Intelligent sensing and early warning system, method and equipment for hoisting state

Abstract

The invention relates to the technical field of data processing, in particular to a hoisting state intelligent sensing and early warning system, method and equipment, and the system comprises an environment interference early warning module, a hoisting equipment abnormity early warning module, a hoisting operation abnormity early warning module and a hoisting system database, according to the intelligent sensing and early warning system, method and equipment for the hoisting state, the influence of environment interference, hoisting equipment abnormity and hoisting state abnormity on hoisting operation is comprehensively analyzed, and a comprehensive hoisting operation abnormity evaluation system is formed; the evaluation system not only can monitor the environmental interference degree of a hoisting operation site in real time, but also can perform analysis and early warning on hoisting equipment abnormity and hoisting state abnormity, and through comprehensive evaluation and early warning on hoisting operation, the emergency response capability of hoisting operation can be improved, and the safety of hoisting operation is improved. And therefore, the hoisting operation can still be kept stable and safe under the emergency condition.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a system, method and device for intelligently sensing and warning a hoisting state. Background Art

[0002] On modern construction sites, hoisting operations are one of the core links, and their safety is directly related to the progress and quality of the entire project. However, traditional hoisting operations face many challenges. With the rapid development of science and technology, especially the continuous advancement of sensor technology, Internet of Things technology, and artificial intelligence technology, the intelligent perception and early warning system for hoisting status has emerged.

[0003] For example, the invention patent with announcement number: CN118183515B is a method and system for early warning control of safety risks in the process of lifting machinery hoisting operations, which involves the field of safety risk early warning technology. The steps of the method include: obtaining the personnel risk threat value through image recognition and personnel situation coefficient calculation; setting the start-stop intelligent control strategy to determine whether to proceed to the next step; installing a sensor network to calculate the working status data of the lifting machinery in real time, and calculating the ore offset value, and jointly obtaining the motion risk threat value; obtaining the total threat value of the lifting machinery operation through the personnel risk threat value and the motion risk threat value; and rating the safety risk of the lifting machinery hoisting operation process based on the total threat value of the lifting machinery operation.

[0004] For example, the invention patent with announcement number: CN112785210B is a method for early warning of the risk of hoisting falling based on sensor fusion, which belongs to the field of intelligent Internet of Things equipment design and construction technology. In order to quantitatively predict the spatial falling area of ​​scattered objects in the hoisting process in advance and issue timely warnings, it uses a combination of multiple sensor data fusion, inequality method to solve envelope displacement, and sound and light alarms as technical means, and deploys sensors, builds a hoisting falling risk warning network system, collects and transmits data, calculates the hoisting falling envelope displacement, calculates the coordinates of the corner points of the falling area, and issues hoisting falling risk alarms as implementation steps. It can real-time calculate the falling area range of objects in the hopper that are thrown obliquely to the ground, and use light projection and sound prompts to mark the falling risks. It can provide real-time visual marking of the falling risk area and falling direction warning information considering the influence of wind direction for personnel and equipment on the ground.

[0005] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, it was found that the above technology has at least the following technical problems: the current intelligent perception and early warning system for hoisting status mainly focuses on safety issues such as personnel intrusion and equipment failure in the hoisting area, but may not be able to effectively monitor and warn some potential and hidden safety hazards. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides a lifting status intelligent perception warning system, method and equipment, which can effectively solve the problems involved in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: The first aspect of the present invention provides an intelligent perception and warning system for hoisting status, including: an environmental interference warning module, a hoisting equipment abnormality warning module, a hoisting operation abnormality warning module and a hoisting system database.

[0008] The environmental interference warning module is used to obtain the environmental data of the target lifting operation area and obtain the environmental interference value after processing.

[0009] The hoisting equipment abnormality warning module is used to obtain the operating data of the hoisting equipment, obtain the abnormal operation evaluation index of each hoisting equipment after processing, and screen and feedback the abnormalities of each hoisting equipment according to the abnormal operation evaluation index of each hoisting equipment.

[0010] The hoisting operation abnormality warning module is used to obtain sensor data of the target hoisting operation area, and obtain the hoisting state abnormality assessment index after processing. According to the environmental interference value, the operation abnormality assessment index of each hoisting equipment and the hoisting state abnormality assessment index, a comprehensive analysis is performed to obtain the hoisting operation abnormality assessment index, and a risk warning is issued for the hoisting operation based on the hoisting operation abnormality assessment index.

[0011] As a further method, the environmental interference value is obtained through processing, and the specific process is: the environmental data of the target lifting operation area, including the wind speed, ground level and temperature of each environmental monitoring point within a preset monitoring period, is extracted from the lifting system database to obtain the critical wind speed, reference standard temperature and allowable deviation temperature, and the environmental interference value is obtained through comprehensive analysis. The environmental interference value is used to quantitatively evaluate the degree of influence of the environment of the target lifting operation area on the lifting operation, and provide a basis for evaluating the abnormal risk of the lifting operation.

[0012] As a further method, the operating data of the lifting equipment include: the vibration intensity and current of each device in the electrical system at each time collection point within a preset monitoring period, the surface temperature and internal pressure of each component of the hydraulic system at each time collection point within the preset monitoring period, the original size and current size of each structural component of the lifting equipment within the preset monitoring period, the number of wear marks and the wear depth.

[0013] As a further method, the abnormal operation evaluation index of each lifting equipment is obtained through processing. The specific process is: extracting the reference standard vibration intensity, allowable deviation vibration intensity, reference standard current, allowable deviation current, reference standard surface temperature, allowable deviation surface temperature, reference standard internal pressure, allowable deviation internal pressure, allowable deviation size, critical number of wear marks and critical wear depth from the lifting system database, and based on the operating data of the lifting equipment, comprehensively analyzing to obtain the abnormal operation evaluation index of each lifting equipment. The abnormal operation evaluation index of each lifting equipment is used to quantitatively evaluate the degree of abnormal operation of each lifting equipment, and provide a basis for screening abnormal equipment.

[0014] The abnormal operation evaluation index of each hoisting equipment includes the abnormal operation evaluation value of each equipment in the electrical system, the abnormal operation evaluation value of each component in the hydraulic system and the abnormal operation evaluation value of each structural component of the hoisting equipment.

[0015] As a further method, each lifting equipment is screened for abnormalities and feedback is given based on the abnormal operation evaluation index of each lifting equipment. The specific screening process is: extracting the electrical equipment operation abnormality evaluation threshold from the lifting system database, and comparing the abnormal operation evaluation value of each equipment in the electrical system with the abnormal operation evaluation threshold of the electrical equipment. If the abnormal operation evaluation value of a certain equipment in the electrical system is higher than or equal to the abnormal operation evaluation threshold of the equipment, the equipment is marked as abnormal equipment and a risk warning is issued for it. If the abnormal operation evaluation value of a certain equipment in the electrical system is lower than the abnormal operation evaluation threshold of the equipment, the equipment is marked as normal equipment and the result is displayed.

[0016] As a further method, the abnormal lifting state evaluation index is obtained after processing. The specific process is: the sensor data of the target lifting operation area, including the arm tilt angle, crane lifting speed and crane rotation speed at each monitoring time point within a preset monitoring period, is extracted from the lifting system database to obtain the critical tilt angle, reference standard lifting speed, allowable deviation lifting speed, reference standard rotation speed and allowable deviation rotation speed, and a comprehensive analysis is performed to obtain the abnormal lifting state evaluation index. The abnormal lifting state evaluation index is used to quantitatively evaluate the abnormal degree of the lifting state and provide a basis for evaluating the abnormal risk of the lifting operation.

[0017] As a further method, the comprehensive analysis obtains the lifting operation abnormality assessment index. The specific analysis process is: according to the environmental interference value, the operation abnormality assessment index of each lifting equipment and the lifting status abnormality assessment index, the lifting operation abnormality assessment index is obtained by comprehensive analysis. The lifting operation abnormality assessment index is used to quantitatively assess the degree of abnormal risk of the crane during operation, and provide a basis for risk warning.

[0018] As a further method, risk warning is issued for hoisting operations based on the hoisting operation abnormality assessment index. The specific analysis process is: extracting the hoisting operation abnormality assessment index threshold from the hoisting system database, comparing the hoisting operation abnormality assessment index with the hoisting operation abnormality assessment index threshold; if the hoisting operation abnormality assessment index is higher than or equal to the hoisting operation abnormality assessment index threshold, the hoisting operation is evaluated as a high-risk operation and a risk warning is issued; if the hoisting operation abnormality assessment index is lower than the hoisting operation abnormality assessment index threshold, the hoisting operation is evaluated as a normal operation.

[0019] A second aspect of the present invention provides a method for intelligent perception and early warning of hoisting status, comprising: acquiring environmental data of a target hoisting operation area, and obtaining an environmental interference value through processing.

[0020] The operation data of the lifting equipment is obtained, and the abnormal operation evaluation index of each lifting equipment is obtained after processing. The abnormalities of each lifting equipment are screened and feedback is given according to the abnormal operation evaluation index of each lifting equipment.

[0021] The sensor data of the target lifting operation area is obtained, and the lifting state abnormality assessment index is obtained after processing. According to the environmental interference value, the abnormal operation assessment index of each lifting equipment and the abnormal lifting state assessment index, the lifting operation abnormality assessment index is obtained through comprehensive analysis. According to the lifting operation abnormality assessment index, risk warning of lifting operation is issued.

[0022] A third aspect of the present invention provides a lifting status intelligent perception and early warning device, comprising: a receiver, a processor, a display and an early warning device.

[0023] The receiver is used to receive relevant data collected by the sensor.

[0024] The processor is used to obtain data received by the receiver and perform risk assessment on the lifting operation.

[0025] The display is used to display and output the result of risk assessment of the processor.

[0026] The early warning device is used to issue an early warning according to the risk assessment result displayed on the display.

[0027] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention provides an intelligent sensing and early warning system, method and device for hoisting status, which comprehensively analyzes the impact of environmental interference, hoisting equipment abnormalities and hoisting status abnormalities on hoisting operations, and forms a comprehensive hoisting operation abnormality assessment system. By comprehensively evaluating and early warning hoisting operations, the emergency response capability of hoisting operations can be improved, which helps to ensure that hoisting operations can remain stable and safe in emergency situations.

[0028] (2) The present invention can timely discover and warn of potential safety hazards by real-time monitoring of the degree of environmental interference at the lifting operation site, so that measures can be taken in advance to avoid accidents, which helps to reduce the interruption and delay of lifting operations caused by environmental factors.

[0029] (3) The present invention can timely detect and handle equipment failures and abnormal conditions by evaluating the abnormal operation and hoisting status of the equipment, thereby avoiding operation interruptions caused by equipment failures and reducing the probability of accidents caused by abnormal conditions. This helps to maintain the continuity and stability of hoisting operations and improve operating efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0031] Figure 1 It is a schematic diagram of the method flow of the present invention.

[0032] Figure 2 It is a schematic diagram of system module connection of the present invention.

[0033] Figure 3 It is a schematic diagram of the functional relationship between the lifting equipment operation abnormality evaluation index and the lifting operation abnormality evaluation index involved in an embodiment of the present invention. DETAILED DESCRIPTION

[0034] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0035] Reference Figure 1 As shown, the first aspect of the present invention provides an intelligent perception warning system for hoisting status, including: an environmental interference warning module, a hoisting equipment abnormality warning module, a hoisting operation abnormality warning module and a hoisting system database.

[0036] The environmental interference warning module is used to obtain the environmental data of the target lifting operation area and obtain the environmental interference value after processing.

[0037] Specifically, the environmental interference value is obtained through processing, and the specific process is as follows: the environmental data of the target lifting operation area, including the wind speed, ground level and temperature of each environmental monitoring point within a preset monitoring period, is extracted from the lifting system database to obtain the critical wind speed, reference standard temperature and allowable deviation temperature, and the environmental interference value is obtained through comprehensive analysis. The environmental interference value is used to quantitatively evaluate the degree of influence of the environment of the target lifting operation area on the lifting operation, and provide a basis for evaluating the abnormal risk of the lifting operation.

[0038] It needs to be explained that anemometers and thermometers can be used to monitor the wind speed and temperature at each environmental monitoring point to obtain comprehensive wind speed data and temperature data, and the horizontal height of different locations can be measured by using a level.

[0039] It should be explained that strong winds may have a significant impact on the stability and controllability of lifting equipment. When the wind force reaches a certain level (such as level 5 or above), it will cause obvious interference to the lifting process, which may cause the lifting process to lose control or accidents. At the same time, changes in wind direction may cause the lifting materials to shift and shake, increasing the difficulty and risk of operations. On the ground with height differences, the stability of the crane will be seriously affected, which may cause the crane to overturn or slip. The height difference of the ground will also affect the walking stability of the crane, making it more prone to slippage or instability during walking. High temperature may cause the material to expand, affecting the stability and safety of the lifting equipment. At the same time, low temperature may cause materials and equipment to freeze, increase the friction between the lifting equipment and materials, and reduce the flexibility of operation.

[0040] In a specific embodiment, the numerical expression of the environmental interference value is: ; In the formula, represents the environmental interference value, t represents the time variable, , Indicates the current time point. Indicates the monitoring start time point, i indicates the number of each environmental monitoring point, , h represents the total number of environmental monitoring points, represents the wind speed of the ith environmental monitoring point at time t, represents the ground level height of the i-th environmental monitoring point at time t, represents the temperature of the i-th environmental monitoring point at time t, represents the critical wind speed, Indicates the reference standard temperature, Indicates the allowable deviation temperature, Indicates the environmental interference impact factor corresponding to the preset wind speed, Indicates the environmental interference factor corresponding to the preset ground level height, Indicates the environmental interference impact factor corresponding to the preset temperature.

[0041] It needs to be explained that when the wind speed is greater, the absolute difference between the ground undulation and the average ground level height is greater, and the absolute difference between the temperature and the reference standard temperature is greater, the corresponding environmental interference value is greater, indicating that the regional environment has a greater impact on the regional lifting operation.

[0042] It should be explained that in this embodiment Indicates the environmental interference impact factor corresponding to the preset wind speed, Indicates the environmental interference factor corresponding to the preset ground level height, The environmental interference influence factors corresponding to the preset temperature respectively represent the numerical values ​​of the influence of the wind speed, ground level and temperature unit values ​​on the environmental interference degree. When used, the environmental interference influence factors corresponding to the wind speed, the environmental interference influence factors corresponding to the ground level and the environmental interference influence factors corresponding to the temperature can be directly obtained from the lifting system database. The corresponding relationship can be a pre-set mapping relationship. For example, the wind speed, ground level and temperature of each environmental monitoring point are respectively mapped with the environmental interference influence factors corresponding to the wind speed, ground level and temperature preset in the lifting system database to form a mapping set. The real-time wind speed, ground level and temperature are input into the mapping set to obtain the environmental interference influence factors corresponding to the wind speed corresponding to the compression time, the environmental interference influence factors corresponding to the ground level and the environmental interference influence factors corresponding to the temperature. The mapping relationship can be one-to-one or many-to-one. The above-mentioned influence factors are all extracted from the lifting system database, and the value range is between 0 and 1.

[0043] It should be explained that the greater the absolute difference between the ground undulation and the average ground level, the more likely the crane itself may tilt or slide due to gravity. At this time, if the wind speed is high, strong winds may further aggravate the shaking of the crane, further affecting its stability. The higher the temperature, the more violent the air flow (i.e. wind speed). This is because high temperatures make air molecules more active, thereby increasing the speed and intensity of air flow. Topographic conditions may affect local climate characteristics, including temperature distribution and wind speed. For example, in mountainous or hilly areas, differences in terrain undulation and vegetation cover may lead to significant changes in local climate. Wind speed, ground level and temperature interact with each other and work together on the safety and efficiency of lifting operations. Comprehensive analysis can make the assessment of environmental interference values ​​more comprehensive and accurate.

[0044] The hoisting equipment abnormality warning module is used to obtain the operating data of the hoisting equipment, obtain the abnormal operation evaluation index of each hoisting equipment after processing, and screen and feedback the abnormalities of each hoisting equipment according to the abnormal operation evaluation index of each hoisting equipment.

[0045] Specifically, the operating data of the lifting equipment include: the vibration intensity and current of each equipment in the electrical system at each time collection point within the preset monitoring period, the surface temperature and internal pressure of each component of the hydraulic system at each time collection point within the preset monitoring period, the original size and current size of each structural component of the lifting equipment within the preset monitoring period, the number of wear marks and the wear depth.

[0046] It should be explained that the vibration of the equipment can be monitored in real time by installing vibration sensors at key parts of the electrical equipment (such as motor bearing seats, drive end covers, non-drive end covers, etc.). These sensors can convert vibration signals into electrical signals, which are then analyzed and processed by the data acquisition system. Installing current transformers in the circuits of the electrical system can monitor the current in the circuit in real time. Current transformers can convert large currents into small currents, which is convenient for measurement and recording. Vibration intensity is an important indicator of the operating status of electrical equipment, which reflects the mechanical movement and electromagnetic interaction inside the equipment. When the electrical equipment is running, if the vibration intensity increases abnormally, it may be caused by wear, looseness of mechanical parts inside the equipment, or imbalance of electromagnetic fields. These fault conditions may cause instability or abnormal increase of current, thereby damaging the electrical system. On the other hand, the magnitude of the current will also affect the vibration state of the electrical equipment. For example, when the current is too large, it may cause overheating and increased vibration of the electrical equipment, thereby accelerating the wear and aging of the equipment.

[0047] It should be explained that the use of infrared thermal imagers to perform non-contact temperature measurement of the hydraulic system can intuitively see the temperature distribution of each component of the system, which helps to find potential overheating problems. Pressure sensors can be installed inside the pipelines or key components of the hydraulic system to monitor the internal pressure of the system in real time. The surface temperature of the hydraulic system reflects the temperature of the hydraulic oil inside the system. When the hydraulic system is running, the hydraulic oil flows in the pump, valve and pipeline, which will generate a certain amount of heat. If the internal pressure of the system is too high, the flow rate of the hydraulic oil will increase, thereby increasing the generation and accumulation of heat and increasing the surface temperature of the system. At the same time, the increase in the surface temperature of the system will also affect the performance of the hydraulic oil, such as viscosity, lubricity and oxidation resistance, and then affect the system's pressure and flow parameters. When the internal pressure of the system is too high, it will accelerate the wear and aging of hydraulic components (such as pumps, valves, seals, etc.), resulting in leakage and performance degradation. The increase in wear will further affect the system's pressure and flow parameters, forming a vicious circle.

[0048] It should be explained that the three-dimensional scanning technology can be used to scan the structural components of the lifting equipment to obtain its three-dimensional size information. Non-destructive testing technology (such as ultrasonic testing, magnetic particle testing, etc.) can be used to detect the wear depth of the structural components of the lifting equipment. By comparing the original size and the current size, the degree of wear and the remaining life of the equipment can be evaluated, providing a basis for the maintenance and replacement of the equipment. The more wear marks the equipment has, the more severe the friction and wear the equipment has been subjected to during use. The wear depth directly reflects the loss of equipment materials.

[0049] Furthermore, the abnormal operation evaluation index of each lifting equipment is obtained through processing. The specific process is as follows: The reference standard vibration intensity, allowable deviation vibration intensity, reference standard current, allowable deviation current, reference standard surface temperature, allowable deviation surface temperature, reference standard internal pressure, allowable deviation internal pressure, allowable deviation size, critical number of wear marks and critical wear depth are extracted from the lifting system database, and based on the operating data of the lifting equipment, a comprehensive analysis is performed to obtain the abnormal operation evaluation index of each lifting equipment. The abnormal operation evaluation index of each lifting equipment is used to quantitatively evaluate the degree of abnormal operation of each lifting equipment, so as to provide a basis for screening abnormal equipment.

[0050] It should be understood that the abnormal operation evaluation index of each lifting equipment includes the abnormal operation evaluation value of each equipment in the electrical system, the abnormal operation evaluation value of each component in the hydraulic system and the abnormal operation evaluation value of each structural component of the lifting equipment.

[0051] The abnormal operation evaluation value of each device in the electrical system is a quantitative evaluation data obtained by comprehensively analyzing the vibration intensity and current of each device in the electrical system, and is used to quantitatively evaluate the degree of abnormal operation of each device in the electrical system, providing a basis for screening abnormal devices.

[0052] The abnormal operation evaluation value of each component of the hydraulic system is a quantitative evaluation data obtained by comprehensively analyzing the surface temperature and internal pressure of each component of the hydraulic system, and is used to quantitatively evaluate the degree of abnormal operation of each component of the hydraulic system, providing a basis for screening abnormal components.

[0053] The abnormal operation evaluation value of each structural component of the lifting equipment is a quantitative evaluation data obtained by comprehensively analyzing the size changes, the number of wear marks and the wear depth of each structural component of the lifting equipment. It is used to quantitatively evaluate the degree of abnormal operation of each structural component of the lifting equipment and provide a basis for screening abnormal structural components.

[0054] It needs to be explained that the electrical system provides power and control signals for the lifting equipment, and the operating status of the lifting equipment will affect the parameters of the electrical system such as current and vibration. For example, when the lifting equipment is overloaded or running at high speed, it will consume more electricity and produce greater vibration and current fluctuations. The hydraulic system provides a stable power source and precise control functions for the lifting equipment, and the operating status of the lifting equipment will also affect the parameters of the hydraulic system such as pressure and temperature. For example, when the lifting equipment is started and stopped frequently, it will cause the pressure and temperature fluctuations of the hydraulic system to increase, accelerating the wear and aging of the hydraulic components.

[0055] In a specific embodiment, the numerical expression of the abnormal operation evaluation value of each device in the electrical system is: ; In the formula, Indicates the electrical system Equipment operation abnormality assessment value, Indicates the number of each device in the electrical system. , A represents the total number of electrical system equipment, g represents the number of each time collection point, , j represents the total number of time acquisition points, Indicates the electrical system The vibration intensity of a device at the gth time point, Indicates the electrical system The current of a device at the sampling point at time g, Indicates the electrical system Each device is referenced to the standard vibration intensity, Allowable deviation vibration intensity, Indicates the electrical system Each device refers to the standard current, Indicates the allowable deviation current, Indicates the abnormal operation impact factor of the electrical system equipment corresponding to the preset vibration intensity. Indicates the abnormal operation impact factor of the electrical system equipment corresponding to the preset current.

[0056] It needs to be explained that when the absolute difference between the equipment vibration intensity and the equipment reference standard vibration intensity is greater, and the absolute difference between the equipment current and the equipment reference standard current is also greater, the corresponding electrical system equipment operation abnormality assessment value is greater, indicating that the greater the degree of electrical system equipment operation abnormality, the greater the risk of electrical system equipment failure.

[0057] It should be explained that in this embodiment Indicates the abnormal operation impact factor of the electrical system equipment corresponding to the preset vibration intensity. The abnormal operation influence factor of the electrical system equipment corresponding to the preset current, respectively represents the numerical value of the influence degree of the vibration intensity and the current unit value on the abnormal operation degree of the electrical system equipment. When used, the abnormal operation influence factor of the electrical system equipment corresponding to the vibration intensity and the abnormal operation influence factor of the electrical system equipment corresponding to the current can be directly obtained from the lifting system database. The corresponding relationship can be a pre-set mapping relationship. For example, the vibration intensity and current of each time acquisition point are respectively mapped with the abnormal operation influence factors of the electrical system equipment corresponding to the preset vibration intensity and current in the lifting system database to form a mapping set. The real-time vibration intensity and current are input into the mapping set to obtain the abnormal operation influence factor of the electrical system equipment corresponding to the vibration intensity and the abnormal operation influence factor of the electrical system equipment corresponding to the current. The mapping relationship can be one-to-one or many-to-one. The above-mentioned influence factors are all extracted from the lifting system database, and the value range is between 0 and 1.

[0058] In a specific embodiment, the numerical expression of the abnormal operation evaluation value of each component of the hydraulic system is: ; In the formula, Indicates the hydraulic system The abnormal operation evaluation value of each component, Indicates the number of each component of the hydraulic system. , B represents the total number of hydraulic system components, Indicates the hydraulic system The surface temperature of a component at the sampling point at time g, Indicates the hydraulic system The internal pressure of a device at the sampling point at time g, Indicates the hydraulic system Each device is referenced to a standard surface temperature. Indicates the allowable deviation surface temperature, Indicates the hydraulic system Each device is referenced to a standard internal pressure, Indicates the allowable deviation of internal pressure, Indicates the influence factor of abnormal operation of hydraulic system components corresponding to the preset surface temperature, Indicates the abnormal operation influencing factor of the hydraulic system components corresponding to the preset internal pressure.

[0059] It needs to be explained that when the absolute difference between the component surface temperature and the equipment reference standard surface temperature is greater, and the absolute difference between the component internal pressure and the equipment reference standard internal pressure is also greater, the corresponding hydraulic system component operation abnormality assessment value is greater, indicating that the greater the degree of hydraulic system component operation abnormality, the greater the risk of hydraulic system component failure.

[0060] It should be explained that in this embodiment Indicates the influence factor of abnormal operation of hydraulic system components corresponding to the preset surface temperature, The hydraulic system component operation abnormality impact factor corresponding to the preset internal pressure, respectively represents the numerical value of the impact degree of the component surface temperature and the internal voltage unit value on the hydraulic system component operation abnormality degree. When used, the hydraulic system component operation abnormality impact factor corresponding to the surface temperature and the hydraulic system component operation abnormality impact factor corresponding to the internal pressure can be directly obtained from the lifting system database. The corresponding relationship can be a pre-set mapping relationship. For example, the surface temperature and internal voltage of the component at each time acquisition point are respectively mapped with the hydraulic system component operation abnormality impact factor corresponding to the surface temperature and the internal voltage of the component preset in the lifting system database to form a mapping set. The real-time component surface temperature and internal voltage are input into the mapping set to obtain the hydraulic system component operation abnormality impact factor corresponding to the surface temperature and the hydraulic system component operation abnormality impact factor corresponding to the internal pressure. The mapping relationship can be one-to-one or many-to-one. The above impact factors are all extracted from the lifting system database, and the value range is between 0 and 1.

[0061] In a specific embodiment, the numerical expression of the abnormal operation evaluation value of each structural component of the lifting equipment is: ; In the formula, Indicates the lifting equipment The abnormal operation assessment value of each structural component, Indicates the number of each structural component of the lifting equipment. , C represents the total number of structural components of the lifting equipment, g represents the time variable, , Indicates the current time collection point, Indicates the time point when the collection starts. Indicates the hydraulic system The size of a component at time g, Indicates the hydraulic system The number of wear marks on a component at time g, Indicates the hydraulic system The wear depth of a component at time g, Indicates the hydraulic system The original size of the component, Indicates the allowable deviation size, represents the critical wear mark number, represents the critical wear depth, Indicates the abnormal operation influencing factor of the lifting equipment structural components corresponding to the preset size change, Indicates the abnormal operation influencing factor of the lifting equipment structural components corresponding to the preset number of wear marks, Indicates the abnormal operation influencing factor of the lifting equipment structural components corresponding to the preset wear depth.

[0062] It should be explained that the wear depth refers to the depth of the deepest marks on the surface of each structural component of the lifting equipment.

[0063] It needs to be explained that when the absolute difference between the size of the structural component and the original size is greater, the number of wear marks on the structural component is greater, and the wear depth is greater, the corresponding lifting equipment structural component operation abnormality assessment value will be greater, indicating that the greater the degree of operation abnormality of the lifting equipment structural component, the greater the risk of failure of the lifting equipment structural component.

[0064] It should be explained that in this embodiment Indicates the abnormal operation influencing factor of the lifting equipment structural components corresponding to the preset size change, Indicates the abnormal operation influencing factor of the lifting equipment structural components corresponding to the preset number of wear marks, The abnormal operation influencing factors of the lifting equipment structural components corresponding to the preset wear depth respectively represent the numerical values ​​of the influence of the unit values ​​of size change, number of wear marks and wear depth on the abnormal operation degree of the lifting equipment structural components. When used, the abnormal operation influencing factors of the lifting equipment structural components corresponding to the size change, the abnormal operation influencing factors of the lifting equipment structural components corresponding to the number of wear marks and the abnormal operation influencing factors of the lifting equipment structural components corresponding to the wear depth can be directly obtained from the lifting system database. The corresponding relationship can be a preset mapping relationship. For example, the size change, number of wear marks and wear depth of the structural components at each time collection point are respectively mapped with the abnormal operation influencing factors of the lifting equipment structural components corresponding to the size change, number of wear marks and wear depth of the components preset in the lifting system database to form a mapping set. The real-time size change, number of wear marks and wear depth of the components are input into the mapping set to obtain the abnormal operation influencing factors of the lifting equipment structural components corresponding to the size change, the abnormal operation influencing factors of the lifting equipment structural components corresponding to the number of wear marks and the abnormal operation influencing factors of the lifting equipment structural components corresponding to the wear depth. The mapping relationship can be one-to-one or many-to-one. The above influencing factors are extracted from the lifting system database, and the value range is between 0 and 1.

[0065] It needs to be explained that the lifting equipment includes various equipment of the electrical system, various components of the hydraulic system and various structural components of the lifting equipment, among which the various components of the electrical system include power supplies, control devices, electrical equipment, power distribution equipment and auxiliary equipment, and the various components of the hydraulic system include power elements (i.e. hydraulic pumps), actuators (such as hydraulic cylinders and hydraulic motors), control elements (including various hydraulic valves, such as directional control valves, pressure control valves and flow control valves), auxiliary elements (including accumulators, filters, coolers, heaters, oil pipes, pipe joints, oil tanks, pressure gauges, flow meters) and working media (such as mineral oil, emulsion or synthetic hydraulic oil), and the various structural components of the lifting equipment include wire ropes, hooks, gears, steel plates and steel rods and drums.

[0066] It should be explained that, in summary, the relationship between the parameters of the electrical system, hydraulic system and lifting equipment is interrelated and mutually influential. In practical applications, it is necessary to comprehensively consider the relationship between these parameters and conduct comprehensive monitoring and analysis of the lifting operation to ensure the safety and efficiency of the operation.

[0067] Furthermore, each lifting equipment is screened for abnormalities and feedback is given based on the abnormal operation evaluation index of each lifting equipment. The specific screening process is: the electrical equipment abnormal operation evaluation threshold is extracted from the lifting system database, and the abnormal operation evaluation value of each equipment in the electrical system is compared with the abnormal operation evaluation threshold of the electrical equipment. If the abnormal operation evaluation value of a certain equipment in the electrical system is higher than or equal to the abnormal operation evaluation threshold of the equipment, the equipment is marked as abnormal equipment and a risk warning is issued for it; if the abnormal operation evaluation value of a certain equipment in the electrical system is lower than the abnormal operation evaluation threshold of the equipment, the equipment is marked as normal equipment and the result is displayed.

[0068] It should be explained that the abnormal screening process of hydraulic system equipment and lifting system result components is consistent with the above screening process.

[0069] The hoisting operation abnormality warning module is used to obtain sensor data of the target hoisting operation area, and obtain the hoisting state abnormality assessment index after processing. According to the environmental interference value, the operation abnormality assessment index of each hoisting equipment and the hoisting state abnormality assessment index, a comprehensive analysis is performed to obtain the hoisting operation abnormality assessment index, and a risk warning is issued for the hoisting operation based on the hoisting operation abnormality assessment index.

[0070] Specifically, an abnormal lifting status assessment index is obtained after processing, and the specific process is as follows: the sensor data of the target lifting operation area, including the arm tilt angle, crane lifting speed and crane rotation speed at each monitoring time point within a preset monitoring period, is extracted from the lifting system database to obtain the critical tilt angle, reference standard lifting speed, allowable deviation lifting speed, reference standard rotation speed and allowable deviation rotation speed, and a comprehensive analysis is performed to obtain the abnormal lifting status assessment index, which is used to quantitatively assess the degree of abnormality of the lifting status and provide a basis for assessing the abnormal risk of the lifting operation.

[0071] In a specific embodiment, the numerical expression of the lifting state abnormality evaluation index is: ; In the formula, represents the abnormal evaluation index of the lifting status, e represents the natural constant, n represents the number of the monitoring point at each time, , m represents the total number of time monitoring points, represents the tilt angle of the boom at the nth time monitoring point, Indicates the crane lifting speed at the nth time monitoring point, Indicates the crane rotation speed at the nth time monitoring point, represents the critical tilt angle, Indicates reference standard lifting speed, Indicates the allowable deviation lifting speed, Indicates reference standard rotation speed, Indicates the allowable deviation rotation speed, Indicates the abnormal impact factor of the lifting state corresponding to the preset tilt angle, Indicates the abnormal impact factor of the hoisting state corresponding to the preset lifting speed. Indicates the abnormal impact factor of the lifting state corresponding to the preset rotation speed.

[0072] It needs to be explained that when the tilt angle of the boom is larger, the absolute difference between the crane lifting speed and the reference standard lifting speed is larger, and the absolute difference between the crane rotation speed and the reference standard rotation speed is larger, the corresponding lifting status abnormality assessment index is larger, indicating that the greater the degree of abnormality of the lifting status, the greater the risk of failure of the lifting equipment.

[0073] It should be explained that in this embodiment Indicates the abnormal impact factor of the lifting state corresponding to the preset tilt angle, Indicates the abnormal impact factor of the hoisting state corresponding to the preset lifting speed. The abnormal hoisting state influence factor corresponding to the preset rotation speed is represented, and the numerical value of the influence degree of the unit value of the boom tilt angle, the crane lifting speed and the crane rotation speed on the abnormal hoisting state is respectively represented. When used, the abnormal hoisting state influence factor corresponding to the tilt angle, the abnormal hoisting state influence factor corresponding to the lifting speed and the abnormal hoisting state influence factor corresponding to the rotation speed can be directly obtained from the hoisting system database, and the corresponding relationship can be a pre-set mapping relationship. For example, the boom tilt angle, the crane lifting speed and the crane rotation speed at each time monitoring point are respectively mapped with the abnormal hoisting state influence factors corresponding to the preset boom tilt angle, the crane lifting speed and the crane rotation speed in the hoisting system database to form a mapping set, and the real-time boom tilt angle, the crane lifting speed and the crane rotation speed are input into the mapping set to obtain the abnormal hoisting state influence factor corresponding to the tilt angle, the abnormal hoisting state influence factor corresponding to the lifting speed and the abnormal hoisting state influence factor corresponding to the rotation speed, wherein the mapping relationship can be one-to-one or a many-to-one relationship. The above-mentioned influence factors are all extracted from the hoisting system database, and the value range is between 0 and 1.

[0074] It needs to be explained that the lifting speed of the lifting equipment is too fast or too slow, which may be caused by hydraulic system failure, electrical system failure or transmission system failure. The unstable or abnormal rotation speed of the lifting equipment may be caused by motor failure, reducer failure or control system failure.

[0075] It should be explained that the inclination sensor is a sensor that can directly measure the inclination angle of an object. Installing the inclination sensor on the crane boom can directly read the inclination angle of the boom and transmit the data to the monitoring center for real-time monitoring and analysis. Installing a speed sensor on the lifting mechanism of the crane can directly measure the lifting speed of the crane. Modern cranes usually use electric transmission and control systems to achieve the rotation function. By adjusting the speed of the motor through the frequency converter, the precise control of the crane rotation speed can be achieved. At the same time, the programmable logic controller (PLC) control system can monitor the rotation speed of the crane in real time and transmit the data to the monitoring center for analysis and processing. The inclination angle of the boom, the lifting speed of the crane and the rotation speed of the crane interact and influence each other. For example, when the inclination angle of the boom is large, in order to maintain stability, it may be necessary to reduce the lifting speed and rotation speed; and when the load mass is large, for safety reasons, it is also necessary to appropriately reduce the lifting speed and rotation speed. Comprehensive analysis of the inclination angle of the boom, the lifting speed of the crane and the rotation speed of the crane can make the assessment of abnormal hoisting status more comprehensive.

[0076] It should be explained that the inclination angle of the boom refers to the angle between the boom and the horizontal plane.

[0077] Furthermore, a comprehensive analysis is performed to obtain an abnormality assessment index for hoisting operations. The specific analysis process is as follows: based on the environmental interference value, the abnormality assessment index for each hoisting equipment operation and the abnormality assessment index for hoisting status, a comprehensive analysis is performed to obtain an abnormality assessment index for hoisting operations. The abnormality assessment index for hoisting operations is used to quantitatively assess the degree of abnormal risk of the crane during operation, and to provide a basis for risk warning.

[0078] In a specific embodiment, the numerical expression of the lifting operation abnormality evaluation index is: ; In the formula, Indicates the abnormal evaluation index of lifting operation. Indicates the environmental interference value, represents the abnormal operation evaluation index of the rth lifting equipment, r represents the number of each lifting equipment, , d represents the total number of hoisting equipment, Indicates the abnormal evaluation index of the lifting status. Indicates the abnormal impact factor of the lifting operation corresponding to the preset environmental interference value, Indicates the hoisting operation abnormality impact factor corresponding to the preset hoisting equipment operation abnormality assessment index, Indicates the lifting operation abnormality impact factor corresponding to the preset lifting status abnormality assessment index.

[0079] It should be understood that if Figure 3 As shown, curve a represents the relationship between the corresponding lifting equipment operation abnormality assessment index and the lifting operation abnormality assessment index when the environmental interference value is 0.56 and the lifting state abnormality assessment index is 0.72. Curve b represents the relationship between the corresponding lifting equipment operation abnormality assessment index and the lifting operation abnormality assessment index when the environmental interference value is 0.43 and the lifting state abnormality assessment index is 0.79. Curve c represents the relationship between the corresponding lifting equipment operation abnormality assessment index and the lifting operation abnormality assessment index when the environmental interference value is 0.5 and the lifting state abnormality assessment index is 0.6.

[0080] It should be explained that, in this embodiment, the lifting operation abnormality impact factor corresponding to the environmental interference value is set to 0.6, the lifting operation abnormality impact factor corresponding to the lifting equipment operation abnormality assessment index is set to 0.5, and the lifting operation abnormality impact factor corresponding to the lifting state abnormality assessment index is set to 0.4.

[0081] It needs to be explained that when the environmental interference value is greater, the lifting equipment operation abnormality assessment index is greater, and the lifting status abnormality assessment index is also greater, the corresponding lifting operation abnormality assessment index is greater, indicating that the more abnormal the lifting operation is, the greater the risk of failure of the lifting equipment.

[0082] It should be explained that in this embodiment Indicates the abnormal impact factor of the lifting operation corresponding to the preset environmental interference value, Indicates the hoisting operation abnormality impact factor corresponding to the preset hoisting equipment operation abnormality assessment index, It represents the lifting operation abnormality impact factor corresponding to the preset lifting state abnormality assessment index, and respectively represents the numerical value of the influence of the environmental interference value, the lifting equipment operation abnormality assessment index and the lifting state abnormality assessment index unit value on the lifting operation abnormality degree. When in use, the lifting operation abnormality impact factor corresponding to the environmental interference value, the lifting operation abnormality impact factor corresponding to the lifting equipment operation abnormality assessment index and the lifting operation abnormality impact factor corresponding to the lifting state abnormality assessment index can be directly obtained from the lifting system database, and the corresponding relationship can be a preset mapping relationship. For example, the environmental interference value, the lifting equipment operation abnormality assessment index and the lifting state abnormality assessment index are respectively mapped with the environmental interference value, the lifting equipment operation abnormality assessment index and the lifting operation abnormality impact factor corresponding to the lifting state abnormality assessment index preset in the lifting system database to form a mapping set, and the real-time environmental interference value, the lifting equipment operation abnormality assessment index and the lifting state abnormality assessment index are input into the mapping set to obtain the lifting operation abnormality impact factor corresponding to the environmental interference value, the lifting operation abnormality impact factor corresponding to the lifting equipment operation abnormality assessment index and the lifting operation abnormality impact factor corresponding to the lifting state abnormality assessment index. The mapping relationship can be one-to-one or many-to-one. The above influencing factors are extracted from the lifting system database, and the value range is between 0 and 1.

[0083] It needs to be explained that the increase in environmental interference values ​​may lead to an increase in the abnormal operation evaluation index of the lifting equipment. This is because environmental interference affects the normal operation and performance of the lifting equipment, thereby increasing the probability of equipment failure or abnormality. The increase in environmental interference values ​​may also lead to an increase in the abnormal lifting status evaluation index. This is because environmental interference affects the stability and safety of the lifting operation, thereby increasing the probability of abnormal conditions such as displacement, shaking or falling of the hoisted objects. The increase in the abnormal operation evaluation index of each lifting equipment may lead to an increase in the abnormal lifting status evaluation index. Because the operating status and performance of the lifting equipment directly affect the stability and safety of the lifting operation, when the equipment is abnormal, it is easy to cause abnormal conditions in the lifting operation. There is a close correlation and influence between the environmental interference value, the abnormal operation evaluation index of each lifting equipment and the abnormal lifting status evaluation index. In the lifting operation, the interaction and influence between these factors should be fully considered to ensure the safety and efficiency of the lifting operation.

[0084] It should be explained that in this embodiment, by real-time monitoring of environmental interference values ​​at the site of the hoisting operation, such as noise, vibration, electromagnetic waves, etc., potential safety hazards can be discovered and warned in time, so that measures can be taken in advance to avoid accidents. By real-time monitoring and abnormal evaluation of the hoisting equipment, equipment failure or performance degradation can be discovered in time. This helps operators to shut down the equipment for maintenance in time to prevent the equipment from running in a sick state, thereby avoiding safety accidents in hoisting operations. By evaluating the hoisting state abnormality index, abnormal conditions such as the deviation, shaking or falling of the hoisted object can be discovered in time. This helps operators to take immediate measures, such as adjusting the boom angle, reducing the speed of the hoisted object, etc., to ensure the safety of the hoisting operation.

[0085] It needs to be explained that by monitoring the environmental interference value, the hoisting operation environment can be optimized. For example, in the case of strong winds, you can choose a sheltered area for operation, or add a stabilizing device when necessary to improve the stability of the hoisting equipment. This helps to reduce operation interruptions and delays caused by environmental factors. Through the evaluation of equipment operation abnormalities, equipment failures can be discovered and handled in a timely manner, thereby avoiding operation interruptions caused by equipment failures. This helps to maintain the continuity and stability of hoisting operations and improve operation efficiency. Through the evaluation of hoisting status abnormalities, abnormal situations in hoisting operations can be discovered and handled in a timely manner. This helps to reduce accident handling time and reduce the impact of accidents on hoisting operations, thereby improving operation efficiency.

[0086] It should be explained that through the abnormal equipment operation assessment, equipment failures can be discovered and handled in a timely manner, thereby improving the reliability and stability of the equipment. This helps to ensure that the hoisting operation is carried out under normal equipment operation conditions and enhances the reliability of the operation. By comprehensively analyzing the above parameters, the hoisting operation process can be optimized. For example, the operation plan can be adjusted according to the environmental interference value, and equipment maintenance can be arranged according to the results of the equipment operation abnormality assessment. This helps to ensure that the hoisting operation is carried out in the best condition and improves the reliability and stability of the operation. Furthermore, by real-time monitoring and evaluation of the above parameters, the emergency response capability of the hoisting operation can be improved. When an abnormal situation occurs, the operator can quickly take measures to deal with it and prevent the situation from escalating. This helps to ensure that the hoisting operation can remain stable and safe in an emergency.

[0087] Specifically, risk warnings are issued for hoisting operations based on the hoisting operation abnormality assessment indicators. The specific analysis process is: the hoisting operation abnormality assessment indicator threshold is extracted from the hoisting system database, and the hoisting operation abnormality assessment indicator is compared with the hoisting operation abnormality assessment indicator threshold. If the hoisting operation abnormality assessment indicator is higher than or equal to the hoisting operation abnormality assessment indicator threshold, the hoisting operation is evaluated as a high-risk operation and a risk warning is issued; if the hoisting operation abnormality assessment indicator is lower than the hoisting operation abnormality assessment indicator threshold, the hoisting operation is evaluated as a normal operation.

[0088] Furthermore, the specific steps of the risk warning are as follows: first, when the system determines that it is a high-risk operation, the risk warning mechanism is immediately triggered. The warning signal can be a pop-up window prompt, sound alarm or flashing light on the monitoring system interface. The warning information can be sent to the person in charge of the hoisting operation, the safety supervisor and the relevant management personnel through a preset communication method (such as SMS, email, telephone, etc.). Among them, the warning information should include the specific location of the hoisting operation, abnormal assessment indicators, risk level and possible consequences. After receiving the warning information, the relevant personnel should immediately take emergency response measures, such as suspending the hoisting operation, checking the hoisting equipment and environment, assessing the risk and taking necessary corrective measures. Especially in emergency situations, the emergency plan should be activated to ensure the safety of personnel and the integrity of equipment. Then, the detailed information of each risk warning is recorded, including the warning time, triggering conditions, response measures and results. Regularly analyze the warning events, summarize the experience and lessons, and provide improvement suggestions for future hoisting operations. Finally, according to the analysis results of the warning events, optimize the parameter settings of the hoisting operation monitoring system and the risk warning system, and regularly maintain and upgrade the system to ensure its accuracy and reliability.

[0089] In a specific embodiment, the hoisting system database is used to store relevant data in the process of hoisting operation abnormality assessment, including reference standard vibration intensity, allowable deviation vibration intensity, reference standard current, allowable deviation current, reference standard surface temperature, allowable deviation surface temperature, reference standard internal pressure, allowable deviation internal pressure, allowable deviation size, critical number of wear marks and critical wear depth, hoisting operation abnormality influencing factors corresponding to environmental interference values, hoisting operation abnormality influencing factors corresponding to hoisting equipment operation abnormality assessment index and hoisting operation abnormality influencing factors corresponding to hoisting status abnormality assessment index, hoisting operation abnormality assessment index threshold and the above-mentioned data extracted from the hoisting system database. The data in the hoisting system database can be obtained by consulting the manufacturer's official website information, product page and product manual, and relevant data can also be obtained through field research and experimental testing.

[0090] Reference Figure 2 As shown, the second aspect of the present invention provides a method for intelligent perception and early warning of hoisting status, comprising: acquiring environmental data of a target hoisting operation area, and obtaining an environmental interference value through processing.

[0091] The operation data of the lifting equipment is obtained, and the abnormal operation evaluation index of each lifting equipment is obtained after processing. The abnormalities of each lifting equipment are screened and feedback is given according to the abnormal operation evaluation index of each lifting equipment.

[0092] The sensor data of the target lifting operation area is obtained, and the lifting state abnormality assessment index is obtained after processing. According to the environmental interference value, the abnormal operation assessment index of each lifting equipment and the abnormal lifting state assessment index, the lifting operation abnormality assessment index is obtained through comprehensive analysis. According to the lifting operation abnormality assessment index, risk warning of lifting operation is issued.

[0093] A third aspect of the present invention provides a lifting status intelligent perception and early warning device, comprising: a receiver, a processor, a display and an early warning device.

[0094] The receiver is used to receive relevant data collected by the sensor.

[0095] The processor is used to obtain data received by the receiver and perform risk assessment on the lifting operation.

[0096] The display is used to display and output the result of risk assessment of the processor.

[0097] The early warning device is used to issue an early warning according to the risk assessment result displayed on the display.

[0098] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. An intelligent sensing and early warning system for hoisting status, characterized in that: include: Environmental interference warning module, hoisting equipment abnormality warning module, hoisting operation abnormality warning module and hoisting system database; Environmental interference warning module, used to obtain environmental data of the target lifting operation area and obtain environmental interference value after processing; The hoisting equipment abnormality warning module is used to obtain the operation data of the hoisting equipment, obtain the abnormal operation evaluation index of each hoisting equipment after processing, and perform abnormal screening and feedback on each hoisting equipment according to the abnormal operation evaluation index of each hoisting equipment; The hoisting operation abnormality warning module is used to obtain sensor data of the target hoisting operation area, and obtain the hoisting state abnormality assessment index after processing. According to the environmental interference value, the operation abnormality assessment index of each hoisting equipment and the hoisting state abnormality assessment index, a comprehensive analysis is performed to obtain the hoisting operation abnormality assessment index, and a risk warning is issued for the hoisting operation based on the hoisting operation abnormality assessment index.

2. According to claim 1, the intelligent sensing and early warning system for hoisting status is characterized in that: The environmental interference value is obtained through processing, and the specific process is: The environmental data of the target lifting operation area, including the wind speed, ground level and temperature of each environmental monitoring point within a preset monitoring period, is extracted from the lifting system database to obtain the critical wind speed, reference standard temperature and allowable deviation temperature, and the environmental interference value is obtained by comprehensive analysis. The environmental interference value is used to quantitatively evaluate the impact of the environment of the target lifting operation area on the lifting operation, and provide a basis for evaluating the abnormal risk of the lifting operation.

3. According to claim 1, the intelligent sensing and early warning system for hoisting status is characterized in that: The operating data of the lifting equipment include: the vibration intensity and current of each device in the electrical system at each time collection point within the preset monitoring period, the surface temperature and internal pressure of each component of the hydraulic system at each time collection point within the preset monitoring period, the original size and current size of each structural component of the lifting equipment within the preset monitoring period, the number of wear marks and the wear depth.

4. According to claim 3, the intelligent sensing and early warning system for hoisting status is characterized in that: The abnormal operation evaluation index of each lifting equipment is obtained through processing, and the specific process is as follows: Extract the reference standard vibration intensity, allowable deviation vibration intensity, reference standard current, allowable deviation current, reference standard surface temperature, allowable deviation surface temperature, reference standard internal pressure, allowable deviation internal pressure, allowable deviation size, critical wear mark quantity and critical wear depth from the lifting system database, and obtain the abnormal operation evaluation index of each lifting equipment through comprehensive analysis based on the operation data of the lifting equipment. The abnormal operation evaluation index of each lifting equipment is used to quantitatively evaluate the degree of abnormal operation of each lifting equipment, so as to provide a basis for screening abnormal equipment; The abnormal operation evaluation index of each hoisting equipment includes the abnormal operation evaluation value of each equipment in the electrical system, the abnormal operation evaluation value of each component in the hydraulic system and the abnormal operation evaluation value of each structural component of the hoisting equipment.

5. According to claim 4, the intelligent sensing and early warning system for hoisting status is characterized in that: The abnormality screening and feedback of each hoisting equipment are performed according to the abnormality evaluation index of each hoisting equipment operation. The specific screening process is as follows: The abnormal operation assessment threshold of electrical equipment is extracted from the lifting system database, and the abnormal operation assessment value of each equipment in the electrical system is compared with the abnormal operation assessment threshold of the electrical equipment. If the abnormal operation assessment value of a certain equipment in the electrical system is higher than or equal to the abnormal operation assessment threshold of the equipment, the equipment is marked as abnormal equipment and a risk warning is issued for it. If the abnormal operation assessment value of a certain equipment in the electrical system is lower than the abnormal operation assessment threshold of the equipment, the equipment is marked as normal equipment and the result is displayed.

6. According to claim 1, the intelligent sensing and early warning system for hoisting status is characterized in that: The abnormal evaluation index of the lifting state is obtained through processing, and the specific process is as follows: The sensor data of the target lifting operation area, including the boom inclination angle, crane lifting speed and crane rotation speed at each monitoring time point within a preset monitoring period, is extracted from the lifting system database to obtain the critical inclination angle, reference standard lifting speed, allowable deviation lifting speed, reference standard rotation speed and allowable deviation rotation speed, and a lifting state abnormality assessment index is obtained through comprehensive analysis. The lifting state abnormality assessment index is used to quantitatively assess the degree of abnormality of the lifting state, and provides a basis for assessing the abnormal risk of the lifting operation.

7. According to claim 6, the intelligent sensing and early warning system for hoisting status is characterized in that: The comprehensive analysis obtains the abnormal evaluation index of the lifting operation, and the specific analysis process is as follows: According to the environmental interference value, the abnormal operation assessment index of each lifting equipment and the abnormal lifting status assessment index, a comprehensive analysis is conducted to obtain the lifting operation abnormality assessment index. The lifting operation abnormality assessment index is used to quantitatively assess the degree of abnormal risk of the crane during operation, providing a basis for risk warning.

8. According to claim 7, the intelligent sensing and early warning system for hoisting status is characterized in that: The risk warning of hoisting operation is carried out according to the abnormal evaluation index of hoisting operation. The specific analysis process is as follows: The lifting operation abnormality assessment index threshold is extracted from the lifting system database, and the lifting operation abnormality assessment index is compared with the lifting operation abnormality assessment index threshold. If the lifting operation abnormality assessment index is higher than or equal to the lifting operation abnormality assessment index threshold, the lifting operation is assessed as a high-risk operation and a risk warning is issued. If the lifting operation abnormality assessment index is lower than the lifting operation abnormality assessment index threshold, the lifting operation is assessed as a normal operation.

9. A method for intelligently sensing and warning a lifting state, applied to a system for intelligently sensing and warning a lifting state according to any one of claims 1 to 8, characterized in that: include: Obtain environmental data of the target lifting operation area and obtain environmental interference values ​​after processing; Obtaining the operation data of the lifting equipment, obtaining the abnormal operation evaluation index of each lifting equipment after processing, and screening and giving feedback on the abnormal operation of each lifting equipment according to the abnormal operation evaluation index of each lifting equipment; The sensor data of the target lifting operation area is obtained, and the lifting state abnormality assessment index is obtained after processing. According to the environmental interference value, the abnormal operation assessment index of each lifting equipment and the abnormal lifting state assessment index, the lifting operation abnormality assessment index is obtained through comprehensive analysis. According to the lifting operation abnormality assessment index, risk warning of the lifting operation is issued.

10. An intelligent sensing and early warning device for hoisting status, applied to an intelligent sensing and early warning system for hoisting status according to any one of claims 1 to 8, characterized in that: include: Receivers, processors, displays and warning devices; The receiver is used to receive relevant data collected by the sensor; The processor is used to obtain data received by the receiver and perform risk assessment on the hoisting operation; The display is used to display and output the result of risk assessment of the processor; The early warning device is used to issue an early warning according to the risk assessment result displayed on the display.

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