Spider crane dangerous state intelligent perception system and safety component use method thereof

Abstract

The application discloses a spider crane dangerous state intelligent perception system and a safety component use method thereof, and relates to the technical field of mechanical safety.The system comprises a collection and processing module, a twin construction module, a danger pre-judgment module, a danger tracing module and a linkage control module.The application stores inherent basic data of a storage device, collects multi-dimensional real-time operation data, completes standardized preprocessing, constructs a digital twin covering each component of the device based on standardized basic data, establishes a real-time data interaction link between the physical device and the virtual model, combines a plurality of types of dangerous state quantitative formula groups to complete deduction and identification of a plurality of types of dangerous states in the operation process of the device, breaks through the passive protection limitation of a single parameter threshold alarm in the prior art, realizes pre-identification of an evolving dangerous state in the operation of the device, covers the whole operation process of each component of the device in the dangerous identification, and provides traceable identification basis for safety control.

Description

Technical Field

[0001] This invention relates to the field of mechanical safety technology, specifically to an intelligent sensing system for the dangerous state of a spider crane and a method for using its safety components. Background Technology

[0002] Spider cranes, as specialized lifting equipment adapted to confined working spaces and complex terrain conditions, are widely used in various engineering scenarios such as municipal emergency repairs, power facility installation, steel structure construction, and indoor stadium construction. Safety management during lifting operations is directly related to the personal safety of workers and the safety of equipment and property, and is a core aspect of engineering construction safety management. The industry has a rigid and continuous demand for improved safety management capabilities during lifting equipment operations.

[0003] However, existing safety protection technologies for spider cranes are mostly based on threshold over-limit alarms for a single parameter, which can only achieve passive alarm and basic protection after a hazard occurs, and cannot identify evolving hazard states in advance; they have not established a digital mapping system for all critical components of the equipment, so they cannot complete the deduction of the evolution process of hazard states; they lack the ability to trace the source of hazard states, so they cannot locate the core source of the hazard; each safety component is triggered in isolation, and no linkage logic and action priority matching the hazard state have been established, so a complete safety control closed loop cannot be formed. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and provide an intelligent perception system for hazardous conditions of spider cranes and a method for using its safety components. This invention stores the inherent basic data of the equipment and collects multi-dimensional real-time operating data, and completes standardized preprocessing. Based on the standardized basic data, it constructs a digital twin covering all components of the equipment, and then establishes a real-time data interaction link between the physical equipment and the virtual model. Combined with a set of quantitative formulas for multiple types of hazardous conditions, it completes the deduction and identification of multiple types of hazardous conditions during equipment operation. This breaks through the passive protection limitations of existing technologies with single-parameter threshold alarms, and realizes the proactive identification of evolving hazardous conditions during equipment operation, rather than a reactive response after the occurrence of a hazard. This allows hazard identification to cover the entire operating process of all components of the equipment, providing an accurate and traceable identification basis for safety management.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In one aspect, a smart sensing system for the hazardous state of a spider crane, the system comprising:

[0006] Acquisition and Processing Module: The basic data of the spider crane is stored in the storage unit, and real-time multi-dimensional operation data is collected through multi-type sensor acquisition units. After preprocessing, standardized basic data and multi-dimensional real-time operation data are obtained.

[0007] Twin construction module: Based on standardized basic data, construct a digital twin, establish a real-time data interaction link between physical devices and the digital twin, and access standardized multi-dimensional real-time operation data to obtain the synchronous status data of the digital twin;

[0008] Hazard prediction module: Based on standardized multi-dimensional real-time operational data and synchronous status data of digital twin, it performs inference and identification of various types of hazardous states that are evolving during the operation of physical equipment, and obtains hazardous state identification data;

[0009] Hazard tracing module: Based on hazard identification data, it reverse-engineers the entire evolution process of the hazard, locates the source of the hazard, and generates tracing result data;

[0010] Linkage and control module: Based on the hazard status identification data and traceability result data, and according to the safety component matching rules, establish linkage logic between the digital twin and multiple sets of safety components, determine the triggering time of the safety components, and issue linkage control commands to the corresponding safety components.

[0011] Furthermore, in the acquisition and processing module, the basic data consists of the inherent parameters calibrated at the factory of the spider crane, including the spider crane's structural parameters, component performance parameters, and operational rating parameters. The multi-type sensor acquisition units include a pin-type weighing acquisition unit deployed on the hoisting mechanism for acquiring load data; an ultrasonic wind speed acquisition unit deployed on the top of the fuselage for acquiring wind speed data; an array-type pressure acquisition unit deployed at the bottom of each outrigger for acquiring outrigger grounding status data; a strain-type deformation acquisition unit deployed on the boom surface for acquiring boom dynamic deformation data; and a motor operating parameter acquisition unit deployed inside each drive motor for acquiring motor operating parameter data. The specific preprocessing operations are as follows: the basic data is standardized in format and dimension; the original values ​​of the multi-dimensional real-time operating data are time-series aligned, the timestamps of all operating data are unified, outliers are removed, and then dimension unification and format conversion are performed to generate standardized multi-dimensional real-time operating data.

[0012] Furthermore, in the twin construction module, based on standardized basic data, the structure, component performance, and operational rating parameters of the spider crane's body, outriggers, boom, wire rope, and safety components are disassembled. Virtual mapping units corresponding to each component are built, and the virtual mapping units of each component are spliced ​​together to form a digital twin. Then, a real-time data interaction link between the physical equipment and the digital twin is established, and standardized multi-dimensional real-time operating data is accessed to complete the full-state synchronization between the digital twin and the physical equipment. Moreover, the synchronized state data covers the operating status and spatial pose parameters of each component of the physical equipment.

[0013] Furthermore, in the hazard prediction module, standardized multi-dimensional real-time operating data is input into the digital twin, and the operating status and spatial pose parameters of the digital twin are updated synchronously. Then, through a set of multi-type hazard state quantification formulas, various types of hazards are quantified and deduced to identify the corresponding hazard states and obtain hazard state identification data.

[0014] Furthermore, in the hazard prediction module, the multi-type hazard state quantification formula group is as follows: ,in, For the overturning risk factor, when At that time, it was determined that there was a risk of overturning. The real-time overturning moment of the equipment is determined using real-time load and boom position data synchronized with a digital twin. To determine the real-time anti-overturning moment of the equipment, the data on the equipment's self-weight distribution and outrigger grounding pressure, synchronized with a digital twin, are used. The correction factor for outrigger grounding status is determined by historical operating data of spider cranes of the same model and is positively correlated with the effective contact area of ​​outrigger grounding. For the overload risk factor, when At that time, it was determined that there was an overload danger. The real-time load torque of the equipment is determined by real-time load and boom amplitude data synchronized with a digital twin. The rated load torque of the equipment under the current boom position is determined by the rated operating parameters in the basic data. For structural fatigue risk factor, when At that time, it was determined that there was a structural fatigue risk. The real-time maximum stress at key sections of the boom is determined using dynamic deformation and load data of the boom synchronized with a digital twin. The allowable stress of the boom material is determined by the component performance parameters in the basic data. The wire rope breakage risk factor is when At that time, it was determined that there was a risk of wire rope breakage. The real-time maximum tension of the wire rope is determined by real-time load and wire rope inclination data synchronized with a digital twin. The minimum breaking strength of the wire rope is determined by the component performance parameters in the basic data.

[0015] Furthermore, in the hazard tracing module, based on the hazard state identification data, the time node corresponding to the hazard state, the hazard state type, and the corresponding data category of multi-dimensional real-time operation data are locked. Starting from the locked time node, the module traces back along the physical equipment operation process to investigate the state change nodes of each parameter within the locked corresponding data category. The contribution of each parameter to the hazard state is calculated through the multi-type hazard source contribution formula to locate the source of the hazard, integrate the entire evolution process of the hazard state, and generate tracing result data containing the hazard cause, location, and evolution path.

[0016] Furthermore, in the hazard tracing module, the formula for the contribution of hazard sources is: ,in, For the first The contribution of parameters corresponding to different types of dangerous states. The set of dangerous states corresponding to overturning hazard, overload hazard, structural fatigue hazard, and wire rope breakage hazard, when When this parameter is identified as the source of the corresponding dangerous state, For the first The change in hazard coefficient caused by changes in parameters corresponding to a hazard state is determined by calculating the state change data of the corresponding parameters during the reverse backtracking process, combined with a set of quantitative formulas for multiple types of hazard states. For the first The total change in the hazard coefficient of a hazardous state is determined by the difference in the corresponding hazard coefficient between the hazard identification node and the normal operation node.

[0017] Furthermore, in the aforementioned linkage control module, based on the hazard identification data and source tracing result data, and according to the safety component matching rules, the corresponding triggered safety components are locked. The safety component matching rules are a one-to-one correspondence between hazard type and safety component. Specifically, the overturning hazard corresponds to the outrigger locking device and the buzzer alarm component; the overload hazard corresponds to the stress torque limiter and the audible and visual alarm component; the structural fatigue hazard corresponds to the automatic speed reduction unit and the shutdown protection unit; and the wire rope breakage hazard corresponds to the hoisting mechanism braking unit and the emergency stop protection unit. By comparing each hazard coefficient in the hazard identification data with the corresponding hazard judgment threshold, and combining the source of the hazard in the source tracing result data, the triggering time is confirmed. The triggering time is when the hazard coefficient of the corresponding hazard reaches the corresponding judgment threshold, and the source cannot be eliminated in real time by adjusting the operating parameters. Then, the action priority of each safety component is calculated using the multi-type safety component trigger priority weight formula, and the corresponding linkage control commands are issued in descending order of priority.

[0018] Furthermore, in the aforementioned linkage control module, the trigger priority weight formula for multiple types of security components is as follows: ,in, For the first The trigger priority weight of each security component This is a set of safety components, including outrigger locking devices, torque limiters, audible and visual alarm components, automatic speed reduction units, hoisting mechanism braking units, and emergency stop protection units. For the first The security component corresponds to the first one under control. Risk factor of a hazardous state For the first The security component corresponds to the first one under control. The contribution of source parameters of hazardous states.

[0019] On the other hand, a method for using a safety component of a spider crane hazardous state intelligent sensing system includes the following specific steps:

[0020] S1. Establish a digital twin based on the basic data of the spider crane, and complete the real-time data interaction link between the digital twin and the physical equipment;

[0021] S2. Real-time multi-dimensional operation data is collected through multiple types of sensor acquisition units, and after preprocessing, it is synchronized to the digital twin to update the synchronization status data of the digital twin.

[0022] S3. Based on the synchronization status data, infer and identify the evolving dangerous states during the operation of physical equipment in real time, and generate dangerous state identification data.

[0023] S4. If any hazard factor in the hazard identification data does not reach the judgment threshold of the corresponding hazard, return to S2 to continue monitoring; if any hazard factor reaches or exceeds the judgment threshold, proceed to S5.

[0024] S5. Based on the hazard identification data, reverse the entire evolution process of the hazard, locate the source of the hazard, and generate source tracing result data;

[0025] S6. Based on the hazard identification data and source tracing results data, and according to the safety component matching rules, identify the corresponding safety components to be triggered and the triggering time, and calculate the action priority of each safety component through the multi-type safety component trigger priority weight formula;

[0026] S7. In order of action priority from high to low, issue linkage control commands to the corresponding safety components. When a tipping danger is determined, first trigger the outrigger locking device to lock the current outrigger posture, and then trigger the buzzer alarm component to issue an audible and visual alarm. When an overload danger is determined, simultaneously trigger the torque limiter to cut off the power output and the audible and visual alarm component to sound an alarm. When a structural fatigue danger is determined, first trigger the automatic speed reduction unit to reduce the boom luffing speed. When the danger factor continues to rise, trigger the shutdown protection unit. When a wire rope breakage danger is determined, simultaneously trigger the hoisting mechanism braking unit for emergency braking and the emergency stop protection unit to cut off the power to the entire machine.

[0027] S8. After the safety component is triggered, it continuously monitors changes in the dangerous state. When the danger factor falls below the judgment threshold and the tracing results show that the source of danger has been eliminated, a reset permission signal is generated to reset the safety component. When the danger factor continues to exceed the standard, the safety component is maintained in operation and an upgraded alarm is issued.

[0028] Compared with existing technologies, the intelligent sensing system for hazardous conditions of spider cranes and its safety components have the following advantages:

[0029] I. This invention stores the inherent basic data of the storage device and collects multi-dimensional real-time operational data, completes standardized preprocessing, constructs a digital twin covering all components of the device based on the standardized basic data, establishes a real-time data interaction link between the physical device and the virtual model, and combines a set of quantitative formulas for multiple types of dangerous states to complete the deduction and identification of multiple types of dangerous states during the operation of the device. This breaks through the passive protection limitations of existing technologies with single parameter threshold alarms, and realizes the proactive identification of dangerous states that are evolving during the operation of the device, rather than a reactive response after the danger occurs. This allows the danger identification to cover the entire operation process of all components of the device, providing an accurate and traceable identification basis for safety management.

[0030] Second, this invention reverse-engineers the entire evolution process of a hazardous state by using hazardous state identification data, calculates the contribution of each relevant parameter to the hazardous state, and locates the source of the hazard. Based on the hazard identification data and the source tracing results, and according to the safety component matching rules, it locks the corresponding safety component and confirms the triggering time. It determines the action priority through weight calculation and issues linkage control commands in sequence. This solves the problems of existing technologies that cannot locate the source of the hazard and that safety components are triggered in isolation without matching logic. It allows the triggering action of the safety component to directly correspond to the type of hazardous state and the core source, forming a complete technical closed loop from hazard identification and source location to safety handling, and adapts to the differentiated safety protection needs under various complex working conditions.

[0031] Other advantages, objectives and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination or study, or may be learned from the practice of the invention. Attached Figure Description

[0032] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0033] Figure 1 A flowchart of a hazardous state intelligent sensing system for a spider crane;

[0034] Figure 2 A framework diagram of a dangerous state intelligent sensing system for a spider crane;

[0035] Figure 3 A flowchart illustrating the usage of a safety component in an intelligent sensing system for hazardous conditions of a spider crane. Detailed Implementation

[0036] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0037] Example:

[0038] In the emergency repair operation of the municipal pipeline network in the old city area, the operation area is located in the narrow streets and alleys of the old city that have been built for more than 30 years. The streets and alleys are adjacent to residential buildings, the operation space is less than 4 meters wide, the ground is an old and damaged paved road, and there are some settlement and unevenness defects. The operation involves hoisting a spider crane with a total weight close to the rated load of the equipment. During the operation, it is necessary to frequently adjust the boom posture and working range, and cross the walls and pipelines on both sides of the street and alley multiple times. The operation conditions are complex.

[0039] Before commencing operations, the inherent basic data of the spider crane, as specified by the manufacturer, is pre-stored into the physical equipment's storage unit. This basic data includes the spider crane's structural parameters, component performance parameters, and operational rating parameters. Simultaneously, the deployment and debugging of various types of sensor acquisition units are completed. These units include: a pin-type weighing acquisition unit deployed on the hoisting mechanism to collect load data; an ultrasonic wind speed acquisition unit deployed on the top of the crane body to collect wind speed data; an array-type pressure acquisition unit deployed at the bottom of each outrigger to collect outrigger grounding status data; a strain-type deformation acquisition unit deployed on the boom surface to collect boom dynamic deformation data; and motor operating parameter acquisition units deployed inside each drive motor to collect electrical... Machine operation parameter data; after the operation starts, multi-dimensional real-time operation data during equipment operation is collected in real time through multiple types of sensor acquisition units. Then, data preprocessing is performed. The preprocessing process first standardizes the format and unifies the units of the pre-stored basic data to generate standardized basic data. Next, the original values ​​of the collected multi-dimensional real-time operation data are time-series aligned to unify the timestamps of all operation data, resolving the data transmission delay deviation problem between different acquisition units in the complex electromagnetic environment of streets and alleys. Outliers are removed from the time-series aligned data, filtering out invalid data collected due to the passage of large vehicles and vibrations from equipment start-up and shutdown. Finally, the processed data undergoes unit unification and format conversion to generate standardized multi-dimensional real-time operation data, such as... Figure 1 As shown, the preprocessed data eliminates the timing deviations and dimensional differences between different acquisition units, providing a unified and standardized data foundation for subsequent full-process control and avoiding misjudgments and omissions of dangerous states caused by data deviations.

[0040] Based on the generated standardized basic data, the structure, component performance, and operational rating parameters of the spider crane's body, outriggers, boom, wire rope, and safety components are disassembled. Virtual mapping units corresponding to each component are built, and these virtual mapping units are spliced ​​together to form a complete digital twin. A real-time data interaction link between the physical equipment and the digital twin is then established, and standardized multi-dimensional real-time operating data is accessed to achieve full-state synchronization between the digital twin and the physical equipment. The synchronization status data output during the synchronization process covers the operating status and spatial pose parameters of each component of the physical equipment, allowing the digital twin to completely reproduce the real-time operating status of the physical equipment, including actual on-site conditions such as slight tilting of the outriggers due to ground subsidence and subtle deformation of the boom under load, rather than a standardized model under ideal conditions. This provides an accurate virtual simulation foundation for subsequent hazardous state simulations and solves the problem of the disconnect between virtual models and actual on-site conditions in existing technologies.

[0041] During the operation, standardized multi-dimensional real-time operational data is continuously input into the digital twin, synchronously updating the digital twin's operational status and spatial pose parameters. Then, a set of multi-type hazard state quantification formulas is used to complete the quantitative deduction of various hazards. The multi-type hazard state quantification formula set is as follows: ,in, For the overturning risk factor, when At that time, it was determined that there was a risk of overturning. The real-time overturning moment of the equipment is determined using real-time load and boom position data synchronized with a digital twin. To determine the real-time anti-overturning moment of the equipment, the data on the equipment's self-weight distribution and outrigger grounding pressure, synchronized with a digital twin, are used. The correction factor for outrigger grounding status is determined by historical operating data of spider cranes of the same model and is positively correlated with the effective contact area of ​​outrigger grounding. For the overload risk factor, when At that time, it was determined that there was an overload danger. The real-time load torque of the equipment is determined by real-time load and boom amplitude data synchronized with a digital twin. The rated load torque of the equipment under the current boom position is determined by the rated operating parameters in the basic data. For structural fatigue risk factor, when At that time, it was determined that there was a structural fatigue risk. The real-time maximum stress at key sections of the boom is determined using dynamic deformation and load data of the boom synchronized with a digital twin. The allowable stress of the boom material is determined by the component performance parameters in the basic data. The wire rope breakage risk factor is when At that time, it was determined that there was a risk of wire rope breakage. The real-time maximum tension of the wire rope is determined by real-time load and wire rope inclination data synchronized with a digital twin. The minimum breaking strength of the wire rope is determined by the component performance parameters in the basic data; corresponding hazardous conditions are identified, and hazardous condition identification data is obtained, such as... Figure 2 As shown, the simulation process covers four core hazard types: overturning hazard, overload hazard, structural fatigue hazard, and wire rope breakage hazard. When the boom crosses street walls or the hoisting equipment experiences slight swaying, the simulation can identify the hazard in advance and capture the upward trend of the risk coefficient, rather than responding after the hazard occurs. This allows operators time to adjust operating parameters in advance, effectively avoiding potential safety hazards during operation and preventing the impact of frequent shutdowns on work efficiency.

[0042] When a hazardous state that reaches the judgment threshold appears in the hazardous state identification data, based on the hazardous state identification data, the corresponding time node, hazardous state type, and corresponding data category of multi-dimensional real-time operation data are identified. Starting from the identified time node, the process is traced back along the physical equipment operation flow to investigate the state change nodes of each parameter within the identified corresponding data category. The contribution of each parameter to the hazardous state is calculated using the multi-type hazard source contribution formula. The hazard source contribution formula is as follows: ,in, For the first The contribution of parameters corresponding to different types of dangerous states. The set of dangerous states corresponding to overturning hazard, overload hazard, structural fatigue hazard, and wire rope breakage hazard, when When this parameter is identified as the source of the corresponding dangerous state, For the first The change in hazard coefficient caused by changes in parameters corresponding to a hazard state is determined by calculating the state change data of the corresponding parameters during the reverse backtracking process, combined with a set of quantitative formulas for multiple types of hazard states. For the first The total change in the hazard coefficient of a hazardous state is determined by the difference in the corresponding hazard coefficient between the hazard identification node and the normal operation node. This allows for the location of the source of the hazard, the integration of the entire evolution process of the hazardous state, and the generation of source tracing data including the cause, location, and evolution path of the hazard. In this operation, after predicting that the risk coefficient of the overturning hazard state would continue to rise, the core source of the risk was accurately located through reverse backtracking and contribution calculation. This was determined to be the continuous subsidence of the ground under the right rear outrigger and the continuous decrease in the ground pressure of the outrigger, rather than the overloading load or the boom amplitude exceeding the limit. This process can accurately locate the parameters that cause the hazardous state, providing precise guidance for subsequent safety management and hazard investigation by operators. Operators do not need to conduct indiscriminate inspections of all parts of the equipment; they only need to reinforce the problematic outrigger with steel plates, which greatly shortens the hazard handling time and avoids ineffective operations in narrow streets and alleys.

[0043] Based on the generated hazard identification data and source tracing results data, a preset safety component matching rule is used to lock the corresponding triggered safety component. The safety component matching rule is a one-to-one correspondence between hazard type and safety component. Overturning hazard corresponds to outrigger locking device and buzzer alarm component; overload hazard corresponds to stress torque limiter and audible and visual alarm component; structural fatigue hazard corresponds to automatic speed reduction unit and shutdown protection unit; wire rope breakage hazard corresponds to hoisting mechanism braking unit and emergency stop protection unit. After locking the safety component, the hazard coefficients in the hazard identification data are compared with the corresponding hazard judgment thresholds. Combined with the source of hazard in the source tracing results data, the triggering time of the safety component is confirmed. The triggering time is when the hazard coefficient of the corresponding hazard reaches the corresponding judgment threshold, and the source cannot be eliminated in real time by adjusting the operating parameters. Then, the action priority of each safety component is calculated using the multi-type safety component trigger priority weight formula. The multi-type safety component trigger priority weight formula is as follows: ,in, For the first The trigger priority weight of each security component This is a set of safety components, including outrigger locking devices, torque limiters, audible and visual alarm components, automatic speed reduction units, hoisting mechanism braking units, and emergency stop protection units. For the first The security component corresponds to the first one under control. Risk factor of a hazardous state For the first The security component corresponds to the first one under control. The contribution of hazardous state source parameters is assessed; corresponding linkage control commands are issued in descending order of priority to control safety components to complete corresponding protective actions; in this operation, after confirming that the risk source of outrigger settlement cannot be eliminated immediately by adjusting the boom posture, the outrigger locking device is triggered first to lock the current outrigger posture to prevent the outrigger from continuing to settle and causing further imbalance of the equipment posture. At the same time, the buzzer alarm component is triggered to warn on-site operators and surrounding personnel, and then a prompt for outrigger reinforcement is pushed to the control panel. The entire process strictly follows the priority of the actions, which not only avoids the risk of the hoisting equipment swaying in the air caused by direct shutdown, but also achieves real-time risk control and is fully adapted to the protection needs of complex on-site working conditions.

[0044] After the safety component is triggered, it continuously monitors changes in the hazardous state. After the operator completes the reinforcement of the steel plates under the outriggers, it collects the grounding pressure data of the outriggers in real time and updates the equipment status of the digital twin synchronously. When the hazard factor falls below the judgment threshold and the source tracing results show that the hazard source has been eliminated, a reset permission signal is generated to complete the reset operation of the safety component. When the hazard factor continues to exceed the standard, the safety component's active state is maintained and an escalation alarm is issued until the hazardous state is eliminated. Figure 3As shown, it fully realizes the closed-loop management of the entire process from pre-identification and source location to joint response of dangerous situations, and is fully adaptable to special working conditions such as narrow streets and complex ground, ensuring the safe and stable operation of lifting operations throughout the process.

[0045] In summary, in the confined spaces and complex ground operation scenarios of emergency repairs to municipal pipelines in old urban areas, a complete closed-loop process of pre-emptive identification of hazardous conditions of spider crane equipment, source location, and coordinated control of safety components has been fully realized. By constructing a digital twin of the equipment to accurately reproduce the actual on-site operation status, the inherent defects of passive protection and disconnected control links in existing technologies have been effectively solved, ensuring the safety and stability of lifting operations throughout the process. This provides a complete and feasible technical solution for the safety management of spider cranes under various complex working conditions.

[0046] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A smart sensing system for the hazardous state of a spider crane, characterized in that, The system includes: Acquisition and Processing Module: The basic data of the spider crane is stored in the storage unit, and real-time multi-dimensional operation data is collected through multi-type sensor acquisition units. After preprocessing, standardized basic data and multi-dimensional real-time operation data are obtained. Twin construction module: Based on standardized basic data, construct a digital twin, establish a real-time data interaction link between physical devices and the digital twin, and access standardized multi-dimensional real-time operation data to obtain the synchronous status data of the digital twin; Hazard prediction module: Based on standardized multi-dimensional real-time operational data and synchronous status data of digital twin, it performs inference and identification of various types of hazardous states that are evolving during the operation of physical equipment, and obtains hazardous state identification data; Hazard tracing module: Based on hazard identification data, it reverse-engineers the entire evolution process of the hazard, locates the source of the hazard, and generates tracing result data; Linkage and control module: Based on the hazard status identification data and traceability result data, and according to the safety component matching rules, establish linkage logic between the digital twin and multiple sets of safety components, determine the triggering time of the safety components, and issue linkage control commands to the corresponding safety components.

2. The intelligent sensing system for hazardous conditions of a spider crane according to claim 1, characterized in that, In the acquisition and processing module, the basic data consists of the inherent parameters calibrated at the factory of the spider crane, including the spider crane's structural parameters, component performance parameters, and operational rating parameters; the multi-type sensor acquisition unit includes a pin-type weighing acquisition unit deployed on the hoisting mechanism, used to acquire load data; An ultrasonic anemometer unit deployed on the top of the fuselage is used to collect wind speed data; An array of pressure acquisition units deployed at the bottom of each outrigger is used to collect outrigger grounding status data; A strain-type deformation acquisition unit deployed on the surface of the boom is used to collect dynamic deformation data of the boom; The motor operation parameter acquisition unit deployed inside each drive motor is used to collect motor operation parameter data. The specific preprocessing operations are as follows: the basic data is standardized in format and unified in units to generate standardized basic data; the original values ​​of multi-dimensional real-time operation data are time-series aligned, the timestamps of all operation data are unified, outliers are removed, and then the units are unified and the format is converted to generate standardized multi-dimensional real-time operation data.

3. The intelligent sensing system for hazardous conditions of a spider crane according to claim 1, characterized in that, In the aforementioned twin construction module, based on standardized basic data, the structure, component performance, and operational rating parameters of the spider crane's body, outriggers, boom, wire rope, and safety components are disassembled. Virtual mapping units corresponding to each component are built, and the virtual mapping units of each component are spliced ​​together to form a digital twin. Then, a real-time data interaction link between the physical equipment and the digital twin is established, and standardized multi-dimensional real-time operating data is accessed to complete the full-state synchronization between the digital twin and the physical equipment. Moreover, the synchronized state data covers the operating status and spatial pose parameters of each component of the physical equipment.

4. The intelligent sensing system for hazardous conditions of a spider crane according to claim 1, characterized in that, In the hazard prediction module, standardized multi-dimensional real-time operating data is input into the digital twin, and the operating status and spatial pose parameters of the digital twin are updated synchronously. Then, the quantitative deduction of various hazards is completed through a set of multi-type hazard state quantification formulas to identify the corresponding hazard state and obtain hazard state identification data.

5. The intelligent sensing system for hazardous conditions of a spider crane according to claim 4, characterized in that, The hazard prediction module contains a set of quantification formulas for multiple types of hazard states: ,in, For the overturning risk factor, when At that time, it was determined that there was a risk of overturning. The real-time overturning moment of the equipment is determined by real-time load and boom position data synchronized with the digital twin. To determine the real-time anti-overturning moment of the equipment, the data on the equipment's self-weight distribution and outrigger grounding pressure, synchronized with a digital twin, are used. The correction factor for outrigger grounding status is determined by historical operating data of spider cranes of the same model and is positively correlated with the effective contact area of ​​outrigger grounding. For the overload risk factor, when At that time, it was determined that there was an overload danger. The real-time load torque of the equipment is determined by real-time load and boom amplitude data synchronized with a digital twin. The rated load torque of the equipment under the current boom position is determined by the rated operating parameters in the basic data. For structural fatigue risk factor, when At that time, it was determined that there was a structural fatigue risk. The real-time maximum stress at key sections of the boom is determined using dynamic deformation and load data of the boom synchronized with a digital twin. The allowable stress of the boom material is determined by the component performance parameters in the basic data. The wire rope breakage risk factor is when At that time, it was determined that there was a risk of wire rope breakage. The real-time maximum tension of the wire rope is determined by real-time load and wire rope inclination data synchronized with a digital twin. The minimum breaking strength of the wire rope is determined by the component performance parameters in the basic data.

6. The intelligent sensing system for hazardous conditions of a spider crane according to claim 1, characterized in that, In the hazard tracing module, based on hazard state identification data, the time node, hazard state type, and corresponding data category of multi-dimensional real-time operation data corresponding to the hazard state are locked. Starting from the locked time node, the module traces back along the physical equipment operation process to investigate the state change nodes of each parameter within the locked corresponding data category. The contribution of each parameter to the hazard state is calculated through the multi-type hazard source contribution formula to locate the source of the hazard, integrate the entire evolution process of the hazard state, and generate tracing result data containing the hazard cause, location, and evolution path.

7. The intelligent sensing system for hazardous conditions of a spider crane according to claim 6, characterized in that, In the hazard tracing module, the formula for the contribution of hazard sources is: ,in, For the first The contribution of parameters corresponding to different types of dangerous states. The set of dangerous states corresponding to overturning hazard, overload hazard, structural fatigue hazard, and wire rope breakage hazard, when When this parameter is identified as the source of the corresponding dangerous state, For the first The change in hazard coefficient caused by changes in parameters corresponding to a hazard state is determined by calculating the state change data of the corresponding parameters during the reverse backtracking process, combined with a set of quantitative formulas for multiple types of hazard states. For the first The total change in the hazard coefficient of a hazardous state is determined by the difference in the corresponding hazard coefficient between the hazard identification node and the normal operation node.

8. The intelligent sensing system for hazardous conditions of a spider crane according to claim 1, characterized in that, In the aforementioned linkage control module, based on hazard identification data and source tracing results data, and according to safety component matching rules, the corresponding triggered safety components are locked. The safety component matching rules are a one-to-one correspondence between hazard type and safety component. Specifically, the overturning hazard corresponds to the outrigger locking device and the buzzer alarm component; the overload hazard corresponds to the stress torque limiter and the audible and visual alarm component; the structural fatigue hazard corresponds to the automatic speed reduction unit and the shutdown protection unit; and the wire rope breakage hazard corresponds to the hoisting mechanism braking unit and the emergency stop protection unit. By comparing each hazard coefficient in the hazard identification data with the corresponding hazard judgment threshold, and combining the source of the hazard in the source tracing results data, the triggering time is confirmed. The triggering time is when the hazard coefficient of the corresponding hazard reaches the corresponding judgment threshold, and the source cannot be eliminated by adjusting the operating parameters in real time. Then, the action priority of each safety component is calculated using the trigger priority weight formula of multiple types of safety components, and the corresponding linkage control commands are issued in order of priority from high to low.

9. The intelligent sensing system for hazardous conditions of a spider crane according to claim 8, characterized in that, In the aforementioned linkage control module, the trigger priority weight formula for multiple types of security components is as follows: ,in, For the first The trigger priority weight of each security component This is a set of safety components, including outrigger locking devices, torque limiters, audible and visual alarm components, automatic speed reduction units, hoisting mechanism braking units, and emergency stop protection units. For the first The security component corresponds to the first one under control. Risk factor of a hazardous state For the first The security component corresponds to the first one under control. The contribution of source parameters of hazardous states.

10. A method of using a safety component of a spider crane hazard sensing system, the method being applicable to the spider crane hazard sensing system according to any one of claims 1-9, characterized in that, The specific steps for using this method are as follows: S1. Establish a digital twin based on the basic data of the spider crane, and complete the real-time data interaction link between the digital twin and the physical equipment; S2. Real-time multi-dimensional operation data is collected through multiple types of sensor acquisition units, and after preprocessing, it is synchronized to the digital twin to update the synchronization status data of the digital twin. S3. Based on the synchronization status data, infer and identify the evolving dangerous states during the operation of physical equipment in real time, and generate dangerous state identification data. S4. If any hazard factor in the hazard identification data does not reach the judgment threshold of the corresponding hazard, return to S2 to continue monitoring; if any hazard factor reaches or exceeds the judgment threshold, proceed to S5. S5. Based on the hazard identification data, reverse the entire evolution process of the hazard, locate the source of the hazard, and generate source tracing result data; S6. Based on the hazard identification data and source tracing results data, and according to the safety component matching rules, identify the corresponding safety components to be triggered and the triggering time, and calculate the action priority of each safety component through the multi-type safety component trigger priority weight formula; S7. In order of action priority from high to low, issue linkage control commands to the corresponding safety components. When a tipping danger is determined, first trigger the outrigger locking device to lock the current outrigger posture, and then trigger the buzzer alarm component to issue an audible and visual alarm. When an overload danger is determined, simultaneously trigger the torque limiter to cut off the power output and the audible and visual alarm component to sound an alarm. When a structural fatigue danger is determined, first trigger the automatic speed reduction unit to reduce the boom luffing speed. When the danger factor continues to rise, trigger the shutdown protection unit. When a wire rope breakage danger is determined, simultaneously trigger the hoisting mechanism braking unit for emergency braking and the emergency stop protection unit to cut off the power to the entire machine. S8. After the safety component is triggered, it continuously monitors changes in the dangerous state. When the danger factor falls below the judgment threshold and the tracing results show that the source of danger has been eliminated, a reset permission signal is generated to reset the safety component. When the danger factor continues to exceed the standard, the safety component is maintained in operation and an upgraded alarm is issued.

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