data screening module to the cloud server and receive instructions from the cloud server.

[0138] The satellite timing module is used to provide the data processing module with the function of obtaining real-time time from the satellite (satellite timing); the packaging shell is used to fix and protect the optical fiber sensor, cable, data processing module, 4G module, and satellite timing module; the optical fiber sensor transmits the sensed vibration signal to the data processing module through the cable, and the data processing module collects, demodulates and processes the vibration signal, and transmits the data to the cloud server through the 4G module.

[0139] The optical fiber sensor, the cable, the data processing module, the 4G module and the satellite timing module are integrated and installed in the packaging shell to form a complete and independent monitoring node. A single monitoring node is a complete set of devices and can be transported and installed separately. The monitoring node is buried ≥0.5 meters below the slope surface and fixed to the slope matrix with an anchoring agent, allowing for quick installation and disassembly. After all monitoring nodes are arranged, the relative coordinates of all monitoring nodes are obtained by calibrating their positions using a total station, and the relative coordinates are uploaded to the cloud server.

[0140] The method of using the monitoring node is as follows: prepare the monitoring points for construction in advance on site, such as drilling a hole ≥ 0.5 meters deep and cleaning the hole; after the monitoring node is fixed in the hole with an anchor, the monitoring node can be powered on and work; after the optical fiber sensor senses the slope vibration signal, the signal is transmitted to the data processing module through the cable, and the data processing module collects and demodulates the data and performs preliminary data screening to filter out environmental noise and invalid signals. The 4G module transmits the data after preliminary screening to the cloud server, and the cloud server performs effective event identification, source location and magnitude assessment on the data in turn, thereby achieving the effect of disaster warning.

[0141] The present invention further analyzes and processes the uploaded microseismic events through the effective event recognition module, source location module, magnitude assessment module and disaster warning module of the cloud server, and performs effective event recognition, source location, magnitude assessment and disaster warning analysis in sequence, thereby playing a role in accurately warning and evaluating slope disasters, and solving the technical problems of untimely warning and inaccurate assessment in traditional monitoring methods.

[0142] The present invention realizes remote data transmission and node-type independent operation of monitoring nodes through the rapid installation and disassembly of node-type monitoring nodes, combined with 4G modules, time calibration modules and satellite timing modules, solves the technical problems of complex construction and difficult maintenance of traditional distributed optical fiber sensors in slope monitoring, and achieves the technical effects of simple construction, rapid deployment and flexible maintenance.

[0143] Although the specification has been described in detail, it should be understood that various changes, substitutions and modifications may be made without departing from the spirit and scope of the invention as defined by the appended claims. In addition, the specific embodiments described are not intended to limit the scope of the invention, and those of ordinary skill in the art can easily understand based on the present invention that currently existing or later to be developed processes, machines, manufactures, material compositions, means, methods, or steps can perform substantially the same functions as the embodiments of the present invention or obtain substantially the same results. Therefore, the appended claims are intended to include such processes, machines, manufactures, material compositions, means, methods or steps within their scope.

Claims

1. A node-type slope monitoring method, characterized in that: The following steps are involved: Step 1: The monitoring nodes are evenly arranged at a position ≥0.5m below the slope surface to form a monitoring node array. The optical fiber sensors in the monitoring nodes sense the vibration signals before the slope disaster occurs in real time and output two optical signals to the photoelectric detector, which are converted into two electrical signals by the photoelectric detector and then output to the ADC; Step 2: The ADC triggers a DMA interrupt every time it collects a frame of data, and in the interrupt service, the two electrical signals synchronously collected by the ADC actively carried by the DMA are packaged and output to the data acquisition module; Step 3: The satellite timing module obtains the time information TOD and the pulse per second signal PPS from the satellite in real time and outputs them to the time calibration module. When the pulse per second signal PPS arrives, the satellite timing module triggers the external interrupt EXTI of the time calibration module, and queries whether the ADC is started in the interrupt service of the external interrupt EXTI. If not, the ADC is started to perform synchronous acquisition of two electrical signals; Step 4: If the ADC is started, query the data point of the two electrical signals actively transferred by the DMA to the current frame, record the index value of the data point at the arrival time of the pulse per second signal PPS, and query the current time information TOD at the same time; Step 5: Output the time information TOD and index value in step 4 to the data acquisition module, and the data acquisition module packages the index value, time information TOD and two electrical signals of the current frame actively transported and input by DMA and outputs them to the data demodulation module; Step 6: The data demodulation module outputs the real-time vibration signal to the data screening module through the data demodulation algorithm. The data screening module determines the presence of microseismic events in the real-time vibration signal exceeding the set threshold through the STA / LTA algorithm, and uploads the microseismic events to the cloud server via the 4G module. The cloud server determines whether the microseismic event involves a slope disaster and issues a disaster warning.

2. A node-type slope monitoring method according to claim 1, characterized in that: The sampling rate of the ADC is 24Ksps, the sampling depth is 16bit, and the duration of one frame of data is 10ms.

3. A node-type slope monitoring method according to claim 1, characterized in that: The satellite timing module adopts UART communication mode with a baud rate of 115200bps. The satellite timing module sends time information TOD to the time calibration module through the NMEA-0183 protocol.

4. A node-type slope monitoring method according to claim 1, characterized in that: The data demodulation algorithm in step 6 comprises the following steps: Step S1: The optical fiber sensor outputs two optical signals with a fixed phase difference, which are converted into two electrical signals with a fixed phase difference by the photoelectric detector and then output to the ADC. The two electrical signals are expressed as: V1=a1+b1cos(θ s ) V2=a2+b2cos(θ s -β) Where a1 and a2 represent the DC bias of the two signals; b1 and b2 represent the AC amplitude of the two signals; θ S is the phase to be measured, indicating the phase change caused by external vibration; β is the fixed phase difference; Step S2: In step 1, V1 and V2 satisfy the ellipse fitting equation: Step S3: After synchronously collecting two electrical signals, the ADC module outputs the parameters a1, a2, b1, b2, β in step 1 after demodulation by the data demodulation module, and constructs a phase θ to be measured. S The two orthogonal signals are expressed as: Step S4: The two orthogonal signals are demodulated by a differential cross-multiplication algorithm and then output as the phase θ to be measured. S That is, real-time vibration signal to the data initial screening module.

5. A node-type slope monitoring method as claimed in claim 4, characterized in that: The fixed phase difference β=2π / 3.

6. A node-type slope monitoring method according to claim 1, characterized in that: The STA / LTA algorithm in step 6 comprises the following steps: Step S1: Assuming that the length of the long time window is nl, a short time window is set within the long time window, the length of the short time window is ns, and the data demodulation module continuously buffers 350 frames of the real-time vibration signal to the data preliminary screening module; Step S2: The end points of the long window and the short window coincide with each other, and the long window and the short window are synchronously slid data point by data point to calculate the value of STA / LTA, and the STA / LTA is expressed as: Where i is the sampling time, j is the starting point of the time window, ns is the length of the short time window, nl is the length of the long time window, λ is the set trigger threshold, and CF(i) is the characteristic function value of the vibration signal at time i, which represents the amplitude or energy change of the vibration signal; Step S3: When the value of STA / LTA exceeds the set trigger threshold, it is determined that a microseismic event exists and the index value of the data point position is recorded; Step S4: starting from the time when the microseismic event occurs, searching the positions of the two second pulse signals PPS forward and backward, and calculating the time differences Δt1 and Δt2 between the time when the microseismic event occurs and the positions of the two second pulse signals PPS before and after the time through the position index value; Step S5: if Δt1≥Δt2, then intercept the real-time vibration signal between the pulse-per-second signal PPS2 to the pulse-per-second signal PPS4; if Δt1<Δt2, then intercept the real-time vibration signal between the pulse-per-second signal PPS1 to the pulse-per-second signal PPS3; Step S6: The intercepted real-time vibration signal, combined with the index value of the microseismic event occurrence time and the corresponding time information TOD and the pulse per second signal PPS are all packaged as a microseismic event and output to the 4G module.

7. A node-type slope monitoring method as claimed in claim 6, characterized in that: The long time window is 120 ms, the short time window is 65 ms, and the threshold is set to 1.

6.

8. A node-type slope monitoring system, using a node-type slope monitoring method as claimed in any one of claims 1 to 7, characterized in that: The system comprises monitoring nodes, which include optical fiber sensors, photoelectric detectors, satellite timing modules, data processing modules and 4G modules; the monitoring nodes are evenly arranged at a position ≥0.5m below the slope surface to form a monitoring node array; the optical fiber sensor senses the vibration signal before the slope disaster occurs in real time and outputs two optical signals to the photoelectric detector, which are converted into two electrical signals by the photoelectric detector and then output to the data processing module; the data processing module collects, demodulates and preliminarily screens the two electrical signals and then outputs microseismic events, which are uploaded to the cloud server via the 4G module; the microseismic events are successively identified by the effective event recognition module, the source location module, the magnitude assessment module and the disaster warning module of the cloud server for effective event recognition, source location, magnitude assessment and disaster warning, so as to determine whether there is a slope disaster and issue a warning.

9. A node-type slope monitoring system as claimed in claim 8, characterized in that: The data processing module includes a time calibration module, a data acquisition module, a data demodulation module, a data preliminary screening module, ADC, DMA, UART and an external interrupt EXTI.

10. A node-type slope monitoring system as claimed in claim 8, characterized in that: The monitoring node also includes a cable and a packaging shell.

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