Environment monitoring and early warning method, device and equipment and computer readable storage medium

Abstract

The invention discloses an environment monitoring and early warning method, device and equipment and a computer readable storage medium, and belongs to the field of navigation and positioning. The environment monitoring and early warning method comprises the following steps: acquiring point cloud data of a target monitoring area along a railway, and constructing a three-dimensional point cloud map of the target monitoring area; calculating a current value of a target parameter corresponding to each target object based on the three-dimensional point cloud map; obtaining a reference value of a target parameter corresponding to each target object in the early warning category reference map; generating abnormal early warning information based on the reference value and the current value; wherein the target object is the object corresponding to the object type in the preset early warning category, and according to the method and the device, the external environment along the railway can be automatically monitored and early warned, and the early warning accuracy and efficiency can be improved.

Description

Technical Field

[0001] The present application relates to the field of navigation and positioning, and specifically to an environmental monitoring and early warning method, device, equipment and computer-readable storage medium. Background Art

[0002] With the continuous development of transportation, trains have become an important means of transportation in our lives. How to quickly and accurately identify hidden dangers in the environment along the railway has become an urgent problem to be solved.

[0003] In the relevant technology, there are two main ways to monitor the environment along the railway. One is to arrange cameras in a more special environment along the railway. The maintenance personnel in the area analyze the data collected by the observation cameras in the monitoring room to identify potential line intrusion hazards, thereby achieving a certain early warning effect; the other is to manually follow the vehicle to patrol the environment along the railway periodically, record the location points of possible line intrusion hazards, and then manually go to the location points where the line intrusion hazards exist again for verification.

[0004] However, both methods rely on manual assessment to determine whether there are potential line intrusion risks in the monitoring area, resulting in poor early warning accuracy and low efficiency. Summary of the invention

[0005] The present application provides an environmental monitoring and early warning method, device, equipment and computer-readable storage medium, which can solve the technical problems existing in the prior art that when monitoring the environment along the railway, the monitoring area mainly relies on manual assessment to determine whether there are hidden dangers of line intrusion, resulting in poor early warning accuracy and low efficiency.

[0006] In a first aspect, an embodiment of the present application provides an environmental monitoring and early warning method, comprising:

[0007] Obtain point cloud data of the target monitoring area along the railway and construct a three-dimensional point cloud map of the target monitoring area;

[0008] Based on the three-dimensional point cloud map, calculating the current value of the target parameter corresponding to each target object;

[0009] Obtain the reference value of the target parameter corresponding to each target object in the warning category reference map;

[0010] Generate abnormal warning information based on the reference value and the current value;

[0011] The target object is an object corresponding to an object type in a preset warning category.

[0012] In some embodiments, the process of constructing the warning category benchmark map includes:

[0013] Use the radar positioning and mapping system to construct a 3D point cloud reference map along the railway;

[0014] Based on the preset warning category, each target object in the three-dimensional point cloud reference map is calibrated to construct a warning category reference map.

[0015] In some embodiments, the radar positioning and mapping system is used to construct a three-dimensional point cloud reference map along the railway, including:

[0016] Time synchronization of the inertial navigation and radar deployed on the working vehicle;

[0017] Unify the coordinate systems of inertial navigation and radar;

[0018] The data collected by the inertial navigation system is input into the radar's positioning and mapping system, and combined with the original point cloud data collected by the radar to construct a three-dimensional point cloud reference map along the railway.

[0019] In some embodiments, the calibrating each target object in the three-dimensional point cloud reference image based on the preset warning category includes:

[0020] Based on the preset warning category, each target object in the three-dimensional point cloud reference image is respectively assigned a point cloud field, and the point cloud field of each target object is calibrated with category information, and the target object is an object corresponding to the object type in the preset warning category.

[0021] In some embodiments, the calculating the current value of the target parameter corresponding to each target object based on the three-dimensional point cloud map includes:

[0022] Segmenting each target object in the three-dimensional point cloud map to obtain an outer box for each target object;

[0023] Based on the edge value of the point cloud within the outer box, the current value of the target parameter corresponding to each target object is calculated.

[0024] In some embodiments, generating abnormal warning information based on the reference value and the current value includes:

[0025] Compare the reference value and the current value to obtain a comparison result;

[0026] When the comparison result does not meet the preset requirements, abnormal warning information is generated.

[0027] In some embodiments, if the target object is a utility pole, the target parameter corresponding to the target object is the falling distance, and the corresponding preset requirement is that the falling distance is less than a first preset threshold;

[0028] If the target object is a building, the target parameter corresponding to the target object is the straight-line distance, and the corresponding preset requirement is that the straight-line distance is less than a second preset threshold.

[0029] In a second aspect, an embodiment of the present application provides an environment monitoring and early warning device, the environment monitoring and early warning device comprising:

[0030] An acquisition and construction unit is used to acquire point cloud data of a target monitoring area along the railway and construct a three-dimensional point cloud map of the target monitoring area;

[0031] A calculation unit, used for calculating the current value of the target parameter corresponding to each target object based on the three-dimensional point cloud map;

[0032] An acquisition unit, used to acquire a reference value of a target parameter corresponding to each target object in the warning category reference map;

[0033] A generating unit, configured to generate abnormal warning information based on the reference value and the current value;

[0034] The target object is an object corresponding to an object type in a preset warning category.

[0035] In a third aspect, an embodiment of the present application provides an environmental monitoring and early warning device, which includes a processor, a memory, and an environmental monitoring and early warning program stored in the memory and executable by the processor, wherein when the environmental monitoring and early warning program is executed by the processor, the steps of the environmental monitoring and early warning method as described in any one of the first aspects are implemented.

[0036] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which an environmental monitoring and early warning program is stored, wherein when the environmental monitoring and early warning program is executed by a processor, the steps of the environmental monitoring and early warning method as described in any one of the first aspects are implemented.

[0037] The beneficial effects brought by the technical solution provided in the embodiments of the present application include:

[0038] First, by acquiring point cloud data of the target monitoring area along the railway, a three-dimensional point cloud map of the target monitoring area is constructed; secondly, based on the three-dimensional point cloud map, the current value of the target parameter corresponding to each target object is calculated; then, the baseline value of the target parameter corresponding to each target object in the warning category baseline map is obtained; further based on the baseline value and the current value, abnormal warning information is generated; wherein the target object is an object corresponding to the object type in the preset warning category, so as to realize automatic monitoring and warning of the external environment along the railway, which can improve the accuracy and efficiency of the warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1One of the flow diagrams of the environmental monitoring and early warning method provided by one embodiment of the present application;

[0040] Figure 2 A second flow chart of an environmental monitoring and early warning method provided in one embodiment of the present application;

[0041] Figure 3 A third flow chart of an environmental monitoring and early warning method provided in one embodiment of the present application;

[0042] Figure 4 A fourth flow chart of an environmental monitoring and early warning method provided in one embodiment of the present application;

[0043] Figure 5 A fifth flow chart of an environmental monitoring and early warning method provided in one embodiment of the present application;

[0044] Figure 6 A schematic diagram of the functional modules of an environmental monitoring and early warning device provided in one embodiment of the present application;

[0045] Figure 7 This is a schematic diagram of the hardware structure of the environmental monitoring and early warning device involved in the embodiment of the present application. DETAILED DESCRIPTION

[0046] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0047] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0048] In a first aspect, an embodiment of the present application provides an environmental monitoring and early warning method.

[0049] In some embodiments, reference Figure 1 , Figure 1 One of the flow charts of the environmental monitoring and early warning method provided by one embodiment of the present application is as follows: Figure 1 As shown, the environmental monitoring and early warning method comprises the following steps:

[0050] Step 110, step 120, step 130 and step 140. The method flow steps are only a possible implementation of the present application.

[0051] Step 110: Acquire point cloud data of the target monitoring area along the railway and construct a three-dimensional point cloud map of the target monitoring area;

[0052] In the specific implementation, for the target monitoring areas along the railway that require environmental monitoring and early warning, monitoring equipment is arranged on the top of the operating vehicle. Optionally, the monitoring equipment includes a radar and an inertial navigation. The monitoring equipment is used to periodically obtain point cloud data of the target monitoring area to construct a three-dimensional point cloud map of the target monitoring area.

[0053] Step 120: Calculate the current value of the target parameter corresponding to each target object based on the three-dimensional point cloud map; wherein the target object is an object corresponding to an object type in a preset warning category.

[0054] It is understandable that the relevant personnel pre-determine the warning categories according to the types of objects that need to be monitored and warned along the railway, and different object types correspond to different numbers and different warning plans. Among them, the types of objects that need to be monitored and warned include but are not limited to trees, electric poles, buildings, etc. If the target object is a electric pole, the target parameter corresponding to the target object is the falling distance; if the target object is a building, the target parameter corresponding to the target object is the straight-line distance.

[0055] In the specific implementation, the point cloud data of each target object in the three-dimensional point cloud map are packaged respectively to form a rectangular block corresponding to each target object, that is, an outer packaging box corresponding to each target object. Further, based on the outer packaging box corresponding to each target object, the current value of the target parameter corresponding to each target object is calculated.

[0056] In some embodiments, Figure 2 A second flow chart of an environmental monitoring and early warning method provided by an embodiment of the present application is as follows: Figure 2 As shown, the calculating the current value of the target parameter corresponding to each target object based on the three-dimensional point cloud map includes:

[0057] Step 210: segment each target object in the three-dimensional point cloud map to obtain an outer box of each target object;

[0058] Step 220: Calculate the current value of the target parameter corresponding to each target object based on the edge value of the point cloud in the outer box.

[0059] The current value of the target parameter corresponding to each target object represents the actual state of the target object, and the warning level can be determined by comparing the value with the corresponding threshold.

[0060] In a specific implementation, each target object in the three-dimensional point cloud map is segmented to obtain an outer box for each target object; it can be understood that the point cloud in the outer box has an edge value, and based on the edge value of the point cloud in the outer box, a preset algorithm is used to calculate the current value of the target parameter corresponding to each target object.

[0061] For example, if the target object is a utility pole, and the target parameter corresponding to the target object is the falling distance, the preset algorithm is to calculate the position of the highest and lowest points of the utility pole based on the center line of the track to determine the height of the utility pole; then, with the lowest point as the center of the circle, calculate the distance from the falling of the utility pole to the center line of the guide rail in the target monitoring area. The position of the highest and lowest points of the utility pole is determined by the edge value of the point cloud in the outer box.

[0062] In this embodiment, each target object in the three-dimensional point cloud map is first segmented to obtain an outer box for each target object; then, based on the edge value of the point cloud within the outer box, the current value of the target parameter corresponding to each target object is calculated to prepare for generating abnormal warning information.

[0063] Step 130, obtaining the reference value of the target parameter corresponding to each target object in the warning category reference map;

[0064] The warning category reference map is constructed based on the three-dimensional point cloud reference map along the railway, which can be obtained by calibrating the category information of each target object in the three-dimensional point cloud reference map. The three-dimensional point cloud reference map along the railway is constructed using a multi-radar positioning and mapping system.

[0065] When classifying the target objects in the three-dimensional point cloud reference map, the reference values ​​of the target parameters corresponding to the target objects in the warning class reference map are calculated synchronously. Therefore, the reference values ​​of the target parameters corresponding to the target objects in the warning class reference map can be directly obtained.

[0066] Step 140: Generate abnormal warning information based on the reference value and the current value;

[0067] By comparing the reference value with the current value, the change value of the target parameter can be determined. Based on the change value, in order to monitor the change trend of the target object, it can be inferred that there may be a potential risk of line violation in the future preset time period. In the case of a potential risk of line violation, abnormal warning information is generated. The abnormal warning information includes but is not limited to the change value of the target parameter corresponding to the target object, the kilometer mark, and the longitude and latitude.

[0068] Furthermore, the abnormal warning information may be pushed to an electronic device of a maintenance personnel in the target monitoring area, so that the maintenance personnel in the target monitoring area can respond to the abnormal warning information and verify the actual status of the target object in the target monitoring area.

[0069] In this embodiment, firstly, by acquiring point cloud data of the target monitoring area along the railway, a three-dimensional point cloud map of the target monitoring area is constructed; secondly, based on the three-dimensional point cloud map, the current value of the target parameter corresponding to each target object is calculated; then, the reference value of the target parameter corresponding to each target object in the warning category reference map is obtained; further based on the reference value and the current value, abnormal warning information is generated; wherein the target object is an object corresponding to the object type in the preset warning category, so as to realize automatic monitoring and warning of the external environment along the railway, which can improve the accuracy and efficiency of the warning.

[0070] In some embodiments, Figure 3 A third flow chart of an environmental monitoring and early warning method provided in an embodiment of the present application is as follows: Figure 3 As shown, the construction process of the warning category benchmark map includes:

[0071] Step 310: Use the radar positioning and mapping system to construct a three-dimensional point cloud reference map along the railway;

[0072] In the specific implementation, monitoring equipment is arranged on the top of the working vehicle. Optionally, the monitoring equipment includes multiple radars and an inertial navigation system. The multi-radar positioning and mapping system (Simultaneous localization and mapping, SLAM) is used for mapping processing to construct a multi-radar wide-angle, large-range, high-precision, and high-density three-dimensional point cloud reference map along the railway.

[0073] In some embodiments, Figure 4 A fourth flow chart of an environmental monitoring and early warning method provided in an embodiment of the present application is as follows: Figure 4 As shown, the radar positioning and mapping system is used to construct a three-dimensional point cloud reference map along the railway, including:

[0074] Step 410: time synchronization of the inertial navigation system and the radar arranged on the working vehicle;

[0075] In the specific implementation, multiple radars are connected to the host in the same network segment using an industrial switch, and Beidou signals are received through the Beidou communication module arranged in the operating vehicle. The received Beidou signals are solved and pulses per second (PPS) signals are output. The PPS signals are imported into the multiple radars and inertial navigation through the serial port or direct wiring, and the time information recorded in the multiple radars and inertial navigation is unified to Beidou time, thereby realizing time synchronization between multiple radars and inertial navigation.

[0076] Step 420, unifying the coordinate systems of the inertial navigation and radar;

[0077] In the specific implementation, the coordinate systems of the inertial navigation and radar are unified based on the multi-radar and inertial navigation external parameter calibration scheme under panoramic coordinates, and the longitude and latitude of the operating vehicle are obtained through the carrier phase difference technology (Real time kinematic, RTK). Based on the longitude and latitude of the operating vehicle, it is converted into a transverse Mercator projection coordinate system, and the transverse Mercator projection coordinate system is input into the multi-radar SLAM system to achieve the unification of the coordinate systems of the inertial navigation and radar, so that the posture changes received by the inertial navigation can be provided to the radar during the mapping process, thereby increasing the mapping accuracy.

[0078] Step 430: Input the data collected by the inertial navigation system into the positioning and mapping system of the radar, and combine it with the original point cloud data collected by the radar to construct a three-dimensional point cloud reference map along the railway.

[0079] Furthermore, after the coordinate systems of the inertial navigation and radar are unified, the data collected by the inertial navigation is input into the radar's positioning and mapping system in real time, and combined with the original point cloud data collected by the radar to achieve multi-source data fusion. While the industrial computer receives multi-source data, it constructs a high-precision, high-density, large-scale three-dimensional point cloud reference map along the railway in real time.

[0080] Specifically, based on the first information collected by the inertial navigation system, the state X of the vehicle is determined. The formula for determining the state of the vehicle is as follows:

[0081]

[0082] The first information includes: the vehicle's posture matrix R, translation matrix P, vehicle speed V, accelerometer b a and gyroscope noise b g , R∈SO(3), SO(3) is a Lie group.

[0083] Preferably, a tight combination strategy of graph optimization is adopted to fuse all sensors involved in the positioning and mapping task. The tight combination strategy refers to the use of multi-sensor observations to construct residuals, which are added to the graph optimization for joint optimization. The factor graph contains factors and nodes, where factors represent the observation inputs of various sensors, and nodes represent the status information of the vehicle. The factors in this embodiment include three types, namely, radar odometer factor, inertial measurement unit (IMU) pre-integration factor and RTK factor. Whenever the operating vehicle's running distance exceeds a threshold, a new pose node is added to the factor graph. While the entire maintained factor graph is updated, all node poses are optimized.

[0084] Since track inspection vehicles have a long operating time and long mileage, in order to ensure that the number of factors does not increase significantly over time and thus reduce operating efficiency, this embodiment uses a keyframe-based sliding window algorithm to maintain the number of factors involved in the optimization, thereby improving operating efficiency and stability. k The sliding window of key frames is used to determine the optimal posture of the working vehicle. The formula for determining the optimal posture of the working vehicle is as follows:

[0085]

[0086] in, is the marginal quantity, is the IMU pre-integration residual, is the radar odometer residual, is the track plane constraint, and Can be directly obtained through inertial navigation, IMU pre-integration residual Determined by the following formula:

[0087]

[0088] in, represents the IMU pre-integration residual from time k to k+1, representing the changes in displacement, velocity and attitude direction respectively; is the gravity factor, [·] 2∶4 Represents extracting the x, y, and z elements from a quaternion.

[0089] The calculation formula of radar odometer residual is as follows:

[0090]

[0091]

[0092]

[0093] in, and represents the correspondence calculation between any edge or plane feature point in the k+1th frame and the kth frame, P k w Represents the laser radar point cloud coordinates in the world coordinate system, {ε1 L w,ε2 L w} represents the edge point in the laser radar coordinate system, {ρ1 L w,ρ2 L w,ρ3 L w} represents a plane point in the laser radar coordinate system, and the radar odometer residual factor can be expressed as:

[0094]

[0095] Since the laser radar adopts a prism design, it does not return point cloud information within 0.5m, and the ranging error within 3 meters is higher than the decimeter level. These data are all unreliable data, so this embodiment selects points in each frame whose laser radar distance exceeds 3 meters to participate in the estimation.

[0096] Furthermore, the ikd-tree method can be used to optimize the three-dimensional point cloud reference map along the railway to improve the operating speed.

[0097] In this embodiment, first, the inertial navigation and radar arranged on the working vehicle are time synchronized; then the coordinate systems of the inertial navigation and radar are unified; further, the data collected by the inertial navigation is input into the positioning and mapping system of the radar, and combined with the original point cloud data collected by the radar, a three-dimensional point cloud reference map along the railway is constructed, in preparation for the construction of the warning category reference map.

[0098] Step 320: Based on the preset warning category, calibrate each target object in the three-dimensional point cloud reference map to construct a warning category reference map.

[0099] In specific implementation, based on the preset warning category, each target object in the three-dimensional point cloud reference image is assigned a point cloud field, and the point cloud field of each target object is calibrated with category information. The target object is an object corresponding to the object type in the preset warning category.

[0100] Exemplarily, if the target object is a utility pole, a point cloud field 1.0001 is assigned to the utility pole in the three-dimensional point cloud reference image, wherein the 1 before the decimal point represents a large category of utility poles, and the 001 after the decimal point represents the serial number of the utility pole.

[0101] In this embodiment, the radar positioning and mapping system is first used to construct a three-dimensional point cloud reference map along the railway. Then, based on the preset warning category, each target object in the three-dimensional point cloud reference map is calibrated to construct a warning category reference map. Further, based on the warning category reference map, the reference value of the target parameter corresponding to each target object can be determined. This prepares for the generation of abnormal warning information and can improve the accuracy and efficiency of the warning.

[0102] In some embodiments, Figure 5 A fifth flow chart of an environmental monitoring and early warning method provided in an embodiment of the present application is as follows: Figure 5 As shown, the generating of abnormal warning information based on the reference value and the current value includes:

[0103] Step 510: Compare the reference value and the current value to obtain a comparison result;

[0104] Step 520: If the comparison result does not meet the preset requirements, generate abnormal warning information.

[0105] In the specific implementation, the baseline value and the current value are first compared to obtain a comparison result; if the comparison result meets the preset requirements, it means that the target object does not have a risk of line invasion; if the comparison result does not meet the preset requirements, it means that the target object has a risk of line invasion; then, if the comparison result does not meet the preset requirements, an abnormal warning information is generated.

[0106] It can be understood that if the target object is a utility pole, the corresponding preset requirement is that the falling distance is less than the first preset threshold; if the target object is a building, the corresponding preset requirement is that the straight-line distance is less than the second preset threshold.

[0107] In this embodiment, a comparison result is first obtained by comparing the baseline value and the current value; then, when the comparison result does not meet the preset requirements, abnormal warning information is generated to automatically monitor and warn the external environment along the railway, thereby improving the accuracy and efficiency of the warning.

[0108] In a second aspect, an embodiment of the present application also provides an environmental monitoring and early warning device.

[0109] In some embodiments, reference Figure 6 , Figure 6 This is a functional module diagram of an environmental monitoring and early warning device provided by an embodiment of the present application. Figure 6 As shown, the environmental monitoring and early warning device includes:

[0110] An acquisition and construction unit 610 is used to acquire point cloud data of a target monitoring area along the railway and construct a three-dimensional point cloud map of the target monitoring area;

[0111] A calculation unit 620, configured to calculate a current value of a target parameter corresponding to each target object based on the three-dimensional point cloud map;

[0112] An acquisition unit 630 is used to acquire a reference value of a target parameter corresponding to each target object in the warning category reference map;

[0113] A generating unit 640, configured to generate abnormal warning information based on the reference value and the current value;

[0114] The target object is an object corresponding to an object type in a preset warning category.

[0115] In some embodiments, the process of constructing the warning category benchmark map includes:

[0116] Use the radar positioning and mapping system to construct a 3D point cloud reference map along the railway;

[0117] Based on the preset warning category, each target object in the three-dimensional point cloud reference map is calibrated to construct a warning category reference map.

[0118] In some embodiments, the radar positioning and mapping system is used to construct a three-dimensional point cloud reference map along the railway, including:

[0119] Time synchronization of the inertial navigation and radar deployed on the working vehicle;

[0120] Unify the coordinate systems of inertial navigation and radar;

[0121] The data collected by the inertial navigation system is input into the radar's positioning and mapping system, and combined with the original point cloud data collected by the radar to construct a three-dimensional point cloud reference map along the railway.

[0122] In some embodiments, the calibrating each target object in the three-dimensional point cloud reference image based on the preset warning category includes:

[0123] Based on the preset warning category, each target object in the three-dimensional point cloud reference image is respectively assigned a point cloud field, and the point cloud field of each target object is calibrated with category information, and the target object is an object corresponding to the object type in the preset warning category.

[0124] In some embodiments, the calculating the current value of the target parameter corresponding to each target object based on the three-dimensional point cloud map includes:

[0125] Segmenting each target object in the three-dimensional point cloud map to obtain an outer box for each target object;

[0126] Based on the edge value of the point cloud within the outer box, the current value of the target parameter corresponding to each target object is calculated.

[0127] In some embodiments, generating abnormal warning information based on the reference value and the current value includes:

[0128] Compare the reference value and the current value to obtain a comparison result;

[0129] When the comparison result does not meet the preset requirements, abnormal warning information is generated.

[0130] In some embodiments, if the target object is a utility pole, the target parameter corresponding to the target object is the falling distance, and the corresponding preset requirement is that the falling distance is less than a first preset threshold;

[0131] If the target object is a building, the target parameter corresponding to the target object is the straight-line distance, and the corresponding preset requirement is that the straight-line distance is less than a second preset threshold.

[0132] It should be noted here that the environmental monitoring and early warning device provided in the embodiment of the present application can implement all the method steps implemented in the above-mentioned environmental monitoring and early warning method embodiment, and can achieve the same technical effect. The parts and beneficial effects of this embodiment that are the same as those in the method embodiment will not be described in detail here.

[0133] It should be noted that each implementation method of the present application can be freely combined, the order can be changed, or it can be executed separately, and does not need to rely on or depend on a fixed execution order.

[0134] In a third aspect, an embodiment of the present application provides an environmental monitoring and early warning device, which may be a personal computer (PC), a laptop computer, a server, or other device with data processing capabilities.

[0135] Reference Figure 7 , Figure 7 Schematic diagram of the hardware structure of the environment monitoring and early warning device involved in the embodiment of the present application. In the embodiment of the present application, the environment monitoring and early warning device may include a processor, a memory, a communication interface and a communication bus.

[0136] The communication bus may be of any type and is used to interconnect the processor, the memory, and the communication interface.

[0137] The communication interface includes input / output (I / O) interface, physical interface and logical interface, etc., which are used to realize the interconnection of devices inside the environmental monitoring and early warning equipment, and the interface used to realize the interconnection between the environmental monitoring and early warning equipment and other devices (such as other computing devices or user devices). The physical interface can be an Ethernet interface, a fiber optic interface, an ATM interface, etc.; the user device can be a display, a keyboard, etc.

[0138] The memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0139] The processor may be a general-purpose processor, and the general-purpose processor may call the environmental monitoring early warning program stored in the memory, and execute the environmental monitoring early warning method provided by the embodiment of the present application. For example, the general-purpose processor may be a central processing unit (CPU). The method executed when the environmental monitoring early warning program is called may refer to the various embodiments of the environmental monitoring early warning method of the present application, and will not be repeated here.

[0140] Those skilled in the art will understand that Figure 7 The hardware structure shown in the figure does not constitute a limitation on the present application, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0141] In a fourth aspect, an embodiment of the present application also provides a computer-readable storage medium.

[0142] The computer-readable storage medium of the present application stores an environmental monitoring and early warning program, wherein when the environmental monitoring and early warning program is executed by a processor, the steps of the environmental monitoring and early warning method as described above are implemented.

[0143] Among them, the method implemented when the environmental monitoring and early warning program is executed can refer to the various embodiments of the environmental monitoring and early warning method of the present application, and will not be repeated here.

[0144] It should be noted that the serial numbers of the above-mentioned embodiments of the present application are only for description and do not represent the advantages or disadvantages of the embodiments.

[0145] The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices. The terms "first", "second" and "third" are used to distinguish different objects, etc., and do not represent a sequence, nor do they limit "first", "second" and "third" to different types.

[0146] In the description of the embodiments of the present application, "exemplary", "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary", "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary", "for example" or "for example" is intended to present related concepts in a specific way.

[0147] In the description of the embodiments of the present application, unless otherwise specified, “ / ” means or, for example, A / B can mean A or B; the “and / or” in the text is merely a description of the association relationship of associated objects, indicating that three relationships may exist, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, “multiple” refers to two or more than two.

[0148] In some processes described in the embodiments of the present application, multiple operations or steps that appear in a specific order are included, but it should be understood that these operations or steps may not be executed in the order in which they appear in the embodiments of the present application or in parallel, and the sequence number of the operation is only used to distinguish the different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed in sequence or in parallel, and these operations or steps may be combined.

[0149] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, disk, CD) as described above, and includes a number of instructions for a terminal device to execute the methods described in each embodiment of the present application.

[0150] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. An environmental monitoring and early warning method, characterized in that: The environmental monitoring and early warning method comprises: Obtain point cloud data of the target monitoring area along the railway and construct a three-dimensional point cloud map of the target monitoring area; Based on the three-dimensional point cloud map, calculating the current value of the target parameter corresponding to each target object; Obtain the reference value of the target parameter corresponding to each target object in the warning category reference map; Generate abnormal warning information based on the reference value and the current value; The target object is an object corresponding to an object type in a preset warning category.

2. The environmental monitoring and early warning method according to claim 1, characterized in that: The construction process of the warning category benchmark map includes: Use the radar positioning and mapping system to construct a 3D point cloud reference map along the railway; Based on the preset warning category, each target object in the three-dimensional point cloud reference map is calibrated to construct a warning category reference map.

3. The environmental monitoring and early warning method according to claim 2, characterized in that: The radar positioning and mapping system is used to construct a three-dimensional point cloud reference map along the railway, including: Time synchronization of the inertial navigation and radar deployed on the working vehicle; Unify the coordinate systems of inertial navigation and radar; The data collected by the inertial navigation system is input into the radar's positioning and mapping system, and combined with the original point cloud data collected by the radar to construct a three-dimensional point cloud reference map along the railway.

4. The environmental monitoring and early warning method according to claim 2, characterized in that: The calibrating each target object in the three-dimensional point cloud reference image based on the preset warning category includes: Based on the preset warning category, each target object in the three-dimensional point cloud reference image is respectively assigned a point cloud field, and the point cloud field of each target object is calibrated with category information, and the target object is an object corresponding to the object type in the preset warning category.

5. The environmental monitoring and early warning method according to claim 1, characterized in that: The calculating, based on the three-dimensional point cloud map, the current value of the target parameter corresponding to each target object comprises: Segmenting each target object in the three-dimensional point cloud map to obtain an outer box for each target object; Based on the edge value of the point cloud within the outer box, the current value of the target parameter corresponding to each target object is calculated.

6. The environmental monitoring and early warning method according to claim 1, characterized in that: The generating abnormal warning information based on the reference value and the current value includes: Compare the reference value and the current value to obtain a comparison result; When the comparison result does not meet the preset requirements, abnormal warning information is generated.

7. The environmental monitoring and early warning method according to claim 6, characterized in that: If the target object is a utility pole, the target parameter corresponding to the target object is the falling distance, and the corresponding preset requirement is that the falling distance is less than a first preset threshold; If the target object is a building, the target parameter corresponding to the target object is the straight-line distance, and the corresponding preset requirement is that the straight-line distance is less than a second preset threshold.

8. An environmental monitoring and early warning device, characterized in that: The environmental monitoring and early warning device comprises: An acquisition and construction unit is used to acquire point cloud data of a target monitoring area along the railway and construct a three-dimensional point cloud map of the target monitoring area; A calculation unit, used for calculating the current value of the target parameter corresponding to each target object based on the three-dimensional point cloud map; An acquisition unit, used to acquire a reference value of a target parameter corresponding to each target object in the warning category reference map; A generating unit, configured to generate abnormal warning information based on the reference value and the current value; The target object is an object corresponding to an object type in a preset warning category.

9. An environmental monitoring and early warning device, characterized in that: The environmental monitoring and early warning device includes a processor, a memory, and an environmental monitoring and early warning program stored in the memory and executable by the processor, wherein when the environmental monitoring and early warning program is executed by the processor, the steps of the environmental monitoring and early warning method as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores an environmental monitoring and early warning program, wherein when the environmental monitoring and early warning program is executed by the processor, the steps of the environmental monitoring and early warning method according to any one of claims 1 to 7 are implemented.

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