Profile steel lifting control system with track monitoring function

Abstract

The invention belongs to the technical field of profile steel lifting control, and discloses a profile steel lifting control system with a track monitoring function, multi-dimensional data such as dynamic force, strain and temperature are collected through a profile steel load coupling recognition module, and PID parameters are corrected in real time in combination with a dynamic load compensation fuzzy PID algorithm; wherein the dynamic force sensor samples lifting impact force at 1kHz, the anti-radiation optical fiber strain sensor captures profile steel stress, the infrared thermal imager monitors temperature, and the dynamic load coefficient is corrected jointly; meanwhile, parameters are adjusted 200 ms ahead of time based on a predicted load sudden change point, motor overload and non-elastic deformation of a lifting appliance are avoided, track deviation is effectively prevented, heavy type section steel dynamic load impact and variable cross-section load sudden change scenes are adapted, and operation safety is greatly improved; a force linkage equation between lifting points is established through a twinborn dynamic coupling planning module, a multi-lifting-point force compensation torque calculation formula is combined, single-lifting-point compensation torque is calculated in real time, and the speed of adjacent lifting points is adjusted.

Description

Technical Field

[0001] This invention belongs to the field of steel section lifting control technology, specifically a steel section lifting control system with trajectory monitoring function. Background Technology

[0002] In complex scenarios such as heavy steel structure installation and hoisting of irregularly shaped steel sections for nuclear power plants, existing steel section lifting control systems suffer from the following technical problems, directly threatening operational safety and precision control: Setting core parameters such as lifting speed and braking torque solely based on the static weight of the steel section completely ignores the dynamic load impact at the moment of lifting (the dynamic load coefficient for lifting heavy steel sections can reach 1.5-2.0) and the sudden load changes when lowering variable cross-section steel sections. This leads to frequent motor overload and inelastic deformation of the lifting device, ultimately causing trajectory deviation. This problem is directly related to the core logic of force-energy matching in the lifting system and is the primary hidden danger restricting safe operation.

[0003] When using multi-point lifting for ultra-long steel sections (such as steel box girders) exceeding 30m in length, existing systems only independently control the speed of each lifting point and lack a model for the force coupling relationship between lifting points. A 1mm lag at a certain lifting point can cause the local stress of the steel section to exceed the 200MPa safety threshold. Accumulated errors can easily lead to steel section twisting or even fracture. This problem exposes the inherent flaws in multi-actuator collaborative control and is a key risk point in the hoisting of large components.

[0004] While some systems have incorporated digital twin technology, it is only used for static trajectory simulation. The dynamic states of physical equipment, such as winch wire rope wear and motor temperature rise, are not synchronized in real time. This results in a deviation of over 10mm between the simulated trajectory and the actual trajectory, rendering the digital twin ineffective. This problem exposes the core contradiction of the disconnect between virtual simulation and physical execution, severely hindering the improvement of accuracy through intelligent systems. Summary of the Invention

[0005] The purpose of this invention is to provide a steel section lifting control system with trajectory monitoring function to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a steel section lifting control system with trajectory monitoring function, the system comprising: Steel load coupling identification module: includes a binocular vision camera, laser profile sensor, weighing sensor, dynamic force sensor, material analyzer, radiation-resistant fiber optic strain sensor and infrared thermal imager, to collect data from multiple aspects; The digital twin dynamic coupling planning module collects temperature and vibration data of the equipment, receives data from the steel load coupling identification module, establishes a steel stress cloud map and maps it to the digital twin system; and optimizes the trajectory of each lifting point through an improved distributed gradient descent algorithm. Extreme environment calibration monitoring module: including laser displacement sensor, military-grade IMU, visual tracking camera, temperature and humidity sensor and laser signal intensity monitoring unit, setting up workshop reference calibration point and mobile laser reference station; Load compensation cooperative control module: including main controller, execution end, adopting dynamic load compensation fuzzy PID algorithm, introducing pre-compensation factor; establishing calculation logic of suspension point displacement error, section steel strain and compensation torque; Fault root cause fault tolerance module: built-in edge computing unit, the edge computing unit is built-in fault diagnosis logic, the fault diagnosis logic identifies the fault reason through multi-layer feature extraction, and adopts the corresponding fault tolerance strategy; Full-cycle parameter tracing module: configure industrial internet of things gateway, collect data of each module, access to improve equipment health data and process parameters, and store in database; Flexible timing coordination module: establish 5G anti-interference communication network, the communication network accesses the operation plan of MES system and the state signal of related equipment; establish timing rules of scene and priority, section steel gravity change law, and output scheduling instruction.

[0007] Preferably, the section steel load coupling identification module comprises: The dynamic force sensor collects the impact force at the moment of lifting, the anti-radiation optical fiber strain sensor collects the section steel strain data, the infrared thermal imager collects the sunlight direct temperature difference of the section steel surface, the laser profile sensor is used for collecting the section steel cross section data, the three-dimensional mechanics analysis of ANSYS is combined to dynamically calculate the gravity center coordinates at different lifting heights, and the mapping table of the relationship between the variable cross section profile, the gravity center offset and the strain threshold value and the corresponding strain risk value of the gravity center offset amount is output; The material analyzer collects spectrum data and temperature data of the infrared thermal imager, corrects the dynamic load coefficient extracted by Hilbert-Huang transform, synchronously calculates the static inertia parameter and the load gravity center offset amount in the variable cross section lifting stage; transmit various data to the twin dynamic coupling planning module and the load compensation cooperative control module.

[0008] Preferably, the twin dynamic coupling planning module comprises: Temperature sensor and vibration sensor are set, temperature and vibration data of key components including lifting equipment motor and sling bearing are collected, section steel strain data of the anti-radiation optical fiber strain sensor and workshop temperature and humidity, nuclear power scene radiation dose are received, section steel stress nephogram is established and mapped to digital twin system, parameter correction rules of corresponding relationship between radiation dose and motor insulation performance attenuation rate and corresponding relationship between humidity and steel wire rope friction coefficient change are established; The model predictive control algorithm is adopted, and the parameters of the digital twin system are corrected regularly according to the physical equipment state and environmental parameters; at the same time, the data collected by the profile steel load coupling identification module is combined to establish a hoisting point interconnection equation in the digital twin system, the trajectory of each hoisting point is optimized through an improved distributed gradient descent algorithm, and based on the historical data of the digital twin system, a load mutation point is predicted, and a buffer trajectory segment is generated; Finally, the optimized trajectory is transmitted to the extreme environment calibration monitoring module and the flexible timing coordination module.

[0009] Preferably, the extreme environment calibration monitoring module comprises: The workshop reference calibration point triggers calibration every 2 minutes, and the mobile laser reference station automatically moves to a new calibration point every 5 minutes; The corresponding relationship between temperature and humidity and sensor drift is established, which is used to correct the monitoring data of the laser displacement sensor and the military-grade IMU; when the laser signal of the laser displacement sensor is attenuated by more than 50% due to dust shielding, the backup combination of the military-grade IMU and the visual tracking camera is automatically switched to, through a federal Kalman filtering and fuzzy reasoning fusion algorithm, strain and displacement conversion data of the anti-radiation optical fiber strain sensor are accessed, and a three-dimensional trajectory of height, horizontal coordinate and tilt angle is generated; The three-dimensional trajectory is compared with the reference trajectory output by the twin dynamic coupling planning module point by point, the position and attitude deviation is calculated, and the corresponding profile steel stress increment of the horizontal trajectory deviation is labeled synchronously; the calculated deviation data is transmitted to the load compensation cooperative control module, and the monitoring data is synchronously transmitted to the fault root cause fault-tolerant module; Trajectory deviation correction calculation formula under extreme environment:

[0010] In the formula: represents the corrected real-time trajectory coordinates, with units of mm; represents the reference trajectory coordinates output by the twin dynamic coupling planning module, with units of mm; represents the sensor drift deviation caused by temperature, with units of mm; represents the sensor drift deviation caused by humidity, with units of mm; represents the strain-displacement conversion coefficient; represents the real-time strain value of the profile steel.

[0011] Preferably, the load compensation cooperative control module comprises: The main controller is a Siemens S7-1500 PLC, which receives the data collected by the steel load coupling identification module and the deviation data from the extreme environment calibration monitoring module; the execution end includes a servo motor and a harmonic reducer. A dynamic load compensation fuzzy PID algorithm is adopted, and a pre-compensation factor is introduced into the algorithm. Based on the load mutation points predicted by the twin dynamic coupling planning module, the PID algorithm parameters are adjusted in advance. In the multi-lifting scenario, the three-dimensional calculation logic of lifting point displacement error, steel strain and compensation torque is established in combination with the multi-lifting point synchronization requirements of the twin dynamic coupling planning module. The output control parameters and execution status are transmitted to the full-cycle parameter traceability module for storage. When the control is abnormal, the abnormal signal is fed back to the fault root cause fault tolerance module. Formula for calculating PID parameters after dynamic load correction:

[0012] This represents the dynamically corrected PID parameters, where For proportionality coefficient, For integral coefficients, These are the differential coefficients; This represents the PID baseline parameter, i.e., the initial set value, which is preset based on the static weight of the steel section. Indicates the dynamic load factor correction weight; The real-time dynamic load coefficient is collected by a dynamic force sensor installed on the spreader connector. This indicates the weight for center of gravity offset correction, in units of 1 / mm; This indicates the real-time load center of gravity offset, in mm.

[0013] Formula for calculating the compensation torque of multiple lifting points:

[0014] Indicates the first The real-time compensation torque of each lifting point is expressed in N·m. This indicates the elastic modulus of the steel section, expressed in GPa. The moment of inertia of the steel section is expressed in units of 1. ; Indicates the first The displacement error of a lifting point refers to the difference between the actual displacement of that lifting point and the reference displacement. denotes the distance between adjacent suspension points, in meters; denotes the force coupling coefficient of the jth suspension point, in N·m / mm; denotes the force coupling coefficient of the jth suspension point, in N·m / mm; denotes the displacement error of the jth suspension point adjacent to the ith suspension point, in mm. denotes the displacement error of the jth suspension point adjacent to the ith suspension point, in mm.

[0015] Preferably, the fault root cause fault-tolerant module comprises: The monitoring data of the extreme environment calibration monitoring module, the abnormal signal of the load compensation collaborative control module, and the extreme environment temperature and humidity, radiation dose data are accessed; the fault diagnosis logic identifies sensor drift, motor failure, section steel stress deformation, and three types of fault causes through multi-layer feature extraction; For different fault root causes, differential fault-tolerant strategies are adopted: when the fault cause is a real-time repairable problem, a parameter reset instruction is automatically sent to the load compensation collaborative control module; when the fault cause is a hardware failure, a backup control mode is triggered, and the lifting speed is simultaneously reduced; when the radiation dose exceeds the standard in a nuclear power scenario, causing the servo motor to fail, the backup motor and lead shield are switched to; The fault impact prediction is sent to the twin dynamic coupling planning module, and the fault information and processing process are transmitted to the full-cycle parameter tracing module for archiving, and the fault signal is sent to the flexible time sequence collaborative module.

[0016] Preferably, the full-cycle parameter tracing module comprises: The industrial Internet of Things gateway collects the section steel parameters of the section steel load coupling identification module, the optimized trajectory of the twin dynamic coupling planning module, the control instructions and execution data of the load compensation collaborative control module, and the fault records of the fault root cause fault-tolerant module. The lifting equipment health data includes motor temperature rise, bearing vibration frequency, and steel wire rope wear amount. The process parameters include the adaptive lifting speed of different section steels and the PID parameter combination. The module also integrates the section steel factory material quality report, welding detection data, historical lifting records, temperature and humidity, radiation dose, and dust concentration data for each lifting; A time sequence database and a relational database architecture are adopted to realize data correlation through the unique section steel number and equipment ID. Based on the bearing vibration frequency change curve, the remaining service life of the equipment is predicted, and the optimal process parameters are calculated based on the operation data of different material section steels; The module designs fault event pointing correlation data, and the correlation data points to the reverse tracing interface of the root cause parameters. Based on historical strain data and material fatigue curves, the remaining lifting times of the section steel are predicted. The lifting equipment health status and process optimization suggestions are fed back to the twin dynamic coupling planning module; Remaining service life of lifting equipment

[0017] Remaining service life of lifting equipment, unit: h Rated service life of equipment, unit: h Fatigue damage coefficient, unit: 1 / h Equipment running time, unit: h Real-time vibration frequency of equipment, unit: Hz Rated vibration frequency of equipment, unit: Hz Integral term, used to quantify the cumulative degree of fatigue damage of the equipment in the running cycle.

[0018] Preferably, the flexible timing coordination module comprises: Receiving the trajectory timing data of the twin dynamic coupling planning module, the fault signal of the fault root cause fault tolerance module and the variation law of the steel centroid of the steel load coupling identification module; A flexible timing scheduling algorithm is adopted, which establishes timing rules for scenarios and priorities: the priority of the reactor steel lining in the nuclear power scenario is higher than that of the conventional steel, and the timing window of the non-emergency operation is compressed when the emergency single is compressed; when strong wind is encountered in the super high-rise scenario, the interval between lifting and static is extended; Meanwhile, based on the variation law of the steel centroid of the steel load coupling identification module, the docking timing of the transfer robot is adjusted, and the scheduling instruction is transmitted to the twin dynamic coupling planning module and the load compensation cooperative control module; The module also configures a visual interface of the workshop monitoring center, which displays the state of each device and the operation time schedule, and supports manual intervention to adjust the scheduling scheme.

[0019] The beneficial effects of the present application are as follows: 1、The steel load coupling identification module of the present application collects multi-dimensional data such as dynamic force, strain and temperature, and combines with the dynamic load compensation fuzzy PID algorithm to correct the PID parameters in real time; among them, the dynamic force sensor samples the lifting impact force at 1kHz, the anti-radiation optical fiber strain sensor captures the steel stress, the infrared thermal imager monitors the temperature, and the dynamic load coefficient is corrected together; at the same time, based on the predicted load mutation point, the parameters are adjusted 200ms in advance to avoid motor overload, sling inelastic deformation, effectively prevent trajectory deviation, adapt to heavy steel dynamic load impact and variable cross-section load mutation scene, greatly improve the operation safety.

[0020] 2、The present application establishes a force linkage equation between the lifting points through a twin dynamic coupling planning module, combines a multi-lifting point force compensation torque calculation formula, and calculates a single lifting point compensation torque in real time and adjusts the speed of adjacent lifting points; at the same time, the improved distributed gradient descent algorithm adds strain constraints to control the local stress increment to ≤20MPa, avoids the risk of distortion and fracture of super-long steel over 30m caused by 1mm lifting point hysteresis, and meets the precision and structural safety requirements of multi-lifting point synchronous hoisting of large components.

[0021] 3、The present application synchronizes the equipment state such as motor temperature, bearing vibration and steel wire rope wear in real time through a twin dynamic coupling planning module, combines a trajectory correction mechanism of an extreme environment calibration monitoring module, uses a trajectory deviation correction formula under extreme environment to control the trajectory deviation to ≤0.8mm; in extreme scenes such as nuclear power and super high-rise buildings, not only can the laser displacement sensor and the military-grade IMU be redundantly coordinated to resist interference, but also the digital twin system can dynamically match the physical state to restore its trajectory guidance value and greatly improve the intelligent precision. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 The present application has a trajectory monitoring function. DETAILED DESCRIPTION

[0023] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0024] As shown in the drawings, Figure 1 The present application provides a type steel lifting control system with trajectory monitoring function, which comprises: A type steel load coupling identification module: including binocular vision camera, laser profile sensor, weighing sensor, dynamic force sensor, material analyzer, anti-radiation optical fiber strain sensor and infrared thermal imager, which collects data in multiple aspects; A twin dynamic coupling planning module: collects temperature and vibration data of the equipment, receives data from the type steel load coupling identification module, establishes a type steel stress cloud map and maps it to a digital twin system; optimizes the trajectory of each lifting point through an improved distributed gradient descent algorithm; Extreme environment calibration monitoring module: including laser displacement sensor, military-grade IMU, visual tracking camera, temperature and humidity sensor, and laser signal intensity monitoring unit, setting up workshop reference calibration point and mobile laser reference station; the laser displacement sensor can withstand -40℃~120℃, set IP69K protection + anti-radiation coating, adapt to nuclear power dust, high pressure washing environment; the military-grade IMU can withstand -55℃~150℃ working temperature, adapt to super high layer low temperature; the error of workshop reference calibration point is ≤0.1mm, and calibration is triggered once every 2 minutes; the mobile laser reference station moves to a new calibration point automatically every 5 minutes, solving the problem of fixed reference point shielding; Load compensation cooperative control module: including main controller, execution end, dynamic load compensation fuzzy PID algorithm, introducing pre-compensation factor; establishing calculation logic of three aspects of hanger point displacement error, steel strain and compensation torque; Fault root cause fault tolerance module: built-in edge computing unit, fault diagnosis logic is built-in in edge computing unit, fault diagnosis logic identifies fault causes through multi-layer feature extraction, and corresponding fault tolerance strategy is adopted; Full-cycle parameter tracing module: configure industrial internet of things gateway, collect data of each module, access equipment health data and process parameters at the same time, and store in database; Flexible timing coordination module: establish 5G anti-interference communication network, and the communication network accesses operation plan of MES system and state signal of related equipment; establish timing rules of scene and priority, change law of steel centroid, and output scheduling instruction.

[0025] Among them, the steel load coupling identification module comprises: The dynamic force sensor collects the impact force at the moment of lifting, the anti-radiation optical fiber strain sensor collects the steel strain data, the infrared thermal imager collects the sunlight direct temperature difference on the surface of the steel, the laser profile sensor is used for collecting the steel section data, the ANSYS three-dimensional mechanics analysis is combined to dynamically calculate the centroid coordinates at different lifting heights, the mapping table of the relationship among the variable cross-section profile, the centroid offset and the strain threshold value and the strain risk value corresponding to the centroid offset is output, and the strain warning is triggered when the centroid offset is greater than 50mm; The anti-radiation optical fiber strain sensor is installed at the key stress point of the steel, and its tolerance dose is ≥ Gy, adapting to the nuclear power scene; The dynamic force sensor is installed on the hoist connecting piece, and its sampling frequency is 1kHz; The material analyzer collects spectral data and temperature data of the infrared thermal imager, and corrects the dynamic load coefficient extracted by Hilbert-Huang transform; the dynamic load coefficient correction coefficient is +0.05 when the temperature rises by 10℃, and the static inertia parameter and the load centroid offset in the variable cross-section lifting stage are calculated synchronously; Spectrum data is used to distinguish the difference in elastic modulus between Q355 steel and Q460 steel and other materials; Finally, the module generates a data package including static weight, dynamic impact coefficient, load distribution curve, strain risk level (1-5 level), and temperature correction dynamic load coefficient, which is transmitted to the twin dynamic coupling planning module and load compensation collaborative control module in real time.

[0026] Among them, the twin dynamic coupling planning module includes: Set up temperature sensors, vibration sensors, collect temperature and vibration data of key components including lifting equipment motors and sling bearings, receive type steel strain data from anti-radiation optical fiber strain sensors, and collect workshop temperature and humidity, nuclear power scene radiation dose in real time from the module's radiation sensors, with a sampling frequency of 1 Hz and a range of 0-200 Gy. Establish a type steel stress cloud map and map it to the digital twin system. Establish parameter correction rules for the correspondence between radiation dose and motor insulation performance decay rate and the correspondence between humidity and steel wire rope friction coefficient change, to ensure that the digital twin system and the physical system are dynamically consistent; The sampling frequency of type steel strain data is 2 kHz; the electric field radiation dose is monitored by a radiation sensor; when the radiation dose is >50 Gy, the upper limit of the motor speed is reduced by 10%; Adopt model predictive control algorithm, regularly correct the parameters of digital twin system according to physical equipment state and environmental parameters, such as the change coefficient of steel wire rope elastic modulus with temperature; at the same time, combined with the data collected by the type steel load coupling identification module, establish the linkage equation between the lifting points in the digital twin system, optimize the trajectory of each lifting point through the improved distributed gradient descent algorithm, add type steel strain constraint condition, when local strain >180MPa, corresponding lifting point speed is forced to reduce by 20%, and based on the historical data of digital twin system, such as the load fluctuation law of the same type of steel lifting in the past 3 times, predict the load mutation point, such as the lowering of variable cross-section section, generate a buffer trajectory segment, and the lifting speed is smoothly reduced from 0.5m / min to 0.2m / min; Finally, the optimized trajectory is transmitted to the extreme environment calibration monitoring module and the flexible time sequence collaborative module; Radiation dose-motor insulation performance decay rate parameter correction logic: Based on the characteristic experimental data of motor insulation materials (such as radiation-resistant epoxy resin) in nuclear power scenarios, the radiation dose interval is divided and the corresponding insulation performance decay rate is obtained. The specific interval and decay rate mapping relationship is as follows:

[0027] Parameter correction link: The insulation performance decay rate directly affects the maximum allowable output power of the motor (power is positively related to insulation resistance, the higher the decay rate, the lower the allowable power), and the motor output power determines the upper limit of the lifting speed (power P=FV, F is the lifting force, V is the lifting speed). Therefore, the speed parameter of the digital twin system is corrected by the following steps: ① Real-time acquisition of radiation dose D, and determination of the corresponding decay rate a according to the above interval; ② Calculate the motor power correction coefficient K1=1-a×β (β is a safety redundancy coefficient, take 0.8, to avoid insulation breakdown in extreme working conditions); ③ The motor reference power P D (based on the static weight of the profile steel, such as 5kW) in the digital twin system is corrected to P1=P D ×K1; ④ Combined with the current lifting force F (obtained by the weighing sensor of the profile steel load coupling identification module), calculate the corrected upper limit of the lifting speed V1=P1 / F, and update to the speed constraint condition of the trajectory planning; Humidity-steel wire rope friction coefficient parameter correction logic: Based on the friction experimental data of steel wire rope (such as 6×37+FC structure) under different humidity, the fitting relationship of friction coefficient (μ) is established with relative humidity (RH) as the variable: μ=0.22-0.0008×(RH-50) RH=50% is the reference humidity, corresponding to μ D =0.22; RH increases by 10%, μ decreases by 0.008, which adapts to the high-rise rain and high-humidity scene of nuclear power plant, RH value range 0-100%; The friction coefficient of steel wire rope directly affects the tension safety margin of the lifting point (friction coefficient is too low, which is easy to cause the steel wire rope to slip, and the tension needs to be adjusted synchronously), and then affects the torque parameter in the trajectory planning. The correction steps are as follows: ① Real-time acquisition of environmental relative humidity RH, and calculate the real-time friction coefficient μ by substituting the above formula; ② Calculate the tension correction coefficient K2=μ D / μ (μ D =0.22 is the reference friction coefficient, K2≥1, to ensure that the tension is enough to resist slipping); ③ The steel wire rope reference tension T D (based on the weight of the profile steel, such as 100kN) in the digital twin system is corrected to T1=T D ×K2; ④ Combined with the lifting point force linkage equation, convert the corrected tension T1 into the lifting point compensating torque correction value ΔM=T1×L (L is the lifting point force arm, such as 0.5m), and update to the torque constraint of trajectory optimization.

[0028] The extreme environment calibration monitoring module comprises: The workshop reference calibration point triggers calibration every 2 minutes, and the mobile laser reference station automatically moves to a new calibration point every 5 minutes; The corresponding relationship between temperature and humidity and sensor drift is established to correct the monitoring data of the laser displacement sensor and the military-grade IMU; when the laser signal of the laser displacement sensor is attenuated by more than 50% due to dust shielding, the system automatically switches to the standby combination of the military-grade IMU and the visual tracking camera, and through the federal Kalman filtering and fuzzy inference fusion algorithm, the strain and displacement conversion data of the anti-radiation optical fiber strain sensor (based on the mechanical analysis of the shaped steel) are accessed to generate a three-dimensional trajectory of height, horizontal coordinates and tilt angle; The three-dimensional trajectory is compared with the reference trajectory output by the twin dynamic coupling planning module point by point, the position and attitude deviation is calculated, and the stress increment of the shaped steel corresponding to the horizontal trajectory deviation is labeled synchronously, for example, when the deviation is 5 mm, the stress increment is less than or equal to 30 MPa; the calculated deviation data is transmitted to the load compensation cooperative control module, and the monitoring data is synchronously transmitted to the fault root cause fault-tolerant module; The trajectory deviation correction calculation formula under extreme environment is:

[0029] In the formula: represents the corrected real-time trajectory coordinates, which are used for the correction of height or horizontal coordinates, and the unit is mm, so that the trajectory accuracy under extreme environment meets the requirements, and the deviation is less than or equal to 5 mm; mm; represents the reference trajectory coordinates output by the twin dynamic coupling planning module, and the unit is mm, which are generated based on initial trajectory planning, for example, the reference coordinates of a super-high-rise steel column lifted to a height of 30 m, which are the reference for trajectory correction; represents the sensor drift deviation caused by temperature, and the unit is mm, which is calculated from the correlation between temperature and humidity and sensor drift, for example, the drift deviation is about 0.2 mm when the temperature difference is 10°C, which is used to correct the influence of high-temperature or low-temperature environment on the sensor; represents the sensor drift deviation caused by humidity, and the unit is mm, which is calculated from the correlation between temperature and humidity and sensor drift, for example, the drift deviation is about 0.1 mm when the humidity difference is 10%, which is suitable for scenes with large humidity fluctuations such as nuclear power and super-high-rise buildings; represents the strain and displacement conversion coefficient, and the unit is mm / μ which is determined by the material of the shaped steel, for example, the strain and displacement conversion coefficient of Q355 steel is 0.001 mm / μ ; and is used to convert the strain data of the shaped steel into displacement data as the basis for sensor redundancy compensation; Real-time strain value of profiled steel, unit: μ (micro-strain), collected by anti-radiation fiber strain sensor at key stress points of profiled steel, and its safety threshold is set to 1800 μ in the scheme, and if it exceeds the value, stress warning is triggered, and it is also used for redundant correction of trajectory deviation.

[0030] The load compensation cooperative control module comprises: The model of the main controller is Siemens S7-1500 PLC, which receives the data collected by the profiled steel load coupling identification module and the deviation data of the extreme environment calibration monitoring module; the execution end comprises a servo motor and a harmonic reducer; the servo motor is configured with an anti-radiation encoder, which is suitable for nuclear power field; the torque control accuracy of the servo motor and the harmonic reducer is ±0.05 N·m, and the response time is ≤30 ms; The dynamic load compensation fuzzy PID algorithm is adopted, a pre-compensation factor is introduced in the algorithm, the load mutation point predicted by the twin dynamic coupling planning module is used to adjust the PID algorithm parameters 200 ms in advance, for example, if the predicted dynamic load coefficient is >1.8, the P value is increased to 1.2 times, and the lifting speed is reduced to 0.25 m / min; in the multi-lifting-point lifting scene, combined with the multi-lifting-point synchronization requirement of the twin dynamic coupling planning module, when the displacement of a lifting point lags behind, the compensation torque of the lifting point is calculated in real time and the speed of the adjacent lifting point is adjusted, for example, the speed of the adjacent lifting point is reduced by 0.05 m / min, the local stress increase value is controlled to be ≤20 MPa, and a three-dimensional calculation logic of lifting point displacement error, profiled steel strain and compensation torque is established; The output control parameters and execution state are transmitted to the full-cycle parameter tracing module for storage, and when the control is abnormal, the abnormal signal is fed back to the fault root cause fault tolerance module; PID parameter calculation formula after dynamic load correction:

[0031] PID parameter after dynamic correction, wherein is a proportional coefficient, is an integral coefficient, is a differential coefficient, which is the real-time parameter finally used for servo motor control, and can be adjusted adaptively according to the dynamic load change; PID reference parameter, i.e. initial set value, is preset based on the static weight of profiled steel, for example, for common profiled steel such as Q355 steel, the initial proportional coefficient is usually set to 2.5; ​This represents the dynamic load coefficient correction weight, which is preset to 0.3 in the scheme. It is derived from the calibration based on the dynamic load impact characteristics of 1.5-2.0 times in the steel section lifting scenario, and is used to balance the influence of the dynamic load coefficient on the PID parameters. This represents the real-time dynamic load coefficient, collected by a dynamic force sensor mounted on the lifting device connector, with a sampling frequency of 1kHz, under conditions of sudden load change during lifting. The value can reach 1.8-2.0, directly reflecting the dynamic impact degree of the current load; This represents the weight of the center of gravity offset correction, in units of 1 / mm. The default value in the scheme is 0.02, which corresponds to the correction rate of the PID parameters when the center of gravity offset changes by 1mm. This is used to adapt to the influence of center of gravity offset when lifting variable cross-section steel. This represents the real-time load center of gravity offset, in mm, calculated by scanning the steel section data using a laser profile sensor and combining it with ANSYS three-dimensional mechanical analysis. This value is applied during the lifting phase of the variable cross-section steel section. The value can reach 50mm.

[0032] Formula for calculating the compensation torque of multiple lifting points:

[0033] Indicates the first The compensation torque of each lifting point, in N·m, is calculated and output to the servo motor of that lifting point to control the lifting speed of the lifting point, thereby balancing the stress differences between multiple lifting points. This refers to the elastic modulus of structural steel, expressed in gigabytes (GPa). It is obtained through spectral analysis using a material analyzer. For example, it can be used to distinguish between Q355 steel and Q460 steel. Taking Q460 steel as an example, its elastic modulus... Typically 206 GPa; The moment of inertia of the steel section is expressed in units of 1. Based on the cross-sectional data of steel sections scanned by a laser profile sensor, the cross-sectional shapes of steel sections, such as H-beams and variable cross-section steel columns, are calculated, including the moment of inertia of a common H-beam. Up to 5000 This reflects the ability of the steel section to resist bending deformation; Indicates the first The displacement error of each lifting point refers to the difference between the actual displacement of the lifting point and the reference displacement, in mm. It is collected by a laser displacement sensor. The scheme sets its out-of-tolerance threshold to 1 mm, because a 1 mm lag can cause the local stress of the steel section to reach the safety threshold of 200 MPa. This indicates the distance between adjacent lifting points, in meters (m). In multi-lifting scenarios involving multiple lifting points, such as lifting steel box girders over 30m, the value is typically 6-10m. Indicates the first Hanging point and the The force coupling coefficient of the lifting point, in N·m / mm, is preset to 5 in the scheme. It reflects the degree of interference of the displacement error of adjacent lifting points on the torque of the current lifting point and is used to quantify the collaborative relationship between multiple lifting points. This represents the displacement error between the j-th and ith lifting points adjacent to each other, in mm. The data acquisition methods are consistent, both using laser displacement sensors to calculate the interference compensation amount of adjacent lifting points on the current lifting point, thus avoiding error accumulation.

[0034] The root cause fault tolerance module includes: The system integrates monitoring data from the extreme environment calibration monitoring module, abnormal signals from the load compensation and collaborative control module, and extreme environment temperature, humidity, and radiation dose data. The fault diagnosis logic uses multi-layer feature extraction to identify sensor drift, motor failure, steel stress deformation, and three other types of fault causes. Different fault tolerance strategies are adopted for different root causes of failure: when the cause of failure is a problem that can be repaired in real time, a parameter reset command is automatically sent to the load compensation collaborative control module; when the cause of failure is a hardware failure, the backup control mode is triggered and the lifting speed is reduced synchronously; when the radiation dose exceeds the standard in the nuclear power scenario and causes the servo motor to fail, the system switches to a combination of backup motor and lead shield. The fault impact prediction is sent to the twin dynamic coupling planning module, and the fault information and processing process are transmitted to the full-cycle parameter traceability module for archiving. At the same time, the fault signal is sent to the flexible time-series coordination module. Extreme environments include special environments of nuclear power plants, ultra-high-rise outdoor environments, and extreme working conditions in heavy workshops: high temperature; special environments of nuclear power plants mainly include high radiation, high dust, and high humidity; ultra-high-rise outdoor environments mainly include strong winds, low temperatures, and high-altitude vibration; extreme working conditions in heavy workshops mainly include high temperature, high dust, and impact loads.

[0035] The full-cycle parameter traceability module includes: The industrial IoT gateway collects steel parameters from the steel load coupling identification module, the optimized trajectory from the twin dynamic coupling planning module, the control commands and execution data from the load compensation collaborative control module, and the fault records from the fault root cause fault tolerance module. It also collects equipment health data, including motor temperature rise, bearing vibration frequency, and wire rope wear, as well as process parameters, including the appropriate lifting speed for different steel profiles and PID parameter combinations. Furthermore, it integrates steel factory material reports, welding inspection data, historical lifting records, and data on temperature and humidity, radiation dose, and dust concentration for each lifting operation. Adopting time series database and relational database architecture, data correlation is realized through unique steel number and equipment ID; based on bearing vibration frequency change curve, equipment remaining service life is predicted, and optimal process parameters are counted according to operation data of steel of different materials; The module designs fault event pointing correlation data, correlation data pointing reverse tracing interface of root cause parameters, and based on historical strain data and material fatigue curve, remaining promotion times of steel are predicted, promotion equipment health state and process optimization suggestions are fed back to twin dynamic coupling planning module; Promotion equipment remaining service life prediction formula:

[0036] In the formula, represents remaining service life of promotion equipment, unit: h, used for whole cycle maintenance warning, for example, when remaining life < 500h, the system automatically prompts to replace the equipment, avoiding work interruption caused by hardware failure; represents rated service life of equipment, unit: h, standard parameter when equipment leaves factory, for example, rated service life of servo motor Usually 10000h; represents fatigue damage coefficient, unit: 1 / h, preset as 0.0005 in the scheme, the value is calibrated based on equipment material fatigue curve (such as fatigue characteristics of motor rotor and bearing steel), used for quantifying influence rate of vibration on fatigue damage of equipment; represents equipment running time, unit: h, recorded in real time by whole cycle parameter tracing module through industrial internet of things gateway, ensuring continuity and accuracy of time data; represents real-time vibration frequency of equipment, unit: Hz, collected by vibration sensor installed at key parts of equipment (such as motor shell and bearing seat), for example, vibration frequency of bearing under normal operation is 20-30Hz, when abnormal wear occurs, frequency will exceed 50Hz; represents rated vibration frequency of equipment, unit: Hz, standard parameter when equipment leaves factory, for example, rated vibration frequency of bearing 25Hz is the basis for judging whether vibration is abnormal, represents ratio of real-time vibration frequency to rated value, reflecting relative size of vibration intensity; represents integral term, used for quantifying fatigue damage accumulation degree of equipment in running cycle, the greater the integral value, the more serious the fatigue damage.

[0037] The flexible timing coordination module comprises: The trajectory timing data of the twin dynamic coupling planning module, the fault signal of the fault root cause fault tolerance module, and the change rule of the steel centroid of the steel load coupling identification module are received. The flexible timing scheduling algorithm is adopted, and the timing rules of the scene and the priority are established: the priority of the reactor steel lining in the nuclear power scene is higher than that of the conventional steel, and the timing window of the non-emergency operation is compressed during the emergency single insertion; when encountering strong wind in the super high-rise scene, the interval between lifting and standing is extended; Meanwhile, the docking timing of the transfer robot is adjusted based on the change rule of the steel centroid of the steel load coupling identification module, and the scheduling instruction is transmitted to the twin dynamic coupling planning module and the load compensation cooperative control module synchronously. The module also configures a visual interface of the workshop monitoring center, which displays the device state and the operation time schedule, and supports manual intervention to adjust the scheduling scheme.

[0038] It should be noted that in this paper, relational terms such as first and second are used only to distinguish one entity or operation from another, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or device.

[0039] Although the embodiments of the present application have been shown and described, it can be understood by those skilled in the art that various changes, modifications, replacements and variations can be made to the embodiments without departing from the principles and spirits of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A steel section lifting control system with trajectory monitoring function, characterized in that: The system includes: Steel load coupling identification module: includes a binocular vision camera, laser profile sensor, weighing sensor, dynamic force sensor, material analyzer, radiation-resistant fiber optic strain sensor and infrared thermal imager, to collect data from multiple aspects; The digital twin dynamic coupling planning module collects temperature and vibration data of the equipment, receives data from the steel load coupling identification module, establishes a steel stress cloud map and maps it to the digital twin system; and optimizes the trajectory of each lifting point through an improved distributed gradient descent algorithm. Extreme Environment Calibration and Monitoring Module: Includes a laser displacement sensor, military-grade IMU, visual tracking camera, temperature and humidity sensor, and laser signal intensity monitoring unit, and sets up workshop benchmark calibration points and mobile laser reference stations; Load compensation collaborative control module: including main controller, actuator, dynamic load compensation fuzzy PID algorithm, introduction of pre-compensation factor; establishes calculation logic for three aspects: lifting point displacement error, steel strain and compensation torque; Fault root cause tolerance module: Built-in edge computing unit, the edge computing unit has built-in fault diagnosis logic, the fault diagnosis logic identifies the cause of the fault through multi-layer feature extraction and adopts the corresponding fault tolerance strategy; Full-cycle parameter traceability module: Configured with an industrial IoT gateway, it collects data from each module, and simultaneously accesses and improves equipment health data and process parameters, storing them in a database; Flexible timing coordination module: Establishes a 5G anti-interference communication network, which accesses the work plan and status signals of related equipment in the MES system; establishes timing rules for scenarios and priorities, the change law of the center of gravity of steel sections, and outputs scheduling instructions.

2. The steel section lifting control system with trajectory monitoring function according to claim 1, characterized in that: The steel load coupling identification module includes: The dynamic force sensor collects the impact force at the moment of lifting, the radiation-resistant fiber optic strain sensor collects the strain data of the steel section, the infrared thermal imager collects the temperature difference of the steel section surface under direct sunlight, and the laser profile sensor is used to collect the cross-sectional data of the steel section. Combined with ANSYS three-dimensional mechanical analysis, the center of gravity coordinates of different lifting heights are dynamically calculated, and the relationship between the variable cross-section profile, the center of gravity offset, and the strain threshold, as well as the mapping table of the strain risk value corresponding to the center of gravity offset, are output. The material analyzer collects spectral data and the infrared thermal imager collects temperature data. It corrects the dynamic load coefficient extracted by the Hilbert-Huang transform and simultaneously calculates the static inertial parameters and the load center of gravity offset during the variable cross-section lifting stage. All types of data are transmitted to the twin dynamic coupling planning module and the load compensation collaborative control module.

3. The steel section lifting control system with trajectory monitoring function according to claim 2, characterized in that: The twin dynamic coupling planning module includes: Temperature and vibration sensors are set up to collect temperature and vibration data of key components, including the motor of the hoisting equipment and the bearing of the lifting device. The strain data of the steel profile from the anti-radiation fiber optic strain sensor, as well as the temperature and humidity of the workshop and the radiation dose in the nuclear power scene, are received. A stress cloud map of the steel profile is established and mapped to the digital twin system. Parameter correction rules are established to establish the correspondence between radiation dose and motor insulation performance attenuation rate and the correspondence between humidity and the change of wire rope friction coefficient. A model predictive control algorithm is used to periodically correct the parameters of the digital twin system based on the physical equipment status and environmental parameters. At the same time, combined with the data collected by the steel load coupling identification module, a force linkage equation between the lifting points is established in the digital twin system. The trajectory of each lifting point is optimized by an improved distributed gradient descent algorithm. Based on the historical data of the digital twin system, load mutation points are predicted and buffer trajectory segments are generated. Finally, the optimized trajectory will be transmitted to the extreme environment calibration monitoring module and the flexible timing collaboration module.

4. The steel section lifting control system with trajectory monitoring function according to claim 3, characterized in that: The extreme environment calibration and monitoring module includes: The workshop reference calibration point is triggered for calibration every 2 minutes, and the mobile laser reference station automatically moves to a new calibration point every 5 minutes; A correspondence between temperature and humidity and sensor drift is established to correct the monitoring data of the laser displacement sensor and the military-grade IMU. When the laser signal of the laser displacement sensor is attenuated by more than 50% due to dust obstruction, the system automatically switches to the backup combination of the military-grade IMU and the visual tracking camera. Through a federated Kalman filter and fuzzy inference fusion algorithm, the strain and displacement conversion data of the radiation-resistant fiber optic strain sensor are input to generate a three-dimensional trajectory with height, horizontal coordinates and tilt angle. The three-dimensional trajectory is compared point by point with the baseline trajectory output by the twin dynamic coupling planning module to calculate the position and attitude deviations and simultaneously mark the stress increment of the steel corresponding to the horizontal trajectory deviation; the calculated deviation data is transmitted to the load compensation collaborative control module, and the monitoring data is synchronized to the fault root cause fault tolerance module.

5. The steel section lifting control system with trajectory monitoring function according to claim 4, characterized in that: The load compensation collaborative control module includes: The main controller is a Siemens S7-1500 PLC, which receives the data collected by the steel load coupling identification module and the deviation data from the extreme environment calibration monitoring module; the execution end includes a servo motor and a harmonic reducer. Based on the load mutation points predicted by the twin dynamic coupling planning module, the PID algorithm parameters are adjusted in advance; in the case of multi-point lifting scenarios, the three-dimensional calculation logic of lifting point displacement error, steel strain and compensation torque is established in combination with the multi-point synchronization requirements of the twin dynamic coupling planning module. The output control parameters and execution status are transmitted to the full-cycle parameter traceability module for storage. When the control is abnormal, the abnormal signal is fed back to the fault root cause fault tolerance module.

6. The steel section lifting control system with trajectory monitoring function according to claim 5, characterized in that: The fault root cause tolerance module includes: The system accesses monitoring data from the extreme environment calibration monitoring module, abnormal signals from the load compensation collaborative control module, and extreme environment temperature, humidity, and radiation dose data. The fault diagnosis logic identifies sensor drift, motor failure, steel stress deformation, and fault causes through multi-layer feature extraction. Different fault-tolerance strategies are adopted for different root causes of failure: when the cause of failure is a problem that can be repaired in real time, a parameter reset command is automatically sent to the load compensation collaborative control module; when the cause of failure is a hardware failure, the backup control mode is triggered and the lifting speed is reduced synchronously; when the servo motor fails due to excessive radiation dose in a nuclear power scenario, the system switches to a combination of backup motor and lead shield. The system sends fault impact predictions to the twin dynamic coupling planning module and transmits fault information and processing procedures to the full-cycle parameter traceability module for archiving. At the same time, it sends fault signals to the flexible time-series coordination module.

7. The steel section lifting control system with trajectory monitoring function according to claim 6, characterized in that: The full-cycle parameter traceability module includes: The industrial IoT gateway collects the steel parameters from the steel load coupling identification module, the optimized trajectory from the twin dynamic coupling planning module, the control commands and execution data from the load compensation collaborative control module, and the fault records from the fault root cause fault tolerance module. The health data of the lifting equipment includes motor temperature rise, bearing vibration frequency, and wire rope wear. The process parameters include the appropriate lifting speed for different steel profiles and PID parameter combinations. It also integrates the steel profile factory material report, welding inspection data, historical lifting records, temperature and humidity, radiation dose, and dust concentration data for each lifting. The system adopts a time-series database and relational database architecture, and achieves data association through the unique number of steel profiles and equipment IDs; it predicts the remaining service life of equipment based on the bearing vibration frequency change curve, and calculates the optimal process parameters based on the operating data of steel profiles of different materials. This module is designed to point fault events to associated data, which in turn points to a reverse tracing interface for root cause parameters. Based on historical strain data and material fatigue curves, it predicts the remaining number of times the steel section can be improved and feeds back suggestions for improving equipment health status and process optimization to the twin dynamic coupling planning module.

8. The steel section lifting control system with trajectory monitoring function according to claim 7, characterized in that: The flexible timing coordination module includes: The system receives trajectory timing data from the twin dynamic coupling planning module, fault signals from the fault root cause fault tolerance module, and the steel profile center of gravity change pattern from the steel profile load coupling identification module. A flexible time-series scheduling algorithm is adopted, which establishes time-series rules for scenarios and priorities: in nuclear power scenarios, the priority of lifting reactor steel lining is higher than that of conventional steel, and the time-series window of non-urgent operations is compressed when emergency orders are inserted; in super high-rise scenarios, the interval between lifting and resting is extended when strong winds occur. Simultaneously, based on the steel load coupling identification module's steel center of gravity change pattern, the docking timing of the transfer robot is adjusted, and the scheduling command is synchronously transmitted to the twin dynamic coupling planning module and the load compensation collaborative control module. The module is also configured with a visualization interface for the workshop monitoring center. The visualization interface displays the status of each piece of equipment and the work schedule, and supports manual intervention to adjust the scheduling scheme.

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