Exploration robot platform based on microtremor survey technology and exploration method

Abstract

An exploration robot platform based on a microtremor survey technology for detecting unknown underground geological bodies in urban environments. The platform includes a robot system configured to con

Description

EXPLORATION ROBOT PLATFORM BASED ON MICROTREMOR SURVEY TECHNOLOGY AND EXPLORATION METHOD CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] The present invention claims priority benefits to Chinese Patent Application number 202410072804.6, entitled “EXPLORATION ROBOT PLATFORM BASED ON MICROTREMOR SURVEY TECHNOLOGY AND EXPLORATION METHOD”, filed on January 17th, 2024, with the China National Intellectual Property Administration (CNIPA), the entire contents of which are incorporated herein by reference. TECHNICAL FIELD

[0002] The present invention relates to the technical field of exploring unknown underground geological bodies in urban environments, and in particular to an exploration robot platform based on a microtremor survey technology and an exploration method. BACKGROUND

[0003] The description in this part only provides background technical information related to the present invention and does not necessarily constitute the prior art.

[0004] Nowadays, geophysical exploration is an essential part of underground engineering construction. Scientific and reasonable exploration of the construction area is of great significance to ensuring smooth construction and improving the personal safety of construction personnel. At present, conventional geophysical exploration methods still have many problems as follows when carrying out work in urban areas.

[0005] 1. There are many unfavorable conditions for conducting geophysical exploration in urban environments, such as, the narrow roads and sites in cities are not conducive to the deployment of exploration instruments; moreover, there are many vehicles and pedestrians, and dense underground pipelines. Commonly used geophysical exploration methods are susceptible to electromagnetic interference and vibration interference. The ground penetrating radar method has high resolution, but its detection depth is small and it is susceptible to interference from electromagnetic signals, buildings, and other sources. The high-density electrical method has a great detection depth, but the cost is relatively high, the narrow urban roads are not conducive to carrying out exploration by adopting the high-density electrical method, the operation is inconvenient to perform, the grounding effect is poor, and the detection effect is poor. The electromagnetic method has a great detection depth and a good detection effect on goaf, but it is susceptible to electromagnetic interference.

[0006] 2. At present, the microtremor survey technology is a novel geophysical exploration technology that does not require artificial sources. By detecting microtremor signals from the Earth or surrounding environments, the development of underground unfavorable geological bodies (such as goaf) can be explored, so as to provide geological safety guarantees for subway design and construction. At present, microtremor survey requires the use of a specific array (such as triangular or circular array) to observe microtremor data from natural sources. However, manual deployment of detectors is often used, which has the problems of low accuracy and efficiency, and long exploration time, thus greatly increasing the impact on urban road traffic.

[0007] 3. The commonly used process for microtremor survey nowadays is to firstly manually deploy detectors, store the microtremor signal data obtained through exploration in a storage card, then remove the storage card after exploration is completed, manually process the data, and then perform interpretation. If the data accuracy is low due to various factors such as array selection and detector deployment in the detection process, manual re-exploration is required. The entire process is timeconsuming and laborious, and the various processes cannot be organically coordinated in real time in exploration.

[0008] 4. At present, the interpretation and evaluation of the microtremor signal data are often done manually, which makes the interpretation and evaluation processes overly dependent on professional knowledge and engineering experience, resulting in significant errors. In addition, manual interpretation and evaluation require a lot of time and effort, prolonging the exploration time will further exacerbate the impact on urban road traffic, and the exploration process is highly subjective and cannot yet achieve intelligence.

[0009] In summary, the current geophysical exploration process in urban environments has drawbacks such as long time, low efficiency, cumbersome process, and significant result errors. Therefore, how to achieve convenient application of the microtremor survey technology and efficient processing of detected signals in the exploration process has become an urgent technical problem that needs to be solved by the existing technology. SUMMARY

[0010] In view of the defects of the existing technology, the purpose of the present invention is to provide an exploration robot platform based on a microtremor survey technology and an exploration method. On the one hand, signal detection and data processing are organically combined to achieve real-time detection, real-time transmission, real-time processing, and real-time evaluation, thus improving the signal processing efficiency. On the other hand, the microtremor survey technology is combined with the robot technology, and processes such as array deployment attitude control, real-time transmission of microtremor data, denoising preprocessing, and data interpretation are made intelligent to achieve organic coordination of various processes of microtremor survey, thus effectively improving the levels of intelligence, mechanization, and precision.

[0011] In order to realize the above purpose, the present invention is implemented by adopting the following technical solutions:

[0012] According to a first aspect, the present invention provides an exploration robot platform based on a microtremor survey technology, including:

[0013] a robot system configured to control movement of a detection robot and detect a microtremor signal, and further configured to preprocess the detected original microtremor signal, store the original microtremor signal and preprocessed data, and transmit the preprocessed data to a data processing system;

[0014] the data processing system configured to receive the microtremor signal data transmitted by the robot system and process the microtremor signal data, and further configured to transmit inputted survey line data to the robot system, where microtremor signal data processing includes one or more of data query, editing, storage, analysis, interpretation, and image recognition; and

[0015] an instant data transmission system configured to realize information interaction between the robot system and the data processing system, instantly transmit a data command inputted by the data processing system to the robot system, and instantly transmit the microtremor signal data detected by the robot system to the data processing system.

[0016] Further, the robot system includes a movement control module, an attitude control module, a microtremor detection module, a signal preprocessing module, and a storage module, the movement control module is configured to control the movement state of the robot, the attitude control module is configured to control and adjust the attitude of the robot, the microtremor detection module is configured to detect an underground microtremor signal and check whether an array and each detector function are normal, the signal preprocessing module is configured to preprocess the detected microtremor signal, and the storage module is configured to store various data and cooperate with a cloud server for backup.

[0017] Further, the movement control module includes a positioning submodule, an intelligent anti-collision submodule, and a survey line data processing submodule, the positioning submodule is configured to complete positioning work during detection by the robot, the intelligent anti-collision submodule is configured to detect obstacles around the detection robot in an exploration process, warn the robot and assist the robot in making a timely adjustment to avoid collision, and the survey line data processing submodule is configured to receive a detection command from the data processing system through the instant data transmission system, store and manage survey points and survey lines during movement for exploration by the detection robot, and transmit a real-time movement path of the detection robot back to the data processing system.

[0018] Further, the attitude control module includes a robot detection attitude selfstabilization submodule and an array deployment attitude self-stabilization submodule, and the robot detection attitude self-stabilization submodule and the array deployment attitude self-stabilization submodule cooperate with each other to dynamically adjust the length of each telescopic rod and the orientation of a rotating support, so as to realize adaptive balance between a robot movement process and an array detection process.

[0019] Further, the robot detection attitude self-stabilization submodule includes a third telescopic rod, a fourth telescopic rod, a fifth telescopic rod, a first supporting arm, a second supporting arm, the rotating support, a third connecting rod, and a fourth connecting rod, one side of the third connecting rod is fixedly connected with a robot body, the other side of the third connecting rod is connected with the third telescopic rod, the third telescopic rod is connected with the first supporting arm and the fourth connecting rod through a rotating joint, a lower part of the fourth connecting rod is connected with the fifth telescopic rod, and the other side of the first supporting arm is fixedly connected with the second supporting arm and the fourth telescopic rod through a rotating joint.

[0020] Further, the array deployment attitude self-stabilization submodule includes a first telescopic rod and a second telescopic rod, and the array deployment attitude selfstabilization submodule dynamically adjusts the lengths of the first telescopic rod and the second telescopic rod according to a terrain, and cooperates with the robot detection attitude self-stabilization submodule to realize the attitude adjustment of the detection robot.

[0021] Further, the microtremor detection module includes a first preamplifier, a first connecting rod, a main amplifier, a filter, and an array, an upper part of the filter is fixedly connected with a robot body, a lower part of the filter is fixedly connected with the main amplifier, an upper part of the preamplifier is fixedly connected with the first connecting rod and is fixedly connected with the main amplifier through the first connecting rod, a lower part of the first connecting rod is fixedly connected with the first telescopic rod, and a lower part of the first telescopic rod is fixedly connected with the array.

[0022] Further, the data processing system includes a data management module, a signal reprocessing module, a signal interpretation module, and an intelligent recognition module, the data management module is configured to view, edit, and store data, the signal reprocessing module is configured to perform re-denoising processing on the microtremor signal data transmitted by the robot system, the signal interpretation module is configured to extract a dispersion curve from the microtremor signal data processed by the signal reprocessing module, and perform inversion imaging to form a geological model image to determine an underground geological body, and the intelligent recognition module is configured to perform intelligent recognition on the geological model image obtained by the signal interpretation module by using a deep learning method, and mark the type and position of a detected unfavorable geological body.

[0023] Further, the data management module includes a survey line management submodule and a data management submodule, the survey line management submodule is configured to view, edit, and store survey line data, and transmit the survey line data to the robot system in real time through the instant data transmission system, the survey line data include detected area survey points, survey lines, and robot movement trajectories, and the data management submodule is configured to view, edit, and store the microtremor signal data transmitted by the instant data transmission system.

[0024] According to a second aspect, the present invention provides an exploration method using the exploration robot platform based on the microtremor survey technology according to the first aspect, including:

[0025] determining survey lines and survey points according to a detected area, and controlling the detection robot to automatically perform geophysical exploration;

[0026] performing microtremor signal exploration according to predetermined survey lines and survey points or through manual control, and monitoring surrounding environments in real time in a movement process of the detection robot to avoid monitored obstacles;

[0027] controlling the detection robot to make an attitude adjustment when the robot reaches a designated survey point, so that detectors effectively fit the detected ground to perform microtremor signal acquisition;

[0028] performing signal acquisition at a next predetermined survey point after the microtremor signal acquisition is completed;

[0029] preprocessing and transmitting the microtremor signals detected by the detectors to the data processing system after completing the detection on the survey line where the current survey point is located, and performing further reprocessing, interpretation, and intelligent image recognition on the detected microtremor signals by using a deep learning method;

[0030] in a case that the data accuracy of the obtained microtremor signals is poor, calling robot movement, robot attitude and array attitude correction data in the storage system in advance to perform re-detection on the detected survey line; and

[0031] performing microtremor signal detection on a next predetermined survey line until exploration on all survey lines is completed.

[0032] The above one or more technical solutions have the following beneficial effects:

[0033] The present invention discloses an exploration robot platform based on a microtremor survey technology and an exploration method. On the one hand, signal detection and data processing are organically combined to achieve real-time detection, real-time transmission, real-time processing, and real-time evaluation, thus improving the exploration efficiency. On the other hand, the microtremor survey technology is combined with the robot technology, and processes such as array deployment attitude control, real-time transmission of microtremor data, denoising preprocessing, and data interpretation are made intelligent to achieve organic coordination of various processes of microtremor survey, thus effectively improving the levels of intelligence, mechanization, and precision. The present invention has the advantages of high efficiency, high precision, high applicability, and high level of intelligence.

[0034] The advantages of the additional aspects of the present invention will be set forth in part in the description below, which will become apparent from the description below, or will be understood by the practice of the present invention. BRIEF DESCRIPTION OF DRAWINGS

[0035] The accompanying drawings of the description, which form a part of the present invention, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to describe the present invention, instead of constituting an improper limitation to the present invention.

[0036] FIG. 1 is a structural diagram of an exploration robot platform based on a microtremor survey technology according to Embodiment 1 of the present invention.

[0037] FIG. 2 is a schematic diagram of an overall apparatus of an exploration robot based on a microtremor survey technology according to Embodiment 1 of the present invention.

[0038] FIG. 3 is a schematic structural diagram of a microtremor detection module of an exploration robot based on a microtremor survey technology according to Embodiment 1 of the present invention.

[0039] FIG. 4 is a flowchart of an exploration method using an exploration robot based on a microtremor survey technology according to Embodiment 2 of the present invention.

[0040] Description of reference signs: 11-robot body, Ill-mechanical leg, 112-GPS signal receiver, 113-high-definition camera, 114-laser radar, 115-instant data transmission system, 12-central control computer, 13-microtremor detection module, 131-first preamplifier, 132-first connecting rod, 133-main amplifier, 134-filter, 135-array, 1351-fixed rod, 1352-fixed plate, 1353-second connecting rod, 1354-second preamplifier, 1355-detector, 1356-circular support, 14-attitude control module, 141-robot detection attitude self-stabilization submodule, 1411-third telescopic rod, 1412-fourth telescopic rod, 1413-fifth telescopic rod, 1414-first supporting arm, 1415-second supporting arm, 1416-rotating support, 1417-third connecting rod, 1418-fourth connecting rod, 142-array deployment attitude self-stabilization submodule, 1421-first telescopic rod, 1422-second telescopic rod, and 15-storage module. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0041] The following detailed descriptions are exemplary and are intended to provide further description of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those of ordinary skill in the art to which the present invention belongs.

[0042] It should be noted that the terms used here are only for describing specific implementations and are not intended to limit exemplary implementations according to the present invention. As used here, unless otherwise explicitly stated in the context, the singular form is also intended to include the plural form. In addition, it should further be understood that when the terms "include" and / or "comprise" are used in this description, they indicate the existence of features, steps, operations, devices, components, and / or combinations thereof.

[0043] Embodiment 1:

[0044] Embodiment 1 of the present invention provides an exploration robot platform based on a microtremor survey technology. With the continuous development of the robot technology, combining the geophysical exploration technology with the robot technology has become an important means to cope with various complex conditions in geophysical exploration. As a novel geophysical technology, the present invention addresses the existing shortcomings of long time, low efficiency, cumbersome process, and large result errors in the geophysical exploration process in urban environments. On the one hand, the robot platform is combined with the microtremor survey technology, thus effectively overcoming the limitations of other geophysical methods in application of complex field sources, achieving less external interference, greater detection depth, and high resolution, and not only reducing the exploration cost, but also effectively improving the deployment efficiency and reducing the impact on urban traffic. On the other hand, processes such as microtremor signal acquisition, signal transmission, signal processing, signal interpretation, and signal evaluation are made intelligent to achieve organic coordination of various processes of microtremor survey, thus effectively improving the exploration accuracy and ensuring the exploration efficiency.

[0045] The specific implementation process in this embodiment will be described below in detail.

[0046] As shown in FIG. 1, an exploration robot platform based on a microtremor survey technology includes a robot system, a data processing system, and an instant data transmission system 115.

[0047] The robot system is configured to control movement of a detection robot and detect a microtremor signal, and further configured to preprocess the detected original microtremor signal, store the original microtremor signal and preprocessed data for subsequent query by working personnel, and transmit the preprocessed data to the data processing system.

[0048] In this embodiment, the robot system acts on an exploration robot apparatus. As shown in FIG. 2, the exploration robot apparatus includes a robot body 11 and a central control computer 12.

[0049] In a specific implementation, the robot body 11 is a high-carrying-capacity robot that may be equipped with a suspension apparatus. The robot body is installed with multiple mechanical legs 111. The mechanical legs 111 are symmetrically installed around the robot body 11 and can meet the carrying capacity of the detection robot to carry an array for detection.

[0050] The robot body 11 is equipped with and surrounded by high-definition cameras 113 and laser radar 114. The high-definition cameras 113 are symmetrically distributed in the front and back. The high-definition cameras 113 and the laser radar 114 are configured to accurately position survey points and survey lines, improve the detection accuracy, and assist in detecting surrounding objects to avoid collision. The robot body 11 is further provided with a GPS signal receiver 112. The GPS signal receiver 112 is located at a top of the robot body and is configured to receive a GPS signal to achieve robot positioning.

[0051] The central control computer 12 may be configured to receive control data transmitted from the data processing system at the position of the working personnel, including, but not limited to, robot movement path, survey points, and survey lines, participate in the control and coordination of various processes of microtremor signal detection, including the acquisition, processing, and storage of microtremor signals, and control the stability of the robot detection attitude and the array deployment attitude.

[0052] The robot body further includes motors and a servo system, which are configured to provide driving force to drive the movement and attitude adjustment of the robot. The motors may be DC motors, stepping motors, or servo motors. The motors may be installed near the components that need to be driven, such as legs or joints, and controlled by the central control computer.

[0053] The robot system includes a movement control module, an attitude control module 14, a microtremor detection module 13, a signal preprocessing module, and a storage module 15. The movement control module is configured to control the movement state of the robot. The attitude control module 14 is configured to control and adjust the attitude of the robot. The microtremor detection module 13 is configured to detect an underground microtremor signal and check whether an array and each detector function are normal. The signal preprocessing module is configured to preprocess the detected microtremor signal. The storage module 15 is configured to store various data and cooperate with a cloud server for backup.

[0054] In this embodiment, the movement control module includes a positioning submodule, an intelligent anti-collision submodule, and a survey line data processing submodule. The positioning submodule is configured to complete positioning work during detection by the robot. The intelligent anti-collision submodule is configured to detect obstacles around the detection robot in an exploration process, warn the robot and assist the robot in making a timely adjustment to avoid collision. The survey line data processing submodule is configured to receive a detection command from the data processing system through the instant data transmission system, to store and manage survey points and survey lines during movement for exploration by the detection robot, and to transmit a real-time movement path of the detection robot back to the data processing system.

[0055] In a specific implementation, the positioning submodule is a Global Positioning System (GPS), which is mounted on the robot body to achieve positioning work, perform positioning for detection by the robot, and perform detection according to predetermined survey points and designed survey lines. Moreover, the robot body may be equipped with an accelerometer and a gyroscope for auxiliary positioning. When this embodiment is used for underground parking lots, underground supermarkets, subways and other buildings (structures), a GPS signal amplifier may be equipped to enhance GPS positioning signals and improve positioning accuracy.

[0056] In a specific implementation, the intelligent anti-collision submodule includes, but is not limited to, devices such as high-definition cameras, infrared sensors, and laser radar.

[0057] In this embodiment, the attitude control module 14 includes a robot detection attitude self-stabilization submodule 141 and an array deployment attitude selfstabilization submodule 142. The robot detection attitude self-stabilization submodule 141 and the array deployment attitude self-stabilization submodule 142 cooperate with each other to dynamically adjust the length of each telescopic rod and the orientation of a rotating support, so as to realize adaptive balance between a robot movement process and an array detection process.

[0058] In a specific implementation, the robot detection attitude self-stabilization submodule 141 includes a third telescopic rod 1411, a fourth telescopic rod 1412, a fifth telescopic rod 1413, a first supporting arm 1414, a second supporting arm 1415, the rotating support 1416, a third connecting rod 1417, and a fourth connecting rod 1418. One side of the third connecting rod 1411 is fixedly connected with a robot body 11. The other side of the third connecting rod is connected with the third telescopic rod 1411. The third telescopic rod 1411 is connected with the first supporting arm 1414 and the fourth connecting rod 1418 through a rotating joint. A lower part of the fourth connecting rod 1418 is connected with the fifth telescopic rod 1413. The other side of the first supporting arm 1414 is fixedly connected with the second supporting arm 1415 and the fourth telescopic rod 1412 through a rotating joint. In this embodiment, the telescopic rods are slidable telescopic rods, or other existing types of telescopic rods may be selected according to the actual situation.

[0059] In the movement process of the detection robot, the high-definition cameras and the laser radar mounted on the robot body monitor the surrounding environments in real time, including, but not limited to, terrain undulations, obstacles, etc. When the height of an obstacle exceeds a preset threshold, the central control computer transmits a control command to the robot detection attitude self-stabilization submodule and the array deployment attitude self-stabilization submodule. By dynamically adjusting the first telescopic rod, the second telescopic rod, the third telescopic rod, the fourth telescopic rod, the fifth telescopic rod, and the rotating support, the obstacle can be avoided and the movement stability can be improved. Specifically, control is performed according to the height of the obstacle. When the distance between the bottom of the robot array and the ground is less than the height of the obstacle, the first telescopic rod, the second telescopic rod, and the third telescopic rod are extended to increase the overall height of the apparatus to achieve the obstacle avoidance function, increase the rotation of the rotating support and cooperate with the robot detection attitude selfstabilization submodule to adjust various components to achieve the purposes of turning the direction and avoiding the obstacle.

[0060] When the detection robot apparatus reaches a survey point, the central control computer transmits an adjustment command to the robot detection attitude selfstabilization submodule. By reducing the length of the fifth telescopic rod and dynamically adjusting the lengths of the third telescopic rod and the fourth telescopic rod, the overall center of gravity of the detection robot apparatus is lowered, thus improving the stability of the apparatus during detection.

[0061] The array deployment attitude self-stabilization submodule 142 includes a first telescopic rod 1421 and a second telescopic rod 1422. The array deployment attitude self-stabilization submodule dynamically adjusts the lengths of the first telescopic rod 1421 and the second telescopic rod 1422 according to a terrain, and cooperates with the robot detection attitude self-stabilization submodule to realize the attitude adjustment of the detection robot. Specifically, when the detection robot apparatus reaches a survey point, the distances between the detectors and the ground are monitored by the laser radar provided at the four corners. When the difference in distance data measured at each point is greater than a preset threshold, the central control computer transmits an adjustment command to the array deployment attitude self-stabilization submodule to dynamically adjust the lengths of the first telescopic rod and the second telescopic rod according to the terrain, and cooperate with the robot detection attitude selfstabilization submodule to improve the detection stability and effectively improve the detection accuracy of microtremor signals.

[0062] In this embodiment, after the detection is completed, the central control computer transmits a movement command to the attitude control module. The first telescopic rod 1421 and the second telescopic rod 1422 are retracted. The third telescopic rod 1411, the fourth telescopic rod 1412, and the fifth telescopic rod 1413 are extended. The apparatus moves upwards as a whole to carry out the detection work at a next survey point.

[0063] In this embodiment, the microtremor detection module 13 includes a first preamplifier 131, a first connecting rod 132, a main amplifier 133, a filter 134, and an array 135. As shown in FIG. 3, the preamplifier and the main amplifier 133 are configured to amplify the detected microtremor signal. The filter 134 is configured to perform pre-filtering processing on the amplified microtremor signal to improve the accuracy of the microtremor signal. An upper part of the filter 134 is fixedly connected with a robot body 11. A lower part of the filter is fixedly connected with the main amplifier 133. An upper part of the first preamplifier 131 is fixedly connected with the first connecting rod 132 and is fixedly connected with the main amplifier 133 through the first connecting rod 132. A lower part of the first connecting rod 132 is fixedly connected with the first telescopic rod 1421. A lower part of the first telescopic rod 1421 is fixedly connected with the array 135.

[0064] The array 135 includes fixed rods 1351, a fixed plate 1352, a second connecting rod 1353, a second preamplifier 1354, detectors 1355, and circular supports 1356.

[0065] In a specific implementation, the number of the detectors is seven, and the detectors are distributed at the corners, the midpoints of each side, and the center of gravity. The array is an embedded triangle. It should be noted that in this embodiment, the shape of the array includes, but is not limited to, an embedded triangle, and different array deployment methods may be selected according to different detection conditions.

[0066] Upper parts of the detectors at each corner and midpoint of each side are fixedly connected with the fixed rods sequentially through the second telescopic rod, the second preamplifier, and the second connecting rod. An upper part of the detector at the center of gravity is fixedly connected with the fixed plate sequentially through the second telescopic rod, the second preamplifier, and the second connecting rod. The fixed plate and the fixed rods are fixedly connected as a whole. The array is embedded with a flexible cable sleeve to achieve the transmission of microtremor signal data.

[0067] In this embodiment, detector supports are circular supports, which are suitable for urban road detection and will not affect the coupling effect, including, but not limited to, the only circular support in this embodiment, and may be selected according to different geological environmental conditions during detection.

[0068] In this embodiment, the signal preprocessing module includes a preamplifier, a main amplifier, and a filter, which are configured to amplify and filter the detected microtremor signal to improve the detection accuracy of the signal.

[0069] In this embodiment, the storage module is configured to store the detected microtremor signal data, preprocessed microtremor signal data, attitude selfstabilization data in an attitude control system, survey lines, movement paths, GPS data, etc., and to cooperate with a cloud server for backup. Moreover, the data are transmitted to the data processing system through the instant data transmission system for subsequent viewing and analysis by the working personnel.

[0070] The data processing system is configured to receive the microtremor signal data transmitted by the robot system and process the microtremor signal data, and further configured to transmit inputted survey line data to the robot system. Microtremor signal data processing includes one or more of data query, editing, storage, analysis, interpretation, and image recognition.

[0071] In this embodiment, the data processing system includes a data management module, a signal reprocessing module, a signal interpretation module, and an intelligent recognition module. The data management module is configured to view, edit, and store data. The data may be detected area survey points and survey lines, microtremor signal data obtained through detection, etc. The signal reprocessing module is configured to perform re-denoising processing on the microtremor signal data transmitted by the robot system, so as to further improve the accuracy of the microtremor signal data. The signal interpretation module is configured to extract a dispersion curve from the microtremor signal data processed by the signal reprocessing module, and perform inversion imaging to form a geological model image to determine an underground geological body. The intelligent recognition module is configured to perform intelligent recognition on the geological model image obtained by the signal interpretation module by using a deep learning method, and mark the type and position of a detected unfavorable geological body.

[0072] The data management module includes a survey line management submodule and a data management submodule. The survey line management submodule is configured to view, edit, and store survey line data, and transmit the survey line data to the robot system in real time through the instant data transmission system. The survey line data include detected area survey points, survey lines, and robot movement trajectories. The data management submodule is configured to view, edit, and store the microtremor signal data transmitted by the instant data transmission system.

[0073] In a specific implementation, the processing and interpretation of the data and the recognition of unfavorable geological bodies in geophysical exploration work are often manually completed, which makes the evaluation of signal data often dependent on the knowledge level and practical experience of the working personnel, resulting in significant errors. This embodiment introduces the deep learning method into the processing and evaluation of the signal and the intelligent recognition of the inverted image, thus effectively reducing errors caused by human factors and improving the levels of detection intelligence and precision. Specific steps are as follows:

[0074] In the signal reprocessing module, the specific steps of performing re-denoising processing on the microtremor signal data transmitted by the robot system include the following steps:

[0075] 1. The microtremor signal is decomposed by using an empirical mode decomposition method to obtain an intrinsic mode function (IMF) component of each order.

[0076] 2. A multiscale entropy (MSE) value of the IMF component of each order is calculated. An MSE algorithm has the advantages of strong noise and interference resistance, and good consistency, and can be applied to microtremor signal data processing.

[0077] 3. A second-order difference of the MSE is calculated to obtain positions corresponding to the maximum value XI and the minimum value X2. IMF components greater than XI are considered to be mostly noise and are directly removed. IMF components smaller than X2 are considered to be effective microtremor signals and are all retained. For IMF components within a range from XI to X2, a soft threshold function is adopted for further denoising processing.

[0078] 4. The microtremor signals after denoising processing are obtained.

[0079] In the signal interpretation module, the specific steps of extracting a dispersion curve from the microtremor signal data processed by the signal reprocessing module, and performing inversion imaging to form a geological model image to determine an underground geological body include the following steps:

[0080] 1. For the microtremor signal processed by the signal reprocessing module, a dispersion curve is extracted by adopting (including but not limited to) an extended spatial autocorrelation (ESPAC) method. The specific process includes converting microtremor data into a power spectrum-frequency image, converting the power spectrum-frequency image into a spatial autocorrelation (SPAC) function-frequency image, converting the SPAC function-frequency image into an SPAC coefficienthorizontal distance image, and converting the SPAC coefficient-horizontal distance image into a dispersion curve (Vr-f, where Vr is Rayleigh wave phase velocity and f is frequency).

[0081] 2. Mathematical transformation is performed on the obtained dispersion curve by converting the Rayleigh wave phase velocity Vr into apparent S-wave velocity.

[0082] 3. Imaging is performed to obtain a depth-horizontal distance apparent S-wave velocity slope surface, thus obtaining a geological model image.

[0083] In the intelligent recognition module, the specific steps of performing intelligent recognition on the geological model image obtained by the signal interpretation module by using a deep learning method, and marking the type and position of a detected unfavorable geological body include the following steps:

[0084] 1. Size processing is performed on the microtremor signal image containing the unfavorable geological body transmitted by the signal interpretation module through a faster region-based convolutional neural network (Faster R-CNN), so as to meet the requirement of the network on the size consistency of inputted images.

[0085] 2. Features of the inputted microtremor signal image are extracted by using a feature extraction network. The feature extraction network is composed of a convolutional layer, a pooling layer, and a rectified linear unit activation layer.

[0086] 3. The generated feature map is inputted into a region proposal network (RPN). In addition, regions of interest selected by the RPN are pooled into fixed-length vectors through region of interest pooling (ROI Pooling) to generate a fixed-size proposed region feature map.

[0087] 4. Classification and regression are performed on the generated proposed region feature map to obtain and mark the type of the recognized specific unfavorable geological body.

[0088] The instant data transmission system is configured to realize information interaction between the robot system and the data processing system, instantly transmit a data command inputted by the data processing system to the robot system, and instantly transmit the microtremor signal data detected by the robot system to the data processing system.

[0089] In a specific implementation, the instant data transmission system is mounted on the robot body and adopts a 5G transmission technology (fifth generation mobile communication technology). 5G transmission provides a higher bandwidth, supports a faster data transmission rate, and has the advantages of lower transmission delay, better coverage and penetration, high rate, real-time performance, and high adaptability.

[0090] Embodiment 2:

[0091] Embodiment 2 of the present invention provides an exploration method using the exploration robot platform based on the microtremor survey technology according to Embodiment 1. As shown in FIG. 4, the exploration method includes the following steps.

[0092] In SI, survey lines and survey points are determined according to a detected area, and the detection robot is controlled to automatically perform geophysical exploration. Specifically, firstly survey lines and survey points are determined according to a detected area, and then the coordinates of the determined survey lines and survey points are inputted into the survey line management submodule and transmitted to the exploration robot through the instant data transmission system, so that the exploration robot performs geophysical exploration automatically, or the exploration robot is manually controlled to perform geophysical exploration.

[0093] In S2, microtremor signal exploration is performed according to predetermined survey lines and survey points or through manual control, and surrounding environments are monitored in real time in a movement process of the detection robot to avoid monitored obstacles. Specifically, the laser radar and high-definition cameras mounted on the detection robot monitor surrounding environments in real time in the movement process of the detection robot. When the height of an obstacle exceeds a preset threshold, the robot detection attitude self-stabilization submodule dynamically adjusts the third telescopic rod, the fourth telescopic rod, the fifth telescopic rod, and the rotating support to avoid the obstacle.

[0094] In S3, the detection robot is controlled to make an attitude adjustment when the robot reaches a designated survey point, so that detectors effectively fit the detected ground to perform microtremor signal acquisition. Specifically, when the detection robot reaches a designated survey point, the central control computer transmits a control command to the attitude control system. The robot detection attitude self-stabilization submodule dynamically adjusts the third telescopic rod, the fourth telescopic rod, and the fifth telescopic rod to lower the overall center of gravity of the apparatus. At the same time, the array deployment attitude self-stabilization submodule dynamically adjusts the first telescopic rod and the second telescopic rod to effectively fit the detectors to the detected ground to improve the detection stability and accuracy.

[0095] In S4, signal acquisition is performed at a next predetermined survey point after the microtremor signal acquisition is completed. Alternatively, the detection robot is manually operated to perform detection at a next survey point.

[0096] In S5, the microtremor signals detected by the detectors are preprocessed and transmitted to the data processing system after completing the detection on the survey line where the current survey point is located, and further reprocessing, interpretation and intelligent image recognition are performed on the detected microtremor signals by using a deep learning method.

[0097] Specifically, the microtremor signals detected by the detectors are preprocessed by the amplifiers and the filter after completing the detection on a survey line where the current survey point is located, and then transmitted to the data processing system. Further reprocessing, interpretation, and intelligent image recognition are performed on the detected microtremor signals by using a deep learning method, so as to achieve intelligence in the processes of processing microtremor data, interpreting microtremor data, and effectively recognize microtremor images. The obtained microtremor signal data are reprocessed by using an empirical mode decomposition algorithm, a multiscale sample entropy, and a soft threshold function. The processing and interpretation of the microtremor signals are performed by using an ESPAC method. At the same time, a Faster R-CNN deep learning algorithm is applied to the intelligent image recognition of microtremor signals to achieve instant intelligent recognition and positioning of unfavorable geological bodies in the image.

[0098] In S6, in a case that the data accuracy of the obtained microtremor signals is poor, re-detection may be performed on the detected survey line to improve the detection accuracy. In a re-detection process, robot movement, robot attitude and array attitude correction data in the storage system may be called in advance to perform redetection on the detected survey line to effectively improve the exploration efficiency. Alternatively, microtremor signal detection is performed on a next predetermined survey line until exploration on all survey lines is completed. Alternatively, the robot is manually operated to perform detection on a next survey line.

[0099] The steps involved in Embodiment 2 correspond to the steps in Embodiment 1. For the specific implementation, reference may be made to the relevant description in Embodiment 1.

[00100] Those skilled in the art should understand that the various modules or steps of the present invention may be implemented by using general-purpose computer devices. Alternatively, they may be implemented by using program codes executable by computing devices, so that they can be stored in storage devices for execution by computing devices, or may be implemented by separately making them into various integrated circuit modules, or making multiple modules or steps thereof into a single integrated circuit module. The present invention is not limited to any specific combination of hardware and software.

[00101] Although the specific embodiments of the present invention have been described with reference to the drawings, they do not limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without contributing any inventive labor based on the technical solution of the present invention still fall within the scope of protection of the present invention.

Claims

1. An exploration robot platform based on a microtremor survey technology, comprising:a robot system configured to control movement of a detection robot and detect a microtremor signal, and further configured to preprocess the detected original microtremor signal, store the original microtremor signal and preprocessed data, and transmit the preprocessed data to a data processing system;the data processing system configured to receive the microtremor signal data transmitted by the robot system and process the microtremor signal data, and further configured to transmit inputted survey line data to the robot system, wherein microtremor signal data processing comprises one or more of data query, editing, storage, analysis, interpretation, and image recognition; andan instant data transmission system configured to realize information interaction between the robot system and the data processing system, instantly transmit a data command inputted by the data processing system to the robot system, and instantly transmit the microtremor signal data detected by the robot system to the data processing system.

2. The exploration robot platform based on the microtremor survey technology according to claim 1, whereinthe robot system comprises a movement control module, an attitude control module, a microtremor detection module, a signal preprocessing module, and a storage module, the movement control module is configured to control the movement state of the robot, the attitude control module is configured to control and adjust the attitude of the robot, the microtremor detection module is configured to detect an underground microtremor signal and check whether an array and each detector function are normal, the signal preprocessing module is configured to preprocess the detected microtremor signal, and the storage module is configured to store various data and cooperate with a cloud server for backup.according to claim 2, wherein the movement control module comprises a positioning submodule, an intelligent anti-collision submodule, and a survey line data processing submodule, the positioning submodule is configured to complete positioning work during detection by the robot, the intelligent anti-collision submodule is configured to detect obstacles around the detection robot in an exploration process, warn the robot and assist the robot in making a timely adjustment to avoid collision, and the survey line data processing submodule is configured to receive a detection command from the data processing system through the instant data transmission system, store and manage survey points and survey lines during movement for exploration by the detection robot, and transmit a real-time movement path of the detection robot back to the data processing system.

4. The exploration robot platform based on the microtremor survey technology according to claim 2, wherein the attitude control module comprises a robot detection attitude self-stabilization submodule and an array deployment attitude self-stabilization submodule, and the robot detection attitude self-stabilization submodule and the array deployment attitude self-stabilization submodule cooperate with each other to dynamically adjust the length of each telescopic rod and the orientation of a rotating support, so as to realize adaptive balance between a robot movement process and an array detection process.

5. The exploration robot platform based on the microtremor survey technology according to claim 4, wherein the robot detection attitude self-stabilization submodule comprises a third telescopic rod, a fourth telescopic rod, a fifth telescopic rod, a first supporting arm, a second supporting arm, the rotating support, a third connecting rod, and a fourth connecting rod, one side of the third connecting rod is fixedly connected with a robot body, the other side of the third connecting rod is connected with the third telescopic rod, the third telescopic rod is connected with the first supporting arm and the fourth connecting rod through a rotating joint, a lower part of the fourth connecting rod is connected with the fifth telescopic rod, and the other side of the first supporting arm is fixedly connected with the second supporting arm and the fourth telescopic rod through a rotating joint.

6. The exploration robot platform based on the microtremor survey technology according to claim 4, wherein the array deployment attitude self-stabilization submodule comprises a first telescopic rod and a second telescopic rod, and the array deployment attitude self-stabilization submodule dynamically adjusts the lengths of the first telescopic rod and the second telescopic rod according to a terrain, and cooperates with the robot detection attitude self-stabilization submodule to realize the attitude adjustment of the detection robot.

7. The exploration robot platform based on the microtremor survey technology according to claim 2, wherein the microtremor detection module comprises a first preamplifier, a first connecting rod, a main amplifier, a filter, and an array, an upper part of the filter is fixedly connected with a robot body, a lower part of the filter is fixedly connected with the main amplifier, an upper part of the preamplifier is fixedly connected with the first connecting rod and is fixedly connected with the main amplifier through the first connecting rod, a lower part of the first connecting rod is fixedly connected with the first telescopic rod, and a lower part of the first telescopic rod is fixedly connected with the array.

8. The exploration robot platform based on the microtremor survey technology according to claim 1, wherein the data processing system comprises a data management module, a signal reprocessing module, a signal interpretation module, and an intelligent recognition module, the data management module is configured to view, edit, and store data, the signal reprocessing module is configured to perform re-denoising processing on the microtremor signal data transmitted by the robot system, the signal interpretation module is configured to extract a dispersion curve from the microtremor signal data processed by the signal reprocessing module, and perform inversion imaging to form a geological model image to determine an underground geological body, and the intelligent recognition module is configured to perform intelligent recognition on the geological model image obtained by the signal interpretation module by using a deep learning method, and mark the type and position of a detected unfavorable geological body.according to claim 8, wherein the data management module comprises a survey line management submodule and a data management submodule, the survey line management submodule is configured to view, edit, and store survey line data, and transmit the survey line data to the robot system in real time through the instant data transmission system, the survey line data comprise detected area survey points, survey lines, and robot movement trajectories, and the data management submodule is configured to view, edit, and store the microtremor signal data transmitted by the instant data transmission system.

10. An exploration method using the exploration robot platform based on the microtremor survey technology according to any one of claims 1 to 9, comprising:determining survey lines and survey points according to a detected area, and controlling the detection robot to automatically perform geophysical exploration;performing microtremor signal exploration according to predetermined survey lines and survey points or through manual control, and monitoring surrounding environments in real time in a movement process of the detection robot to avoid monitored obstacles;controlling the detection robot to make an attitude adjustment when the robot reaches a designated survey point, so that detectors effectively fit the detected ground to perform microtremor signal acquisition;performing signal acquisition at a next predetermined survey point after the microtremor signal acquisition is completed;preprocessing and transmitting the microtremor signals detected by the detectors to the data processing system after completing the detection on the survey line where the current survey point is located, and performing further reprocessing, interpretation, and intelligent image recognition on the detected microtremor signals by using a deep learning method;in a case that the data accuracy of the obtained microtremor signals is poor, calling robot movement, robot attitude and array attitude correction data in the storage system in advance to perform re-detection on the detected survey line; andperforming microtremor signal detection on a next predetermined survey line until

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