Intelligent remote early warning method and system for tower crane

Abstract

The present application relates to the technical field of cranes, in particular to a tower crane intelligent remote early warning method and system, the method comprising: collecting working environment data and regional network environment of each target tower crane, and comprehensively analyzing to obtain environmental influence characteristic indexes of each target tower crane; collecting working condition data and system performance data of each target tower crane, and comprehensively analyzing to obtain working abnormal risk assessment indexes of each target tower crane; according to the working abnormal risk assessment indexes and the environmental influence characteristic indexes of each target tower crane, performing risk assessment on each target tower crane, obtaining an assessment result and performing early warning. The present application provides a tower crane intelligent remote early warning method and system, comprehensively analyzes the operation abnormality and failure risk of the tower crane, and performs assessment and early warning on the working abnormal risk of the tower crane, which can help to formulate a more accurate maintenance plan, avoid over-maintenance or insufficient maintenance, and is beneficial to improving the maintenance efficiency and effect.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of cranes, in particular to a tower crane intelligent remote early warning method and system. BACKGROUND

[0002] On construction sites, safety accidents often occur during the operation of tower cranes. These accidents usually involve tower crane overturning, falling from a height, falling objects hitting people, etc., causing casualties and property losses. With the development of digitalization, informatization and intelligentization technologies such as sensor technology, wireless communication technology, 5G technology, artificial intelligence, etc., new possibilities are 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 the 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 assembly includes a side pressure sensor and a position acquisition device; through the communication assembly, the various parameters collected by the sensor assembly in real time are transmitted to the cloud processor; the cloud processor processes the various parameters to obtain a processing result, and transmits the processing result to the mobile terminal; the processing result is visually displayed on the mobile terminal.

[0004] For example, the invention patent with the announcement number CN107539887B is a building construction tower crane group anti-collision early warning auxiliary system, which includes an anti-collision early warning central processing device and multiple building construction tower cranes. Each tower crane has an alarm device. The anti-collision early warning central processing device includes: a first tower crane jib height determination unit module that determines the jib height H1 of the first tower crane; a second tower crane jib height determination unit module that determines the jib height H2 of the second tower crane; a jib height comparison unit module that compares H1 and H2, determines the tower crane with the lower jib height as the low-height tower crane, and determines the tower crane with the higher jib height as the high-height tower crane; a rope position determination unit module that determines the position of the rope of the high-height tower crane; a jib position determination unit module that determines the position of the jib of the low-height tower crane; a spatial distance determination unit module that determines the spatial distance between the rope and the jib; and an alarm indication unit module that instructs 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 scheme of the present application, the above-mentioned technology at least has the following technical problems: the current early warning system mainly relies on fixed sensors and algorithms, which often cannot fully adapt to complex and variable construction environments, easily leading to decreased early warning accuracy or false alarms. SUMMARY

[0006] In view of the deficiencies of the prior art, the present application provides a tower crane intelligent remote early warning method and system, which can effectively solve the problems involved in the above background art.

[0007] To achieve the above object, the present application is implemented by the following technical solutions: The present application provides a tower crane intelligent remote early warning method in the first aspect, comprising: acquiring target tower cranes in a target building area, marking each target tower crane, collecting working environment data of each target tower crane and regional network environment of each target tower crane, and comprehensively analyzing to obtain environmental influence characteristic indexes of each target tower crane.

[0008] Collecting working condition data of each target tower crane and system performance data of each target tower crane, analyzing the working condition data to obtain operation abnormality evaluation indexes of each target tower crane, analyzing the system performance data to obtain fault risk evaluation indexes of each target tower crane, and comprehensively analyzing to obtain working abnormality risk evaluation indexes of each target tower crane.

[0009] According to the working abnormality risk evaluation indexes and the environmental influence characteristic indexes of each target tower crane, risk evaluation is performed on each target tower crane, an evaluation result is obtained, and early warning is performed.

[0010] As a further method, the comprehensive analysis obtains the environmental influence characteristic indexes of each target tower crane, and the specific analysis process is: deploying a plurality of environment monitoring points and time monitoring points in the tower crane working area, collecting working environment data of each target tower crane in a preset working period, including tower top wind speed of each target tower crane at each time monitoring point and slope of each target tower crane at each environment monitoring point, extracting a critical tower top wind speed from a tower crane database, and comprehensively analyzing to obtain working environment characteristic values of each target tower crane.

[0011] The regional network environment of each target tower crane includes electromagnetic interference intensity and network delay of each time monitoring point, a critical electromagnetic interference intensity and a critical network delay are extracted from a tower crane database, and network environment characteristic values of each target tower crane are comprehensively analyzed.

[0012] According to the working environment characteristic values and the network environment characteristic values of each target tower crane, the environmental influence characteristic indexes of each target tower crane are comprehensively analyzed, and the environmental influence characteristic indexes of each target tower crane are used to quantitatively evaluate the influence degree of the external environment on the tower crane operation.

[0013] As a further method, the analysis of the working condition data obtains the operation abnormality evaluation indexes of each target tower crane, and the specific analysis process is: the working condition data of each target tower crane includes working amplitude, amplitude change speed and rotation speed of each target tower crane at each time monitoring point, maximum allowed working amplitude, maximum allowed amplitude change speed and maximum allowed rotation speed are extracted from a tower crane database, and the operation abnormality evaluation indexes of each target tower crane are comprehensively analyzed.

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

[0015] As a further method, the comprehensive analysis obtains a work abnormal risk evaluation index of each target tower crane, and the specific analysis process is as follows: according to the operation abnormal evaluation index of each target tower crane and the fault risk evaluation index of each target tower crane, the work abnormal risk evaluation index of each target tower crane is obtained through comprehensive analysis, and the work abnormal risk evaluation index of each target tower crane is used to quantitatively evaluate the risk degree of the work abnormality of each target tower crane.

[0016] As a further method, the risk of each target tower crane is evaluated according to the work abnormal risk evaluation index of each target tower crane and the environmental influence characteristic index, and the specific evaluation process is as follows: the work abnormal risk evaluation index threshold of each target tower crane corresponding to the environmental influence characteristic index interval of each target tower crane is extracted from the tower crane database, the work abnormal risk evaluation index of each target tower crane is compared with the work abnormal risk evaluation index threshold of each target tower crane, if the work abnormal risk evaluation index of each target tower crane is lower than or equal to the work abnormal risk evaluation index threshold of each target tower crane, the risk evaluation of the target tower crane is marked as qualified, if the work abnormal risk evaluation index of each target tower crane is higher than the work abnormal risk evaluation index threshold of each target tower crane, the risk evaluation of the target tower crane is marked as unqualified, and the target tower crane that is unqualified is warned.

[0017] As a further method, the operation abnormal evaluation index of each target tower crane is quantitative evaluation data obtained by comprehensive analysis of the working amplitude, amplitude speed and rotating speed of each target tower crane at each time monitoring point, which is used to quantitatively evaluate the abnormality degree of the tower crane during operation, and provides a basis for evaluating the risk of tower crane work abnormality.

[0018] As a further method, the environmental influence characteristic index of each target tower crane has the following specific numerical expression:

[0019] ;

[0020] In the formula, E(n) represents the environmental influence characteristic index of the nth target tower crane, e represents a natural constant, E(n) represents the environmental influence characteristic index of the nth target tower crane, e represents a natural constant, E(n) represents the environmental influence characteristic index of the nth target tower crane, e represents a natural constant, represent an environment impact characteristic factor corresponding to a preset target tower crane working environment characteristic value, represent an environment impact characteristic factor corresponding to a preset target tower crane network environment characteristic value.

[0021] As a further method, the working abnormal risk assessment index of each target tower crane has a specific numerical expression as follows:

[0022] ;

[0023] In the formula, represent the working abnormal risk assessment index of the nth target tower crane, represent the operation abnormality assessment index of the nth target tower crane, represent the fault risk assessment index of the nth target tower crane, represent a tower crane working abnormal risk impact factor corresponding to a preset operation abnormality assessment index, represent a tower crane working abnormal risk impact factor corresponding to a preset fault risk assessment index.

[0024] The second aspect of the present application provides a tower crane intelligent remote early warning system, comprising: a tower crane environment data acquisition and analysis module, which is used to acquire target tower cranes in a target building area, mark each target tower crane, collect working environment data and regional network environment of each target tower crane, and comprehensively analyze to obtain environment impact characteristic indexes of each target tower crane.

[0025] A tower crane working data acquisition and analysis module is used to collect working condition data and system performance data of each target tower crane, analyze the working condition data to obtain operation abnormality assessment indexes of each target tower crane, analyze the system performance data to obtain fault risk assessment indexes of each target tower crane, and comprehensively analyze to obtain working abnormal risk assessment indexes of each target tower crane.

[0026] A tower crane risk assessment and early warning module is used to perform risk assessment on each target tower crane according to the working abnormal risk assessment indexes and the environment impact characteristic indexes of each target tower crane, obtain an assessment result, and perform early warning.

[0027] Compared with the prior art, the embodiments of the present application have at least the following advantages or beneficial effects:

[0028] (1) The present application provides a tower crane intelligent remote early warning method and system, comprehensively analyzes the operation abnormality and fault risk of the tower crane, and performs working abnormal risk assessment on the tower crane, which can help to develop a more accurate maintenance plan, avoid over-maintenance or insufficient maintenance, and is beneficial to improve the maintenance efficiency and effect. It can also reduce downtime caused by faults, ensure continuous operation of the tower crane, and is beneficial to improve the operation efficiency and reduce the construction cost.

[0029] (2) The present application can timely discover potential safety hazards, such as abnormal hydraulic station pressure, reducer temperature, etc., through real-time monitoring of tower crane operation abnormalities, thereby providing early warning and avoiding safety accidents. By periodically evaluating the fault risk of the tower crane, the 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.

[0030] (3) The present application can comprehensively evaluate the influence of external environment on the tower crane operation by comprehensively considering the tower crane working environment characteristic value and the network environment characteristic value, and can timely discover and eliminate safety hazards, thereby improving the safety of the tower crane operation. According to the evaluation results, the design scheme 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 influence of external environment on the operation of the tower crane, the downtime caused by environmental factors can be reduced, and the construction efficiency and quality can be improved. BRIEF DESCRIPTION OF DRAWINGS

[0031] The present application will be further described with reference to the accompanying drawings, but the embodiments in the drawings do not constitute any limitation on the present application. For ordinary skilled persons in the art, other drawings can be obtained without creative labor on the basis of the following drawings.

[0032] Figure 1 The present application is a method flowchart.

[0033] Figure 2 The present application is a system module connection diagram.

[0034] Figure 3 The present application is a function relationship diagram between the fault risk evaluation index of the target tower crane and the working abnormal risk evaluation index of the target tower crane. DETAILED DESCRIPTION

[0035] The technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary skilled persons in the art without creative labor are within the scope of protection of the present application.

[0036] Referring to Figure 1 The first aspect of the present application provides a tower crane intelligent remote early warning method, comprising: acquiring target tower cranes in a target building area, marking each target tower crane, collecting working environment data of each target tower crane and regional network environment of each target tower crane, and comprehensively analyzing to obtain environmental influence characteristic index of each target tower crane.

[0037] Specifically, the environmental influence characteristic index of each target tower crane is obtained through comprehensive analysis, and the specific analysis process is as follows: a plurality of environmental monitoring points and time monitoring points are arranged in the working area of the tower crane, the working environment data of each target tower crane in a preset working period is 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.

[0038] It should be understood that the working environment characteristic value of each target tower crane is quantitative evaluation data obtained through 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 is used to quantitatively evaluate the influence of the working environment of the tower crane on the operation of the tower crane.

[0039] In a specific embodiment, the numerical expression of the working environment characteristic value of each target tower crane is:

[0040] ;

[0041] In the formula, n represents the number of each target tower crane, m represents the total number of target tower cranes, and i represents the number of each time monitoring point, t represents the total number of time monitoring points, and r represents the number of each environmental monitoring point, h represents the total number of environmental monitoring points, Vn,i represents the tower top wind speed of the nth target tower crane at the ith time monitoring point, Snr represents the slope of the nth target tower crane at the rth environmental monitoring point, Vc represents the critical tower top wind speed, f represents the working environment characteristic influence factor of the target tower crane corresponding to the preset tower top wind speed, g represents the working environment characteristic influence factor of the target tower crane corresponding to the preset slope.

[0042] It should be understood that in this embodiment, when the slope change value is larger and the tower top wind speed is larger during the operation of the tower crane, the working environment characteristic value of the corresponding target tower crane is also larger, indicating that the degree of interference of the working environment on the tower crane is larger.

[0043] It should be explained that in this embodiment, The working environment characteristic influence factor of the target tower corresponding to the preset slope is a numerical value representing the influence degree of the slope on the working environment of the tower. When used, the working environment characteristic influence factor of the target tower corresponding to the slope can be directly obtained from the tower database. The corresponding relationship can be a pre-set mapping relationship. For example, the slope of the environment monitoring point and the working environment characteristic influence factor of the target tower corresponding to the slope pre-set in the tower database form a mapping set. The slope of the real-time environment monitoring point is input into the mapping set to obtain the working environment characteristic influence factor of the target tower corresponding to the slope. The mapping relationship can be one-to-one or many-to-one.

[0044] It should be explained that in the embodiment The working environment characteristic influence factor of the target tower corresponding to the preset slope is a numerical value representing the influence degree of the slope on the working environment of the tower. When used, the working environment characteristic influence factor of the target tower corresponding to the slope can be directly obtained from the tower database. The corresponding relationship can be a pre-set mapping relationship. For example, the slope of the environment monitoring point and the working environment characteristic influence factor of the target tower corresponding to the slope pre-set in the tower database form a mapping set. The slope of the real-time environment monitoring point is input into the mapping set to obtain the working environment characteristic influence factor of the target tower corresponding to the slope. The mapping relationship can be one-to-one or many-to-one. The above influence factors are extracted from the tower database and have a value range of 0 to 1.

[0045] It should be explained that in the embodiment the slope refers to the terrain slope, which is the steepness of the ground unit. The ratio of the vertical height to the horizontal distance of the slope surface is called the slope (or slope ratio), which is an important parameter for describing the terrain characteristics. Professional measuring tools such as total station and laser range finder can be used to measure the terrain around the tower foundation and directly obtain the slope data. The tower top wind speed is an important indicator for evaluating the safety of the tower working environment. A wind speed meter can be installed on the top of the tower to monitor the tower top wind speed in real time. This is the most direct and accurate way to obtain the data. The greater the slope, the greater the resistance and turbulence generated by the wind when passing through the terrain, which may affect the stability of the tower. Terrain with a large slope may require higher bearing capacity of the tower foundation, and appropriate foundation treatment measures need to be taken. Terrain with a large slope may increase the difficulty of tower installation and disassembly, and a more complex construction plan needs to be developed. The tower top wind speed is a key factor affecting the safety of the tower. Excessive wind speed may cause the tower to lose stability, overturn and other serious accidents. Excessive wind speed may affect the normal operation of the tower and reduce the construction efficiency. Comprehensive analysis of the slope and the tower top wind speed can make the evaluation of the tower working environment characteristic value more comprehensive.

[0046] The network environment characteristic value of each target tower crane is obtained by comprehensively analyzing the electromagnetic interference intensity and the network delay of each time monitoring point.

[0047] It should be understood that the network environment characteristic value of each target tower crane is quantitative evaluation data obtained by comprehensively analyzing the electromagnetic interference intensity and the network delay of each time monitoring point, and is used to quantitatively evaluate the influence of the network environment on the operation of the tower crane.

[0048] In a specific embodiment, the numerical expression of the network environment characteristic value of each target tower crane is:

[0049] ;

[0050] In the formula, denotes the network environment characteristic value of the nth target tower crane, denotes the electromagnetic interference intensity of the nth target tower crane at the ith time monitoring point, denotes the network delay of the nth target tower crane at the ith time monitoring point, denotes the critical electromagnetic interference intensity, denotes the critical network delay, denotes the network environment characteristic influence factor of the target tower crane corresponding to the preset electromagnetic interference intensity, denotes the network environment characteristic influence factor of the target tower crane corresponding to the preset network delay.

[0051] It should be understood that in this embodiment, when the electromagnetic interference intensity is greater and the network delay is greater, the network environment characteristic value of the corresponding target tower crane is greater, indicating that the degree of interference of the tower crane by the network environment is greater.

[0052] It should be explained that in this embodiment, is the network environment characteristic influence factor of the target tower crane corresponding to the preset electromagnetic interference intensity, which 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 influence factor of the target tower crane corresponding to the electromagnetic interference intensity can be directly obtained from the tower crane database. The corresponding relationship can be a pre-set mapping relationship, for example, the electromagnetic interference intensity of the time monitoring point and the network environment characteristic influence factor of the target tower crane corresponding to the preset electromagnetic interference intensity in the tower crane database form a mapping set. The electromagnetic interference intensity of the real-time time monitoring point is input into the mapping set to obtain the network environment characteristic influence factor of the target tower crane corresponding to the electromagnetic interference intensity. The mapping relationship can be one-to-one or many-to-one.

[0053] It should be explained that in this embodiment, The network environment characteristic influence factor of the target tower crane corresponding to the preset network delay represents a numerical value of the influence degree of the network delay on the network environment of the tower crane. When used, the network environment characteristic influence 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 of the time monitoring point and the network environment characteristic influence factor of the target tower crane corresponding to the preset network delay in the tower crane database form a mapping set. The network environment characteristic influence factor of the target tower crane corresponding to the network delay is obtained by inputting the real-time network delay of the time monitoring point into the mapping set. The mapping relationship can be one-to-one or many-to-one.

[0054] It should be explained that in the embodiment, professional electromagnetic field strength measuring instruments (such as electromagnetic radiation testers) can be used to conduct field measurement at the tower crane working site to directly obtain the data of electromagnetic interference intensity. Network performance testing tools (such as Ping, Traceroute, network delay testers, etc.) can be used to test the tower crane working network to obtain the data of network delay. These tools can measure the time of data packets in the network to evaluate the delay of the network. The performance indicators such as network traffic, packet loss rate, and delay can also be viewed through the monitoring interface or management software of network devices (such as switches, routers, etc.). Electromagnetic interference may interfere with the normal operation of network devices (such as switches, routers, etc.), causing device performance degradation, data packet loss or retransmission, etc. These problems will increase the burden of the network, which may indirectly cause the increase of network delay. Comprehensive analysis of electromagnetic interference intensity and network delay in the evaluation of tower crane working network environment can make the evaluation more accurate and comprehensive.

[0055] According to the working environment characteristic values and the network environment characteristic values of the target tower cranes, the environmental influence characteristic indexes of the target tower cranes are obtained by comprehensive analysis. The environmental influence characteristic indexes of the target tower cranes are used to quantitatively evaluate the influence degree of the external environment on the tower crane operation.

[0056] In a specific embodiment, the numerical expression of the environmental influence characteristic index of the target tower crane is:

[0057] ;

[0058] In the formula, e represents the natural constant, represents the environmental influence characteristic index of the nth target tower crane, represents the working environment characteristic value of the nth target tower crane, represents the network environment characteristic value of the nth target tower crane, represents the environmental influence characteristic factor corresponding to the preset working environment characteristic value of the target tower crane, represents the preset environmental impact characteristic factor corresponding to the network environment characteristic value of the target tower crane.

[0059] It should be understood that, in the embodiment, when the working environment characteristic value of the target tower crane is larger, the network environment characteristic value of the target tower crane is also larger, and 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.

[0060] It should be explained that, in the embodiment, is the preset environmental impact characteristic factor corresponding to the working environment characteristic value of the target tower crane, representing the proportion of the working environment characteristic value of the tower crane in the degree of influence of the external environment on the tower crane. In use, 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. The corresponding relationship can be a pre-set 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 preset tower crane in the tower crane database form a mapping set. The 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. The mapping relationship can be one-to-one or many-to-one.

[0061] It should be explained that, in the embodiment, is the preset environmental impact characteristic factor corresponding to the network environment characteristic value of the target tower crane, representing the proportion of the network environment characteristic value of the tower crane in the degree of influence of the external environment on the tower crane. In use, 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 preset tower crane in the tower crane database form a mapping set. The 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 impact factors are extracted from the tower crane database and have a value range of 0 to 1.

[0062] It should be explained that, in the embodiment, by comprehensively considering the tower crane working environment characteristic value and the network environment characteristic value, the influence of the external environment on the tower crane working can be comprehensively evaluated, and safety hazards can be discovered and eliminated in time, and the safety of the tower crane working can be improved. According to the evaluation result, the design scheme of the tower crane can be optimized and adjusted, such as improving the basic design, strengthening the windproof measures, optimizing the network layout, etc., so as to improve the adaptability and stability of the tower crane. At the same time, by reducing the influence of the external environment on the tower crane working, the downtime caused by environmental factors can be reduced, and the construction efficiency and quality can be improved.

[0063] The working condition data and the system performance data of each target tower crane are collected, the operation abnormality evaluation index of each target tower crane is obtained by analyzing the working condition data, the fault risk evaluation index of each target tower crane is obtained by analyzing the system performance data, and the working abnormality risk evaluation index of each target tower crane is obtained by comprehensive analysis.

[0064] Specifically, the operation abnormality evaluation index of each target tower crane is obtained by analyzing the working condition data, and the specific analysis process is as follows: the working condition data of each target tower crane includes the working amplitude, the amplitude speed and the slewing speed of each target tower crane at each time monitoring point, the maximum allowable working amplitude, the maximum allowable amplitude speed and the maximum allowable slewing speed are extracted from the tower crane database, and the operation abnormality evaluation index of each target tower crane is obtained by comprehensive analysis.

[0065] It should be understood that the operation abnormality evaluation index of each target tower crane is quantitative evaluation data obtained by comprehensive analysis of the working amplitude, the amplitude speed and the slewing speed of each target tower crane at each time monitoring point, which is used to quantitatively evaluate the abnormality degree of the tower crane operation and provide a basis for evaluating the working abnormality risk of the tower crane.

[0066] In one specific embodiment, the numerical expression of the operation abnormality evaluation index of each target tower crane is as follows:

[0067] ;

[0068] In the formula, represents the operation abnormality evaluation index of the nth target tower crane, represents the working amplitude over-limit value of the nth target tower crane at the ith time monitoring point, , represents the working amplitude of the nth target tower crane at the ith time monitoring point, represents the amplitude speed over-limit value of the nth target tower crane at the ith time monitoring point, , represents the amplitude speed of the nth target tower crane at the ith time monitoring point, represents the slewing speed over-limit value of the nth target tower crane at the ith time monitoring point, , represents the slewing speed of the nth target tower crane at the ith time monitoring point, represents the maximum allowable working amplitude, represents the maximum allowable amplitude speed, represents the maximum allowable slewing speed, represents the tower crane operation abnormality influence factor corresponding to the preset working amplitude, represents the tower crane operation abnormality influence factor corresponding to the preset amplitude speed, The tower crane operation abnormality influence factor corresponding to the preset swing speed is represented.

[0069] It should be understood that, in the embodiment, the greater the deviation value between the working amplitude and the maximum allowable working amplitude, the greater the deviation value between the amplitude speed and the maximum allowable amplitude speed, and the greater the deviation value between the swing speed and the maximum allowable swing speed, the greater the tower crane operation abnormality evaluation index corresponding thereto, indicating that the greater the degree of abnormality in the operation of the tower crane, and when the deviation value between the working amplitude and the maximum allowable working amplitude, the deviation value between the amplitude speed and the maximum allowable amplitude speed, and the deviation value between the swing speed and the maximum allowable swing speed are all less than 0, the tower crane operation abnormality evaluation index corresponding thereto is equal to 0, indicating that no abnormality occurs in the operation of the tower crane.

[0070] It should be understood that, in the embodiment, the greater the deviation value between the working amplitude and the maximum allowable working amplitude, the greater the deviation value between the amplitude speed and the maximum allowable amplitude speed, and the greater the deviation value between the swing speed and the maximum allowable swing speed, the greater the tower crane operation abnormality evaluation index corresponding thereto, indicating that the greater the degree of abnormality in the operation of the tower crane, and when the deviation value between the working amplitude and the maximum allowable working amplitude, the deviation value between the amplitude speed and the maximum allowable amplitude speed, and the deviation value between the swing speed and the maximum allowable swing speed are all less than 0, the tower crane operation abnormality evaluation index corresponding thereto is equal to 0, indicating that no abnormality occurs in the operation of the tower crane. The tower crane operation abnormality influence factor corresponding to the preset working amplitude is represented, which is a numerical value indicating the influence degree of the working amplitude of the tower crane on the tower crane operation abnormality. In use, the tower crane operation abnormality influence factor corresponding to the working amplitude can be directly obtained from the tower crane database. 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 influence factor corresponding to the preset working amplitude of the tower crane in the tower crane database form a mapping set. The working amplitude corresponding to the tower crane operation abnormality influence factor is obtained by inputting the real-time working amplitude of the tower crane at the time monitoring point into the mapping set. The mapping relationship can be one-to-one or many-to-one.

[0071] It should be understood that, in the embodiment, the greater the deviation value between the working amplitude and the maximum allowable working amplitude, the greater the deviation value between the amplitude speed and the maximum allowable amplitude speed, and the greater the deviation value between the swing speed and the maximum allowable swing speed, the greater the tower crane operation abnormality evaluation index corresponding thereto, indicating that the greater the degree of abnormality in the operation of the tower crane, and when the deviation value between the working amplitude and the maximum allowable working amplitude, the deviation value between the amplitude speed and the maximum allowable amplitude speed, and the deviation value between the swing speed and the maximum allowable swing speed are all less than 0, the tower crane operation abnormality evaluation index corresponding thereto is equal to 0, indicating that no abnormality occurs in the operation of the tower crane. The tower crane operation abnormality influence factor corresponding to the preset amplitude speed is represented, which is a numerical value indicating the influence degree of the amplitude speed of the tower crane on the tower crane operation abnormality. In use, the tower crane operation abnormality influence factor corresponding to the amplitude speed can be directly obtained from the tower crane database. The corresponding relationship can be a preset mapping relationship. For example, the amplitude speed of the tower crane at the time monitoring point and the tower crane operation abnormality influence factor corresponding to the preset amplitude speed of the tower crane in the tower crane database form a mapping set. The amplitude speed corresponding to the tower crane operation abnormality influence factor is obtained by inputting the real-time amplitude speed of the tower crane at the time monitoring point into the mapping set. The mapping relationship can be one-to-one or many-to-one.

[0072] It should be understood that, in the embodiment, the greater the deviation value between the working amplitude and the maximum allowable working amplitude, the greater the deviation value between the amplitude speed and the maximum allowable amplitude speed, and the greater the deviation value between the swing speed and the maximum allowable swing speed, the greater the tower crane operation abnormality evaluation index corresponding thereto, indicating that the greater the degree of abnormality in the operation of the tower crane, and when the deviation value between the working amplitude and the maximum allowable working amplitude, the deviation value between the amplitude speed and the maximum allowable amplitude speed, and the deviation value between the swing speed and the maximum allowable swing speed are all less than 0, the tower crane operation abnormality evaluation index corresponding thereto is equal to 0, indicating that no abnormality occurs in the operation of the tower crane. The tower crane operation abnormality influence factor corresponding to the preset slewing speed represents the numerical value of the influence degree of the slewing speed of the tower crane on the tower crane operation abnormality. When used, the tower crane operation abnormality influence factor corresponding to the slewing speed can be directly obtained from the tower crane database. The corresponding relationship can be a preset mapping relationship. For example, the slewing speed of the tower crane at the time monitoring point and the tower crane operation abnormality influence factor corresponding to the preset tower crane slewing speed in the tower crane database form a mapping set. The slewing speed of 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 slewing speed. The mapping relationship can be one-to-one or many-to-one.

[0073] It needs to 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 amplitude, amplitude speed and slewing speed. The working amplitude, also known as the working radius, is the horizontal distance from the center point to the end of the maximum cantilever of the tower crane, usually measured in meters. This parameter determines the effective working range of the tower crane. The size of the working amplitude directly affects the construction area that the tower crane can cover and is one of the important measures of the lifting capacity of the tower crane. The amplitude speed refers to the speed at which the hook on the main arm of the tower crane moves horizontally, usually measured in meters per minute. This speed determines the efficiency of the tower crane when changing the working amplitude. A fast amplitude speed can speed up the hoisting operation and improve the construction efficiency. However, the amplitude speed is also limited by factors such as tower crane structure and load, and needs to be adjusted according to specific conditions in actual operation. The slewing speed refers to the speed at which the entire tower crane rotates on the horizontal plane, usually measured in degrees per second or revolutions per minute (rpm). This speed determines the flexibility of the tower crane when covering a wider construction range. A fast slewing speed helps the tower crane quickly move the load from one location to another, improving construction efficiency. At the same time, the stability of the slewing speed is also very important to ensure the stability and safety of the load during rotation. The working amplitude, amplitude speed and slewing speed are interrelated. The size of the working amplitude will limit the range of amplitude and slewing, while the speed of the amplitude speed and the slewing speed will affect the working efficiency of the tower crane at different working amplitudes. The working amplitude, amplitude speed and slewing speed of the tower crane need to work together to achieve efficient hoisting operations.

[0074] It needs to 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 may cause structural fatigue, fracture and other failures in the long run. The 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. The excessive amplitude changing speed will generate a large inertial force, which will impact the structure of the tower crane and the load, and may cause structural damage or loss of control of the load. During high-speed amplitude changing, the control accuracy may decrease, resulting in inaccurate positioning or excessive swinging of the load. The high-speed rotation may cause uneven stress on the structure of the tower crane, increasing the stress concentration and fatigue damage of the structure. High-speed rotation will increase the difficulty of operation, requiring the operator to have higher skills and reaction speed. Once the operation is failed, it may cause loss of control of the load or collision accident. The lack of coordination between working amplitude, amplitude changing 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 changing, the tower crane may not be able to maintain stable and accurate control. The abnormality of the above parameters may cause the safety performance of the tower crane to decrease, increasing the risk of accidents. Comprehensive analysis of the above parameters can make the evaluation of the abnormal operation of the tower crane more comprehensive and accurate.

[0075] Further, the system performance data is analyzed to obtain the fault risk evaluation index of each target tower crane, and the specific analysis process is: the system performance data of each target tower crane includes the hydraulic station pressure and the reducer temperature of each target tower crane at each time monitoring point, the reference standard hydraulic station pressure and the allowable deviation hydraulic station pressure and the critical reducer temperature are extracted from the tower crane database, and the fault risk evaluation index of each target tower crane is obtained by comprehensive analysis.

[0076] It should be understood that the fault risk evaluation index of each target tower crane is a quantitative evaluation data obtained by comprehensive analysis of the hydraulic station pressure and the reducer temperature of each target tower crane at each time monitoring point, which is used to quantitatively evaluate the risk degree of the tower crane system failure during work, and provides a basis for evaluating the abnormal risk of the tower crane.

[0077] In a specific embodiment, the numerical expression of the fault risk evaluation index of each target tower crane is:

[0078] ;

[0079] In the formula, represents the fault risk evaluation index of the nth target tower crane, represents the hydraulic station pressure of the nth target tower crane at the ith time monitoring point, represents the reducer temperature of the nth target tower crane at the ith time monitoring point, represents the reference standard hydraulic station pressure, represents the allowable deviation hydraulic station pressure, represents a critical retarder temperature, represents a preset hydraulic station pressure corresponding tower machine failure risk impact factor, represents a preset retarder temperature corresponding tower machine failure risk impact factor.

[0080] It should be understood that when the deviation value between the hydraulic station pressure and the reference standard hydraulic station pressure is greater, and the retarder temperature is also greater, the failure risk assessment index of the corresponding tower machine is greater, indicating that the risk degree of failure of the tower machine is greater.

[0081] It should be explained that in the embodiment is a preset hydraulic station pressure corresponding tower machine failure risk impact factor, which represents the numerical value of the influence degree of the tower machine hydraulic station pressure on the risk of failure of the tower machine. When used, the hydraulic station pressure corresponding tower machine failure risk impact factor can be directly obtained from the tower machine database. The corresponding relationship can be a pre-set mapping relationship. For example, the hydraulic station pressure of the tower machine at the time monitoring point and the tower machine hydraulic station pressure corresponding tower machine failure risk impact factor in the tower machine database form a mapping set. The hydraulic station pressure corresponding tower machine failure risk impact factor is obtained by inputting the real-time hydraulic station pressure of the tower machine at the time monitoring point into the mapping set. The mapping relationship therein can be one-to-one or many-to-one.

[0082] It should be explained that in the embodiment is a preset retarder temperature corresponding tower machine failure risk impact factor, which represents the numerical value of the influence degree of the tower machine retarder temperature on the risk of failure of the tower machine. When used, the retarder temperature corresponding tower machine failure risk impact factor can be directly obtained from the tower machine database. The corresponding relationship can be a pre-set mapping relationship. For example, the retarder temperature of the tower machine at the time monitoring point and the tower machine retarder temperature corresponding tower machine failure risk impact factor in the tower machine database form a mapping set. The retarder temperature corresponding tower machine failure risk impact factor is obtained by inputting the real-time retarder temperature of the tower machine at the time monitoring point into the mapping set. The mapping relationship therein can be one-to-one or many-to-one. The above impact factors are extracted from the tower machine database and the value range is between 0 and 1.

[0083] In a specific embodiment, there is 1 time monitoring point data, calculated according to t=1.

[0084] Table 1 Data example of failure risk assessment index of each target tower machine

[0085]

[0086] It needs to be explained that in this embodiment, the standard hydraulic station pressure is set to 150 psi, the allowable deviation hydraulic station pressure is set to 50 psi, the critical reducer temperature is set to 90 , the tower crane failure risk influence factor corresponding to the hydraulic station pressure is set to 0.6, and the tower crane failure risk influence factor corresponding to the reducer temperature is set to 0.4.

[0087] It needs to be explained that in this embodiment, the hydraulic station pressure is one of the key parameters for the normal operation of the tower crane hydraulic system. The tower crane hydraulic station usually has pressure gauges installed directly in key positions of the hydraulic system for real-time monitoring and display of the pressure of the hydraulic system. The hydraulic station pressure directly affects the flowability 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 bear excessive pressure, thereby increasing the risk of wear and failure. At the same time, excessive pressure may also cause the temperature of the hydraulic oil to rise, thereby affecting the temperature of the reducer. Conversely, 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 a decrease in 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 the internal gears and other components of the reducer to be subjected to uneven forces, 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 a 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 lubricating oil failure and seal aging, thereby affecting the normal operation of the hydraulic station and other system components. Although the reducer temperature does not directly determine the hydraulic station pressure, excessive temperature may cause problems such as reduced lubricating oil viscosity and increased system friction, thereby indirectly affecting the stability and accuracy of the hydraulic station pressure. 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 interaction 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 the change in the reducer temperature may indirectly affect the hydraulic station pressure through the influence on system heat dissipation and lubricating oil performance. Comprehensive analysis of these two parameters can make the system performance evaluation of the tower crane more comprehensive.

[0088] Specifically, the working abnormal risk evaluation index of each target tower crane is obtained through comprehensive analysis, and the specific analysis process is as follows: according to the operation abnormal evaluation index of each target tower crane and the fault risk evaluation index of each target tower crane, the working abnormal risk evaluation index of each target tower crane is obtained through comprehensive analysis, and the working abnormal risk evaluation index of each target tower crane is used to quantitatively evaluate the risk degree of the working abnormality of each target tower crane.

[0089] In a specific embodiment, the numerical expression of the working abnormal risk evaluation index of each target tower crane is as follows:

[0090] ;

[0091] In the formula, represents the working abnormal risk evaluation index of the nth target tower crane, represents the operation abnormal evaluation index of the nth target tower crane, represents the fault risk evaluation index of the nth target tower crane, represents the tower crane working abnormal risk impact factor corresponding to the preset operation abnormal evaluation index, represents the tower crane working abnormal risk impact factor corresponding to the preset fault risk evaluation index.

[0092] It should be understood that in the embodiment, when the operation abnormal evaluation index of the target tower crane is larger, the fault risk evaluation index of the target tower crane is also larger, and the working abnormal risk evaluation index of the corresponding target tower crane is also larger, indicating that the working abnormal risk degree of the tower crane is larger and the working abnormality is more likely to occur.

[0093] It should be explained that in the embodiment, is the tower crane working abnormal risk impact factor corresponding to the preset operation abnormal evaluation index, which represents the numerical value of the influence degree of the tower crane operation abnormal evaluation index on the tower crane working abnormal risk, and when used, the tower crane working abnormal risk impact factor corresponding to the operation abnormal evaluation index can be directly obtained from the tower crane database. The corresponding relationship can be a pre-set mapping relationship, for example, the operation abnormal evaluation index of the target tower crane and the tower crane working abnormal risk impact factor corresponding to the preset operation abnormal evaluation index of the tower crane in the tower crane database form a mapping set. The operation abnormal evaluation index of the real-time target tower crane is input into the mapping set to obtain the tower crane working abnormal risk impact factor corresponding to the operation abnormal evaluation index, and the mapping relationship can be one-to-one or a many-to-one relationship.

[0094] It should be explained that in the embodiment, This refers to the tower crane operation anomaly risk impact factor corresponding to the preset fault risk assessment index. It represents the numerical value of the tower crane fault risk assessment index's influence on the risk of tower crane operation anomalies. When using this feature, the tower crane operation anomaly risk impact factor corresponding to the fault risk assessment index can be directly obtained from the tower crane database. The correspondence can be a pre-defined mapping relationship. For example, the fault risk assessment index of the target tower crane and the preset tower crane operation anomaly risk impact factors corresponding to the fault risk assessment index in the tower crane database form a mapping set. Inputting the real-time fault risk assessment index of the target tower crane into this mapping set yields the tower crane operation anomaly risk impact factor corresponding to the fault risk assessment index. The mapping relationship can be one-to-one or many-to-one. All of the above impact factors are extracted from the tower crane database and their values ​​range from 0 to 1.

[0095] It should be understood that, by Figure 3 As shown, curve a represents the relationship between the target tower crane's fault risk assessment index and its operational anomaly risk assessment index when the target tower crane's operational anomaly assessment index is 1.03; curve b represents the relationship between the target tower crane's fault risk assessment index and its operational anomaly risk assessment index when the target tower crane's operational anomaly assessment index is 1.42; and curve c represents the relationship between the target tower crane's fault risk assessment index and its operational anomaly risk assessment index when the target tower crane's operational anomaly assessment index is 1.83.

[0096] It should be noted that in this embodiment, the tower crane operation anomaly risk impact factor corresponding to the operation anomaly assessment index is set to 0.5, and the tower crane operation anomaly risk impact factor corresponding to the fault risk assessment index is set to 0.3.

[0097] It needs to be explained that in this embodiment, through real-time monitoring of the abnormal operation of the tower crane, potential safety hazards such as abnormal pressure of the hydraulic station, excessive temperature of the reducer, etc. can be found in time, so as to give early warning and avoid the occurrence of safety accidents. By periodically evaluating the fault risk of the tower crane, the vulnerable parts and potential fault 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, and the safety of the construction site is ensured. In this embodiment, based on the operation abnormality evaluation index and the fault risk evaluation index, a more accurate maintenance plan can be developed to avoid over-maintenance or insufficient maintenance, and the maintenance efficiency and effect can be improved. The downtime caused by failure can also be reduced, the continuous operation of the tower crane can be ensured, the work efficiency can be improved, and the construction cost can be reduced. At the same time, the evaluation index and the risk evaluation result provide rich data support for the management of the tower crane, which helps the managers to make more scientific management decisions and optimize resource allocation. Through the feedback of the evaluation result, the industrial upgrading of the entire tower crane industry is promoted, and the overall technical level and market competitiveness of the industry are improved.

[0098] According to the working abnormality risk evaluation index and the environmental influence characteristic index of each target tower crane, the risk of each target tower crane is evaluated, and an evaluation result is obtained and a warning is given.

[0099] Specifically, according to the working abnormality risk evaluation index and the environmental influence characteristic index of each target tower crane, the risk of each target tower crane is evaluated, and the specific evaluation process is as follows: the working abnormality risk evaluation index threshold of each target tower crane corresponding to the environmental influence characteristic index interval of each target tower crane is extracted from the tower crane database, the working abnormality risk evaluation index of each target tower crane is compared with the working abnormality risk evaluation index threshold of each target tower crane, if the working abnormality risk evaluation index of each target tower crane is lower than or equal to the working abnormality risk evaluation index threshold of each target tower crane, the risk evaluation of the target tower crane is marked as qualified, if the working abnormality risk evaluation index of each target tower crane is higher than the working abnormality risk evaluation index threshold of each target tower crane, the risk evaluation of the target tower crane is marked as unqualified, and the unqualified target tower crane is warned.

[0100] Further, the process of warning the unqualified target tower crane is as follows: for the target tower crane whose risk evaluation is marked as unqualified, the system automatically triggers the warning mechanism, sends warning information to relevant personnel (such as operators, maintenance personnel, safety supervisors) through email, short message, system notification, etc. And generate a detailed report containing abnormal details, risk evaluation results, suggested measures, etc. so that relevant personnel can quickly understand the problem and take appropriate handling measures. After receiving the warning, the relevant personnel need to immediately check and maintain the target tower crane to ensure that the problem is solved in time and prevent potential risks from turning into actual accidents.

[0101] In a specific embodiment, the tower crane database is used to store data related to the tower crane operation abnormal risk assessment process, including the maximum allowed working amplitude, the maximum allowed amplitude speed and the maximum allowed rotation speed, the network environment characteristic influence factor of the target tower crane corresponding to the electromagnetic interference intensity, the network environment characteristic influence factor of the target tower crane corresponding to the network delay, and the working abnormal risk assessment index threshold of each target tower crane corresponding to the environmental influence characteristic index interval of each target tower crane, and the data extracted in the above embodiments. The data in the tower crane database can be obtained by various sensors equipped in modern tower cranes for real-time monitoring of the operating state and environmental parameters of the tower crane. These data can be transmitted to the database in real time through Internet of Things technology. In this case, the data acquisition is automatic, real-time, and can be customized and developed as needed.

[0102] Referring to Figure 2 The second aspect of the present application provides a tower crane intelligent remote early warning system, comprising: a tower crane environment data acquisition and analysis module for acquiring target tower cranes in a target building area, labeled as each target tower crane, collecting working environment data and regional network environment of each target tower crane, and comprehensively analyzing to obtain an environmental influence characteristic index of each target tower crane.

[0103] A tower crane working data acquisition and analysis module is used to collect working condition data and system performance data of each target tower crane, analyze the working condition data to obtain an operation abnormality assessment index of each target tower crane, analyze the system performance data to obtain a fault risk assessment index of each target tower crane, and comprehensively analyze to obtain a working abnormal risk assessment index of each target tower crane.

[0104] A tower crane risk assessment and early warning module is used to assess the risk of each target tower crane according to the working abnormal risk assessment index and the environmental influence characteristic index of each target tower crane, obtain an assessment result and perform early warning.

[0105] The above content is only an example and description of the structure of the present application. Those skilled in the art can make various modifications or supplements or use similar ways to replace the described specific embodiments, as long as they do not deviate from the structure of the present application or exceed the scope defined by the present claims, and they should belong to the protection scope of the present application.

Claims

1. A method for intelligent remote early warning of tower cranes, characterized in that, include: Identify the 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 them to obtain the environmental impact characteristic index of each target tower crane. Collect the operating status data and system performance data of each target tower crane, analyze the operating status data to obtain the operation anomaly 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 operation anomaly risk assessment index of each target tower crane. Risk assessments are conducted on each target tower crane based on its operational anomaly risk assessment indicators and environmental impact characteristic indices, and assessment results are obtained and early warnings are issued. The analysis of the working status data yields the operational anomaly assessment index for each target tower crane. The specific analysis process is as follows: The working status data of each target tower crane includes the working amplitude, luffing speed and slewing speed of each target tower crane at each time monitoring point. The maximum allowable working amplitude, maximum allowable luffing speed and maximum allowable slewing speed are extracted from the tower crane database. The comprehensive analysis yields the operational anomaly assessment index of each target tower crane. The analysis of system performance data yields the failure risk assessment index for each target tower crane. The specific analysis process is as follows: The system performance data of each target tower crane includes the hydraulic station pressure and reducer temperature of each target tower crane at each time monitoring point. The reference standard hydraulic station pressure, allowable deviation hydraulic station pressure, and critical reducer temperature are extracted from the tower crane database. The failure risk assessment index of each target tower crane is obtained through comprehensive analysis. The comprehensive analysis yielded operational anomaly risk assessment indicators for each target tower crane. The specific analysis process is as follows: Based on the operational anomaly assessment index and the fault risk assessment index of each target tower crane, a comprehensive analysis is conducted to obtain the operational anomaly risk assessment index of each target tower crane. The operational anomaly risk assessment index of each target tower crane is used to quantitatively assess the risk level of operational anomalies of each target tower crane. The system extracts the threshold values ​​of the work anomaly risk assessment indicators for each target tower crane from the tower crane database, corresponding to the environmental impact characteristic index range. It then compares the work anomaly risk assessment indicators of each target tower crane with the threshold values. If the work anomaly risk assessment indicators of each target tower crane are higher than the threshold values, the risk assessment of that target tower crane is marked as unqualified. For target tower cranes marked as unqualified in risk assessment, the system automatically triggers an early warning mechanism, sends an early warning message, and generates a detailed anomaly report. The comprehensive analysis yielded the environmental impact characteristic index for 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 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. 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. The critical electromagnetic interference intensity and critical network delay are extracted from the tower crane database, and the network environment characteristic values ​​of each target tower crane are obtained through comprehensive analysis. Based on the working environment characteristics and network environment characteristics of each target tower crane, a comprehensive analysis is conducted to obtain the environmental impact characteristic index of each target tower crane. The environmental impact characteristic index of each target tower crane is used to quantitatively assess the degree of influence of the external environment on the operation of the tower crane.

2. The intelligent remote early warning method for tower cranes according to claim 1, characterized in that: The risk assessment of each target tower crane is conducted based on the operational anomaly risk assessment index and environmental impact characteristic index. The specific assessment process is as follows: The threshold values ​​of the work anomaly risk assessment indicators for each target tower crane are extracted from the tower crane database, corresponding to the environmental impact characteristic index ranges of each target tower crane. The work anomaly risk assessment indicators of each target tower crane are compared with the threshold values. If the work anomaly risk assessment indicators of each target tower crane are lower than or equal to the threshold values, the risk assessment of that target tower crane is marked as qualified. If the work anomaly risk assessment indicators of each target tower crane are higher than the threshold values, the risk assessment of that target tower crane is marked as unqualified, and an early warning is issued for the unqualified target tower cranes.

3. The intelligent remote early warning method for tower cranes according to claim 1, characterized in that: The operational anomaly assessment index for each target tower crane is a quantitative assessment data obtained by comprehensively analyzing the working amplitude, luffing speed, and slewing speed of each target tower crane at each time monitoring point. It is used to quantitatively assess the degree of anomaly during tower crane operation and to provide a basis for assessing the risk of tower crane operational anomalies.

4. The intelligent remote early warning method for tower cranes according to claim 1, characterized in that: The specific numerical expression for the environmental impact characteristic index of each target tower crane is as follows: ； In the formula, This represents the environmental impact characteristic index of the nth target tower crane, where e represents the natural constant. This represents the working environment characteristic value of the nth target tower crane. This represents the network environment characteristic value of the nth target tower crane. This represents the environmental impact characteristic factor corresponding to the preset target tower crane's working environment characteristic values. This represents the environmental impact characteristic factor corresponding to the preset network environment characteristic value of the target tower crane.

5. The intelligent remote early warning method for tower cranes according to claim 1, characterized in that: The specific numerical expressions for the operational anomaly risk assessment indicators of each target tower crane are as follows: ； In the formula, This represents the operational anomaly risk assessment index for the nth target tower crane. This represents the operational anomaly assessment index of the nth target tower crane. This represents the failure risk assessment index of the nth target tower crane. This represents the risk impact factor of tower crane malfunction corresponding to the preset malfunction assessment index. This indicates the tower crane operation abnormality risk impact factor corresponding to the preset fault risk assessment index.

6. A tower crane intelligent remote early warning system applying the tower crane intelligent remote early warning method as described in any one of claims 1-5, characterized in that: include: The tower crane environmental data acquisition and analysis module is used to acquire 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 them to obtain the environmental impact characteristic index of each target tower crane. The tower crane operation data acquisition and analysis module is used to collect the operation status data and system performance data of each target tower crane, analyze the operation status data to obtain the operation anomaly 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 operation anomaly risk assessment index of each target tower crane. The tower crane risk assessment and early warning module is used to conduct risk assessments on each target tower crane based on the abnormal operation risk assessment indicators and environmental impact characteristic indices, obtain assessment results, and issue early warnings.

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