Intelligent remote early warning method and system for tower crane

Abstract

The invention relates to the technical field of cranes, in particular to a tower crane intelligent remote early warning method and system.The method comprises the steps that working environment data and regional network environments of all target tower cranes are collected, and environment influence characteristic indexes of all the target tower cranes are obtained through comprehensive analysis; acquiring working condition data and system performance data of each target tower crane, and comprehensively analyzing to obtain a working abnormity risk assessment index of each target tower crane; and carrying out risk assessment on each target tower crane according to the abnormal working risk assessment index and the environmental influence characteristic index of each target tower crane to obtain an assessment result and carrying out early warning. According to the intelligent remote early warning method and system for the tower crane, the abnormal operation and fault risks of the tower crane are comprehensively analyzed, the abnormal working risks of the tower crane are evaluated and early warned, a more accurate maintenance plan can be made, the situation of excessive maintenance or insufficient maintenance can be avoided, and the maintenance efficiency and effect can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of cranes, and in particular to an intelligent remote early warning method and system for tower cranes. Background Art

[0002] Safety accidents during tower crane operation are relatively frequent on construction sites. These accidents usually involve overturning of tower cranes, falling from heights, and falling objects hitting people, causing casualties and property losses. With the development of digital, information and intelligent technologies, such as sensor technology, wireless communication technology, 5G technology, and artificial intelligence, new possibilities have been provided for tower crane safety monitoring and early warning. The application of these technologies makes real-time monitoring, data analysis, remote control and early warning possible.

[0003] For example, the invention patent with announcement number: CN111170184B is a real-time monitoring and early warning system and method for a tower crane, which collects various parameters of the tower crane in real time. The sensor component includes a lateral pressure sensor and a position acquisition device; the various parameters collected in real time by the sensor component are transmitted to the cloud processor through the communication component; the cloud processor processes the various parameters to obtain processing results, and transmits the processing results to the mobile terminal; and the processing results are visually displayed through the mobile terminal.

[0004] For example, the invention patent with announcement number: CN107539887B is an anti-collision warning auxiliary system for a group of construction tower cranes. The system includes an anti-collision warning central processing device and multiple construction tower cranes. Each tower crane has an alarm device. The anti-collision warning central processing device includes: a first tower crane cross arm height determination unit module, which determines the cross arm height H1 of the first tower crane; a second tower crane cross arm height determination unit module, which determines the cross arm height H2 of the second tower crane; a cross arm height comparison unit module, which compares H1 and H2, and determines the tower crane with a lower cross arm height as a low-height tower crane, and determines the tower crane with a higher cross arm height as a high-height tower crane; a rope position determination unit module, which determines the position of the rope of the high-height tower crane; a cross arm position determination unit module, which determines the position of the cross arm of the low-height tower crane; a spatial distance determination unit module, which determines the spatial distance between the rope and the cross arm; an alarm indication unit module, which indicates the alarm devices of the first and second tower cranes to alarm when the spatial distance is less than the anti-collision distance.

[0005] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application discovered that the above-mentioned technology has at least the following technical problems: the current early warning system mainly relies on fixed sensors and algorithms, which are often unable to fully adapt to the complex and changeable construction environment, and easily lead to reduced early warning accuracy or false alarms. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides an intelligent remote early warning method and system for a tower crane, 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 remote early warning method for tower cranes, including: acquiring tower cranes in a target building area, marking them as target tower cranes, collecting working environment data of each target tower crane and the regional network environment of each target tower crane, and comprehensively analyzing to obtain the environmental impact characteristic index of each target tower crane.

[0008] The working status data and system performance data of each target tower crane are collected, and the working status data are analyzed to obtain the operation abnormality assessment index of each target tower crane. The system performance data are analyzed to obtain the fault risk assessment index of each target tower crane. Comprehensive analysis is performed to obtain the working abnormality risk assessment index of each target tower crane.

[0009] Conduct risk assessment on each target tower crane based on its abnormal working risk assessment index and environmental impact characteristic index, obtain assessment results and issue early warning.

[0010] As a further method, the comprehensive analysis obtains the environmental impact characteristic index of each target tower crane. The specific analysis process is: deploy a number of environmental monitoring points and time monitoring points in the working area of ​​the tower crane, collect the working environment data of each target tower crane within a preset working cycle, including the tower top wind speed of each target tower crane at each time monitoring point and the slope of each target tower crane at each environmental monitoring point, extract the critical tower top wind speed from the tower crane database, and obtain the working environment characteristic value of each target tower crane through comprehensive analysis.

[0011] The regional network environment of each target tower crane includes the electromagnetic interference intensity and network delay at each time monitoring point. The critical electromagnetic interference intensity and critical network delay are extracted from the tower crane database, and the network environment characteristic value of each target tower crane is obtained by comprehensive analysis.

[0012] According to the working environment characteristic value and network environment characteristic value of each target tower crane, the environmental impact characteristic index of each target tower crane is obtained by comprehensive analysis. The environmental impact characteristic index of each target tower crane is used to quantitatively evaluate the degree of influence of the external environment when the tower crane is in operation.

[0013] As a further method, the working condition data is analyzed to obtain the operation abnormality evaluation index of each target tower crane. The specific analysis process is: the working condition data of each target tower crane, including the working amplitude, amplitude change speed and rotation speed of each target tower crane at each time monitoring point, is extracted from the tower crane database to obtain the maximum allowable working amplitude, the maximum allowable amplitude change speed and the maximum allowable rotation speed, and the operation abnormality evaluation index of each target tower crane is obtained by comprehensive analysis.

[0014] As a further method, the system performance data is analyzed to obtain the fault risk assessment index of each target tower crane. The specific analysis process is: the system performance data of each target tower crane, including the hydraulic station pressure and reducer temperature of each target tower crane at each time monitoring point, is extracted from the tower crane database to obtain the reference standard hydraulic station pressure and the allowable deviation hydraulic station pressure and the critical reducer temperature, and the fault risk assessment index of each target tower crane is obtained by comprehensive analysis.

[0015] As a further method, the comprehensive analysis obtains the working abnormality risk assessment index of each target tower crane. The specific analysis process is: based on the operation abnormality assessment index of each target tower crane and the fault risk assessment index of each target tower crane, the working abnormality risk assessment index of each target tower crane is obtained by comprehensive analysis. The working abnormality risk assessment index of each target tower crane is used to quantitatively assess the risk degree of working abnormality of each target tower crane.

[0016] As a further method, the risk assessment of each target tower crane is performed based on the abnormal working risk assessment index and environmental impact characteristic index of each target tower crane. The specific assessment process is: extracting the abnormal working risk assessment index threshold of each target tower crane corresponding to the environmental impact characteristic index interval of each target tower crane from the tower crane database, comparing the abnormal working risk assessment index of each target tower crane with the abnormal working risk assessment index threshold of each target tower crane, if the abnormal working risk assessment index of each target tower crane is lower than or equal to the abnormal working risk assessment index threshold of each target tower crane, then the risk assessment of the target tower crane is marked as qualified, if the abnormal working risk assessment index of each target tower crane is higher than the abnormal working risk assessment index threshold of each target tower crane, then the risk assessment of the target tower crane is marked as unqualified, and an early warning is issued for the unqualified target tower crane.

[0017] As a further method, the operation abnormality assessment index of each target tower crane is a quantitative assessment data obtained by comprehensively analyzing the working amplitude, amplitude change speed and rotation speed of each target tower crane at each time monitoring point, which is used to quantitatively assess the degree of abnormality during the operation of the tower crane and provide a basis for assessing the abnormality risk of the tower crane.

[0018] As a further method, the environmental impact characteristic index of each target tower crane is specifically expressed as: ; In the formula, represents the environmental impact characteristic index of the nth target tower crane, e represents the natural constant, represents the working environment characteristic value of the nth target tower crane, Represents the network environment characteristic value of the nth target tower crane, Indicates the environmental impact characteristic factor corresponding to the preset target tower crane working environment characteristic value, Indicates the environmental impact characteristic factor corresponding to the network environment characteristic value of the preset target tower crane.

[0019] As a further method, the specific numerical expression of the abnormal operation risk assessment index of each target tower crane is: ; In the formula, represents the abnormal risk assessment index of the nth target tower crane. represents the abnormal operation evaluation index of the nth target tower crane, represents the failure risk assessment index of the nth target tower crane, It indicates the tower crane operation abnormality risk impact factor corresponding to the preset operation abnormality assessment index. It indicates the tower crane operation abnormality risk impact factor corresponding to the preset fault risk assessment index.

[0020] The second aspect of the present invention provides an intelligent remote warning system for tower cranes, including: a tower crane environmental data collection and analysis module, which is used to obtain tower cranes in a target building area, mark them as target tower cranes, collect working environment data and regional network environment of each target tower crane, and comprehensively analyze to obtain the environmental impact characteristic index of each target tower crane.

[0021] The tower crane working data collection and analysis module is used to collect the working status data and system performance data of each target tower crane, analyze the working status data to obtain the operation abnormality assessment index of each target tower crane, analyze the system performance data to obtain the fault risk assessment index of each target tower crane, and comprehensively analyze to obtain the working abnormality risk assessment index of each target tower crane.

[0022] The tower crane risk assessment and early warning module is used to conduct risk assessment on each target tower crane based on its abnormal working risk assessment index and environmental impact characteristic index, obtain assessment results and issue early warning.

[0023] 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 remote early warning method and system for tower cranes, which comprehensively analyzes the abnormal operation and failure risks of tower cranes and evaluates the abnormal operation risks of tower cranes. It can help formulate more accurate maintenance plans, avoid over-maintenance or under-maintenance, and help improve maintenance efficiency and effectiveness. It can also reduce downtime caused by failures, ensure the continuous operation of tower cranes, and help improve operating efficiency and reduce construction costs.

[0024] (2) The present invention can timely discover potential safety hazards, such as abnormal pressure in the hydraulic station and excessive temperature of the reducer, through real-time monitoring of abnormal operation of the tower crane, so as to provide early warning and avoid the occurrence of safety accidents. By regularly evaluating the failure risk of the tower crane, vulnerable parts and potential failure points can be identified, and preventive maintenance measures can be taken to reduce the possibility of failure and improve the overall safety performance of the tower crane.

[0025] (3) By comprehensively considering the characteristic values ​​of the tower crane's working environment and the characteristic values ​​of the network environment in which it is located, the present invention can comprehensively evaluate the impact of the external environment on the tower crane's work, timely discover and eliminate potential safety hazards, and improve the safety of the tower crane's work. According to the evaluation results, the design of the tower crane can be optimized and adjusted to improve the adaptability and stability of the tower crane. At the same time, by reducing the impact of the external environment on the tower crane's work, the downtime caused by environmental factors can be reduced, and the construction efficiency and quality can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] 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.

[0027] Figure 1 It is a schematic diagram of the method flow of the present invention.

[0028] Figure 2 It is a schematic diagram of system module connection of the present invention.

[0029] Figure 3 It is a schematic diagram of the functional relationship between the fault risk assessment index of the target tower crane and the working abnormality risk assessment index of the target tower crane involved in the embodiment of the present invention. DETAILED DESCRIPTION

[0030] 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.

[0031] Reference Figure 1 As shown, the first aspect of the present invention provides an intelligent remote early warning method for tower cranes, including: acquiring tower cranes in a target building area, marking them as target tower cranes, collecting working environment data of each target tower crane and the regional network environment of each target tower crane, and comprehensively analyzing to obtain an environmental impact characteristic index of each target tower crane.

[0032] Specifically, a comprehensive analysis is performed to obtain the environmental impact characteristic index of each target tower crane. The specific analysis process is as follows: a number of environmental monitoring points and time monitoring points are deployed in the working area of ​​the tower crane, and the working environment data of each target tower crane within a preset working cycle are collected, including the tower top wind speed of each target tower crane at each time monitoring point and the slope of each target tower crane at each environmental monitoring point. The critical tower top wind speed is extracted from the tower crane database, and the working environment characteristic value of each target tower crane is obtained through comprehensive analysis.

[0033] It should be understood that the working environment characteristic values ​​of each target tower crane are quantitative evaluation data obtained by comprehensive analysis of the tower top wind speed of each target tower crane at each time monitoring point and the slope of each target tower crane at each environmental monitoring point, and are used to quantitatively evaluate the impact of the tower crane working environment on the tower crane operation.

[0034] In a specific embodiment, the numerical expression of the working environment characteristic value of each target tower crane is: ; In the formula, represents the working environment characteristic value of the nth target tower crane, n represents the number of each target tower crane, , m represents the total number of target tower cranes, i represents the number of monitoring points at each time, , t represents the total number of time monitoring points, r represents the number of each environmental monitoring point, , h represents the total number of environmental monitoring points, It represents the wind speed at the top of the nth target tower crane at the i-th time monitoring point, It represents the slope of the nth target tower crane at the rth environmental monitoring point, represents the critical tower top wind speed, Indicates the working environment characteristic influencing factor of the target tower crane corresponding to the preset tower top wind speed, It represents the influencing factor of the working environment characteristics of the target tower crane corresponding to the preset slope.

[0035] It should be understood that, in this embodiment, when the slope change value during the operation of the tower crane is greater and the wind speed at the top of the tower is greater, the corresponding working environment characteristic value of the target tower crane is also greater, indicating that the tower crane is more disturbed by the working environment.

[0036] It should be explained that in this embodiment It is the working environment characteristic influencing factor of the target tower crane corresponding to the preset tower top wind speed, which represents the numerical value of the influence degree of the tower top wind speed on the working environment of the tower crane. When used, the working environment characteristic influencing factor of the target tower crane corresponding to the tower top wind speed can be directly obtained from the tower crane database, and the corresponding relationship can be a preset mapping relationship. For example, the tower top wind speed at the time monitoring point and the working environment characteristic influencing factor of the target tower crane corresponding to the tower top wind speed preset in the tower crane database form a mapping set, and the tower top wind speed at the real-time time monitoring point is input into the mapping set to obtain the working environment characteristic influencing factor of the target tower crane corresponding to the tower top wind speed. The mapping relationship can be one-to-one or many-to-one.

[0037] It should be explained that in this embodiment The working environment characteristic influencing factor of the target tower crane corresponding to the preset slope represents the numerical value of the influence degree of the slope on the working environment of the tower crane. When used, the working environment characteristic influencing factor of the target tower crane corresponding to the slope can be directly obtained from the tower crane database. The corresponding relationship can be a pre-set mapping relationship. For example, the slope of the environmental monitoring point and the working environment characteristic influencing factor of the target tower crane corresponding to the preset slope in the tower crane database form a mapping set. The slope of the real-time environmental monitoring point is input into the mapping set to obtain the working environment characteristic influencing factor of the target tower crane corresponding to the slope. The mapping relationship can be one-to-one or many-to-one. The above-mentioned influencing factors are all extracted from the tower crane database and the value range is between 0 and 1.

[0038] It should be explained that the slope in this embodiment refers to the slope of the terrain, which is the degree of steepness of the surface unit. The ratio of the vertical height of the slope to the horizontal distance is usually called the slope (or slope ratio), which is an important parameter for describing the terrain characteristics. Professional measuring tools, such as total stations, laser rangefinders, etc., can be used to conduct field measurements of the tower crane foundation and the surrounding terrain to directly obtain slope data. The wind speed at the top of the tower is an important indicator for evaluating the safety of the working environment of the tower crane. The wind speed at the top of the tower can be monitored in real time by installing an anemometer on the top of the tower crane. This is the most direct and accurate way to obtain it. The greater the slope, the stronger the resistance and turbulence generated by the wind when passing through the terrain, which will have a certain impact on the stability of the tower crane. Terrain with a large slope may place higher requirements on the bearing capacity of the tower crane foundation, and corresponding foundation treatment measures need to be taken. Terrain with a large slope may increase the difficulty of installing and disassembling the tower crane, and a more complex construction plan needs to be formulated. The wind speed at the top of the tower is a key factor affecting the safety of the tower crane. Excessive wind speed may cause serious accidents such as instability and overturning of the tower crane. Excessive wind speed will affect the normal operation of the tower crane and reduce construction efficiency. Comprehensive analysis of the slope and wind speed at the top of the tower can provide a more comprehensive assessment of the characteristic values ​​of the tower crane's working environment.

[0039] The regional network environment of each target tower crane includes the electromagnetic interference intensity and network delay at each time monitoring point, and the critical electromagnetic interference intensity and critical network delay are extracted from the tower crane database, and the network environment characteristic value of each target tower crane is obtained by comprehensive analysis; It should be understood that the network environment characteristic values ​​of each target tower crane are quantitative evaluation data obtained by comprehensive analysis of the electromagnetic interference intensity and network delay at each time monitoring point, and are used to quantitatively evaluate the impact of the network environment of the tower crane on the operation of the tower crane.

[0040] In a specific embodiment, the numerical expression of the network environment characteristic value of each target tower crane is: ; In the formula, Represents the network environment characteristic value of the nth target tower crane, It represents the electromagnetic interference intensity of the nth target tower crane at the i-th time monitoring point, represents the network delay of the nth target tower crane at the i-th time monitoring point, Indicates the critical electromagnetic interference intensity, represents the critical network delay, Indicates the network environment characteristic influencing factor of the target tower crane corresponding to the preset electromagnetic interference intensity, Indicates the network environment characteristic influencing factor of the target tower crane corresponding to the preset network delay.

[0041] It should be understood that, in this embodiment, when the electromagnetic interference intensity is greater and the network delay is greater, the corresponding network environment characteristic value of the target tower crane is greater, indicating that the tower crane is more interfered by the network environment.

[0042] It should be explained that in this embodiment The network environment characteristic influencing factor of the target tower crane corresponding to the preset electromagnetic interference intensity represents the numerical value of the influence degree of the electromagnetic interference intensity on the working network environment of the tower crane. When used, the network environment characteristic influencing factor of the target tower crane corresponding to the electromagnetic interference intensity can be directly obtained from the tower crane database, and the corresponding relationship can be a preset mapping relationship. For example, the electromagnetic interference intensity at the time monitoring point and the network environment characteristic influencing factor of the target tower crane corresponding to the electromagnetic interference intensity preset in the tower crane database form a mapping set, and the electromagnetic interference intensity of the real-time time monitoring point is input into the mapping set to obtain the network environment characteristic influencing factor of the target tower crane corresponding to the electromagnetic interference intensity. The mapping relationship can be one-to-one or many-to-one.

[0043] It should be explained that in this embodiment The network environment characteristic influencing factor of the target tower crane corresponding to the preset network delay represents the numerical value of the influence degree of the network delay on the working network environment of the tower crane. When used, the network environment characteristic influencing factor of the target tower crane corresponding to the network delay can be directly obtained from the tower crane database. The corresponding relationship can be a preset mapping relationship. For example, the network delay at the time monitoring point and the network environment characteristic influencing factor of the target tower crane corresponding to the preset network delay in the tower crane database form a mapping set. The network delay at the real-time time monitoring point is input into the mapping set to obtain the network environment characteristic influencing factor of the target tower crane corresponding to the network delay. The mapping relationship can be one-to-one or many-to-one. The above-mentioned influencing factors are all extracted from the tower crane database and the value range is between 0 and 1.

[0044] It should be explained that in this embodiment, a professional electromagnetic field strength measuring instrument (such as an electromagnetic radiation tester) can be used to conduct field measurements at the tower crane work site to directly obtain electromagnetic interference intensity data. The tower crane work network can be tested by using network performance testing tools (such as Ping, Traceroute, network delay tester, etc.) to obtain network delay data. These tools can measure the time it takes for a data packet to be transmitted in the network, thereby evaluating the network delay. It is also possible to view performance indicators such as network traffic, packet loss rate, and delay through the monitoring interface or management software of network equipment (such as switches, routers, etc.). Electromagnetic interference may interfere with the normal operation of network equipment (such as switches, routers, etc.), resulting in problems such as device performance degradation, packet loss or retransmission. These problems will increase the burden on the network, which may indirectly lead to an increase in network delay. Comprehensively analyzing the electromagnetic interference intensity and network delay in the evaluation of the tower crane work network environment can make the evaluation more accurate and comprehensive.

[0045] According to the working environment characteristic value and network environment characteristic value of each target tower crane, the environmental impact characteristic index of each target tower crane is obtained by comprehensive analysis. The environmental impact characteristic index of each target tower crane is used to quantitatively evaluate the degree of influence of the external environment when the tower crane is in operation.

[0046] In a specific embodiment, the numerical expression of the environmental impact characteristic index of each target tower crane is: ; In the formula, represents the environmental impact characteristic index of the nth target tower crane, e represents the natural constant, represents the working environment characteristic value of the nth target tower crane, Represents the network environment characteristic value of the nth target tower crane, Indicates the environmental impact characteristic factor corresponding to the preset target tower crane working environment characteristic value, Indicates the environmental impact characteristic factor corresponding to the network environment characteristic value of the preset target tower crane.

[0047] It should be understood that, in this embodiment, when the working environment characteristic value of the target tower crane is larger and the network environment characteristic value of the target tower crane is also larger, the corresponding environmental impact characteristic index of the target tower crane is also larger, indicating that the tower crane is more affected by the external environment.

[0048] It should be explained that in this embodiment It is the environmental impact characteristic factor corresponding to the preset working environment characteristic value of the target tower crane, which represents the numerical value of the working environment characteristic value of the tower crane in the proportion of the degree of influence of the tower crane by the external environment. When used, the environmental impact characteristic factor corresponding to the working environment characteristic value of the target tower crane can be directly obtained from the tower crane database, and the corresponding relationship can be a preset mapping relationship. For example, the working environment characteristic value of the target tower crane and the environmental impact characteristic factor corresponding to the working environment characteristic value of the tower crane preset in the tower crane database form a mapping set, and the real-time working environment characteristic value of the target tower crane is input into the mapping set to obtain the environmental impact characteristic factor corresponding to the working environment characteristic value of the target tower crane, and the mapping relationship can be one-to-one or many-to-one.

[0049] It should be explained that in this embodiment The environmental impact characteristic factor corresponding to the preset network environment characteristic value of the target tower crane indicates the numerical value of the network environment characteristic value of the tower crane in the degree of influence of the tower crane by the external environment. When used, the environmental impact characteristic factor corresponding to the network environment characteristic value of the target tower crane can be directly obtained from the tower crane database. The corresponding relationship can be a pre-set mapping relationship. For example, the network environment characteristic value of the target tower crane and the environmental impact characteristic factor corresponding to the network environment characteristic value of the tower crane preset in the tower crane database form a mapping set. The real-time network environment characteristic value of the target tower crane is input into the mapping set to obtain the environmental impact characteristic factor corresponding to the network environment characteristic value of the target tower crane. The mapping relationship can be one-to-one or many-to-one. The above-mentioned influence factors are all extracted from the tower crane database and the value range is between 0 and 1.

[0050] It should be explained that, in this embodiment, by comprehensively considering the characteristic values ​​of the tower crane's working environment and the characteristic values ​​of the network environment in which it is located, the influence of the external environment on the tower crane's work can be comprehensively evaluated, potential safety hazards can be discovered and eliminated in a timely manner, and the safety of the tower crane's work can be improved. According to the evaluation results, the design of the tower crane can be optimized and adjusted, such as improving the basic design, strengthening wind protection measures, optimizing the network layout, etc., to improve the adaptability and stability of the tower crane. At the same time, by reducing the impact of the external environment on the tower crane's work, the downtime caused by environmental factors can be reduced, and the construction efficiency and quality can be improved.

[0051] The working status data and system performance data of each target tower crane are collected, and the working status data are analyzed to obtain the operation abnormality assessment index of each target tower crane. The system performance data are analyzed to obtain the fault risk assessment index of each target tower crane. Comprehensive analysis is performed to obtain the working abnormality risk assessment index of each target tower crane.

[0052] Specifically, the working condition data is analyzed to obtain the operation abnormality evaluation index of each target tower crane. The specific analysis process is: the working condition data of each target tower crane, including the working amplitude, amplitude change speed and rotation speed of each target tower crane at each time monitoring point, is extracted from the tower crane database to obtain the maximum allowable working amplitude, the maximum allowable amplitude change speed and the maximum allowable rotation speed, and the operation abnormality evaluation index of each target tower crane is obtained through comprehensive analysis.

[0053] It should be understood that the operation abnormality assessment index of each target tower crane is a quantitative assessment data obtained by comprehensively analyzing the working amplitude, amplitude change speed and rotation speed of each target tower crane at each time monitoring point, which is used to quantitatively assess the degree of abnormality during the operation of the tower crane and provide a basis for assessing the abnormality risk of the tower crane.

[0054] In a specific embodiment, the numerical expression of the operation abnormality evaluation index of each target tower crane is: ; In the formula, represents the abnormal operation evaluation index of the nth target tower crane, It means that the working amplitude of the nth target tower crane exceeds the limit value at the i-th time monitoring point. , It represents the working range of the nth target tower crane at the i-th time monitoring point, Indicates that the luffing speed of the nth target tower crane exceeds the limit value at the i-th time monitoring point. , It represents the luffing speed of the nth target tower crane at the i-th time monitoring point, Indicates that the rotation speed of the nth target tower crane exceeds the limit value at the i-th time monitoring point. , It represents the rotation speed of the nth target tower crane at the i-th time monitoring point, Indicates the maximum allowable operating range, Indicates the maximum allowable luffing speed, Indicates the maximum permissible rotation speed, Indicates the abnormal operation impact factor of the tower crane corresponding to the preset working range, Indicates the abnormal operation impact factor of the tower crane corresponding to the preset luffing speed. Indicates the abnormal operation impact factor of the tower crane corresponding to the preset rotation speed.

[0055] It should be understood that, in this embodiment, when the deviation value between the working amplitude and the maximum allowable working amplitude is larger, the deviation value between the amplitude change speed and the maximum allowable amplitude change speed is larger, and the deviation value between the rotation speed and the maximum allowable rotation speed is also larger, the corresponding tower crane operation abnormality evaluation index is larger, indicating that the degree of abnormality during the operation of the tower crane is greater. At the same time, when the deviation value between the working amplitude and the maximum allowable working amplitude, the deviation value between the amplitude change speed and the maximum allowable amplitude change speed, and the deviation value between the rotation speed and the maximum allowable rotation speed are all less than 0, the corresponding tower crane operation abnormality evaluation index is equal to 0, indicating that no abnormality occurs during the operation of the tower crane.

[0056] It should be explained that in this embodiment It is a tower crane operation abnormality impact factor corresponding to a preset working amplitude, which represents a numerical value of the degree of influence of the working amplitude of the tower crane on the tower crane operation abnormality. When in use, the tower crane operation abnormality impact factor corresponding to the working amplitude can be directly obtained from the tower crane database, and the corresponding relationship can be a preset mapping relationship. For example, the working amplitude of the tower crane at the time monitoring point and the tower crane operation abnormality impact factor corresponding to the tower crane working amplitude preset in the tower crane database form a mapping set, and the real-time tower crane working amplitude at the time monitoring point is input into the mapping set to obtain the tower crane operation abnormality impact factor corresponding to the working amplitude. The mapping relationship can be one-to-one or many-to-one.

[0057] It should be explained that in this embodiment It is a tower crane operation abnormality influence factor corresponding to a preset luffing speed, which represents a numerical value of the influence degree of the luffing speed of the tower crane on the tower crane operation abnormality. When in use, the tower crane operation abnormality influence factor corresponding to the luffing speed can be directly obtained from the tower crane database, and the corresponding relationship can be a preset mapping relationship. For example, the luffing speed of the tower crane at the time monitoring point and the tower crane operation abnormality influence factor corresponding to the luffing speed preset in the tower crane database form a mapping set, and the real-time tower crane at the time monitoring point is input into the mapping set to obtain the tower crane operation abnormality influence factor corresponding to the luffing speed. The mapping relationship can be one-to-one or many-to-one.

[0058] It should be explained that in this embodiment The tower crane operation abnormality impact factor corresponding to the preset rotation speed represents the numerical value of the influence degree of the rotation speed of the tower crane on the abnormal operation of the tower crane. When used, the tower crane operation abnormality impact factor corresponding to the rotation speed can be directly obtained from the tower crane database, and the corresponding relationship can be a preset mapping relationship. For example, the rotation speed of the tower crane at the time monitoring point and the tower crane operation abnormality impact factor corresponding to the tower crane rotation speed preset in the tower crane database form a mapping set, and the real-time tower crane rotation speed at the time monitoring point is input into the mapping set to obtain the tower crane operation abnormality impact factor corresponding to the rotation speed, wherein the mapping relationship can be one-to-one or many-to-one. The above impact factors are all extracted from the tower crane database and the value range is between 0 and 1.

[0059] It should be explained that modern tower cranes are usually equipped with real-time monitoring systems that can monitor and display various operating parameters of the tower crane in real time, including working range, luffing speed and slewing speed. Working range, also known as working radius, is the horizontal distance from the center point of the tower crane to the maximum cantilever end, usually in meters. This parameter determines the effective operating range of the tower crane. The size of the working range directly affects the construction area that the tower crane can cover and is one of the important criteria for measuring the lifting capacity of the tower crane. The luffing speed refers to the speed at which the hook on the main arm of the tower crane moves in the horizontal direction, usually in meters per minute. This speed determines the efficiency of the tower crane when changing the working range. Fast luffing speed can speed up the progress of hoisting operations and improve construction efficiency. However, the luffing speed is also limited by factors such as the tower crane structure and load, and needs to be adjusted according to specific circumstances in actual operation. The slewing speed refers to the speed at which the tower crane rotates as a whole on the horizontal plane, usually in degrees per second or revolutions per minute (rpm). This speed determines the flexibility of the tower crane in covering a wider construction range. Fast slewing speed helps the tower crane to quickly move the load from one location to another, improving construction efficiency. At the same time, the smoothness of the slewing speed is also very important to ensure the stability and safety of the load during the rotation. The working range, luffing speed and slewing speed affect each other. The size of the working range will limit the range of luffing and slewing, while the speed of the luffing speed and slewing speed will affect the operating efficiency of the tower crane at different working ranges. The working range, luffing speed and slewing speed of the tower crane need to work together to achieve efficient lifting operations.

[0060] It should be explained that in this embodiment, when the working amplitude of the tower crane exceeds its design range, it may cause overload work. This will increase the stress of the tower crane structure, and in the long run, it may cause structural fatigue, fracture and other faults. Excessive working amplitude will reduce the stability of the tower crane, especially in the case of large wind load, which may cause the tower crane to overturn. Too fast amplitude change speed will generate a large inertial force, which will impact the tower crane structure and load, and may cause structural damage or load loss of control. During high-speed amplitude change, the control accuracy may decrease, resulting in inaccurate load positioning or excessive swing. Too fast rotation speed may cause uneven force on the tower crane structure, increase stress concentration and fatigue damage of the structure. High-speed rotation will increase the difficulty of operation and require operators to have higher skills and reaction speed. Once the operation is wrong, it may cause load loss of control or collision accidents. The incoordination between the working amplitude, amplitude change speed and rotation speed may cause abnormal operation of the tower crane as a whole. For example, in the case of large amplitude, high-speed rotation and rapid amplitude change, the tower crane may not be able to maintain stable and precise control. Abnormality of the above parameters may cause the safety performance of the tower crane to decline and increase the risk of accidents. Comprehensive analysis of the above parameters can make the evaluation of tower crane operation abnormalities more comprehensive and accurate.

[0061] Furthermore, the system performance data is analyzed to obtain the fault risk assessment index of each target tower crane. The specific analysis process is as follows: the system performance data of each target tower crane, including the hydraulic station pressure and reducer temperature of each target tower crane at each time monitoring point, is extracted from the tower crane database to obtain the reference standard hydraulic station pressure and the allowable deviation hydraulic station pressure and the critical reducer temperature, and the fault risk assessment index of each target tower crane is obtained through comprehensive analysis.

[0062] It should be understood that the failure risk assessment index of each target tower crane is a quantitative assessment data obtained by comprehensively analyzing the hydraulic station pressure and reducer temperature of each target tower crane at each monitoring point in time, which is used to quantitatively assess the risk level of failure of the tower crane system during operation, and provide a basis for assessing the abnormal operation risk of the tower crane.

[0063] In a specific embodiment, the numerical expression of the failure risk assessment index of each target tower crane is: ; In the formula, represents the failure risk assessment index of the nth target tower crane, It represents the hydraulic station pressure of the nth target tower crane at the i-th time monitoring point, represents the reducer temperature of the nth target tower crane at the i-th time monitoring point, Indicates the reference standard hydraulic station pressure. Indicates the allowable deviation hydraulic station pressure, represents the critical reducer temperature, Indicates the tower crane failure risk influencing factor corresponding to the preset hydraulic station pressure, Indicates the tower crane failure risk influencing factor corresponding to the preset reducer temperature.

[0064] It should be understood that, in this embodiment, when the deviation value between the hydraulic station pressure and the reference standard hydraulic station pressure is greater and the reducer temperature is greater, the corresponding tower crane failure risk assessment index is greater, indicating that the risk of failure of the tower crane is greater.

[0065] It should be explained that in this embodiment It is the tower crane failure risk impact factor corresponding to the preset hydraulic station pressure, which represents the numerical value of the impact degree of the tower crane hydraulic station pressure on the tower crane failure risk. When used, the tower crane failure risk impact factor corresponding to the hydraulic station pressure can be directly obtained from the tower crane database, and the corresponding relationship can be a preset mapping relationship. For example, the hydraulic station pressure of the tower crane at the time monitoring point and the tower crane failure risk impact factor corresponding to the tower crane hydraulic station pressure preset in the tower crane database form a mapping set, and the real-time tower crane hydraulic station pressure at the time monitoring point is input into the mapping set to obtain the tower crane failure risk impact factor corresponding to the hydraulic station pressure. The mapping relationship can be one-to-one or many-to-one.

[0066] It should be explained that in this embodiment It is a tower crane failure risk impact factor corresponding to the preset reducer temperature, which indicates the numerical value of the influence degree of the tower crane reducer temperature on the tower crane failure risk. When used, the tower crane failure risk impact factor corresponding to the reducer temperature can be directly obtained from the tower crane database, and its corresponding relationship can be a pre-set mapping relationship. For example, the reducer temperature of the tower crane at the time monitoring point and the tower crane failure risk impact factor corresponding to the tower crane reducer temperature preset in the tower crane database form a mapping set, and the real-time tower crane reducer temperature at the time monitoring point is input into the mapping set to obtain the tower crane failure risk impact factor corresponding to the reducer temperature, wherein the mapping relationship can be one-to-one or many-to-one. The above-mentioned impact factors are all extracted from the tower crane database and the value range is between 0 and 1.

[0067] In a specific embodiment, there is data at one time monitoring point, which is calculated as t=1.

[0068] Table 1 Data example of failure risk assessment index of each target tower crane

[0069] It should be explained that in this embodiment, the reference standard hydraulic station pressure is set to 150psi, the allowable deviation hydraulic station pressure is set to 50psi, and the critical reducer temperature is set to 90 , the tower crane failure risk impact factor corresponding to the hydraulic station pressure is set to 0.6, and the tower crane failure risk impact factor corresponding to the reducer temperature is set to 0.4.

[0070] It should be explained that the hydraulic station pressure in this embodiment is one of the key parameters for the normal operation of the tower crane hydraulic system. The tower crane hydraulic station is usually equipped with pressure gauges, which are directly installed at the key position of the hydraulic system to monitor and display the pressure of the hydraulic system in real time. The hydraulic station pressure directly affects the fluidity of the hydraulic oil and the working efficiency of the system components. When the hydraulic station pressure is too high, it may cause the system components to be subjected to excessive pressure, thereby increasing the risk of wear and failure. At the same time, excessive pressure may also increase the temperature of the hydraulic oil, thereby affecting the temperature of the reducer. On the contrary, if the hydraulic station pressure is too low, the system may not be able to provide enough power to drive the reducer and other components, resulting in reduced working efficiency. The hydraulic station provides power to the reducer through hydraulic oil. Therefore, the stability and accuracy of the hydraulic station pressure directly affect the working performance and life of the reducer. If the hydraulic station pressure fluctuates greatly, it may cause uneven force on the gears and other components inside the reducer, thereby increasing the risk of wear and failure. Temperature sensors are usually installed inside the reducer to monitor the temperature of the reducer output shaft in real time. These sensors can accurately sense the working temperature of the reducer and transmit data to the monitoring system or control unit. The reducer generates heat during operation, which needs to be dissipated through the cooling system. If the reducer temperature is too high, it may affect the heat dissipation effect of the entire tower crane system. Excessive reducer temperature may also cause problems such as lubricant failure and seal aging, which in turn affects the normal operation of the hydraulic station and other system components. Although the reducer temperature does not directly determine the hydraulic station pressure, excessively high temperature may cause problems such as reduced lubricant viscosity and increased system friction, which in turn indirectly affects the pressure stability and accuracy of the hydraulic station. In order to maintain the stability and accuracy of the hydraulic station pressure, it is necessary to ensure that the reducer temperature fluctuates within a reasonable range. There is an interactive relationship between the hydraulic station pressure and the reducer temperature. The stability and accuracy of the hydraulic station pressure directly affect the working performance and temperature of the reducer; and changes in the reducer temperature may indirectly affect the hydraulic station pressure by affecting the system heat dissipation and lubricant performance. Comprehensive analysis of these two parameters can make the system performance evaluation of the tower crane more comprehensive.

[0071] Specifically, a comprehensive analysis is performed to obtain the working abnormality risk assessment index of each target tower crane. The specific analysis process is as follows: based on the operation abnormality assessment index of each target tower crane and the failure risk assessment index of each target tower crane, a comprehensive analysis is performed to obtain the working abnormality risk assessment index of each target tower crane. The working abnormality risk assessment index of each target tower crane is used to quantitatively assess the risk degree of working abnormality of each target tower crane.

[0072] In a specific embodiment, the numerical expression of the abnormal operation risk assessment index of each target tower crane is: ; In the formula, represents the abnormal risk assessment index of the nth target tower crane. represents the abnormal operation evaluation index of the nth target tower crane, represents the failure risk assessment index of the nth target tower crane, It indicates the tower crane operation abnormality risk impact factor corresponding to the preset operation abnormality assessment index. It indicates the tower crane operation abnormality risk impact factor corresponding to the preset fault risk assessment index.

[0073] It should be understood that, in this embodiment, when the operation abnormality assessment index of the target tower crane is larger and the fault risk assessment index of the target tower crane is also larger, the corresponding operation abnormality risk assessment index of the target tower crane is also larger, indicating that the operation abnormality risk degree of the tower crane is greater and the operation abnormality is more likely to occur.

[0074] It should be explained that in this embodiment It is the tower crane operation abnormality risk impact factor corresponding to the preset operation abnormality assessment index, which represents the numerical value of the influence degree of the tower crane operation abnormality assessment index on the operation abnormality risk of the tower crane. When used, the tower crane operation abnormality risk impact factor corresponding to the operation abnormality assessment index can be directly obtained from the tower crane database, and the corresponding relationship can be a preset mapping relationship. For example, the operation abnormality assessment index of the target tower crane and the tower crane operation abnormality risk impact factor corresponding to the operation abnormality assessment index of the tower crane preset in the tower crane database form a mapping set, and the real-time operation abnormality assessment index of the target tower crane is input into the mapping set to obtain the tower crane operation abnormality risk impact factor corresponding to the operation abnormality assessment index. The mapping relationship can be one-to-one or many-to-one.

[0075] It should be explained that in this embodiment The tower crane abnormal operation risk impact factor corresponding to the preset fault risk assessment index represents the numerical value of the influence degree of the tower crane fault risk assessment index on the tower crane abnormal operation risk. When used, the tower crane abnormal operation risk impact factor corresponding to the fault risk assessment index can be directly obtained from the tower crane database. The corresponding relationship can be a pre-set mapping relationship. For example, the fault risk assessment index of the target tower crane and the tower crane abnormal operation risk impact factor corresponding to the fault risk assessment index of the tower crane preset in the tower crane database form a mapping set. The real-time target tower crane fault risk assessment index is input into the mapping set to obtain the tower crane abnormal operation risk impact factor corresponding to the fault risk assessment index. The mapping relationship can be one-to-one or many-to-one. The above-mentioned impact factors are all extracted from the tower crane database and have a value range of 0 to 1.

[0076] It should be understood that Figure 3 As shown, curve a represents the relationship between the fault risk assessment index of the target tower crane and the working abnormality risk assessment index of the target tower crane when the operating abnormality assessment index of the target tower crane is 1.03, curve b represents the relationship between the fault risk assessment index of the target tower crane and the working abnormality risk assessment index of the target tower crane when the operating abnormality assessment index of the target tower crane is 1.42, and curve c represents the relationship between the fault risk assessment index of the target tower crane and the working abnormality risk assessment index of the target tower crane when the operating abnormality assessment index of the target tower crane is 1.83.

[0077] It should be explained that, in this embodiment, the tower crane operation abnormality risk impact factor corresponding to the operation abnormality assessment index is set to 0.5, and the tower crane operation abnormality risk impact factor corresponding to the fault risk assessment index is set to 0.3.

[0078] It should be explained that in this embodiment, through real-time monitoring of abnormal operation of the tower crane, potential safety hazards can be discovered in time, such as abnormal pressure of the hydraulic station and excessive temperature of the reducer, so as to give early warning and avoid the occurrence of safety accidents. By regularly evaluating the failure risk of the tower crane, vulnerable parts and potential failure points can be identified, preventive maintenance measures can be taken, the possibility of failure can be reduced, and the overall safety performance of the tower crane can be improved. The safety accident rate of the target tower crane can be significantly reduced, ensuring the safety of the construction site. In this embodiment, based on the operation abnormality assessment index and the failure risk assessment index, a more accurate maintenance plan can be formulated to avoid excessive or insufficient maintenance, and improve maintenance efficiency and effect. It can also reduce the downtime caused by failures, ensure the continuous operation of the tower crane, improve operating efficiency, and reduce construction costs. At the same time, the evaluation index and risk assessment results provide rich data support for tower crane management, which helps managers to make management decisions more scientifically and optimize resource allocation. Through the feedback of the evaluation results, the industrial upgrading of the entire tower crane industry is promoted, and the overall technical level and market competitiveness of the industry are improved.

[0079] Conduct risk assessment on each target tower crane based on its abnormal working risk assessment index and environmental impact characteristic index, obtain assessment results and issue early warning.

[0080] Specifically, a risk assessment is performed on each target tower crane based on its working abnormality risk assessment index and environmental impact characteristic index. The specific assessment process is: extracting the working abnormality risk assessment index threshold of each target tower crane corresponding to the environmental impact characteristic index interval of each target tower crane from the tower crane database, comparing the working abnormality risk assessment index of each target tower crane with the working abnormality risk assessment index threshold of each target tower crane, if the working abnormality risk assessment index of each target tower crane is lower than or equal to the working abnormality risk assessment index threshold of each target tower crane, then the risk assessment of the target tower crane is marked as qualified, if the working abnormality risk assessment index of each target tower crane is higher than the working abnormality risk assessment index threshold of each target tower crane, then the risk assessment of the target tower crane is marked as unqualified, and an early warning is issued for the unqualified target tower crane.

[0081] Furthermore, the process of early warning for unqualified target tower cranes is that for target tower cranes marked as unqualified by risk assessment, the system automatically triggers the early warning mechanism and sends early warning information to relevant personnel (such as operators, maintenance personnel, and safety supervisors) through emails, text messages, system notifications, etc. A detailed report containing abnormal details, risk assessment results, recommended measures, etc. is generated so that relevant personnel can quickly understand the problem and take corresponding measures. After receiving the early warning, relevant personnel need to immediately inspect and maintain the target tower crane to ensure that the problem is solved in a timely manner and prevent potential risks from turning into actual accidents.

[0082] In a specific embodiment, the tower crane database is used to store relevant data in the process of abnormal risk assessment of tower crane operation, including the maximum allowable operating amplitude, the maximum allowable amplitude change speed and the maximum allowable rotation speed, the network environment characteristic influencing factor of the target tower crane corresponding to the electromagnetic interference intensity, the network environment characteristic influencing factor of the target tower crane corresponding to the network delay, and the threshold value of the abnormal risk assessment index of each target tower crane corresponding to the environmental impact characteristic index interval of each target tower crane, etc. The data in the tower crane database can be used to monitor the operating status and environmental parameters of the tower crane in real time through various sensors equipped by modern tower cranes. These data can be transmitted to the database in real time through the Internet of Things technology. In this case, the acquisition of data is automatic and real-time, and can be customized according to needs.

[0083] Reference Figure 2 As shown, the second aspect of the present invention provides an intelligent remote warning system for tower cranes, including: a tower crane environmental data collection and analysis module, which is used to obtain tower cranes in a target building area, mark them as target tower cranes, collect working environment data and regional network environment of each target tower crane, and comprehensively analyze to obtain the environmental impact characteristic index of each target tower crane.

[0084] The tower crane working data collection and analysis module is used to collect the working status data and system performance data of each target tower crane, analyze the working status data to obtain the operation abnormality assessment index of each target tower crane, analyze the system performance data to obtain the fault risk assessment index of each target tower crane, and comprehensively analyze to obtain the working abnormality risk assessment index of each target tower crane.

[0085] The tower crane risk assessment and early warning module is used to conduct risk assessment on each target tower crane based on its abnormal working risk assessment index and environmental impact characteristic index, obtain assessment results and issue early warning.

[0086] 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. A tower crane intelligent remote early warning method and system, characterized in that: include: Obtain tower cranes in the target building area, mark them as target tower cranes, collect working environment data of each target tower crane and regional network environment of each target tower crane, and comprehensively analyze to obtain the environmental impact characteristic index of each target tower crane; Collect the working status data and system performance data of each target tower crane, analyze the working status data to obtain the operation abnormality assessment index of each target tower crane, analyze the system performance data to obtain the fault risk assessment index of each target tower crane, and comprehensively analyze to obtain the working abnormality risk assessment index of each target tower crane; Conduct risk assessment on each target tower crane based on its abnormal working risk assessment index and environmental impact characteristic index, obtain assessment results and issue early warning.

2. According to claim 1, a tower crane intelligent remote early warning method is characterized in that: The comprehensive analysis obtains the environmental impact characteristic index of each target tower crane. The specific analysis process is as follows: Several environmental monitoring points and time monitoring points are deployed in the tower crane working area to collect the working environment data of each target tower crane within the preset working cycle, including the tower top wind speed of each target tower crane at each time monitoring point and the slope of each target tower crane at each environmental monitoring point. The critical tower top wind speed is extracted from the tower crane database, and the working environment characteristic value of each target tower crane is obtained through comprehensive analysis. The regional network environment of each target tower crane includes the electromagnetic interference intensity and network delay at each time monitoring point, extracts the critical electromagnetic interference intensity and critical network delay from the tower crane database, and comprehensively analyzes to obtain the network environment characteristic value of each target tower crane; According to the working environment characteristic value and network environment characteristic value of each target tower crane, the environmental impact characteristic index of each target tower crane is obtained by comprehensive analysis. The environmental impact characteristic index of each target tower crane is used to quantitatively evaluate the degree of influence of the external environment when the tower crane is in operation.

3. According to claim 1, a tower crane intelligent remote early warning method is characterized in that: The operation abnormality evaluation index of each target tower crane is obtained by analyzing the working condition data. The specific analysis process is as follows: The working condition data of each target tower crane, including the working amplitude, luffing speed and rotation speed of each target tower crane at each time monitoring point, is extracted from the tower crane database to obtain the maximum allowable working amplitude, maximum allowable luffing speed and maximum allowable rotation speed, and a comprehensive analysis is performed to obtain the operation abnormality evaluation index of each target tower crane.

4. The tower crane intelligent remote early warning method according to claim 1 is characterized in that: The system performance data is analyzed to obtain the failure risk assessment index of each target tower crane. The specific analysis process is as follows: The system performance data of each target tower crane, including the hydraulic station pressure and reducer temperature of each target tower crane at each time monitoring point, is extracted from the tower crane database to obtain the reference standard hydraulic station pressure, the allowable deviation hydraulic station pressure and the critical reducer temperature, and a comprehensive analysis is performed to obtain the fault risk assessment index of each target tower crane.

5. The tower crane intelligent remote early warning method according to claim 4 is characterized in that: The comprehensive analysis obtains the abnormal operation risk assessment index of each target tower crane. The specific analysis process is as follows: According to the operation abnormality assessment index of each target tower crane and the fault risk assessment index of each target tower crane, a comprehensive analysis is performed to obtain the operation abnormality risk assessment index of each target tower crane, and the operation abnormality risk assessment index of each target tower crane is used to quantitatively assess the risk degree of the operation abnormality of each target tower crane.

6. The tower crane intelligent remote early warning method according to claim 5 is characterized by: The risk assessment of each target tower crane is performed according to the abnormal operation risk assessment index and environmental impact characteristic index of each target tower crane. The specific assessment process is as follows: The working abnormality risk assessment index threshold of each target tower crane corresponding to the environmental impact characteristic index interval of each target tower crane is extracted from the tower crane database, and the working abnormality risk assessment index of each target tower crane is compared with the working abnormality risk assessment index threshold of each target tower crane. If the working abnormality risk assessment index of each target tower crane is lower than or equal to the working abnormality risk assessment index threshold of each target tower crane, the risk assessment of the target tower crane is marked as qualified; if the working abnormality risk assessment index of each target tower crane is higher than the working abnormality risk assessment index threshold of each target tower crane, the risk assessment of the target tower crane is marked as unqualified, and an early warning is issued for the unqualified target tower crane.

7. The tower crane intelligent remote early warning method according to claim 3 is characterized by: The operation abnormality assessment index of each target tower crane is a quantitative assessment data obtained by comprehensively analyzing the working amplitude, amplitude change speed and rotation speed of each target tower crane at each time monitoring point, which is used to quantitatively assess the degree of abnormality during the operation of the tower crane and provide a basis for assessing the abnormality risk of the tower crane.

8. The tower crane intelligent remote early warning method according to claim 2 is characterized in that: The specific numerical expression of the environmental impact characteristic index of each target tower crane is: ； In the formula, represents the environmental impact characteristic index of the nth target tower crane, e represents the natural constant, represents the working environment characteristic value of the nth target tower crane, Represents the network environment characteristic value of the nth target tower crane, Indicates the environmental impact characteristic factor corresponding to the preset target tower crane working environment characteristic value, Indicates the environmental impact characteristic factor corresponding to the network environment characteristic value of the preset target tower crane.

9. The tower crane intelligent remote early warning method according to claim 5 is characterized by: The specific numerical expression of the abnormal risk assessment index of each target tower crane is: ； In the formula, represents the abnormal risk assessment index of the nth target tower crane. represents the abnormal operation evaluation index of the nth target tower crane, represents the failure risk assessment index of the nth target tower crane, It indicates the tower crane operation abnormality risk impact factor corresponding to the preset operation abnormality assessment index. It indicates the tower crane operation abnormality risk impact factor corresponding to the preset fault risk assessment index.

10. A tower crane intelligent remote warning system using a tower crane intelligent remote warning method as claimed in any one of claims 1 to 9, characterized in that: include: The tower crane environmental data collection and analysis module is used to obtain tower cranes in the target building area, mark them as target tower cranes, collect the working environment data and regional network environment of each target tower crane, and comprehensively analyze to obtain the environmental impact characteristic index of each target tower crane; The tower crane working data collection and analysis module is used to collect the working status data and system performance data of each target tower crane, analyze the working status data to obtain the operation abnormality evaluation index of each target tower crane, analyze the system performance data to obtain the fault risk evaluation index of each target tower crane, and comprehensively analyze to obtain the working abnormality risk evaluation index of each target tower crane; The tower crane risk assessment and early warning module is used to conduct risk assessment on each target tower crane based on its abnormal working risk assessment index and environmental impact characteristic index, obtain assessment results and issue early warning.

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