A method for precise positioning and installation of complex regional electromechanical equipment

Abstract

The application provides a complex regional electromechanical equipment accurate positioning installation method, and belongs to the technical field of electromechanical equipment installation. The application obtains three-dimensional space point cloud data through a multi-dimensional positioning instrument to construct an initial positioning vector database, combines with electromechanical equipment technical specifications to determine an installation coordinate matrix, utilizes a coordinate measuring arm and a laser tracking interferometer to measure and calculate a space compensation variable vector and a thermal expansion variable vector to form a comprehensive variable vector. Based on the obtained data, a computer simulation is performed on an installation environment to determine an optimal installation path, a space region overlap matrix and a space region idle matrix are constructed to calculate and generate selectable regions, a Lagrange multiplier constraint optimization equation set is applied to determine an optimal installation point and to perform installation and adjustment, a deviation value is monitored in real time, when the deviation value is less than a preset threshold value, fixed installation is completed, and finally, installation precision is verified to meet design requirements through operation test.

Description

Technical Field

[0001] This invention belongs to the field of electromechanical equipment installation technology, and more specifically, relates to a method for precise positioning and installation of electromechanical equipment in complex areas. Background Technology

[0002] In industrial production, aerospace, and precision manufacturing, precise positioning and installation of electromechanical equipment in complex areas is crucial. Traditional installation methods rely primarily on manual measurement and experience, using tools such as tape measures, levels, and laser levels for measurement and positioning, supplemented by mechanical supports and adjustment devices to complete the equipment placement. While this method can meet basic needs in simple environments, the operational process lacks systematicity and scientific rigor.

[0003] However, with the increasing integration of industrial equipment and the increasing complexity of installation environments, traditional installation methods have many shortcomings: First, manual measurement is subject to subjective errors and cannot meet the requirements of sub-millimeter accuracy; second, it cannot effectively cope with the spatial constraints and environmental changes in complex areas; third, it lacks comprehensive consideration of multi-dimensional influencing factors, such as thermal expansion and structural deformation; and finally, the installation process lacks dynamic monitoring and real-time adjustment mechanisms, making it difficult to guarantee the final installation accuracy.

[0004] In complex installation scenarios with high precision requirements, existing technologies struggle to address the combined impact of environmental factors on the positioning and installation accuracy of electromechanical equipment. When complex areas are subject to multiple influencing factors such as temperature variations, space constraints, and structural deformation, traditional methods cannot accurately calculate and compensate for these errors. This leads to deviations between the actual installation position and the theoretical position, affecting the normal operation of the equipment and the overall system performance. In other words, existing technologies suffer from the inability to meet high-precision positioning and installation requirements for electromechanical equipment in complex areas. Summary of the Invention

[0005] In view of this, the present invention provides a method for precise positioning and installation of electromechanical equipment in complex areas, which can solve the technical problem in the prior art that the positioning and installation accuracy of electromechanical equipment in complex areas is difficult to meet the high precision requirements.

[0006] This invention is implemented as follows: It provides a method for precise positioning and installation of electromechanical equipment in complex areas, comprising: using a multi-dimensional positioning instrument to perform omnidirectional scanning of the complex area, acquiring three-dimensional spatial point cloud data of the complex area, and constructing an initial positioning vector database; determining the installation coordinate matrix according to the technical specifications of the electromechanical equipment; using a coordinate measuring arm to mark control points and generate a spatial compensation variation vector; measuring the structural deformation caused by changes in ambient temperature using a laser tracking interferometer, calculating the thermal expansion variation vector, and forming a comprehensive variation vector; determining the optimal installation path for the electromechanical equipment based on the traveling salesman problem algorithm; constructing a spatial region overlap matrix and a spatial region free matrix, and calculating and generating optional installation areas for the electromechanical equipment; applying a Lagrange multiplier constraint optimization equation set to determine the optimal installation point, and using a five-axis adjustment platform for fine-tuning positioning; using a high-precision measurement sensor to monitor the deviation between the installation position and the theoretical position in real time, completing the fixed installation; and verifying that the installation accuracy meets the design requirements through operational testing.

[0007] The multidimensional positioning device consists of a laser ranging system, an angle encoder, a high-resolution imaging system, and a data processing unit, and has millimeter-level spatial positioning capability and three-dimensional modeling function.

[0008] The initial positioning vector refers to the three-dimensional vector dataset of the relationship between the theoretical installation position of the equipment and the surrounding environment, obtained by a multi-dimensional positioning instrument before the installation of electromechanical equipment. It includes two parts: position vector and direction vector.

[0009] Among them, the spatial compensation variation vector refers to the amount of position and angle correction required due to the deviation between the actual environment of the complex area and the theoretical design. It is manifested as translation and rotation in three-dimensional space.

[0010] Among them, the thermal expansion variation vector refers to the positional shift caused by the thermal expansion or contraction of structural materials due to temperature changes, which is calculated by multiplying the thermal expansion coefficient and the temperature difference.

[0011] Among them, the comprehensive variation vector is the final positioning correction amount calculated by combining the spatial compensation variation vector and the thermal expansion variation vector through the principle of vector superposition, which is used to achieve accurate installation positioning.

[0012] Among them, the spatial region overlap matrix is ​​a mathematical model that describes the degree of overlap between different spatial regions in the installation space. It is used to evaluate the conflict between the equipment installation location and the surrounding equipment or structural space, and is generated by calculating the spatial relationship between each element in the initial positioning vector database.

[0013] The spatial area vacancy matrix is ​​a mathematical model describing the availability of each area in the installation space. It is formed by dividing the entire installation space into grids and marking the occupancy status of each grid cell, and is used to quickly locate suitable vacant installation spaces.

[0014] The selectable area refers to the spatial range that meets the installation accuracy requirements of electromechanical equipment. It is determined by the initial positioning vector, the comprehensive change vector, and the spatial area free matrix, and is represented as a three-dimensional spatial tolerance area.

[0015] The Lagrange multiplier-constrained optimization equation set includes objective function equation, position constraint equation, attitude constraint equation, and stability constraint equation. The objective function equation is used to evaluate the comprehensive value of the computer equipment installation location, the position constraint equation is used to limit the spatial coordinate range of the equipment installation, the attitude constraint equation is used to ensure that the installation angle of the equipment meets the requirements, and the stability constraint equation is used to evaluate the structural stability of the installation location.

[0016] This invention constructs an initial positioning vector database through omnidirectional scanning with a multi-dimensional positioning instrument, combines a coordinate measuring arm and a laser tracking interferometer to measure environmental changes, calculates a comprehensive variation vector, uses the traveling salesman problem algorithm to determine the optimal installation path, and applies a set of Lagrange multiplier constraint optimization equations to determine the optimal installation point, thereby achieving high-precision positioning and installation of electromechanical equipment in complex areas.

[0017] This method addresses several shortcomings of traditional techniques: by constructing an initial positioning vector database and a comprehensive change vector, it achieves accurate description and error compensation of the installation environment; by constructing a spatial region overlap matrix and a spatial region free matrix, it solves the spatial constraint problem in complex regions; by using the Lagrange multiplier constraint optimization equation set, it ensures that the optimal installation position is found under multiple constraints; and by using high-precision measurement sensors to monitor the installation process in real time, it achieves dynamic adjustment and precise control.

[0018] This invention solves the technical problem of the inability to meet the high-precision requirements of positioning and installation of electromechanical equipment in complex areas through a systematic and digital approach. It improves the installation accuracy to the sub-millimeter level, meets the installation requirements of high-precision electromechanical equipment in complex environments, and improves installation efficiency and equipment operation reliability. Attached Figure Description

[0019] Figure 1 This is a flowchart of the method of the present invention.

[0020] Figure 2 This is a diagram showing the equipment deployment in Example 2. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.

[0022] like Figure 1The diagram shown is a flowchart of a method for precise positioning and installation of electromechanical equipment in complex areas provided by the present invention. This method includes the following steps:

[0023] S01. Use a multi-dimensional positioning instrument to perform a full-range scan of the complex area, obtain three-dimensional spatial point cloud data of the complex area, and construct an initial positioning vector database to determine the installation reference position of electromechanical equipment.

[0024] S02. Based on the technical specifications of the electromechanical equipment, determine the coordinates of the center of gravity and the coordinates of the fixed points of the electromechanical equipment, calculate and form the installation coordinate matrix, and set correction parameters according to the actual situation of the installation surface.

[0025] S03. Use a coordinate measuring arm to mark control points in complex areas, measure the deviation between the actual coordinate values ​​and theoretical values ​​of the control points, and generate a spatial compensation variation vector.

[0026] S04. Measure the structural deformation caused by changes in ambient temperature using a laser tracking interferometer, calculate the thermal expansion variation vector, and superimpose the thermal expansion variation vector with the spatial compensation variation vector to form a comprehensive variation vector.

[0027] S05. Based on the acquired data, the installation environment is simulated by computer. The Traveling Salesman Problem algorithm is used to determine the optimal installation path for the electromechanical equipment. The minimization of the total path length and obstacle avoidance are considered, and the critical region of the change of the comprehensive variation vector during the transmission of the electromechanical equipment is marked.

[0028] S06. Construct a spatial region overlap matrix and a spatial region idle matrix. Based on the initial positioning vector database, the comprehensive change vector, and the spatial region overlap matrix, calculate and generate optional areas for electromechanical equipment installation. Dynamically monitor the optional areas through a visual recognition system.

[0029] S07. Apply the Lagrange multiplier constraint optimization equations to determine the optimal installation point, call the air flotation auxiliary device to transport the electromechanical equipment to the selectable area, and use the five-axis adjustment platform for fine-tuning and positioning to precisely control the six degrees of freedom offset.

[0030] S08. Use a high-precision measuring sensor to monitor the deviation between the installation position and the theoretical position of the electromechanical equipment in real time. When the deviation is less than a preset threshold, the fixed installation is completed.

[0031] S09. Verify the no-load and load operation status of the electromechanical equipment through operational testing, and confirm that the positioning and installation accuracy of the electromechanical equipment meets the design requirements.

[0032] Among them, the multidimensional positioning instrument is a precision measuring device composed of a laser ranging system, an angle encoder, a high-resolution imaging system, and a data processing unit, which has millimeter-level spatial positioning capability and three-dimensional modeling function.

[0033] The initial positioning vector refers to the three-dimensional vector dataset of the relationship between the theoretical installation position of the equipment and the surrounding environment, obtained by a multi-dimensional positioning instrument before the installation of electromechanical equipment. It includes two parts: position vector and direction vector.

[0034] Among them, the spatial compensation variation vector refers to the position and angle correction required due to the deviation between the actual environment of the complex area and the theoretical design, which is manifested as translation and rotation in three-dimensional space.

[0035] Among them, the thermal expansion variation vector refers to the positional shift caused by the thermal expansion or contraction of the structural material due to temperature changes, which is calculated by multiplying the thermal expansion coefficient and the temperature difference.

[0036] Among them, the comprehensive variation vector is the final positioning correction amount calculated by combining the spatial compensation variation vector and the thermal expansion variation vector through the principle of vector superposition, which is used to achieve accurate installation positioning.

[0037] Among them, the spatial region overlap matrix is ​​a mathematical model that describes the degree of overlap between different spatial regions in the installation space. It is used to evaluate the spatial conflict between the equipment installation location and surrounding equipment or structures, and is generated by calculating the spatial relationship between each element in the initial positioning vector database.

[0038] The spatial area vacancy matrix is ​​a mathematical model describing the availability of each area in the installation space. It is formed by dividing the entire installation space into grids and marking the occupancy status of each grid cell, and is used to quickly locate vacant spaces suitable for installation.

[0039] The selectable area refers to the spatial range that meets the installation accuracy requirements of electromechanical equipment. It is determined by the initial positioning vector, the comprehensive change vector, and the spatial area free matrix, and is represented as a three-dimensional spatial tolerance area.

[0040] The five-axis adjustment platform is a precision adjustment device composed of five independent control axes, which can achieve precise adjustment of translation in three directions and rotation in two directions in space, with an accuracy of micrometer level.

[0041] Among them, the air flotation auxiliary device is an auxiliary system that uses the principle of air cushion to reduce friction and enable heavy machinery and equipment to move easily and smoothly. It consists of an air pump, an air cushion plate, a pressure regulating valve and a control system.

[0042] The Lagrange multiplier-constrained optimization equation set includes an objective function equation, a position constraint equation, an attitude constraint equation, and a stability constraint equation. The objective function equation is used to comprehensively evaluate the installation location of the computer equipment. Inputs include the equipment's center of gravity coordinates, mounting surface normal vector, comprehensive variation vector, expected stress distribution, and support point coordinates. The output is the optimal installation location evaluation function value. The position constraint equation is used to limit the spatial coordinate range of the equipment installation. Inputs include the selectable region boundary coordinates, equipment perimeter dimensions, safety clearance values, channel reserved dimensions, and equipment interface locations. The output is a set of feasible solutions that meet the spatial constraints. The attitude constraint equation is used to ensure that the equipment installation angle meets requirements. Inputs include the equipment's main axis direction vector, allowable tilt angle, interface mating angle requirements, force direction parameters, and operating interface orientation requirements. The output is a set of feasible solutions that meet the angle constraints. The stability constraint equation is used to evaluate the structural stability of the installation location. Inputs include the support point force distribution, vibration transmission coefficient, center of gravity offset, expected dynamic load, and ground bearing capacity. The output is a set of feasible solutions that meet the stability requirements.

[0043] Among them, the Traveling Salesman Problem algorithm is a graph theory optimization algorithm used to determine the optimal path for the installation of electromechanical equipment. By constructing a distance matrix between spatial nodes, it finds the closed loop that passes through all necessary nodes and has the shortest path, thus ensuring the highest movement efficiency during the installation of electromechanical equipment.

[0044] The specific implementation methods of the above steps are described in detail below.

[0045] The specific implementation of step S01 involves using a multi-dimensional positioning device to perform omnidirectional scanning measurements of a complex area. This multi-dimensional positioning device employs the principle of triangulation, emitting a laser beam and receiving reflected signals through a laser ranging system. Combined with horizontal and vertical angle data recorded by an angle encoder, it calculates the spatial point coordinates. First, the multi-dimensional positioning device is activated, with a scanning resolution set to 0.5 mm, covering the entire installation area. Then, an omnidirectional scan is performed to acquire the coordinates of reflected points on all surfaces within the area, forming raw point cloud data. Next, a nearest neighbor clustering algorithm is used to denoise the raw point cloud data, filtering out outliers and noise points. Subsequently, an iterative nearest point algorithm is applied to register the point cloud data, eliminating coordinate system differences caused by scanning from different stations. Finally, an initial positioning vector database is constructed based on an octree spatial partitioning algorithm, converting the spatial point cloud data into a set of directed vectors to determine the installation reference position of the electromechanical equipment. The purpose of this step is to obtain accurate three-dimensional spatial information of the complex area, providing basic data support for subsequent positioning and installation, with positioning accuracy controlled within ±1 mm.

[0046] The specific implementation of step S02 involves determining key parameters and installation coordinates based on the technical specifications of the electromechanical equipment. First, the technical documents of the electromechanical equipment are consulted to obtain parameters such as the equipment's external dimensions, weight distribution, and fixed point locations. Then, based on the principle of center of mass calculation, the finite element analysis method is applied to determine the coordinates of the electromechanical equipment's center of mass. Let the mass of the equipment be m, and the mass of each component be m. i The centroid coordinates of each component are (x i y i , z i If the coordinates of the equipment's center of gravity are (∑m), then the coordinates of the center of gravity are (∑m). i x i / m,∑m i y i / m,∑m i z i / m); Next, based on the equipment installation requirements, determine the relative coordinates of the equipment's fixed points, typically selecting 4 to 8 fixed points to ensure stability; then, combine the center of gravity coordinates with the fixed point coordinates to form an installation coordinate matrix, which contains the coordinates of all key points requiring positioning; finally, based on the actual conditions of the installation surface, set correction parameters, including elevation adjustment, horizontal displacement, and rotation angle. The threshold values ​​for these correction parameters are ±5mm for elevation adjustment, ±3mm for horizontal displacement, and ±0.5° for rotation angle. The purpose of this step is to determine the precise coordinates of the theoretical installation position of the electromechanical equipment, providing a data basis for subsequent actual installation.

[0047] The specific implementation of step S03 involves using a coordinate measuring arm to mark and measure control points. First, control points are set at locations with distinct characteristics and uniform distribution within the complex area, with no fewer than 12 control points spaced 2–5 meters apart. Then, the coordinate measuring arm is used to perform three-dimensional coordinate measurements on these control points, achieving a measurement accuracy of ±0.02 mm. Next, the measured actual coordinates are compared with the theoretical coordinates on the design drawings, and the coordinate deviation value for each control point is calculated. Subsequently, a least squares fitting algorithm is used to calculate a spatial compensation variation vector based on the obtained deviation values. This vector includes spatial translation (Δx, Δy, Δz) and rotation (θx, θy, θz). Finally, residual analysis is performed on the fitting results to ensure that the fitting accuracy meets the requirements, with a residual standard deviation of less than 0.1 mm. The purpose of this step is to obtain the deviation information between the actual space and the theoretical space, generate a spatial compensation variation vector, and provide a correction basis for subsequent installation and positioning.

[0048] The specific implementation of step S04 involves measuring the structural deformation caused by changes in ambient temperature and calculating the thermal expansion displacement vector. First, a laser tracking interferometer is set up, with multiple measurement target points established in a complex area. Then, the ambient reference temperature T0 and the real-time temperature T are recorded, with a temperature monitoring accuracy of ±0.1℃. Next, the laser tracking interferometer is used to continuously measure the changes in the target point position under different temperatures, with a measurement frequency of 10 times / hour. Subsequently, based on the linear thermal expansion theory, the thermal expansion displacement vector is calculated. Let the linear thermal expansion coefficient of the material be α, then the thermal expansion displacement ΔL = L0·Δ·(T-T0), where L0 is the reference length. Finally, the spatial compensation displacement vector and the thermal expansion displacement vector are synthesized using the principle of vector superposition to form a comprehensive displacement vector. The calculation of the comprehensive displacement vector considers the directionality and magnitude of both displacement vectors. The purpose of this step is to compensate for the positioning error caused by temperature changes and improve installation accuracy. The effective temperature range for thermal expansion compensation is 15–35℃.

[0049] The specific implementation of step S05 is based on computer simulation of the installation environment using acquired data to determine the optimal installation path. First, the initial positioning vector database and the comprehensive change vector are imported into the computer simulation system to construct a three-dimensional virtual installation environment. Then, the starting and ending points for the electromechanical equipment installation are set in the virtual environment, and all necessary nodes and obstacle locations are marked. Next, an improved traveling salesman problem algorithm is applied for path planning. This algorithm combines ant colony optimization and genetic algorithms, setting the pheromone decay coefficient to 0.8, the population size to 100, and the number of iterations to 500, to find the optimal path with the minimum total path length that meets obstacle avoidance requirements. Subsequently, the equipment transmission process is dynamically simulated along the planned path to identify areas where the comprehensive change vector changes significantly, i.e., critical regions. The criterion for determining critical regions is that the rate of change of the comprehensive change vector exceeds 5% / m. Finally, the critical regions are marked, and a detailed path navigation map is generated. The threshold for minimizing the total path length is set to ensure that the actual path length does not exceed 120% of the theoretical shortest path. The purpose of this step is to ensure the safe and efficient transmission of electromechanical equipment from the entrance to the installation location, avoiding collisions and unnecessary path extensions.

[0050] The specific implementation of step S06 involves constructing a spatial region matrix and calculating the selectable installation areas for electromechanical equipment. First, a spatial gridding method is used to divide the installation space into cubic grid cells with sides of 10cm. Then, based on the spatial occupancy information in the initial positioning vector database, a spatial region overlap matrix is ​​constructed. This matrix uses a three-dimensional sparse matrix storage format, where element values ​​represent the spatial overlap of each grid cell. Next, a spatial region vacancy matrix is ​​constructed, marking the occupancy status of each grid cell: 0 indicates vacancy, 1 indicates occupancy, and 0.5 indicates partial occupancy. Subsequently, combining the initial positioning vector database, the comprehensive change vector, and the spatial region overlap matrix, Boolean operations and spatial filtering algorithms are applied to calculate and generate selectable installation areas for electromechanical equipment. These areas satisfy the conditions of spatial overlap less than 10% and good continuity. Finally, a visual recognition system is deployed to dynamically monitor the selectable areas, using a deep learning object detection algorithm to identify dynamic obstacles within the area in real time, with a detection frequency of 30 frames / second and a recognition accuracy greater than 95%. The purpose of this step is to determine the available space range that meets the installation requirements, providing spatial constraints for the selection of the optimal installation location.

[0051] The specific implementation of step S07 involves using the Lagrange multiplier constrained optimization equations to determine the optimal installation point and then carrying out the installation. First, a Lagrange multiplier constrained optimization equation set is constructed, including the objective function equation, position constraint equation, attitude constraint equation, and stability constraint equation. Then, relevant parameters are input, including the coordinates of the electromechanical equipment's center of gravity, the mounting surface normal vector, and the comprehensive variation vector. The augmented Lagrange method is then applied to solve the optimization equation set, with the iterative convergence accuracy set to 10. -6 Next, based on the solution results, the optimal installation point is determined, and positioning parameters for six degrees of freedom are generated. Then, an air-float auxiliary device is activated, with the air cushion pressure controlled between 0.6 and 0.8 MPa, to smoothly transport the electromechanical equipment to the selectable area. Finally, a five-axis adjustment platform is used for fine-tuning the positioning. The platform's translational accuracy is ±0.005 mm, and its rotational accuracy is ±0.001°. A closed-loop control system precisely adjusts the equipment's translational displacement in three directions and its rotational angle in two directions until the theoretically optimal position is reached. The purpose of this step is to determine the optimal installation position of the electromechanical equipment and achieve precise transport and positioning while satisfying various constraints.

[0052] The specific implementation of step S08 involves using high-precision measurement sensors to monitor the deviation between the installation position and the theoretical position in real time and then completing the fixed installation. First, optical reflective targets and displacement sensors are installed at key locations on the electromechanical equipment. Then, a high-precision measurement system, including a laser tracker and an electronic level, is activated to continuously monitor the actual position of the equipment at a sampling frequency of 5Hz. Next, the deviation between the current position and the theoretical optimal position is calculated in real time, including positional and angular deviations. Subsequently, based on the deviation values, a five-axis adjustment platform is used for real-time position correction until the deviation is less than a preset threshold, which is set to a positional deviation of less than 0.05mm and an angular deviation of less than 0.01°. Finally, after the preset accuracy requirements are met, the adjustment platform is locked, and the equipment is fixed using matching fasteners according to the torque control method, with a torque control accuracy of ±2%. The purpose of this step is to ensure high precision in the installation position of the electromechanical equipment, achieving accurate positioning and stable installation through real-time monitoring and feedback adjustment.

[0053] The specific implementation of step S09 involves verifying the installation accuracy and performance of the electromechanical equipment through operational testing. First, a no-load operation test is conducted on the installed electromechanical equipment, recording parameters such as vibration, noise, and temperature rise. Then, a load operation test is performed, with the load gradually increasing from 25% to 100%, and each load point lasting at least 30 minutes. Next, precision measuring instruments are used to monitor the positional changes of the equipment during operation, including foundation settlement, horizontal displacement, and rotation angle changes. Subsequently, the test data is compared and analyzed with the design requirements to determine whether the equipment's positioning and installation accuracy meets the requirements. The criteria are a positional error of less than 0.1 mm, an angle error of less than 0.05°, and a vibration amplitude of less than 80% of the design limit. Finally, an installation quality acceptance report is generated based on the test results, recording all key parameters and test data. The purpose of this step is to verify the installation quality of the electromechanical equipment through actual operational testing, ensuring that the accuracy and performance of the equipment in its working state meet the design requirements.

[0054] Optionally, the multi-dimensional positioning device consists of a laser ranging system, an angle encoder, a high-resolution imaging system, and a data processing unit. The laser ranging system includes a semiconductor laser emitter and a photodetector, with a working wavelength of 780nm and a ranging accuracy of ±0.3mm. The angle encoder adopts a high-precision grating structure with a horizontal angle resolution of 0.0005° and a vertical angle resolution of 0.0005°, and an angle measurement range of 360° horizontally and ±45° vertically. The high-resolution imaging system consists of a 10-megapixel industrial camera and an autofocus lens, with a field of view of 60°, supporting scene texture capture and feature recognition. The data processing unit adopts an embedded high-performance computing platform, equipped with a digital signal processing chip and a real-time point cloud processing algorithm, which can simultaneously process ranging, angle, and image data to achieve millimeter-level spatial positioning and 3D reconstruction functions.

[0055] Optionally, the coordinate measuring arm is a multi-joint robotic arm-type high-precision three-dimensional measuring device, consisting of a base, multi-stage carbon fiber linkages, joint encoders, probes, and a control system. The base adopts a stable triangular support structure with a built-in automatic horizontal compensation mechanism. The multi-stage carbon fiber linkages typically have 6 to 7 stages and are made of high-modulus carbon fiber composite material, possessing high rigidity and a low coefficient of thermal expansion. The joint encoders are installed at the joints of each linkage, achieving a resolution of 0.0001°, and are used for real-time monitoring of the angles of each joint. The probes include both hard styluses and non-contact laser scanning heads. The styluses have a measurement accuracy of ±0.01mm, while the laser scanning head has a point cloud acquisition density of 1000 points / second. The control system employs real-time dynamic compensation technology, which can eliminate measurement errors caused by joint deflection and temperature drift. The effective measurement range is 2 to 3m, and the overall measurement accuracy reaches ±0.02mm.

[0056] Optionally, a laser tracking interferometer is a device for high-precision, large-scale three-dimensional coordinate measurement. It consists of a laser interferometric measurement system, a high-precision servo turntable, an automatic target tracking system, and a measurement data processing system. The laser interferometric measurement system uses a frequency-stabilized helium-neon laser with a wavelength stability better than 10. -7 The resolution reaches 0.1μm; the high-precision servo turntable has two-axis rotational degrees of freedom, an angular resolution of 0.00001°, and an angular repeatability accuracy of ±0.0001°; the automatic target tracking system includes a four-quadrant photoelectric detector and a high-speed servo control loop, which can lock and track moving targets in real time, with a tracking speed of up to 4m / s; the measurement data processing system adopts an adaptive Kalman filter algorithm to realize real-time fusion processing of distance and angle data, with a measurement range of up to 80m and an absolute measurement accuracy of ±10μm+0.5μm / m.

[0057] Optional,

[0058] The air flotation auxiliary device is an auxiliary system for the easy handling of heavy machinery and equipment. It consists of an air pump, an air cushion plate, a pressure regulating valve, and a control system. The air pump uses an oil-free screw compressor with a maximum output pressure of 1.0 MPa and a flow rate of 1.2 m³ / h. 3 / min; The air cushion is made of high-strength aluminum alloy, with a special microporous membrane structure on the bottom. The micropore diameter is 50-100μm and the density is 400-600 pores / cm³. 2 It forms a uniform air film; the pressure regulating valve adopts electronic proportional regulation technology, with a pressure regulation range of 0.2~0.8MPa and an adjustment accuracy of ±0.01MPa; the control system includes a pressure sensor, an tilt sensor and a microprocessor, which realizes real-time balanced regulation of the air cushion pressure through closed-loop control, with a maximum load capacity of 5000kg and a friction coefficient reduced to below 0.001, which can effectively reduce movement resistance and realize the smooth and precise movement of heavy equipment.

[0059] Optionally, the five-axis adjustment platform is a high-precision position adjustment device, consisting of a base platform, a three-dimensional displacement mechanism, a two-dimensional rotation mechanism, and a control system. The base platform uses a heavy-duty steel structure with a precision-ground surface achieving a flatness of 0.01 mm / m. The three-dimensional displacement mechanism includes three sets of mutually perpendicular precision guide rails and lead screw drive units, with a stroke of ±50 mm per axis and a positioning resolution of 0.001 mm. The two-dimensional rotation mechanism uses a worm gear transmission structure, coupled with a high-precision reducer, to achieve precise rotation around the X and Y axes, with a rotation range of ±5° and an angular resolution of 0.0005°. The control system employs six-axis linkage closed-loop control technology, equipped with high-precision displacement sensors and angle encoders, achieving sub-micron level positioning accuracy through a PID algorithm. The system's repeatability reaches ±0.005 mm, and its rated load capacity is 2000 kg.

[0060] Optionally, the high-precision measurement sensor system is a comprehensive measurement system used for real-time monitoring of the installation position of electromechanical equipment. It consists of an optical reflective target, a displacement sensor, a laser tracker, an electronic level, and a data acquisition and processing system. The optical reflective target adopts a spherical reflector design with a reflection error of less than 0.5μm; the displacement sensor adopts a capacitive non-contact measurement principle with a measurement range of 0–10mm and a resolution of 0.1μm; the laser tracker adopts absolute interferometric ranging technology with a measurement range of 2–40m and an accuracy of ±5μm+2μm / m; the electronic level adopts a liquid pendulum sensor with a measurement range of ±10′ and a resolution of 0.1″; the data acquisition and processing system adopts real-time multi-sensor data fusion technology, supports high-precision position calculation at a sampling frequency of 5Hz, and the overall measurement accuracy of the system is better than ±0.05mm.

[0061] Optionally, the visual recognition system is an intelligent system for dynamically monitoring the optional installation area. It consists of multiple high-definition cameras, a depth camera, an image processing unit, and an artificial intelligence recognition module. The high-definition cameras are 4-megapixel industrial cameras with a frame rate of 60fps and a field of view of 120°. The depth camera is based on the principle of structured light, with a depth resolution of 1mm and a measurement range of 0.5–8m. The image processing unit adopts a GPU-accelerated computing architecture, supporting real-time image filtering, feature extraction, and target tracking. The artificial intelligence recognition module is based on a deep learning convolutional neural network and uses the YOLO v5 target detection algorithm. After training with more than 10,000 samples, it can identify dynamic obstacles and personnel in the installation environment in real time with an accuracy greater than 95% and a response time of less than 30ms. It also supports simultaneous tracking of multiple targets.

[0062] The mathematical model or calculation process involved in this invention will be described in detail below.

[0063] Step S01 involves a multi-dimensional positioning instrument performing omnidirectional scanning measurements on a complex area. The calculation of spatial point coordinates is primarily based on the principle of laser triangulation. Specifically, it is shown below:

[0064] P i =(x i y i , z i )=(d i ·sinθ i ·cosφ i d i ·sinθ i ·sinφ i d i ·cosθ i );

[0065] In the formula, P i d represents the three-dimensional coordinates of the i-th spatial point; i θ represents the distance measured by the laser ranging system, in millimeters. i This represents the vertical angle value, measured by a vertical angle encoder, and is expressed in radians; φ i This represents the horizontal angle value, measured by a horizontal angle encoder, and is expressed in radians.

[0066] For noise reduction of point cloud data, the nearest neighbor clustering algorithm is used, as shown below:

[0067]

[0068] C i ={P j |D ij <δ, j = 1, 2, ..., n};

[0069] O i ={P i ||C i |<τ};

[0070] In the formula, D ij Point P i With point P j The Euclidean distance between them; C i Indicated by point P i The clustering result centered on; δ represents the cluster radius threshold, ranging from 2 to 5 mm; |C i | represents clustering C i The number of points included; τ represents the noise point judgment threshold, with a value ranging from 5 to 10; O i This represents the set of outliers that have been identified.

[0071] The iterative nearest-point algorithm is used for point cloud registration. Its objective function and transformation matrix are specifically represented as follows:

[0072]

[0073] In the formula, E(R, t) represents the error function of point cloud registration; N p P represents the number of point pairs participating in registration. i Q represents a point in the target point cloud; i Indicates the relationship between the source point cloud and P i The corresponding closest point; R represents the rotation matrix, which is a 3×3 matrix; t represents the translation vector, which is a 3×1 vector; T represents the homogeneous transformation matrix, which is a 4×4 matrix; r ij Represents the elements of the rotation matrix; t x t y t z The three components of the translation vector are represented. The iterative nearest-point algorithm achieves point cloud registration by minimizing the error function E(R, t) and solving for the optimal transformation matrix T.

[0074] The initial localization vector database is constructed using an octree space partitioning algorithm, and its node splitting criteria and vector calculation are specifically represented as follows:

[0075] V ijk ={(x, y, z)|x min +iΔx≤x <x min +(i+1)Δx, y min +jΔt≤y <y min +(j+1)Δy,z min +kΔz≤z <z min +(k+1)Δz};

[0076]

[0077] In the formula, V ijk The octet represents a voxel in the octree; i, j, and k represent the voxel indices; Δx, Δy, and Δz represent the voxel dimensions, ranging from 10 to 50 mm; x min y min z min D represents the minimum coordinate value of the point cloud data. v Represents the initial localization vector database; p i Represents points in a point cloud; Point p i The normal vector at point N(p); i ) represents point p i The neighborhood point set; |N(p iThe '|' represents the size of the neighborhood point set. The normal vector is calculated using the average of the cross products of the neighborhood points. This method effectively reduces the impact of noise and improves the accuracy of the normal vector calculation.

[0078] Step S02 involves calculating the coordinates of the center of gravity and the installation coordinate matrix of the electromechanical equipment. Specifically, it is shown below:

[0079]

[0080] A modified =A·R(α,β,γ)+T(Δx,Δy,Δz);

[0081] In the formula, G represents the coordinates of the center of gravity of the electromechanical equipment; x G y G z G The three coordinate components represent the center of gravity; M represents the total mass of the equipment, in kilograms; N c Indicates the number of device components; m i The mass of the i-th component is expressed in kilograms; x i y i z i Represents the coordinates of the centroid of the i-th component; F represents the set of fixed point coordinates; N f This indicates the number of fixed points, typically 4 to 8; F i A represents the coordinates of the i-th fixed point; A represents the installation coordinate matrix, which includes the centroid coordinates and the coordinates of all fixed points; A modified This represents the installation coordinate matrix after parameter correction; R(α, β, γ) represents the rotation matrix, determined by rotation angles α, β, and γ; T(Δx, Δy, Δz) represents the translation matrix, determined by translation amounts Δx, Δy, and Δz. The threshold values ​​for the correction parameters are: elevation adjustment Δz: ±5mm, horizontal displacement Δx, Δy: ±3mm, and rotation angles α, β, γ: ±0.5°.

[0082] Step S03 involves calculating the spatial compensation variation vector. Specifically, it is represented as follows:

[0083]

[0084] ΔCP i =CP actual，i -CP i =(Δx) i Δy i Δz i );

[0085]

[0086] ΔT(P)=R Δ ·P+T Δ-P;

[0087] R Δ =R z (δγ)·R y (δβ)·R x (δα);

[0088] T Δ = (δx, δy, δz);

[0089]

[0090] In the formula, CP represents the theoretical coordinate set of the control points; N cp Indicates the number of control points, not less than 12; CP i Represents the theoretical coordinates of the i-th control point; CP actual CP represents the set of actual measured coordinates of control points. actual，i ΔCP represents the actual measured coordinates of the i-th control point; i Represents the coordinate deviation of the i-th control point; ΔT represents the spatial transformation function; ||·|| represents the Euclidean distance norm; R Δ R represents the rotation correction matrix; x R y R z δα, δβ, and δγ represent the rotation matrices about the x-axis, y-axis, and z-axis, respectively; δα, δβ, and δγ represent the rotation angles in the three directions, in radians; T Δ δx, δy, and δz represent the translation correction vectors; δx, δy, and δz represent the translation amounts in the three directions, in millimeters. The spatial compensation variation vector contains three translational components and three rotational components. The spatial compensation variation vector is calculated using a least-squares fitting algorithm, which solves for the optimal spatial transformation parameters by minimizing the sum of squares of the control point deviations.

[0091] Step S04 involves calculating the thermal expansion variation vector and synthesizing the combined variation vector. Specifically, it is expressed as follows:

[0092] ΔL i =L 0i ·α i ·(T-T0);

[0093]

[0094] In the formula, ΔL i L represents the thermal expansion displacement at the i-th measurement point, in millimeters; 0i α represents the reference length of the i-th measurement point, in millimeters; i This represents the linear thermal expansion coefficient of a material, expressed in units of 1 / ℃. The value for common materials typically ranges from 1 × 10⁻⁶. -6~25×10 -6 / ℃; T represents the real-time temperature in ℃; T0 represents the ambient reference temperature in ℃; Let represent the direction vector of the i-th measurement point, which is a unit vector; N represents the thermal expansion variation vector at the i-th measurement point; t Indicates the number of thermal expansion measurement points; This represents the average thermal expansion variation vector; Represents the overall change vector; The term represents the interaction between the spatial compensation variation vector and the thermal expansion variation vector; k represents the interaction coefficient, ranging from 0.01 to 0.1. The calculation of the combined variation vector not only considers the simple superposition of the spatial compensation variation vector and the thermal expansion variation vector, but also introduces the interaction term. Used to represent the coupling effect between two changing vectors.

[0095] Step S05 involves path planning calculations for the Traveling Salesman Problem algorithm. Specifically, it is represented as follows:

[0096] D={d ij} n×n ;

[0097]

[0098] τ ij (t+1)=(1-ρ)·τ ij (t)+Δτ ij ;

[0099]

[0100] η ij =1 / d ij ;

[0101] R = {r1, r2, ..., r} n};

[0102]

[0103] CR={r i |ΔV comp (r i ) / ||r i -r i-1 ||>ε};

[0104] In the formula, d represents the distance matrix; d ij x represents the weighted distance from node i to node j; i y i z iRepresents the three-dimensional coordinates of node i; λ represents the obstacle avoidance weight coefficient, with a value ranging from 10 to 100; O ij The obstacle avoidance function represents the path (i, j); π represents the path arrangement; τ ij (t) represents the pheromone concentration along path (i, j); ρ represents the pheromone attenuation coefficient, with a value of 0.8; Δτ ij This represents the increment of pheromones along the path (i, j); m represents the number of ants in the ant colony algorithm, with a value of 100. L represents the pheromone increment left by the k-th ant on the path (i, j); Q represents the pheromone intensity coefficient, ranging from 10 to 100; k This represents the total length of the path constructed by the k-th ant; α represents the probability that the k-th ant chooses to move from node i to node j; α represents the pheromone importance factor, ranging from 1 to 3; β represents the heuristic pheromone importance factor, ranging from 2 to 5; allowed k η represents the set of nodes that the k-th ant is allowed to visit; ij Represents the heuristic information for path (i, j); R represents the sequence of paths obtained through planning; ΔV comp (r i ) represents the path point r i The change in the overall change vector relative to the previous point; CR represents the critical region of the overall change vector; ε represents the threshold for determining the critical region, with a value of 5% / m.

[0105] Step S06 involves constructing the spatial region matrix and calculating the optional regions for electromechanical equipment installation. Specifically, it is shown below:

[0106] G ijk ={(x, y, z)|x min +iΔs≤x <x min +(i+1)Δs,y min +jΔs≤y <y min +(j+1)Δs,z min +kΔs≤z <z min +(k+1)Δs};

[0107] M overlap ={o ijk} I × J×K ;

[0108]

[0109] M free ={f ijk} I×J×K ;

[0110]

[0111] A selectable ={G ijk |f ijk ≤0.5 and G ijk Satisfying the continuity condition;

[0112] C continuity (G ijk )=∑ p，q，r∈{-1，0，1} f i+p，j+q，k+r <c threshold ;

[0113] In the formula, G ijk represents a spatial grid cell; Δs represents the side length of the grid cell, with a value of 10cm; M overlap Represents the spatial region overlap matrix; o ijk Represents the grid cell G ijk Spatial overlap; S occupied Indicates the occupied space area; |G ijk | Represents the grid cell G ijk The volume of |G ijk ∩S occupied | Represents the grid cell G ijk With occupied space S occupied The volume of the intersection; M free f represents the free space matrix; ijk Represents the grid cell G ijk Occupancy status value; o threshold This represents the overlap threshold, with a value of 0.1, or 10%. (A) selectable Indicates the optional installation area for electromechanical equipment; C continuity c represents a continuity conditional function; threshold This represents the continuity threshold, ranging from 10 to 15. The continuity condition requires that the sum of the occupancy state values ​​of a grid cell and its 26 neighboring cells be less than the threshold c. threshold Ensure that the available areas have sufficient contiguous space.

[0114] Step S07 involves solving the Lagrange multiplier-constrained optimization equations. Specifically, it is expressed as follows:

[0115]

[0116] X = (x, y, z, θ) x θ y θ z );

[0117] f(X) = w1f stability (X)+w2f stress(X)+w3f access (X)+w4f deviation (X);

[0118]

[0119] g i (X)≤0, i=1, 2,...,m;

[0120] h j (X)=0, j=1, 2,...,n;

[0121] g position (X)=max{||P(X)-P boundary ||-d safety ,0};

[0122] g orientation (X)=max{|θ i (X)-θ allowable，i |-δθ i ,0},i=1,2,3;

[0123] g stability (X)=max{CoS min -CoS(X), 0};

[0124] h interface (X)=||P interface (X)-P interface，target ||;

[0125] In the formula, L(X, λ) represents the Lagrangian function; X represents the optimization variable vector, which includes the position coordinates (x, y, z) and the attitude angle (θ). x θ y θ z f(X) represents the objective function; g i (X) represents the inequality constraint function; h j (X) represents the equality constraint function; λ i and μ j Let represent the Lagrange multiplier; w1, w2, w3, and w4 represent the weight coefficients of each term in the objective function, ranging from 0 to 1, and satisfying the following conditions: f stability N represents the stability evaluation function; s Indicates the number of support points; F i (X) represents the actual force at the i-th support point; F ideal，i f represents the ideal force at the i-th support point; stress N represents the stress evaluation function; a Indicates the number of stress assessment points; σ i(X) represents the actual stress at the i-th evaluation point; σ allowable，i f represents the allowable stress at the i-th evaluation point; access N represents the interface accessibility evaluation function; p Indicates the number of interface points; P i (X) represents the actual position of the i-th interface point; P interface，i The target position of the i-th interface point is represented by d(·,·); d(·,·) represents the distance function; f deviation G(X) represents the position deviation evaluation function; G(X) represents the actual position of the center of gravity; G ideal Indicates the important psychological position; w r，i The weighting coefficient representing the rotational deviation; g position P(X) represents the position constraint function; P(X) represents the set of points on the outer contour of the device at position X; P boundary Indicates boundary constraints; d safety This indicates a safety clearance, with a value ranging from 50 to 100 mm; g orientation Represents the attitude constraint function; θ allowable，i Indicates the permissible angle range; δθ i Indicates the angular tolerance, ranging from 0.1° to 1°; g stability CoS(X) represents the stability constraint function; CoS(X) represents the stability coefficient; CoS min This represents the minimum stability coefficient requirement, with a value ranging from 1.5 to 2.5; h interface P represents the interface location constraint function; interface (X) indicates the actual location of the interface; P interface，target Indicates the target location of the interface. The iterative convergence accuracy of the augmented Lagrange method is set to 10. -6 .

[0126] Step S08 involves calculating the installation position deviation value. Specifically, it is expressed as follows:

[0127]

[0128] ΔP i =p actual，i -p theoretical，i =(Δx) i Δy i Δz i );

[0129]

[0130] ΔΘ i =θ actual，i -θ theoretical，i i = 1, 2, 3;

[0131]

[0132] ΔP threshold =0.05mm;

[0133] ΔΘ threshold =0.01°;

[0134] In the formula, P actual N represents the set of actual measured locations; m Indicates the number of measurement points; p actual，i P represents the actual position of the i-th measurement point; theoretical p represents the theoretical location point set; theoretical，i ΔP represents the theoretical position of the i-th measurement point; i ΔP represents the positional deviation of the i-th measurement point. rms ΔΘ represents the root mean square value of the positional deviation. i θ represents the angular deviation in the three rotational directions. actual，i Indicates the actual measured angle; θ theoretical，i Indicates a theoretical perspective; ΔΘ rms ΔP represents the root mean square value of the angular deviation. threshold Indicates the position deviation threshold; ΔΘ threshold This represents the angular deviation threshold. When ΔP rms <ΔP threshold And ΔΘ rms <ΔΘ threshold At that time, it was determined that the installation position met the accuracy requirements and fixed installation could be carried out.

[0135] Step S09 involves the location monitoring and acceptance criteria for equipment in operation, as detailed below:

[0136] ΔP operation =P operation -P initial =(Δx) op Δy op Δz op );

[0137] ΔΘ operation =Θ operation -Θ initial =(Δθ) x，op , Δθ y，op , Δθ z，op );

[0138]

[0139] E position =max{||ΔP operation ||,δ settlement};

[0140] E angle =||ΔΘoperation ||;

[0141]

[0142] Q installation =w p ·f p (E position )+w a ·f a (E angle )+w v ·f v (E vibration );

[0143] In the formula, ΔP operation P represents the position change vector of the device during operation; operation P represents the position coordinates of the device during operation; initial Indicates the initial installation position coordinates; ΔΘ operation Θ represents the angular change vector under the operating conditions of the equipment; operation Θ represents the angle while the equipment is in operation; initial Indicates the initial installation angle; δ settlement This indicates the foundation settlement, expressed in millimeters (N). b Indicates the number of basic measuring points; z bi z represents the current elevation of the i-th basic measuring point; bi，initial A represents the initial elevation of the i-th base measuring point; vibration The root mean square value of the vibration amplitude is expressed in millimeters or micrometers; T represents the measurement duration in seconds; a(t) represents the time-domain signal of the vibration acceleration in m / s². 2 E position E represents the position error evaluation index. angle E represents the angular error evaluation index. vibration Indicates the ratio of vibration amplitudes; A design Indicates the design limit vibration amplitude; Q installation This indicates the overall installation quality score; w p w a w v This represents the weighting coefficient, which ranges from 0 to 1 and satisfies w p +w a +w v =1; f p f a f v This represents the scoring mapping function for each error index. The standard for judging whether the installation accuracy meets the requirements is E. position <0.1mm, E angle <0.05°, E vibration <0.8.

[0144] Specifically, the principle of this invention is as follows: the technical principle of this invention is based on the cross-integration of multiple disciplines such as precision measurement, vector analysis, thermodynamics, optimization theory and computer simulation, and constructs a complete method for precise positioning and installation of electromechanical equipment in complex areas.

[0145] First, this invention uses a multi-dimensional positioning device to perform a 3D spatial point cloud data scan of a complex area. This data accurately describes the geometric features of the installation environment, providing a benchmark for subsequent positioning. The initial positioning vector database built based on the point cloud data includes position and direction vectors, comprehensively characterizing the spatial relationship between the electromechanical equipment and its surrounding environment, thus solving the problem of inaccurate environmental description in traditional technologies.

[0146] Secondly, this invention introduces the concepts of spatial compensation variation vector and thermal expansion variation vector. Actual measurement data is acquired using a coordinate measuring arm and a laser tracking interferometer to calculate the comprehensive variation vector. This process essentially establishes a dynamic error compensation model that can calculate positional shifts caused by environmental changes in real time, mathematically solving the problem that traditional methods cannot accurately compensate for the influence of environmental factors.

[0147] Furthermore, this invention uses spatial region overlap matrices and spatial region vacancy matrices to describe the installation space status, combines the Traveling Salesman Problem algorithm to determine the optimal installation path, and applies a set of Lagrange multiplier-constrained optimization equations to determine the optimal installation point. This optimization system transforms the electromechanical equipment installation problem into an optimization problem under multiple constraints, and solves the optimal installation scheme through a mathematical model, theoretically guaranteeing the optimality of the installation location.

[0148] Finally, this invention employs high-precision measurement sensors to monitor the installation process in real time, combined with a five-axis adjustment platform for fine-tuning and positioning, forming a closed-loop control system. This real-time feedback mechanism ensures precision control during installation; the installation is only completed when the deviation is less than a preset threshold, guaranteeing installation accuracy from an engineering practice perspective.

[0149] In summary, this invention acquires basic data through precision measurement technology, establishes an error compensation model using vector analysis, applies optimization theory to solve for the optimal installation scheme, and combines real-time feedback to form closed-loop control, thereby achieving high-precision positioning and installation of electromechanical equipment in complex areas and effectively solving core technical problems.

[0150] The following provides a specific embodiment 1 of the present invention, and the specific implementation of each step in this embodiment 1 is described in detail below.

[0151] The specific implementation of step S01 involves using a multi-dimensional positioning device to perform omnidirectional scanning measurements of a complex area, acquiring spatial point cloud data and constructing an initial positioning vector database. First, the multi-dimensional positioning device is started, with a scanning resolution set to 0.5mm, and the scanning range covering the entire installation area. Then, an omnidirectional scan is performed, measuring the position coordinates of spatial points based on the principle of laser triangulation. The formula for calculating the coordinates of each spatial point is:

[0152] P i =(x i y i , z i )=(d i ·sinθ i ·cosφ i d i ·sinθ i ·sinφ i d i ·cosθ i );

[0153] In the formula, P i d represents the three-dimensional coordinates of the i-th spatial point; i θ represents the distance measured by the laser ranging system, in millimeters. i This represents the vertical angle value, measured by a vertical angle encoder, and is expressed in radians; φ i The horizontal angle value is measured by a horizontal angle encoder and is expressed in radians. Next, the original point cloud data is denoised using a nearest neighbor clustering algorithm to filter out outliers and noise points. The calculation process is as follows:

[0154]

[0155] C i ={P j |D ij <δ, j = 1, 2, ..., n};

[0156] O i ={P i ||C i |<τ};

[0157] In the formula, D ij Point P i With point P j The Euclidean distance between them; C i Indicated by point P i The clustering result centered on; δ represents the cluster radius threshold, ranging from 2 to 5 mm; |C i | represents clustering C i The number of points included; τ represents the noise point judgment threshold, with a value ranging from 5 to 10; Oi This represents the set of identified outliers. Subsequently, the iterative nearest-point algorithm is applied to register the point cloud data, eliminating coordinate system differences caused by scanning from different stations. The objective function and transformation matrix are as follows:

[0158]

[0159] In the formula, E(R, t) represents the error function of point cloud registration; N p P represents the number of point pairs participating in registration. i Q represents a point in the target point cloud; i Indicates the relationship between the source point cloud and P i The corresponding closest point; R represents the rotation matrix, which is a 3×3 matrix; t represents the translation vector, which is a 3×1 vector; T represents the homogeneous transformation matrix, which is a 4×4 matrix; r ij Represents the elements of the rotation matrix; t x t y t z The translation vector has three components. Finally, an initial positioning vector database is constructed based on an octree spatial partitioning algorithm, converting the spatial point cloud data into a set of directed vectors to determine the installation reference position of the electromechanical equipment. The specific calculations are as follows:

[0160] V ijk ={(x, y, z)|x min +iΔx≤x <x min +(i+1)Δx, y min +jΔy≤y <y min +(j+1)Δy,z min +kΔz≤z <z min +(k+1)Δz};

[0161]

[0162] In the formula, V ijk The octet represents a voxel in the octree; i, j, and k represent the voxel indices; Δx, Δy, and Δz represent the voxel dimensions, ranging from 10 to 50 mm; x min y min z min D represents the minimum coordinate value of the point cloud data. v Represents the initial localization vector database; p i Represents points in a point cloud; Point p i The normal vector at point N(p); i ) represents point p i The neighborhood point set; |N(p iThe value )| represents the size of the neighborhood point set. The purpose of this step is to obtain accurate three-dimensional spatial information of complex areas, providing basic data support for subsequent positioning and installation, with positioning accuracy controlled within ±1mm.

[0163] The specific implementation of step S02 involves determining key parameters and the installation coordinate matrix based on the technical specifications of the electromechanical equipment. First, the technical documents of the electromechanical equipment are consulted to obtain parameters such as the equipment's external dimensions, weight distribution, and fixed point locations. Then, based on the principle of centroid calculation, the finite element analysis method is applied to determine the coordinates of the electromechanical equipment's center of gravity. The calculation formula is as follows:

[0164]

[0165] In the formula, G represents the coordinates of the center of gravity of the electromechanical equipment; x G y G z G The three coordinate components represent the center of gravity; M represents the total mass of the equipment, in kilograms; N c Indicates the number of device components; m i The mass of the i-th component is expressed in kilograms; x i y i z i This represents the coordinates of the center of gravity of the i-th component. Next, based on the equipment installation requirements, the relative coordinates of the equipment's fixed points are determined. Typically, 4 to 8 fixed points are selected to ensure stability. The set of fixed point coordinates is as follows:

[0166]

[0167] In the formula, F represents the set of fixed point coordinates; N f Indicates the number of fixed points; F i This represents the coordinates of the i-th fixed point. The centroid coordinates are then combined with the fixed point coordinates to form an installation coordinate matrix, which contains the coordinates of all key points requiring positioning.

[0168]

[0169] In the formula, A represents the installation coordinate matrix, which includes the coordinates of the centroid and all fixed points. Finally, based on the actual situation of the installation surface, correction parameters are set, including elevation adjustment, horizontal displacement, and rotation angle. The corrected installation coordinate matrix is ​​as follows:

[0170] A modified =A·R(α,β,γ)+T(Δx,Δy,Δz);

[0171] In the formula, A modifiedThis represents the installation coordinate matrix after parameter correction; R(α, β, γ) represents the rotation matrix, determined by rotation angles α, β, and γ; T(Δx, Δy, Δz) represents the translation matrix, determined by translation amounts Δx, Δy, and Δz. The threshold values ​​for the correction parameters are: elevation adjustment Δz: ±5mm, horizontal displacement Δx, Δy: ±3mm, and rotation angles α, β, γ: ±0.5°. The purpose of this step is to determine the precise coordinates of the theoretical installation position of the electromechanical equipment, providing a data foundation for subsequent actual installation.

[0172] The specific implementation of step S03 involves using a coordinate measuring arm to mark and measure control points, generating a spatial compensation variation vector. First, control points are set at locations with distinct characteristics and uniform distribution within the complex area, with no fewer than 12 control points spaced 2–5 m apart. Then, the coordinate measuring arm is used to perform three-dimensional coordinate measurements on these control points, achieving a measurement accuracy of ±0.02 mm. The control point coordinate set is represented as follows:

[0173]

[0174] In the formula, CP represents the theoretical coordinate set of the control points; N cp Indicates the number of control points; CP i Represents the theoretical coordinates of the i-th control point; CP actual CP represents the set of actual measured coordinates of control points. actual，i This represents the actual measured coordinates of the i-th control point. Next, the measured actual coordinates are compared with the theoretical coordinates on the design drawings to calculate the coordinate deviation value for each control point:

[0175] ΔCP i =CP actual，i -CP i =(Δx) i Δy i Δz i );

[0176] In the formula, ΔCP i Let represent the coordinate deviation of the i-th control point. Then, using a least squares fitting algorithm, the spatial compensation variation vector is calculated based on the obtained deviation value, and the objective is to solve for:

[0177]

[0178] ΔT(P)=R Δ ·P+T Δ -P;

[0179] R Δ =R z (δγ)·R y (δβ)·R x(δα);

[0180] T Δ = (δx, δy, δz);

[0181] In the formula, ΔT represents the spatial transformation function; ||·|| represents the Euclidean distance norm; R Δ R represents the rotation correction matrix; x R y R z δα, δβ, and δγ represent the rotation matrices about the x-axis, y-axis, and z-axis, respectively; δα, δβ, and δγ represent the rotation angles in the three directions, in radians; T Δ This represents the translation correction vector; δx, δy, and δz represent the translation amounts in the three directions, in millimeters. Finally, the spatial compensation variation vector is obtained:

[0182]

[0183] In the formula, This represents the spatial compensation variation vector, which includes three translational components and three rotational components. The purpose of this step is to obtain the deviation information between the actual space and the theoretical space, generate the spatial compensation variation vector, and provide a basis for correction in subsequent installation and positioning.

[0184] The specific implementation of step S04 involves measuring the structural deformation caused by changes in ambient temperature and calculating the thermal expansion variation vector and the comprehensive variation vector. First, a laser tracking interferometer is set up, and multiple measurement target points are established in a complex area. Then, the ambient reference temperature T0 and the real-time temperature T are recorded, with a temperature monitoring accuracy of ±0.1℃. Next, the laser tracking interferometer is used to continuously measure the changes in the target point position under different temperatures, with a measurement frequency of 10 times / hour. Subsequently, based on the linear thermal expansion theory, the thermal expansion variation vector is calculated.

[0185] ΔL i =L 0i ·α i ·(T-T0);

[0186]

[0187] In the formula, ΔL i L represents the thermal expansion displacement at the i-th measurement point, in millimeters; 0i α represents the reference length of the i-th measurement point, in millimeters; i This represents the linear thermal expansion coefficient of a material, expressed in units of 1 / ℃. The value for common materials typically ranges from 1 × 10⁻⁶. -6 ~25×10 -6 / ℃; Let represent the direction vector of the i-th measurement point, which is a unit vector; N represents the thermal expansion variation vector at the i-th measurement point; t Indicates the number of thermal expansion measurement points; This represents the average thermal expansion variation vector. Finally, the spatial compensation variation vector and the thermal expansion variation vector are synthesized using the principle of vector superposition to form a comprehensive variation vector:

[0188]

[0189] In the formula, Represents the overall change vector; This represents the intersection of the spatial compensation variation vector and the thermal expansion variation vector; k represents the intersection coefficient, with a value ranging from 0.01 to 0.1. The purpose of this step is to compensate for positioning errors caused by temperature changes and improve installation accuracy. The effective temperature range for thermal expansion compensation is 15 to 35℃.

[0190] The specific implementation of step S05 is based on computer simulation of the installation environment using acquired data to determine the optimal installation path. First, the initial positioning vector database and the comprehensive change vector are imported into the computer simulation system to construct a three-dimensional virtual installation environment. Then, the starting and ending points for the installation of electromechanical equipment are set in the virtual environment, and the positions of all necessary nodes and obstacles are marked. Next, an improved traveling salesman problem algorithm is applied for path planning. The mathematical model of the algorithm is as follows:

[0191] D={d ij} n×n ;

[0192]

[0193] In the formula, D represents the distance matrix; d ij x represents the weighted distance from node i to node j; i y i z i Represents the three-dimensional coordinates of node i; λ represents the obstacle avoidance weight coefficient, with a value ranging from 10 to 100; O ij Let represent the obstacle avoidance function for path (i, j); π represents the path arrangement. This algorithm combines ant colony optimization and genetic algorithms. The key formula for the ant colony optimization part is:

[0194] τ ij (t+1)=(1-ρ)·τ ij (t)+Δτ ij ;

[0195]

[0196] η ij =1 / d ij ;

[0197] In the formula, τ ij (t) represents the pheromone concentration along path (i, j); ρ represents the pheromone attenuation coefficient, with a value of 0.8; Δτ ij This represents the increment of pheromones along the path (i, j); m represents the number of ants in the ant colony algorithm, with a value of 100. L represents the pheromone increment left by the k-th ant on the path (i, j); Q represents the pheromone intensity coefficient, ranging from 10 to 100; k This represents the total length of the path constructed by the k-th ant; α represents the probability that the k-th ant chooses to move from node i to node j; α represents the pheromone importance factor, ranging from 1 to 3; β represents the heuristic pheromone importance factor, ranging from 2 to 5; allowed k η represents the set of nodes that the k-th ant is allowed to visit; ij This represents the heuristic information for the path (i, j). Subsequently, a dynamic simulation of the device transmission process is performed along the planned path to identify regions where the overall change vector changes significantly, i.e., the critical regions.

[0198] R = {r1, r2, ..., r} n};

[0199]

[0200] CR={r i |ΔV comp (r i ) / ||r i -r i-1 ||>ε};

[0201] In the formula, R represents the planned path sequence; ΔV comp (r i ) represents the path point r i The change in the overall change vector relative to the previous point; CR represents the critical region of the overall change vector; ε represents the threshold for determining the critical region, with a value of 5% / m. This step ensures the safe and efficient transmission of electromechanical equipment from the entrance to the installation location, avoiding collisions and unnecessary path extensions.

[0202] The specific implementation of step S06 involves constructing a spatial region matrix and calculating the selectable installation areas for electrical equipment. First, a spatial gridding method is used to divide the installation space into cubic grid units with sides of 10cm.

[0203] G ijk ={(x, y, z)|x min +iΔs≤x <x min +(i+1)Δs,ymin +jΔs≤y <y min +(j+1)Δs,z min +kΔs≤z <z min +(k+1)Δs};

[0204] In the formula, G ijk This represents a spatial grid cell; Δs represents the side length of the grid cell, with a value of 10cm. Then, based on the spatial occupancy information in the initial positioning vector database, a spatial region overlap matrix is ​​constructed:

[0205] M overlap ={o ijk} I×J×K ;

[0206]

[0207] In the formula, M overlap Represents the spatial region overlap matrix; o ijk Represents the grid cell G ijk Spatial overlap; S occupied Indicates the occupied space area; |G ijk | Represents the grid cell G ijk The volume of |G ijk ∩S occupied | Represents the grid cell G ijk With occupied space S occupied The intersection volume. Next, construct the spatial region free space matrix:

[0208] M free ={f ijk} I×J×K ;

[0209]

[0210] In the formula, M free f represents the free space matrix; ijk Represents the grid cell G ijk Occupancy status value; o threshold This represents the overlap threshold, with a value of 0.1, or 10%. Subsequently, combining the initial positioning vector database, the comprehensive change vector, and the spatial region overlap matrix, Boolean operations and spatial filtering algorithms are applied to calculate and generate the optional installation areas for electromechanical equipment.

[0211] A selectable ={G ijk |f ijk ≤0.5 and G ijk Satisfying the continuity condition;

[0212]

[0213] In the formula, A selectable Indicates the optional installation area for electromechanical equipment; C continuity c represents a continuity conditional function; threshold The continuity threshold is represented, ranging from 10 to 15. Finally, a visual recognition system is deployed to dynamically monitor the selectable area, employing a deep learning object detection algorithm to identify dynamic obstacles within the area in real time. The detection frequency is 30 frames per second, and the recognition accuracy is greater than 95%. The purpose of this step is to determine the available space range that meets the installation requirements, providing spatial constraints for selecting the optimal installation location.

[0214] The specific implementation of step S07 involves using the Lagrange multiplier constrained optimization equations to determine the optimal installation location and then carrying out the installation. First, the Lagrange multiplier constrained optimization equations are constructed:

[0215]

[0216] X = (x, y, z, θ) x θ y θ z );

[0217] In the formula, L(X, λ) represents the Lagrangian function; X represents the optimization variable vector, which includes the position coordinates (x, y, z) and the attitude angle (θ). x θ y θ z );λ i and μ j Let represent the Lagrange multiplier. The objective function is:

[0218] f(X) = w1f stability (X)+w2f stress (X)+w3f access (X)+w4f deviation (X);

[0219]

[0220] In the formula, f(X) represents the objective function; w1, w2, w3, and w4 represent the weight coefficients of each term in the objective function, with values ​​ranging from 0 to 1, and satisfying the following condition: f stability N represents the stability evaluation function; s Indicates the number of support points; F i (X) represents the actual force at the i-th support point; F ideal，i f represents the ideal force at the i-th support point; stress N represents the stress evaluation function; a Indicates the number of stress assessment points; σ i(X) represents the actual stress at the i-th evaluation point; σ allowable，i f represents the allowable stress at the i-th evaluation point; access N represents the interface accessibility evaluation function; p Indicates the number of interface points; P i (X) represents the actual position of the i-th interface point; P interface，i The target position of the i-th interface point is represented by d(·,·); d(·,·) represents the distance function; f deviation G(X) represents the position deviation evaluation function; G(X) represents the actual position of the center of gravity; G ideal Indicates the ideal position of importance;

[0221] w r，i These represent the weighting coefficients for rotational deviations. The constraint functions include:

[0222] g i (X)≤0, i=1, 2,...,m;

[0223] h j (X)=0, j=1, 2,...,n;

[0224] g position (X)=max{||P(X)-P boundary ||-d safety ,0};

[0225] g orientation (X)=max{|θ i (X)-θ allowable，i |-δθ i ,0},i=1,2,3;

[0226] g stability (X)=max{CoS min -CoS(X), 0};

[0227] h interface (X)=||P interface (X)-P interface，target ||;

[0228] In the formula, g i (X) represents the inequality constraint function; h j (X) represents the equality constraint function; g position P(X) represents the position constraint function; P(X) represents the set of points on the outer contour of the device at position X; P boundary Indicates boundary constraints; d safety This indicates a safety clearance, with a value ranging from 50 to 100 mm; g orientation Represents the attitude constraint function; θ allowable，i Indicates the permissible angle range; δθ iIndicates the angular tolerance, ranging from 0.1° to 1°; g stability CoS(X) represents the stability constraint function; CoS(X) represents the stability coefficient; CoS min This represents the minimum stability coefficient requirement, with a value ranging from 1.5 to 2.5; h interface P represents the interface location constraint function; interface (X) indicates the actual location of the interface; P interface，target This indicates the target location of the interface. Then, input the relevant parameters and apply the augmented Lagrange method to solve the optimization equations, setting the iterative convergence accuracy to 10. -6 Next, based on the solution results, the optimal installation point is determined, and positioning parameters for six degrees of freedom are generated. Then, an air-float auxiliary device is activated, with the air cushion pressure controlled between 0.6 and 0.8 MPa, to smoothly transport the electromechanical equipment to the selectable area. Finally, a five-axis adjustment platform is used for fine-tuning the positioning. The platform's translational accuracy is ±0.005 mm, and its rotational accuracy is ±0.001°. A closed-loop control system precisely adjusts the equipment's translational displacement in three directions and its rotational angle in two directions until the theoretically optimal position is reached. The purpose of this step is to determine the optimal installation position of the electromechanical equipment and achieve precise transport and positioning while satisfying various constraints.

[0229] The specific implementation of step S08 involves using a high-precision measurement sensor to monitor the deviation between the installed position and the theoretical position in real time and completing the fixed installation. First, optical reflective targets and displacement sensors are installed at key locations on the electromechanical equipment. Then, a high-precision measurement system, including a laser tracker and an electronic level, is activated to continuously monitor the actual position of the equipment at a sampling frequency of 5Hz. Next, the deviation between the current position and the theoretical optimal position is calculated in real time. The formula for calculating the deviation is:

[0230]

[0231] ΔP i =p actual，i -p theoretical，i =(Δx) i Δy i Δz i );

[0232]

[0233] ΔΘ i =θ actual，i -θ theoretical，i i = 1, 2, 3;

[0234]

[0235] In the formula, P actual N represents the set of actual measured locations; mIndicates the number of measurement points; p actual，i P represents the actual position of the i-th measurement point; theoretical p represents the theoretical location point set; theoretical，i ΔP represents the theoretical position of the i-th measurement point; i ΔP represents the positional deviation of the i-th measurement point. rms ΔΘ represents the root mean square value of the positional deviation. i θ represents the angular deviation in the three rotational directions. actual，i Indicates the actual measured angle; θ theoretical，i Indicates a theoretical perspective; ΔΘ rms This represents the root mean square value of the angular deviation. Subsequently, based on the deviation value, the five-axis adjustment platform performs real-time position correction until the deviation value is less than a preset threshold, which is set as follows:

[0236] ΔP threshold =0.05mm;

[0237] ΔΘ threshold =0.01°;

[0238] In the formula, ΔP threshold Indicates the position deviation threshold; ΔΘ threshold This indicates the angular deviation threshold. After reaching the preset accuracy requirement, the adjustment platform is locked, and the matching fasteners are used for fixed installation according to the torque control method, with a torque control accuracy of ±2%. The purpose of this step is to ensure high precision in the installation position of the electromechanical equipment, achieving accurate positioning and stable installation through real-time monitoring and feedback adjustments.

[0239] The specific implementation of step S09 involves verifying the installation accuracy and performance of the electromechanical equipment through operational testing. First, a no-load operation test is conducted on the installed electromechanical equipment, recording parameters such as vibration, noise, and temperature rise. Then, a load operation test is performed, with the load gradually increased from 25% to 100%, and the operation time at each load point not less than 30 minutes. Next, a precision measuring instrument is used to monitor the position changes of the equipment during operation. The formula for calculating the position change is:

[0240] ΔP operation =P operation -P initial =(Δx) op Δy op Δz op );

[0241] ΔΘ operation =Θ operation -Θ initial =(Δθ) x，op , Δθ y，op , Δθ z，op );

[0242]

[0243] In the formula, ΔP operation P represents the position change vector of the device during operation; operation P represents the position coordinates of the device during operation; initial Indicates the initial installation position coordinates; ΔΘ operation Θ represents the angular change vector under the operating conditions of the equipment; operation Θ represents the angle while the equipment is in operation; initial Indicates the initial installation angle; δ settlement This indicates the foundation settlement, expressed in millimeters (N). b Indicates the number of basic measuring points; z bi z represents the current elevation of the i-th basic measuring point; bi，initial This represents the initial elevation of the i-th base measuring point. The vibration amplitude is then calculated.

[0244]

[0245] In the formula, A vibration The root mean square value of the vibration amplitude is expressed in millimeters or micrometers; T represents the measurement duration in seconds; a(t) represents the time-domain signal of the vibration acceleration in m / s². 2 Then, the test data is compared and analyzed with the design requirements to determine whether the equipment positioning and installation accuracy meets the requirements.

[0246] E position =max{||ΔP operation ||,δ settlement};

[0247] E angle =||ΔΘ operation ||;

[0248]

[0249] Q installation =w p ·f p (E position )+w a ·f a (E angle )+w v ·f v (E vibration );

[0250] In the formula, E position E represents the position error evaluation index. angle E represents the angular error evaluation index. vibration Indicates the ratio of vibration amplitudes; A designIndicates the design limit vibration amplitude; Q installation This indicates the overall installation quality score; w p w a w v This represents the weighting coefficient, which ranges from 0 to 1 and satisfies w p +w a +w v =1; f p f a f v This represents the scoring mapping function for each error index. The standard for judging whether the installation accuracy meets the requirements is E. position <0.1mm, E angle <0.05°, E vibration <0.8. Finally, an installation quality acceptance report is generated based on the test results, recording all key parameters and test data. The purpose of this step is to verify the installation quality of the electromechanical equipment through actual operation testing, ensuring that the accuracy and performance of the equipment in working condition meet the design requirements.

[0251] To better understand and implement this invention, a specific application scenario of the invention is provided below as Example 2: A nuclear power plant is undergoing a phase one expansion project, requiring the installation of four steam generators in the secondary loop building. Each steam generator weighs 320 tons, is 11.2m high, and has a diameter of 4.5m. Precise positioning and installation are required in a complex area with dense piping and equipment. Because the steam generators require strict alignment with multiple interfaces such as the main pump, main steam pipeline, and feedwater system, and the installation space is limited, traditional lifting methods are insufficient to meet the positioning accuracy requirements. Therefore, the researchers decided to implement the invention's method for precise positioning and installation of electromechanical equipment in complex areas.

[0252] First, step S01 was performed, using a multi-dimensional positioning device to conduct a 360-degree scan and measurement of the installation area within the secondary circuit plant. The multi-dimensional positioning device used was an MDL-5000 model, with a laser ranging accuracy of ±0.3mm and an angle measurement accuracy of ±0.0005°. Eight scanning stations were set up within the plant, covering approximately 1200m. 2 The installation area was scanned at a resolution of 0.5 mm. After approximately 4 hours of scanning, raw point cloud data of 280 million spatial points was acquired. Noise reduction was performed using a nearest neighbor clustering algorithm, with a cluster radius threshold δ of 3 mm and a noise point detection threshold τ of 8, filtering out approximately 2% of outliers and noise points. Then, an iterative nearest-point algorithm was applied to register the point cloud data from different stations. After 35 iterations, the registration error converged to within 0.7 mm. Finally, an initial positioning vector database was constructed based on an octree spatial partitioning algorithm, with a voxel size of 25 mm, generating a set of approximately 2.3 million directed vectors as the installation reference.

[0253] In step S02, the researchers determined the key parameters and installation coordinate matrix based on the steam generator's technical specifications. Detailed equipment parameters were obtained by consulting technical documents, and the centroid coordinates were calculated using finite element analysis to be (0, 0, 4.28) m (relative to the center point of the equipment's bottom). Based on the installation requirements, the coordinates of eight fixed points were determined, distributed around the bottom support ring of the steam generator. The combination of the centroid coordinates and the fixed point coordinates forms the installation coordinate matrix, as shown in Table 1.

[0254] Table 1. Steam generator installation coordinate matrix (unit: m)

[0255]

[0256]

[0257] Based on the actual conditions of the installation surface, the correction parameters are set as follows: elevation adjustment Δz = +2.5mm, horizontal displacement Δx = -1.2mm, Δy = +0.8mm, rotation angle α = +0.12°, β = -0.08°, γ = +0.03°.

[0258] In step S03, researchers used a coordinate measuring arm to mark and measure control points, generating a spatial compensation variation vector. The coordinate measuring arm used was a CMA-7520, with a measurement accuracy of ±0.015mm and an effective measurement range of 2.5m. Sixteen control points were set up in the installation area, with a spacing of 3–4m between them. The actual coordinates of the control points were obtained through measurement and compared with the theoretical design coordinates. The calculated coordinate deviation values ​​are shown in Table 2 (partial data).

[0259] Table 2 Control point coordinate deviation values ​​(unit: mm)

[0260] Control point numbering Δx Δy Δz CP01 +2.15 -1.87 +3.42 CP02 +2.28 -1.95 +3.56 CP03 +2.42 -2.08 +3.62 CP04 +2.31 -2.12 +3.58 CP05 +1.98 -1.76 +3.45 … … … … CP16 +2.05 -1.82 +3.39

[0261] Using the least squares fitting algorithm, the spatial compensation variation vector is calculated based on the above data.

[0262] In step S04, the researchers measured the structural deformation caused by changes in ambient temperature and calculated the thermal expansion vector. The laser tracking interferometer used was an LTI-3000 with a measurement accuracy of ±5μm + 2μm / m. Twelve measurement target points were set up in the installation area, and the reference temperature T0 = 20.0℃ was recorded, with the real-time temperature fluctuating between 19.2 and 22.8℃. Some of the thermal expansion data obtained through continuous measurement are shown in Table 3.

[0263] Table 3. Partial thermal expansion displacement measurement data

[0264]

[0265] The average thermal expansion variation vector is obtained through calculation. By superimposing the spatial compensation variation vector and the thermal expansion variation vector, and considering the cross-term coefficient k = 0.05, the comprehensive variation vector is obtained.

[0266] In step S05, researchers conducted a computer simulation of the installation environment and determined the optimal installation path. The initial positioning vector database and the comprehensive variation vector were imported into the computer simulation system to construct a three-dimensional virtual installation environment. An improved traveling salesman problem algorithm was used for path planning, with a pheromone decay coefficient ρ set to 0.8, a population size of 100, and 500 iterations. The optimal path from the entrance to the installation location was obtained, with a total length of 87.6 m, 6.8% longer than the theoretical shortest path. Three critical regions of comprehensive variation vector change were identified through dynamic simulation, with a critical region determination threshold ε set at 5% / m. These critical regions are mainly located in areas with large temperature gradient changes and locations where structural support deformation is significant.

[0267] In step S06, the researchers constructed a spatial region matrix and calculated the selectable areas for equipment installation. The installation space was divided into cubic grid cells with sides of 10cm, generating approximately 7.8 million grid cells. The spatial region overlap matrix constructed based on the initial positioning vector database showed that approximately 68% of the space was occupied by surrounding equipment and pipes. An overlap threshold of O was set. threshold The value is 0.1. The optional installation area for electromechanical equipment is calculated using a spatial filtering algorithm, and the continuity threshold c is used. threshold The value is set to 12. The final determined volume of the selectable region is approximately 85m³. 3 It occupies approximately 180% of the steam generator volume, providing ample adjustment space for installation and operation. The deployed visual recognition system can monitor dynamic obstacles in the area in real time, with a recognition accuracy of 97.8%.

[0268] In step S07, the researchers used the Lagrange multiplier-constrained optimization equations to determine the optimal installation point. The objective function weight coefficients were set as w1 = 0.35, w2 = 0.25, w3 = 0.3, and w4 = 0.1. The constraints included: safety clearance d. safety =75mm, angular tolerance δθ i =0.5°, minimum stability coefficient requirement CoS min =2.0. The augmented Lagrangian method is applied to solve the optimization equations, with an iterative convergence accuracy set to 10. -6After 28 iterations, the optimal installation point was obtained. An air flotation auxiliary device was activated, and the air cushion pressure was controlled at 0.72 MPa, smoothly transporting the 320-ton steam generator to the selected area. Fine-tuning and positioning were achieved using a five-axis adjustment platform, realizing sub-millimeter level position control.

[0269] In step S08, researchers used high-precision measurement sensors to monitor the deviation between the installed position and the theoretical position in real time. Optical reflective targets and displacement sensors were installed at eight key locations on the steam generator, and continuous monitoring was performed using a high-precision measurement system with a sampling frequency of 5Hz. After multiple adjustments, the root mean square value of the position deviation ΔP was determined. rms The angle deviation was reduced to 0.042 mm, with the root mean square value ΔΘ. rms The angle decreased to 0.008°, all of which were less than the preset threshold (position deviation threshold ΔP). threshold =0.05mm, angular deviation threshold ΔΘ threshold =0.01°). After achieving the required accuracy, use the matching fasteners to fix and install according to the torque control method, with a torque control accuracy of ±1.5%.

[0270] Finally, in step S09, the researchers verified the installation accuracy and performance of the steam generator through operational tests. A 48-hour no-load operation test and a 72-hour load operation test were conducted, with the load gradually increasing from 25% to 100%. Measurement results showed that the position change vector ΔP under the equipment's operating state... operation The maximum value is 0.082 mm, and the angle change vector is ΔΘ. operation The maximum value is 0.038°, and the foundation settlement δ settlement The amplitude of vibration is 0.035 mm. vibration The value is 0.068 mm, only 72% of the design limit. The calculated position error evaluation index E... position = 0.082mm, angular error evaluation index E angle =0.038°, vibration amplitude ratio E vibration =0.72, which meets the acceptance criteria.

[0271] Traditional nuclear power equipment installation methods rely primarily on large lifting equipment and manual measurement and experience-based positioning. This approach struggles to simultaneously consider spatial compensation and thermal expansion effects, resulting in positioning accuracy typically around ±3mm. Furthermore, it requires multiple trial installations and adjustments, taking 2-3 weeks. In contrast, this invention employs a precise positioning and installation method for electromechanical equipment in complex areas. By acquiring accurate spatial data through a multi-dimensional positioning instrument and considering both spatial compensation and thermal expansion vectors, a Lagrange multiplier constraint optimization algorithm is applied to determine the optimal installation point, improving positioning accuracy to ±0.05mm and reducing installation time to 5 days, significantly enhancing installation efficiency. Moreover, traditional methods are ineffective in addressing obstacle avoidance and confined space operations in complex environments. This invention, however, optimizes the path using a traveling salesman problem algorithm, combined with an air flotation auxiliary device and a five-axis adjustment platform, enabling precise positioning in complex environments with dense pipelines and equipment. This reduces installation risks and improves the safety and reliability of nuclear power equipment installation.

[0272] It should be noted that the variables involved in this invention are explained in detail in Tables 4, 5, 6, and 7 below.

[0273] Table 4. Variable Explanation Table (Part 1)

[0274]

[0275]

[0276] Table 5. Variable Explanation Table (Part Two)

[0277]

[0278]

[0279] Table 6. Variable Explanation Table (Part 3)

[0280]

[0281] Table 7. Variable Explanation Table (Part Four)

[0282]

[0283]

[0284] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for precise positioning and installation of electromechanical equipment in complex areas, characterized in that, include: A multi-dimensional positioning instrument is used to perform a 3D spatial point cloud data of the complex area to construct an initial positioning vector database. Based on the technical specifications of the electromechanical equipment, the installation coordinate matrix is ​​determined. A coordinate measuring arm is used to mark control points and generate spatial compensation variation vectors. A laser tracking interferometer is used to measure the structural deformation caused by changes in ambient temperature, calculate the thermal expansion variation vector, and form a comprehensive variation vector. The optimal installation path for the electromechanical equipment is determined based on the traveling salesman problem algorithm. A spatial region overlap matrix and a spatial region free space matrix are constructed to calculate and generate selectable installation areas for the electromechanical equipment. The optimal installation point was determined by applying the Lagrange multiplier constraint optimization equations, and fine-tuning was performed using a five-axis adjustment platform. High-precision measuring sensors were used to monitor the deviation between the installation position and the theoretical position in real time to complete the fixed installation. Operational testing verified that the installation accuracy met design requirements. The comprehensive variation vector, calculated by superimposing the spatial compensation variation vector and the thermal expansion variation vector, yielded the final positioning correction for precise installation positioning. The selectable region refers to the spatial range that meets the installation accuracy requirements of the electromechanical equipment. It is determined by the initial positioning vector, the comprehensive variation vector, and the spatial region free matrix, representing a three-dimensional spatial tolerance region. The Lagrange multiplier constraint optimization equations include the objective function equation, position constraint equation, attitude constraint equation, and stability constraint equation. The objective function equation is used to calculate the comprehensive evaluation value of the electromechanical equipment installation position; the position constraint equation is used to limit the spatial coordinate range of the electromechanical equipment installation; the attitude constraint equation is used to ensure that the installation angle of the electromechanical equipment meets the requirements; and the stability constraint equation is used to evaluate the structural stability of the installation position.

2. The method for precise positioning and installation of electromechanical equipment in complex areas according to claim 1, characterized in that, The multidimensional positioning device consists of a laser ranging system, an angle encoder, a high-resolution imaging system, and a data processing unit, and has millimeter-level spatial positioning capability and three-dimensional modeling function.

3. The method for precise positioning and installation of electromechanical equipment in complex areas according to claim 2, characterized in that, The initial positioning vector refers to the three-dimensional vector dataset of the relationship between the theoretical installation position of the equipment and the surrounding environment, obtained by a multi-dimensional positioning instrument before the installation of electromechanical equipment. It includes two parts: position vector and direction vector.

4. The method for precise positioning and installation of electromechanical equipment in complex areas according to claim 3, characterized in that, Spatial compensation variation vector refers to the amount of position and angle correction required due to the deviation between the actual environment and theoretical design in complex areas. It is manifested as translation and rotation in three-dimensional space.

5. The method for precise positioning and installation of electromechanical equipment in complex areas according to claim 4, characterized in that, The thermal expansion variation vector refers to the positional shift caused by the thermal expansion or contraction of structural materials due to temperature changes. It is calculated by multiplying the thermal expansion coefficient by the temperature difference.

6. The method for precise positioning and installation of electromechanical equipment in complex areas according to claim 5, characterized in that, The spatial region overlap matrix is ​​a mathematical model that describes the degree of overlap between different spatial regions in the installation space. It is used to assess the conflict between the equipment installation location and the surrounding equipment or structural space. It is generated by calculating the spatial relationship between each element in the initial positioning vector database.

7. The method for precise positioning and installation of electromechanical equipment in complex areas according to claim 6, characterized in that, The spatial area vacancy matrix is ​​a mathematical model describing the availability of each area in the installation space. It is formed by dividing the entire installation space into grids and marking the occupancy status of each grid cell, and is used to quickly locate suitable vacant installation spaces.

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