A safe distance control method for overhead line engineering machinery operations based on high-precision positioning and laser point cloud data

Abstract

The present invention relates to the technical field of operation distance control methods, and specifically to an overhead line engineering machinery operation safety distance control method based on high-precision positioning and laser point cloud data, comprising the following steps: establishing a comprehensive spatial model including line direction, line height and three-dimensional terrain; mapping a planned construction path into the comprehensive spatial model, and calculating the minimum distance between the position of the engineering machinery and the overhead line in the entire planned construction path, obtaining the maximum operation range of the engineering machinery, and performing comparison; parsing the content of the construction project plan, analyzing the minimum distance between the engineering machinery and the overhead line, judging the actual operation range of the engineering machinery at the position, and performing comparison; monitoring the construction path of the engineering machinery in real time during construction to avoid deviation from the planned construction path; the present invention effectively prevents the risk of collision between the engineering machinery and the overhead line during the construction process, ensures the precise control of the construction path, and improves the overall construction safety.

Description

Technical Field

[0001] The present invention relates to the technical field of operation distance control methods, and in particular to an overhead line engineering machinery operation safety distance control method based on high-precision positioning and laser point cloud data. Background Art

[0002] After the initial installation of the overhead lines, relevant engineering machinery is still needed to assist in the installation work. At this time, the overhead lines have been installed, and the safe working distance must be controlled to prevent the arm span of the engineering machinery from damaging the overhead lines. With the continuous expansion and complexity of line construction, the construction site is usually accompanied by the coordinated operation of a variety of engineering machinery, such as lifting equipment, excavators, cranes, etc. These equipment often have a large arm span and operating range when operating. Once they approach or contact the overhead lines, they may cause damage to the power lines and even cause personal injury and safety accidents. Therefore, how to effectively monitor and control the safe distance between engineering machinery and overhead lines has become an important technical problem in construction management.

[0003] Traditional safety distance control methods rely on human experience or simple equipment limitations, which are difficult to meet the changing and complex environmental requirements of modern construction sites. Especially in scenarios of high altitude, complex terrain or multi-machine collaborative operation, traditional methods cannot accurately monitor the actual operation path of the equipment in real time, which may lead to equipment misoperation or exceeding the safety range, increasing the risk of safety accidents. In addition, the standard operating range used by many existing systems is a fixed maximum value, which lacks the ability to flexibly adjust according to specific construction tasks and environments, limiting the efficiency and flexibility of construction. Summary of the invention

[0004] The present invention provides a method for controlling the safe distance of overhead line engineering machinery operations based on high-precision positioning and laser point cloud data.

[0005] The method for controlling the safe distance of overhead line engineering machinery operations based on high-precision positioning and laser point cloud data includes the following steps:

[0006] S1, collects 3D point cloud data of overhead lines and their surrounding terrain through LiDAR scanning, and establishes a comprehensive spatial model including line direction, line height and 3D terrain;

[0007] S2, obtain the planned construction path of the construction machinery, map the planned construction path to the comprehensive space model, and calculate the minimum distance between the construction machinery position and the overhead line in the entire planned construction path, set as , obtain the maximum operating range of the construction machinery (such as the operating range of the construction machinery when the arm is at its maximum span), and set the maximum operating range diameter ,Will and For comparison, if , then adjust the maximum operating range of the construction machinery to avoid d1 exceeding dij in actual construction;

[0008] S3, obtain the construction project plan, analyze the content of the construction project plan, and analyze the minimum distance between the construction machinery and the overhead line When the specific construction details of the construction machinery at this location are determined, the actual operation range of the construction machinery at this location is set to and use Update S2 ,Will and For comparison, if , then no adjustment;

[0009] S4, using the Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS), real-time positioning of construction machinery at the overhead line construction site is carried out to obtain the three-dimensional coordinates of the construction machinery. The coordinate system of the unified and integrated space model is used to establish the relative position relationship between the construction machinery and the overhead line. The construction path is monitored in real time during construction to avoid deviation from the planned construction path.

[0010] Optionally, the S1 specifically includes:

[0011] S11, using a drone equipped with a laser radar device to perform multi-angle scanning over the overhead line construction area to obtain 3D point cloud data of the overhead line represent The position of a point on the horizontal plane, Represents height, and the data includes the direction of the line and the height of the line;

[0012] S12, at the same time, performs laser radar scanning on the surrounding terrain of the construction area to collect three-dimensional point cloud data of terrain undulations, obstacle heights and locations. ,in is the topographic point number, Indicates the height of a terrain point;

[0013] S13, using a point cloud data processing algorithm, fusing the three-dimensional spatial data of the overhead line with the three-dimensional point cloud data of the surrounding terrain, and performing coordinate conversion;

[0014] S14 generates a comprehensive three-dimensional spatial model including the direction of overhead lines, line height, terrain undulations and obstacle distribution, providing reliable spatial reference data for safety distance calculation and construction path planning.

[0015] Optionally, the S2 specifically includes:

[0016] S21, obtaining the planned construction path of the construction machinery, wherein the planned construction path represents the predetermined movement trajectory of the construction machinery during the construction process, and the path data includes the coordinates of each position in the time series ,in The coordinates of the location of the construction machinery on the construction path;

[0017] S22, each location point of the planned construction path Mapped into the established comprehensive spatial model, the comprehensive spatial model includes the 3D point cloud data of the overhead line and the surrounding terrain data. The point cloud data of the overhead line is , align the planned construction path with the point cloud data in the comprehensive spatial model to ensure that the position of the construction machinery is consistent with the three-dimensional spatial coordinates of the overhead line;

[0018] S23, based on the mapped comprehensive spatial model, calculate the location of each construction machinery Minimum distance to overhead lines ,in The calculation formula is:

[0019] ,in, is the coordinate of a point on the overhead line, The coordinates of the location of the construction machinery on the planned construction path;

[0020] S24, obtain the maximum operating range of the construction machinery, set the diameter of the maximum operating range ,if , the maximum operating range of the construction machinery is automatically adjusted to ensure that the operating range of the construction machinery does not exceed the minimum safety distance of the overhead lines during actual construction.

[0021] Optionally, assuming that the path of the construction machinery is generated in a local coordinate system, the mapping of the planned construction path includes converting the coordinates of the path points Transform to the global coordinate system where the integrated spatial model is located, through the known coordinate system transformation matrix Realize and obtain the coordinates of the global coordinate system ;

[0022] The planned construction path is registered with the point cloud data in the comprehensive spatial model to accurately align the path points to the comprehensive spatial model, ensuring that each path point can accurately correspond to the terrain and overhead lines in the spatial model, and each path point is found by nearest neighbor matching. The nearest neighbor matching of the closest points to the overhead line and terrain model in the integrated spatial model is expressed as:

[0023] , for each path point , find the nearest overhead line point , thereby achieving the registration of construction path points with the comprehensive spatial model.

[0024] Optionally, the construction project plan includes the operation type of the construction machinery, the operation schedule, and the operation instructions for each construction stage; based on the minimum distance position of the construction machinery Coordinates , extract the construction details corresponding to the location from the construction project plan, and determine the work tasks for the specific construction location;

[0025] According to the operation scope of the construction machinery under the operation task in the construction details, obtain its actual operation scope The operating range includes the maximum arm span, turning radius, operating height and other parameters of the equipment. It is expressed as: ,in, is the maximum horizontal operating radius of the construction machinery, is the maximum operating height under this construction task; Respectively Compare and determine whether it exceeds the safe distance.

[0026] Optionally, the parsing of the contents of the construction project plan in S3 specifically includes:

[0027] S31, Structured analysis of construction project plans: Construction project plans contain multiple information formats such as text descriptions, tables, and drawings. Natural language processing (NLP) technology is used to perform semantic analysis on the plans, converting complex text descriptions into structured data. Through word segmentation, part-of-speech tagging, and entity recognition, key task information is extracted, such as operation types such as "excavation" and "hoisting", and structured information is extracted from tables or drawings.

[0028] S32, construction of equipment parameter database: In order to obtain the accurate operation scope of construction machinery from the task information extracted from the planning book, an equipment parameter database is established to store the basic operating parameters of different construction machinery (such as maximum arm span, operating height, rotation radius, etc.). The knowledge graph is used to associate the mechanical equipment model, operating parameters, and construction tasks, so as to facilitate the rapid query of the operating parameters of mechanical equipment under different working conditions;

[0029] S33, determine the operating scope: After obtaining the basic operating parameters of the mechanical equipment, determine the actual operating scope according to the specific construction task. The operating scope includes the horizontal operating radius and operating height of the equipment:

[0030] Calculation of horizontal operation range: Determined based on the association results of knowledge graph technology ;

[0031] Vertical operation height calculation: determined based on the association results of knowledge graph technology .

[0032] Optionally, the S31 specifically includes:

[0033] S311, semantic parsing: pre-process the text of the construction project plan to ensure the uniform format of the content, break down the sentences in the project plan into independent words or phrases, remove stop words and mark the part of speech for each word to help the subsequent semantic analysis process, and use entity recognition to extract key information in the text, including mechanical equipment models, task types, and operating parameters. By identifying entities, the elements in the project plan are clarified, and the text is annotated through the model, such as marking which words are equipment models and which are task descriptions. Dependency analysis is used to identify the grammatical relationship between different words in the sentence, thereby helping to determine the relationship between entities.

[0034] S312, extracting structured information from the table: using optical character recognition technology to extract the text in the image into parseable text, and the extracted table data is mapped into a key-value pair structure.

[0035] Optionally, the knowledge graph consists of nodes and edges, where nodes represent entities and edges represent relationships between entities;

[0036] The nodes include:

[0037] Equipment (construction machinery) model node: represents different mechanical equipment;

[0038] Operation parameter nodes: maximum arm span, operation height;

[0039] Construction task nodes: hoisting and excavation construction tasks;

[0040] Edges connect nodes, including:

[0041] "Execute Task" edge: connects the equipment model node with the construction task node, indicating that a certain equipment can perform a certain task;

[0042] “Apply to” edge: connects the construction task node with the operation parameter node.

[0043] Optionally, the construction of the knowledge graph includes:

[0044] Creation of device entity: Create an entity node for each device model;

[0045] Task association: associate the equipment model node with the construction task node;

[0046] Association of operation parameters: add the corresponding operation parameter node (such as maximum arm span 20 meters, maximum height 30 meters) to each construction task node, and connect the operation parameter with the construction task node with an edge;

[0047] After the knowledge graph is constructed, the minimum distance between construction machinery and overhead lines is extracted from the knowledge graph through query technology. When the construction machinery is in the specific construction details at the location, determine the actual operation scope of the construction machinery at the location .

[0048] Optionally, the construction of the knowledge graph is implemented through an association model, connecting devices, operating parameters and tasks, specifically including:

[0049] definition is the device model, For the operational requirements in construction tasks, is the operating parameter of the device;

[0050] Through the association operation of the knowledge graph, the construction machinery and its operating parameters corresponding to the construction task at the specific construction location are found;

[0051] The association model is expressed as: ,in, It is a set of device parameters obtained through knowledge graph query, including (maximum arm span), (maximum operating altitude), Represents the device model node, Represents a task node, It is a query operation in the knowledge graph, returning the device On Task The operating parameters under the above conditions are obtained by querying the knowledge graph based on the actual location of the equipment and the construction task requirements.

[0052] Beneficial effects of the present invention:

[0053] The present invention, by establishing a comprehensive spatial model including line direction, line height and three-dimensional terrain, can accurately map the planned construction path into the model and calculate the closest distance between the construction machinery and the overhead line in real time. Combined with the maximum operating range of the construction machinery (such as parameters such as arm span), the operating range is compared with the closest distance to determine in real time whether the equipment exceeds the safe distance, effectively preventing the risk of collision between the construction machinery and the overhead line during the construction process, ensuring the precise control of the construction path, and improving the overall construction safety.

[0054] The present invention dynamically associates mechanical equipment models, operating parameters and specific construction tasks by introducing knowledge graph technology. When the closest distance point between the construction machinery and the overhead line is determined, the knowledge graph can automatically adjust the actual operating range of the construction machinery according to the specific construction task requirements corresponding to the point, replacing the original maximum operating range, making the construction safety distance analysis more accurate, and the operating range is no longer limited to the standard maximum value, thereby making the construction path planning more flexible, effectively improving the construction efficiency, and avoiding the risk of equipment exceeding the safety range.

[0055] The present invention utilizes the combination of the global navigation satellite system (GNSS) and the inertial navigation system (INS) to provide accurate three-dimensional positioning, realize real-time monitoring of the relative position relationship between the construction machinery and the overhead lines, effectively prevent the machinery from deviating from the planned path or getting too close to the overhead lines during the construction process, and improve construction safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0057] Figure 1 A schematic diagram of a method flow chart of an embodiment of the present invention;

[0058] Figure 2 A schematic diagram of a knowledge graph according to an embodiment of the present invention. DETAILED DESCRIPTION

[0059] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0060] It should be noted that the references to "one embodiment", "embodiment", "exemplary embodiments", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0061] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0062] like Figure 1-Figure 2 As shown, the overhead line engineering machinery operation safety distance control method based on high-precision positioning and laser point cloud data includes the following steps:

[0063] S1, collects 3D point cloud data of overhead lines and their surrounding terrain through LiDAR scanning, and establishes a comprehensive spatial model including line direction, line height and 3D terrain;

[0064] S2, obtain the planned construction path of the construction machinery, map the planned construction path to the comprehensive space model, and calculate the minimum distance between the construction machinery position and the overhead line in the entire planned construction path, set as , obtain the maximum operating range of the construction machinery (such as the operating range of the construction machinery when the arm is at its maximum span), and set the maximum operating range diameter ,Will and For comparison, if , then adjust the maximum operating range of the construction machinery to avoid d1 exceeding dij in actual construction;

[0065] S3, obtain the construction project plan, analyze the content of the construction project plan, and analyze the minimum distance between the construction machinery and the overhead line When the specific construction details of the construction machinery at this location are determined, the actual operation range of the construction machinery at this location is set to and use Update S2 ,Will and For comparison, if , then adjust the maximum operating range of the construction machinery. , then no adjustment;

[0066] S4, using the Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS), real-time positioning of construction machinery at the overhead line construction site is carried out to obtain the three-dimensional coordinates of the construction machinery. The coordinate system of the unified and integrated space model is used to establish the relative position relationship between the construction machinery and the overhead line. The construction path is monitored in real time during construction to avoid deviation from the planned construction path.

[0067] S1 specifically includes:

[0068] S11, using a drone equipped with a laser radar device to perform multi-angle scanning over the overhead line construction area to obtain 3D point cloud data of the overhead line represent The position of a point on the horizontal plane, Represents height, the data includes the direction of the line and the height of the line;

[0069] S12, at the same time, performs laser radar scanning on the surrounding terrain of the construction area to collect three-dimensional point cloud data of terrain undulations, obstacle heights and locations. ,in is the topographic point number, Indicates the height of a terrain point;

[0070] S13, using a point cloud data processing algorithm, fusing the three-dimensional spatial data of the overhead line with the three-dimensional point cloud data of the surrounding terrain, and performing coordinate conversion;

[0071] S14 generates a comprehensive three-dimensional spatial model including the direction of overhead lines, line height, terrain undulations and obstacle distribution, providing reliable spatial reference data for safety distance calculation and construction path planning.

[0072] 1. The three-dimensional spatial data of the overhead line is obtained by scanning with a drone equipped with a laser radar device, which is specifically expressed as follows:

[0073] Route direction: Assume that the laser radar obtains multiple point cloud data points ,in Represents the scan point serial number, Represents the position of the point on the horizontal plane, Represents the height, and the direction of the overhead line is obtained by fitting algorithm to obtain the linear equation: in, is the slope of the line, reflecting the direction of the line. is the vertical intercept of the line, obtained by least squares fitting and , the fitting process can be given by the following formula:

[0074] ;

[0075] ;in, is the total number of points.

[0076] Line height: Based on the laser radar point cloud data Coordinates, the average height of the overhead line can be calculated by the following formula: ,in, Represents the average height of the line, is the total number of points collected.

[0077] 2. Terrain undulations: point cloud data of the surrounding terrain scanned by drone lidar ,in is the topographic point number, Indicates the height of the terrain point. The terrain undulation is expressed by calculating the height difference of the scanned area. The height difference of the terrain undulation is expressed as:

[0078] ,in, is the height difference of the terrain, They are the heights of the highest and lowest points of the terrain in the point cloud data, respectively.

[0079] 3. A comprehensive three-dimensional spatial model can be generated by coordinate conversion and fusion of line direction, line height, terrain undulation and obstacle data;

[0080] Coordinate transformation: The data of overhead lines and terrain are unified into a global coordinate system. The initial position of the UAV is , then the line and terrain point cloud data can be converted to the global coordinate system: ;

[0081] Similarly, terrain point cloud data also needs to be converted:

[0082] ;

[0083] Ultimately, the line direction, line height, terrain undulations and obstacle data are integrated into a unified coordinate system to form a three-dimensional spatial model containing complete information, providing a data basis for subsequent construction path planning and safety distance calculation.

[0084] S2 specifically includes:

[0085] S21, obtaining the planned construction path of the construction machinery. The planned construction path represents the predetermined movement trajectory of the construction machinery during the construction process. The path data includes the coordinates of each position in the time series. ,in The coordinates of the location of the construction machinery on the construction path;

[0086] S22, each location point of the planned construction path Mapped into the established comprehensive spatial model, the comprehensive spatial model includes the 3D point cloud data of the overhead line and the surrounding terrain data. The point cloud data of the overhead line is , align the planned construction path with the point cloud data in the comprehensive spatial model to ensure that the position of the construction machinery is consistent with the three-dimensional spatial coordinates of the overhead line;

[0087] S23, based on the mapped comprehensive spatial model, calculate the location of each construction machinery Minimum distance to overhead lines ,in The calculation formula is:

[0088] ,in, is the coordinate of a point on the overhead line, The coordinates of the location of the construction machinery on the planned construction path;

[0089] S24, obtain the maximum operating range of the construction machinery, set the diameter of the maximum operating range ,if The maximum operating range of the machinery is determined to ensure that the operating range of the construction machinery will not exceed the minimum safety distance of the overhead lines during actual construction.

[0090] Assuming that the path of the construction machinery is generated in the local coordinate system, the mapping of the planned construction path includes converting the coordinates of the path points Transform to the global coordinate system where the integrated spatial model is located, through the known coordinate system transformation matrix Realize and obtain the coordinates of the global coordinate system , the conversion formula is as follows:

[0091] ,in, is the rotation matrix, is the translation vector, It is the coordinate of the construction path point in the global coordinate system. This transformation ensures that the path points of the construction machinery and the point cloud data of the overhead line are in the same coordinate system.

[0092] The planned construction path is registered with the point cloud data in the integrated spatial model to accurately align the path points to the integrated spatial model, ensuring that each path point can accurately correspond to the terrain and overhead lines in the spatial model, and each path point is found through nearest neighbor matching. The nearest neighbor matching of the closest points to the overhead line and terrain model in the integrated spatial model is expressed as:

[0093] , for each path point , find the nearest overhead line point , thereby achieving the registration of construction path points with the comprehensive spatial model.

[0094] It also includes error correction and calibration: there are certain errors in the registration process, especially when the acquisition accuracy of laser point cloud data and path planning data is different. Therefore, after the registration is completed, an error correction algorithm is needed to optimize the matching results.

[0095] The results of the preliminary registration are optimized using the iterative closest point algorithm (ICP). The closest point algorithm finds the best correspondence between the path points of the construction machinery and the corresponding points in the comprehensive spatial model through repeated iterations, and minimizes the overall posture error. The goal of the closest point algorithm is to minimize the following objective function:

[0096] ,in, represents a path point, Representing the point cloud data points of the overhead line, the objective function is optimized through continuous iteration, and finally the accurate alignment of the path points with the comprehensive spatial model is achieved.

[0097] The construction project plan includes the type of construction machinery operations, the operation schedule, and the operating instructions for each construction phase; Coordinates , extract the construction details corresponding to the location from the construction project plan, and determine the work tasks for the specific construction location;

[0098] According to the operation scope of the construction machinery under the operation task in the construction details, obtain its actual operation scope The operating range includes the maximum arm span, turning radius, operating height and other parameters of the equipment. It is expressed as: ,in, is the maximum horizontal operating radius of the construction machinery, is the maximum operating height under this construction task; Respectively Compare and determine whether it exceeds the safe distance.

[0099] The analysis of the contents of the construction project plan in S3 specifically includes:

[0100] S31, Structured parsing of construction project plans: Construction project plans contain multiple information formats such as text descriptions, tables, and drawings. Natural language processing (NLP) technology is used to perform semantic parsing on the plans, converting complex text descriptions into structured data. Through word segmentation, part-of-speech tagging, and entity recognition, key task information is extracted, such as operation types such as "excavation" and "hoisting". Structured information is extracted from tables or drawings. For data in tables (such as equipment type, operation radius, maximum arm span, and other parameters), table parsing tools (such as Pandas) can be used to extract relevant information and associate it with specific construction tasks.

[0101] S32, construction of equipment parameter database: in order to obtain accurate operation range of construction machinery from the task information extracted from the plan, an equipment parameter database is established to store basic operation parameters of different construction machinery (such as maximum arm span, operation height, rotation radius, etc.). The machine model extracted from the construction project plan is queried in the equipment parameter database to obtain the operation range information of the corresponding machine. For example, if the model of a certain excavator is "EX2000", its maximum operation range (arm span radius, operation height, etc.) can be obtained from the database. The knowledge graph is used to associate the machine equipment model, operation parameters, and construction tasks, so as to facilitate quick query of the operation parameters of the machine equipment under different working conditions.

[0102] S33, determine the operating scope: After obtaining the basic operating parameters of the mechanical equipment, determine the actual operating scope according to the specific construction task. The operating scope includes the horizontal operating radius and operating height of the equipment:

[0103] Calculation of horizontal operation range: Determined based on the association results of knowledge graph technology ;

[0104] Vertical operation height calculation: determined based on the association results of knowledge graph technology .

[0105] In order to effectively manage different types of construction machinery and their operating parameters, it is necessary to establish an equipment parameter database. The database should include the following fields:

[0106] Device Model: A unique identifier for each device.

[0107] Operating parameters: Specific equipment capabilities, including maximum reach, maximum operating radius, maximum operating height, and maximum load.

[0108] Equipment purpose: Typical application scenarios or task types of the equipment (lifting, excavation, etc.).

[0109] The design of the equipment parameter database is structured and queryable. Each record stores the basic operating parameters of a certain device. The specific fields include:

[0110] Device model: indicates the type of device;

[0111] Maximum operating radius: The maximum operating range that the equipment can reach on the horizontal plane, in meters.

[0112] Maximum operating altitude: The maximum operating altitude of the equipment in the vertical direction, in meters.

[0113] S31 specifically includes:

[0114] S311, semantic analysis: pre-process the text of the construction project plan to ensure the uniform format of the content, break down the sentences in the project plan into independent words or phrases, remove stop words and mark each word with its part of speech to help the subsequent semantic analysis process, and use entity recognition to extract key information from the text, including mechanical equipment models, task types, and operating parameters. By identifying entities, the elements in the project plan are clarified, and the text is annotated through the model, such as marking which words are equipment models and which are task descriptions. Dependency analysis is used to identify the grammatical relationship between different words in the sentence, thereby helping to determine the association between entities;

[0115] Entity recognition is used to extract specific key entities from documents, such as mechanical equipment model, task type, and operating parameters. Suppose the document contains this words, the goal of entity recognition is to identify a series of entity tags from these words ,in Represents an entity in a document, for example:

[0116] Mechanical equipment model, Task type, Operation parameters;

[0117] Named Entity Recognition Model Using Conditional Random Fields for Words Label and get entity tags , entity recognition can be accomplished by maximizing the following probability formula:

[0118] ,in, is in the text Identify entities given a sequence of words in The probability of is the first Words Entity annotation.

[0119] Dependency analysis represents the grammatical dependency of each word in a sentence on other words, using a dependency tree. Suppose the document contains the sentence , the goal of dependency analysis is to generate a dependency tree , each node of the tree represents a word, and the edges represent the dependency relationship between words. In the dependency relationship, given a sentence , dependency tree The generation formula is:

[0120] ,in, Expressive words and The probability of the dependency relationship between Expressive words Pair of words The commonly used dependency relationships are subject-predicate relationship and verb-object relationship.

[0121] S312, extracting structured information from the table: using optical character recognition technology to extract the text in the image into parseable text, and the extracted table data is mapped into a key-value pair structure.

[0122] When the table exists in image or PDF format, you first need to use OCR technology to extract the text in the image into parseable text. OCR generates corresponding characters by recognizing pixel information in the image, which is expressed as: ,in, represents the input image, It is the process of optical character recognition, and the output is the recognized text Text. After extracting the text in the table, the data in the table needs to be mapped into key-value pairs. For example, the device model and operation parameters in the table are mapped into fields and values:

[0123] Keys: equipment model, operating radius, working height;

[0124] Value: specific data value;

[0125] Assume that the table contains OK The mapping process is expressed as follows:

[0126] ,in, is the key of the table, For the corresponding value, the final output structured data .

[0127] The knowledge graph consists of nodes and edges. Nodes represent entities, and edges represent the relationships between entities.

[0128] The nodes include:

[0129] Equipment (construction machinery) model node: represents different mechanical equipment;

[0130] Operation parameter nodes: maximum arm span, operation height;

[0131] Construction task nodes: hoisting and excavation construction tasks;

[0132] Edges connect nodes, including:

[0133] "Execute Task" edge: connects the equipment model node with the construction task node, indicating that a certain equipment can perform a certain task;

[0134] “Apply to” edge: connects the construction task node with the operation parameter node.

[0135] The construction of the knowledge graph includes:

[0136] Creation of device entity: Create an entity node for each device model;

[0137] Task association: associate the equipment model node with the construction task node;

[0138] Association of operation parameters: add the corresponding operation parameter node (such as maximum arm span 20 meters, maximum height 30 meters) to each construction task node, and connect the operation parameter with the construction task node with an edge;

[0139] After the knowledge graph is constructed, the minimum distance between construction machinery and overhead lines is extracted from the knowledge graph through query technology. When the construction machinery is in the specific construction details at the location, determine the actual operation scope of the construction machinery at the location .

[0140] The knowledge graph is constructed through an association model that connects devices, operating parameters, and tasks, including:

[0141] definition is the device model, For the operational requirements in construction tasks, is the operating parameter of the device;

[0142] Through the association operation of the knowledge graph, the construction machinery and its operating parameters corresponding to the construction task at the specific construction location are found;

[0143] The association model is expressed as: ,in, It is a set of device parameters obtained through knowledge graph query, including (maximum arm span), (maximum operating altitude), Represents the device model node, Represents a task node, It is a query operation in the knowledge graph, returning the device On Task The operating parameters under the above conditions are obtained by querying the knowledge graph based on the actual location of the equipment and the construction task requirements.

[0144] Real-time positioning of GNSS and INS:

[0145] The Global Navigation Satellite System (GNSS) provides the global positioning coordinates of the equipment through satellite signals and outputs the three-dimensional coordinates of the construction machinery in the earth reference system. The coordinates represent the absolute position of the construction machinery in the earth reference system.

[0146] The inertial navigation system (INS) is based on accelerometers and gyroscopes to track the attitude of construction machinery (such as acceleration and rotation angle). Especially when the GNSS signal is limited, INS can provide local and fine position change information.

[0147] The attitude information output by INS includes:

[0148] Acceleration data: records the acceleration of the device in the local coordinate system.

[0149] Angular velocity data: records the rotation speed of the device to help determine changes in the device's orientation.

[0150] By combining INS with GNSS data, the INS can continue to provide high-precision relative position and attitude data through inertial measurement when GNSS signals are poor.

[0151] In order to unify the construction machinery coordinates acquired by GNSS and INS with the comprehensive spatial model in the construction area, the global coordinates must be converted to the local coordinate system of the construction site through the coordinate transformation method. The comprehensive spatial model is usually based on the local coordinate system of the construction area, such as the point cloud data collected by LiDAR, so the GNSS / INS coordinates need to be converted to the same reference frame.

[0152] The coordinate conversion process is the same as the coordinate conversion of the planned construction path mentioned above. It includes translation and rotation to convert the global coordinates into local coordinates. In this way, it can be matched with the overhead lines, terrain and other information in the comprehensive spatial model.

[0153] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0154] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for controlling the safe distance of overhead line engineering machinery operations based on high-precision positioning and laser point cloud data, characterized in that: The following steps are involved: S1, collects 3D point cloud data of overhead lines and their surrounding terrain through LiDAR scanning, and establishes a comprehensive spatial model including line direction, line height and 3D terrain; S2, obtain the planned construction path of the construction machinery, map the planned construction path to the comprehensive space model, and calculate the minimum distance between the construction machinery position and the overhead line in the entire planned construction path, set as , obtain the maximum operating range of the construction machinery, the maximum operating range diameter is set ,Will and For comparison, if , then adjust the maximum operating range of the construction machinery; S3, obtain the construction project plan, analyze the content of the construction project plan, and analyze the minimum distance between the construction machinery and the overhead line When the specific construction details of the construction machinery at this location are determined, the actual operation range of the construction machinery at this location is set to and use renew In ,Will and For comparison, if , then adjust the maximum operating range of the construction machinery. , then no adjustment; S4, using the global navigation satellite system and inertial navigation system, real-time positioning of construction machinery at the overhead line construction site, obtaining the three-dimensional coordinates of the construction machinery, using the coordinate transformation method to unify and integrate the coordinate system of the spatial model, establish the relative position relationship between the construction machinery and the overhead line, and monitor its construction path in real time during construction to avoid deviation from the planned construction path.

2. The method for controlling the safe distance of overhead line engineering machinery operations based on high-precision positioning and laser point cloud data according to claim 1 is characterized in that: The S1 specifically includes: S11, using a drone equipped with a laser radar device to perform multi-angle scanning over the overhead line construction area to obtain 3D point cloud data of the overhead line represent The position of a point on the horizontal plane, Represents height, and the data includes the direction of the line and the height of the line; S12, at the same time, performs laser radar scanning on the surrounding terrain of the construction area to collect three-dimensional point cloud data of terrain undulations, obstacle heights and locations. ,in is the topographic point number, Indicates the height of a terrain point; S13, using a point cloud data processing algorithm, fusing the three-dimensional spatial data of the overhead line with the three-dimensional point cloud data of the surrounding terrain, and performing coordinate conversion; S14, generating a comprehensive three-dimensional spatial model including the overhead line direction, line height, terrain undulation and obstacle distribution.

3. The method for controlling the safe distance of overhead line engineering machinery operations based on high-precision positioning and laser point cloud data according to claim 2 is characterized in that: The S2 specifically includes: S21, obtaining the planned construction path of the construction machinery, wherein the planned construction path represents the predetermined movement trajectory of the construction machinery during the construction process, and the path data includes the coordinates of each position in the time series ,in The coordinates of the location of the construction machinery on the construction path; S22, each location point of the planned construction path Mapped into the established comprehensive spatial model, the comprehensive spatial model includes the 3D point cloud data of the overhead line and the surrounding terrain data. The point cloud data of the overhead line is , align the planned construction path with the point cloud data in the comprehensive spatial model to ensure that the position of the construction machinery is consistent with the three-dimensional spatial coordinates of the overhead line; S23, based on the mapped comprehensive spatial model, calculate the location of each construction machinery Minimum distance to overhead lines ,in The calculation formula is: ,in, is the coordinate of a point on the overhead line, The coordinates of the location of the construction machinery on the planned construction path; S24, obtain the maximum operating range of the construction machinery, set the diameter of the maximum operating range ,if , the maximum operating range of the construction machinery is automatically adjusted to ensure that the operating range of the construction machinery does not exceed the minimum safety distance of the overhead lines during actual construction.

4. The method for controlling the safe distance of overhead line engineering machinery operations based on high-precision positioning and laser point cloud data according to claim 3 is characterized in that: The mapping of the planned construction path includes mapping the coordinates of the path points Transform to the global coordinate system where the integrated spatial model is located, through the known coordinate system transformation matrix Realize and obtain the coordinates of the global coordinate system ; The planned construction path is registered with the point cloud data in the comprehensive spatial model to accurately align the path points to the comprehensive spatial model, and each path point is found by nearest neighbor matching. The nearest neighbor matching of the closest points to the overhead line and terrain model in the integrated spatial model is expressed as: , for each path point , find the nearest overhead line point , thereby achieving the registration of construction path points with the comprehensive spatial model.

5. The method for controlling the safe distance of overhead line engineering machinery operations based on high-precision positioning and laser point cloud data according to claim 1 is characterized in that: The construction project plan includes the type of construction machinery operation, the operation schedule, and the operation instructions for each construction stage; Coordinates , extracted from the construction project plan The construction details corresponding to the location are determined Position job tasks; According to the operation scope of the construction machinery under the operation task in the construction details, obtain its actual operation scope The operating range includes the maximum arm span, turning radius, operating height and other parameters of the equipment. It is expressed as: ,in, is the maximum horizontal operating radius of the construction machinery, is the maximum operating height under this task; Respectively Compare and determine whether it exceeds the safe distance.

6. The method for controlling the safe distance of overhead line engineering machinery operations based on high-precision positioning and laser point cloud data according to claim 5 is characterized in that: The analysis of the contents of the construction project plan in S3 specifically includes: S31, Structural analysis of construction project planning documents: Use natural language processing technology to perform semantic analysis on planning documents, convert complex text descriptions into structured data, and extract structured information from tables or drawings; S32, construction of equipment parameter database: establish an equipment parameter database to store the basic operating parameters of different construction machinery, and use the knowledge graph to associate the machinery equipment models, operating parameters, and construction tasks; S33, determine the operating scope: After obtaining the basic operating parameters of the mechanical equipment, determine the actual operating scope according to the specific construction task. The operating scope includes the horizontal operating radius and operating height of the equipment: Calculation of horizontal operation range: Determined based on the association results of knowledge graph technology ; Vertical operation height calculation: determined based on the association results of knowledge graph technology .

7. The method for controlling the safe distance of overhead line engineering machinery operations based on high-precision positioning and laser point cloud data according to claim 6 is characterized in that: The S31 specifically includes: S311, semantic analysis: pre-process the text of the construction project plan to ensure the uniform format of the content, break down the sentences in the project plan into independent words or phrases, remove stop words and mark the part of speech for each word, and use entity recognition to extract key information in the text, including mechanical equipment model, task type, and operating parameters. By identifying entities, the elements in the project plan are clarified, and the grammatical relationship between different words in the sentence is identified through dependency analysis; S312, extracting structured information from the table: using optical character recognition technology to extract the text in the image into parseable text, and the extracted table data is mapped into a key-value pair structure.

8. The method for controlling the safe distance of overhead line engineering machinery operations based on high-precision positioning and laser point cloud data according to claim 7 is characterized in that: The knowledge graph is composed of nodes and edges, where nodes represent entities and edges represent relationships between entities; The nodes include equipment model nodes, operation parameter nodes, and construction task nodes; Edges connect nodes, including: "Execute Task" edge: connects the equipment model node with the construction task node; "Applies to" edge: connects the construction task node with the operation parameter node.

9. The method for controlling the safe distance of overhead line engineering machinery operations based on high-precision positioning and laser point cloud data according to claim 8, characterized in that: The construction of the knowledge graph includes: Creation of device entity: Create an entity node for each device model; Task association: associate the equipment model node with the construction task node; Association of operation parameters: add the corresponding operation parameter node to each construction task node, and connect the operation parameter with the construction task node with an edge; After the knowledge graph is constructed, the minimum distance between construction machinery and overhead lines is extracted from the knowledge graph through query technology. When the construction machinery is in the specific construction details at the location, determine the actual operation scope of the construction machinery at the location .

10. The method for controlling the safe distance of overhead line engineering machinery operations based on high-precision positioning and laser point cloud data according to claim 9, characterized in that: The construction of the knowledge graph is achieved through an association model, which connects equipment, operating parameters and tasks, including: definition is the device model, For the operational requirements in construction tasks, is the operating parameter of the device; Through the association operation of the knowledge graph, the construction machinery and its operating parameters corresponding to the construction task at the specific construction location are found; The association model is expressed as: ,in, It is a set of device parameters obtained through knowledge graph query, including , Represents the device model node, Represents a task node, It is a query operation in the knowledge graph, returning the device On Task The operating parameters under the above conditions are obtained by querying the knowledge graph based on the actual location of the equipment and the construction task requirements.

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