Safety monitoring and early warning system for infrastructure line operation

Abstract

The invention relates to the technical field of infrastructure line safety monitoring, and particularly discloses an infrastructure line operation safety monitoring and early warning system which is provided with a sensor deployment module, a data transmission module, a geographical environment analysis module, a safety monitoring threshold matching module, a state data analysis module and an infrastructure line operation risk judgment module. According to the method, the problems of insufficient dynamic response capability, insufficient adaptive capability and incomplete considered factors of traditional infrastructure line operation safety monitoring are solved. The comprehensive data of an infrastructure line operation site can be obtained, and the transmission reliability can be enhanced. And personalized risk assessment of the infrastructure line operation site can be obtained. Various types of data are analyzed, and potential safety hazards hidden behind the data can be mined. And the risk is early warned in time, so that accidents are effectively avoided or reduced, the life safety and body health of operators are protected, and meanwhile, equipment damage and loss are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of infrastructure line safety monitoring, and in particular to an infrastructure line operation safety monitoring and early warning system. Background Art

[0002] In recent years, investment in infrastructure construction has continued to increase worldwide. The scale of infrastructure investment in the fields of transportation, energy, etc. is huge. However, infrastructure line operations usually face complex construction environments and high-risk operation links. When constructing power transmission lines in mountainous areas, construction workers need to assemble towers and string lines on steep slopes in the mountains, facing multiple safety risks such as falling and being hit by objects; when constructing rail transit lines in cities, underground excavation operations may encounter problems such as complex underground pipelines and unstable geological conditions, which can easily cause collapse accidents.

[0003] With the rapid development of sensor technology, communication technology, data analysis technology, etc., technical support has been provided for the safety monitoring and early warning of infrastructure line operations. Communication technology enables data to be transmitted quickly and stably. The low latency and high bandwidth characteristics of 5G networks allow monitoring data to be transmitted to the monitoring center in real time, facilitating timely analysis and processing. Data analysis technologies, such as machine learning and data mining, can conduct in-depth analysis of large amounts of monitoring data and establish a safety risk prediction model.

[0004] Nowadays, there are still some shortcomings in the research on safety monitoring and early warning of infrastructure line operations, which are specifically reflected in the fact that traditional infrastructure line operation safety monitoring has insufficient dynamic response capabilities, insufficient adaptability, and insufficient consideration of factors. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a infrastructure line operation safety monitoring and early warning system, which can effectively solve the problems involved in the above-mentioned background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a safety monitoring and early warning system for infrastructure line operations, including a sensor deployment module, a data transmission module, a geographic environment analysis module, a safety monitoring threshold matching module, a status data analysis module and an infrastructure line operation risk judgment module, wherein: the sensor deployment module deploys data acquisition sensors at the infrastructure line operation site based on the sensor deployment plan stored in the database, and the data acquisition sensors include GPS sensors, temperature and humidity sensors, harmful gas sensors, equipment operation status sensors and video surveillance cameras; the data transmission module transmits the data collected by the data acquisition sensors to a data processing center in real time, and uses a data verification algorithm to determine whether the data needs to be retransmitted. The data received by the data processing center specifically includes infrastructure line operation environment status data, infrastructure line operation equipment status data, and infrastructure line operation personnel behavior data.

[0007] The geographical environment analysis module analyzes the geographical environment factors of the infrastructure line to obtain the geographical environment characteristic signal of the infrastructure line; the safety monitoring threshold matching module analyzes the basic characteristics of the infrastructure line, combines the geographical environment characteristic signal of the infrastructure line, obtains the infrastructure line operation characteristic factor, and matches the infrastructure line operation safety monitoring threshold; the status data analysis module analyzes the infrastructure line operation environment status data, the infrastructure line operation equipment status data, and the infrastructure line operation personnel behavior data to obtain the infrastructure line operation safety analysis factor; the infrastructure line operation risk judgment module judges whether there is a risk in the infrastructure line operation based on the infrastructure line operation safety analysis factor and the infrastructure line operation safety monitoring threshold, and issues an early warning for the infrastructure line operation with risk.

[0008] As a further solution, it is determined whether the data needs to be retransmitted. The specific analysis process includes: using a data verification algorithm, which is a cyclic redundancy check, to calculate the CRC check code of each data M transmitted: determine the generating polynomial G stored in the database; obtain the number of binary bits of the data M to be sent, recorded as n bits, and the number of binary bits of the generating polynomial G is r+1 bits, where r is the degree of the generating polynomial stored in the database; add r 0 bits after the data M to obtain new data M1, and divide the generating polynomial G by the data M1 using modulo 2 division, and the remainder is the remainder, that is, the CRC check code; attach the CRC check code of the data M to the end of the data M and send it together; the receiving end recalculates the CRC check code of the received data M, and compares it with the CRC check code of the received data M to determine whether the data needs to be retransmitted: if they are consistent, the data does not need to be retransmitted; if they are inconsistent, the data needs to be retransmitted, and the sending end is requested to resend the data.

[0009] As a further solution, the geographical environment factors of the infrastructure lines are analyzed to obtain the geographical environment characteristic signals of the infrastructure lines. The specific analysis process is: obtaining the geographical environment factor data of the infrastructure lines, the geographical environment factor data of the infrastructure lines specifically include the geographical environment rainfall of the infrastructure lines, the geographical environment rock hardness of the infrastructure lines, and the geographical environment river water level of the infrastructure lines; based on the obtained geographical environment factor data of the infrastructure lines, a comprehensive analysis is performed to obtain the geographical environment characteristic signals of the infrastructure lines, and the geographical environment characteristic signals of the infrastructure lines are used as the analysis basis for obtaining the infrastructure line operation characteristic factors.

[0010] As a further solution, the basic characteristics of the infrastructure lines are analyzed, and combined with the geographical environment characteristic signals of the infrastructure lines to obtain the infrastructure line operation characteristic factors. The specific analysis process is: obtaining the basic characteristic data of the infrastructure lines, the basic characteristic data of the infrastructure lines specifically include the inclination of the infrastructure line towers, the proportion of the corrosion area of ​​the infrastructure line towers, and the pollution flashover frequency of the infrastructure line insulators; based on the obtained basic characteristic data of the infrastructure lines, combined with the geographical environment characteristic signals of the infrastructure lines, a comprehensive analysis is performed to obtain the infrastructure line operation characteristic factors, and the infrastructure line operation characteristic factors are used as the analysis basis for matching the infrastructure line operation safety monitoring thresholds.

[0011] As a further solution, the characteristic factors of infrastructure line operation, the specific analysis process is as follows: ; In the formula, zyt is the characteristic factor of infrastructure line operation, dht is the characteristic signal of geographical environment of infrastructure line, qxd is the inclination of infrastructure line tower, gfs is the proportion of infrastructure line tower corrosion area, wsp is the pollution flashover frequency of infrastructure line insulator, is the compensation factor of the set qxd, is the compensation factor of the set gfs, is the compensation factor of the set wsp.

[0012] As a further solution, the infrastructure line operation safety monitoring threshold is matched. The specific analysis process is: the infrastructure line operation characteristic factor is stored as a specified label, the specified label is compared with each set label stored in the database, and the set label corresponding to the specified label is obtained, and the infrastructure line operation safety monitoring threshold corresponding to the set label stored in the database is obtained.

[0013] As a further solution, the infrastructure line operation environment status data, infrastructure line operation equipment status data, and infrastructure line operation personnel behavior data are analyzed to obtain the infrastructure line operation safety analysis factor. The specific analysis process is as follows: Analyze the infrastructure line operation environment status data: obtain the infrastructure line ambient temperature shw, infrastructure line ambient humidity shs, infrastructure line rated ambient temperature ehw, and infrastructure line rated ambient humidity ehs; comprehensively consider the infrastructure line ambient temperature, infrastructure line ambient humidity, infrastructure line rated ambient temperature, and infrastructure line rated ambient humidity to construct the environmental comfort index CI; ; In the formula, is the compensation factor of the set shw, is the compensation factor of the set shs; Obtain the carbon monoxide concentration CON and the sulfur dioxide concentration SO2N in the infrastructure line environment; comprehensively consider the carbon monoxide concentration and the sulfur dioxide concentration in the infrastructure line environment to construct the environmental harmful gas risk index HRI; ; In the formula, is the compensation factor of the set CON, is the compensation factor of the set SO2N; Analyze the status data of infrastructure line operation equipment: obtain the braking response time zxy of the infrastructure line crane and the operating power deviation rate qyg of the infrastructure line crane motor; comprehensively consider the braking response time zxy of the infrastructure line crane and the operating power deviation rate of the infrastructure line crane motor to construct the equipment failure prediction index GR; ; In the formula, is the compensation factor of the set zxy, is the compensation factor of the set qyg, and e is a natural constant; Analyze the behavior data of infrastructure line operators: obtain the normal wearing ratio of infrastructure line operators’ safety equipment cdb and the length of time that infrastructure line operators stay in dangerous areas wtl; comprehensively consider the normal wearing ratio of infrastructure line operators’ safety equipment and the length of time that infrastructure line operators stay in dangerous areas, and construct the operator behavior abnormality index XYB; ; In the formula, is the compensation factor of the set cdb, is the compensation factor of the set wtl; Obtain the body inclination angle sqx of the infrastructure line operator and the deviation rate of the chin and chest angle jjp of the infrastructure line operator; comprehensively consider the body inclination angle of the infrastructure line operator and the deviation rate of the chin and chest angle of the infrastructure line operator to construct the operator posture abnormality index ZTB; ; In the formula, is the compensation factor of the set sqx, is the compensation factor of the set jjp; Based on the environmental comfort index, environmental harmful gas risk index, equipment failure prediction index, operator behavior abnormality index and operator posture abnormality index, a comprehensive analysis is conducted to obtain the infrastructure line operation safety analysis factor.

[0014] As a further solution, the safety analysis factor of infrastructure line operation, the specific analysis process is as follows: ; In the formula, It is the safety analysis factor of infrastructure line operation. Factor analysis for the working environment status, is the operating equipment status analysis factor, Analyze factors for operators.

[0015] As a further solution, based on the infrastructure line operation safety analysis factor and combined with the infrastructure line operation safety monitoring threshold, it is judged whether there is a risk in the infrastructure line operation. The specific analysis process is: compare the infrastructure line operation safety analysis factor with the infrastructure line operation safety monitoring threshold; if the infrastructure line operation safety analysis factor is not lower than the infrastructure line operation safety monitoring threshold, then there is no risk in the infrastructure line operation; if the infrastructure line operation safety analysis factor is lower than the infrastructure line operation safety monitoring threshold, then there is a risk in the infrastructure line operation.

[0016] As a further solution, an early warning is issued for infrastructure line operations that are at risk. The specific analysis process is: if there is a risk in the infrastructure line operation, an early warning is issued for the infrastructure line operation that is at risk: the difference between the infrastructure line operation safety monitoring threshold and the infrastructure line operation safety analysis factor corresponding to the infrastructure line operation that is at risk is recorded as the infrastructure line operation safety deviation value; the infrastructure line operation safety deviation value is compared with the infrastructure line operation safety deviation warning value stored in the database; if the infrastructure line operation safety deviation value is not lower than the infrastructure line operation safety deviation warning value, a second-level early warning is issued for the infrastructure line operation that is at risk; if the infrastructure line operation safety deviation value is lower than the infrastructure line operation safety deviation warning value, a first-level early warning is issued for the infrastructure line operation that is at risk.

[0017] 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 a safety monitoring and early warning system for infrastructure line operations. By deploying various types of sensors, it is possible to obtain all-round data on the infrastructure line operation site. The combination of industrial Ethernet and 4G / 5G networks is used for data transmission, which can enhance the reliability of transmission while ensuring real-time data transmission. The use of data verification algorithms can effectively reduce the transmission of erroneous data.

[0018] (2) The present invention obtains geographical environment characteristic signals by analyzing the geographical environment factors of the infrastructure line, which is helpful for risk prevention. Different geographical environments will bring different risks to the infrastructure line operation. By analyzing the geographical environment characteristic signals, a personalized risk assessment of the infrastructure line operation site can be obtained. Analyzing various types of data can dig out the hidden safety hazards behind the data. Timely warning of risks can effectively avoid or reduce the occurrence of accidents, protect the life safety and physical health of operators, and reduce equipment damage and losses.

[0019] (3) The present invention obtains the infrastructure line operation characteristic factors by analyzing the basic characteristics of the infrastructure line, combined with the infrastructure line geographical environment characteristic signals, and matches the infrastructure line operation safety monitoring threshold. The basic characteristics and geographical environment of the infrastructure line are different. By comprehensively analyzing these factors to obtain the operation characteristic factors, a safety monitoring plan exclusive to each infrastructure line can be obtained. Based on the matching of the safety monitoring threshold based on the infrastructure line operation characteristic factors, safety resources can be reasonably allocated according to the actual risk level of different lines. This enables the safety monitoring system to flexibly respond to various complex and changeable situations, improves the flexibility of the system, and reduces the false alarm and missed alarm rates. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] 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.

[0021] Figure 1 It is a schematic diagram of system module connection of the present invention.

[0022] Figure 2 Flowchart of steps for issuing early warning of infrastructure line operations that are at risk. DETAILED DESCRIPTION

[0023] 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.

[0024] See also Figure 1 An embodiment of the present invention provides a technical solution for infrastructure line operation safety monitoring and early warning: an infrastructure line operation safety monitoring and early warning system, including a sensor deployment module, a data transmission module, a geographic environment analysis module, a safety monitoring threshold matching module, a status data analysis module and an infrastructure line operation risk judgment module.

[0025] The sensor deployment module deploys data acquisition sensors at the infrastructure line operation site based on the sensor deployment plan stored in the database. The data acquisition sensors include GPS sensors, temperature and humidity sensors, harmful gas sensors, equipment operation status sensors and video surveillance cameras. Among them, harmful gas sensors include electrochemical carbon monoxide sensors and electrochemical sulfur dioxide sensors, and equipment operation status sensors include displacement sensors, speed sensors, and power sensors.

[0026] The data transmission module transmits the data collected by the data acquisition sensor to the data processing center in real time through a combination of industrial Ethernet and 4G / 5G networks, and uses a data verification algorithm to determine whether the data needs to be retransmitted. The data received by the data processing center specifically includes infrastructure line operating environment status data, infrastructure line operating equipment status data, and infrastructure line operating personnel behavior data.

[0027] The specific analysis process includes: using a data verification algorithm, which is a cyclic redundancy check, to calculate the CRC check code of each data M transmitted: determine the generating polynomial G stored in the database; obtain the number of binary bits of the data M to be sent, recorded as n bits, and the number of binary bits of the generating polynomial G is r+1 bits, where r is the degree of the generating polynomial stored in the database; add r 0 bits after the data M to obtain new data M1, divide the generating polynomial G by the data M1 using modulo 2 division, and the remainder is the remainder, i.e., the CRC check code; attach the CRC check code of the data M to the end of the data M and send it together; the receiving end recalculates the CRC check code of the received data M, and compares it with the CRC check code of the received data M to determine whether the data needs to be retransmitted: if they are consistent, the data does not need to be retransmitted; if they are inconsistent, the data needs to be retransmitted, and the sending end is requested to resend the data.

[0028] Cyclic Redundancy Check (CRC) is a powerful error detection method. During data transmission, data may be erroneous due to various interference factors (such as electromagnetic interference, network fluctuations, etc.). Through CRC verification, these errors can be detected with a high probability. For example, at the construction line operation site, if the equipment operation status data or environmental data transmitted by the sensor is wrong, it will lead to a wrong judgment of the safety status of the operation. The CRC check can effectively capture these data errors and ensure that only correct data is used for subsequent analysis and decision-making. Avoid the propagation of erroneous data in the system and the incorrect processing. Without this retransmission mechanism, erroneous data will enter the data processing center, which will affect a series of subsequent links such as matching of safety monitoring thresholds, status data analysis, and risk judgment.

[0029] In a complex infrastructure line operation environment, data transmission will be interfered by many factors. Through data verification and retransmission mechanism, these interferences can be overcome to a certain extent and the stability of data transmission can be improved.

[0030] The geographical environment analysis module analyzes the geographical environment factors of the infrastructure line and obtains the geographical environment characteristic signals of the infrastructure line.

[0031] The specific analysis process is: obtaining geographical environment factor data of infrastructure lines, which specifically include geographical environment rainfall of infrastructure lines, geographical environment rock hardness of infrastructure lines, and geographical environment river water level of infrastructure lines; based on the obtained geographical environment factor data of infrastructure lines, comprehensive analysis is performed to obtain geographical environment characteristic signals of infrastructure lines, and the geographical environment characteristic signals of infrastructure lines are used as the analysis basis for obtaining characteristic factors of infrastructure line operations.

[0032] All data in this embodiment are normalized.

[0033] The specific analysis process of the characteristic signals of the geographical environment of infrastructure lines is as follows: ; In the formula, dht is the characteristic signal of the geographical environment of the infrastructure line, jyl is the rainfall of the geographical environment of the infrastructure line, syd is the rock hardness of the geographical environment of the infrastructure line, hsw is the river water level of the geographical environment of the infrastructure line, is the compensation factor of the set jyl, is the compensation factor of the set syd, is the compensation factor of the set hsw.

[0034] It should be explained that the compensation factors of jyl, syd and hsw set above are obtained from the database. According to the historical data, a mapping set of the historically measured rainfall in the geographical environment of the infrastructure line, the rock hardness in the geographical environment of the infrastructure line, the river water level in the geographical environment of the infrastructure line and the compensation factors of jyl, syd and hsw is established to obtain the compensation factors of jyl, syd and hsw corresponding to the current jyl, syd and hsw.

[0035] It should be noted that the following , , , , , , , , , , , , They are also obtained through a mapping set of historical data and compensation factors established in a database, that is, the corresponding compensation factors are obtained according to the current data.

[0036] Infrastructure lines in different geographical environments face different levels of risk. Geographical environmental characteristic signals can help determine personalized safety monitoring thresholds so that potential safety hazards can be discovered in a timely manner and accurate safety monitoring can be achieved. When an emergency occurs, geographic environmental characteristic signals can help reasonably allocate emergency resources and determine emergency strategies that are more in line with the actual situation.

[0037] The safety monitoring threshold matching module analyzes the basic characteristics of the infrastructure line, combines the geographical environment characteristic signals of the infrastructure line, obtains the infrastructure line operation characteristic factors, and matches the infrastructure line operation safety monitoring threshold.

[0038] The specific analysis process is as follows: obtaining the basic characteristic data of the infrastructure lines, which specifically include the inclination of the infrastructure line towers, the proportion of the corrosion area of ​​the infrastructure line towers, and the pollution flashover frequency of the infrastructure line insulators; based on the obtained basic characteristic data of the infrastructure lines, combined with the characteristic signals of the geographical environment of the infrastructure lines, a comprehensive analysis is performed to obtain the characteristic factors of the infrastructure line operations, and the characteristic factors of the infrastructure line operations are used as the analysis basis for matching the thresholds for safety monitoring of infrastructure line operations.

[0039] The specific analysis process of the characteristic factors of infrastructure line operations is as follows: ; In the formula, zyt is the characteristic factor of infrastructure line operation, qxd is the inclination of infrastructure line tower, gfs is the proportion of infrastructure line tower corrosion area, wsp is the pollution flashover frequency of infrastructure line insulator, is the compensation factor of the set qxd, is the compensation factor of the set gfs, is the compensation factor of the set wsp.

[0040] By combining basic characteristic data such as the inclination of infrastructure line towers, the percentage of tower corrosion area, and the frequency of insulator flashover with the characteristic signals of the geographical environment, various risk factors in the process of infrastructure line operations can be fully considered. The inclination of towers is affected by the terrain, soil quality, and natural disasters (such as earthquakes and landslides) in the geographical environment; the percentage of tower corrosion area is closely related to geographical factors such as environmental humidity and rainfall; the frequency of insulator flashover varies in different climates (such as fog and acid rain) and geographical environments.

[0041] By combining various factors and their compensation factors through mathematical formulas, the degree of risk can be measured more accurately, avoiding the situation where only a single factor is focused on while ignoring other potential risks. Since the basic characteristics and geographical environment of each infrastructure line are different, the calculated operation characteristic factors can be used as an analytical basis for determining the personalized safety monitoring strategy for each line to adapt to the complex and changing operating environment.

[0042] The infrastructure line operation characteristic factor is stored as a specified label, the specified label is compared with each set label stored in the database, the set label corresponding to the specified label is obtained, and the infrastructure line operation safety monitoring threshold corresponding to the set label stored in the database is obtained.

[0043] By storing the infrastructure line operation characteristic factors as specified tags and comparing them with the set tags in the database, an automated threshold matching process is implemented. This avoids the errors and inefficiencies that occur when manually searching and matching thresholds. The set tags stored in the database and the corresponding infrastructure line operation safety monitoring thresholds are pre-studied and verified in practice. The safety monitoring threshold can be accurately determined based on the actual characteristics of the infrastructure line operation. Different infrastructure lines have different operation characteristic factors and can flexibly adapt to this diversity. Whether it is a transmission line, a communication line, or a railway line, as long as its operation characteristic factors can be accurately quantified and stored as tags, the matching safety monitoring threshold can be found in the database.

[0044] The status data analysis module analyzes the infrastructure line operation environment status data, infrastructure line operation equipment status data, and infrastructure line operation personnel behavior data to obtain the infrastructure line operation safety analysis factors.

[0045] The specific analysis process is as follows: Analyze the infrastructure line operation environment status data: obtain the infrastructure line ambient temperature shw, infrastructure line ambient humidity shs, infrastructure line rated ambient temperature ehw, infrastructure line rated ambient humidity ehs; comprehensively consider the infrastructure line ambient temperature, infrastructure line ambient humidity, infrastructure line rated ambient temperature, infrastructure line rated ambient humidity, and infrastructure line rated ambient temperature to construct the environmental comfort index CI; ; In the formula, is the compensation factor of the set shw, is the compensation factor of the set shs; Obtain the carbon monoxide concentration CON and the sulfur dioxide concentration SO2N in the infrastructure line environment; comprehensively consider the carbon monoxide concentration and the sulfur dioxide concentration in the infrastructure line environment to construct the environmental harmful gas risk index HRI; ; In the formula, is the compensation factor of the set CON, is the compensation factor of the set SO2N; Analyze the status data of infrastructure line operation equipment: obtain the braking response time zxy of the infrastructure line crane and the operating power deviation rate qyg of the infrastructure line crane motor; comprehensively consider the braking response time zxy of the infrastructure line crane and the operating power deviation rate of the infrastructure line crane motor to construct the equipment failure prediction index GR; ; In the formula, is the compensation factor of the set zxy, is the compensation factor of the set qyg, and e is a natural constant; Analyze the behavior data of infrastructure line operators: obtain the normal wearing ratio of infrastructure line operators’ safety equipment cdb and the length of time that infrastructure line operators stay in dangerous areas wtl; comprehensively consider the normal wearing ratio of infrastructure line operators’ safety equipment and the length of time that infrastructure line operators stay in dangerous areas, and construct the operator behavior abnormality index XYB; ; In the formula, is the compensation factor of the set cdb, is the compensation factor of the set wtl; Obtain the body inclination angle sqx of the infrastructure line operator and the deviation rate of the chin and chest angle jjp of the infrastructure line operator; comprehensively consider the body inclination angle of the infrastructure line operator and the deviation rate of the chin and chest angle of the infrastructure line operator to construct the operator posture abnormality index ZTB; ; In the formula, is the compensation factor of the set sqx, is the compensation factor of the set jjp; Based on the environmental comfort index, environmental harmful gas risk index, equipment failure prediction index, operator behavior abnormality index and operator posture abnormality index, a comprehensive analysis is conducted to obtain the infrastructure line operation safety analysis factor.

[0046] Safety analysis factors for infrastructure line operations, the specific analysis process is as follows: ; In the formula, It is the safety analysis factor of infrastructure line operation. Factor analysis for the working environment status, is the operating equipment status analysis factor, Analyze factors for operators.

[0047] The deviation rate refers to the ratio of the absolute value of the difference between the actual value and the reference value to the reference value. Through the comprehensive analysis of the operating environment status data, equipment status data and personnel behavior data of the infrastructure line, various factors affecting the safety of the operation can be fully considered. This multi-dimensional evaluation method avoids focusing on a single factor and ignoring other potential risks, making the safety assessment more comprehensive and accurate, and also constructing specific quantitative indicators for each factor.

[0048] CI and HRI can help determine whether the environment is safe. The construction of equipment failure prediction index (GR) helps to detect equipment failures in advance. By comprehensively considering key equipment parameters such as crane braking response time and motor operating power deviation rate, early warning can be issued before equipment failure occurs. The operator behavior abnormality index (XYB) and posture abnormality index (ZTB) can promptly detect unsafe behaviors and postures of personnel. Each sub-indicator (α, β, γ) is calculated through detailed formulas, which can accurately quantify the impact of each aspect on the safety of infrastructure line operations, and then summarize it into ω to more accurately reflect the overall safety level.

[0049] The infrastructure line operation risk judgment module determines whether there are risks in the infrastructure line operation based on the infrastructure line operation safety analysis factors and the infrastructure line operation safety monitoring threshold, and issues early warnings for infrastructure line operations with risks.

[0050] The specific analysis process is: compare the infrastructure line operation safety analysis factor with the infrastructure line operation safety monitoring threshold; if the infrastructure line operation safety analysis factor is not lower than the infrastructure line operation safety monitoring threshold, then there is no risk in the infrastructure line operation; if the infrastructure line operation safety analysis factor is lower than the infrastructure line operation safety monitoring threshold, then there is a risk in the infrastructure line operation.

[0051] By setting clear thresholds for infrastructure line operation safety monitoring and comparing them with the calculated operation safety analysis factors, an objective and unified standard is provided for judging whether the operation is risky, and it can adapt to the differences in different operation scenarios. No longer relying on subjective experience or vague feelings to assess risks. It can clearly distinguish between the two clear states of risk and non-risk. This helps to quickly and accurately grasp the current safety situation of infrastructure line operations. During the infrastructure line operation process, real-time comparison of safety analysis factors and monitoring thresholds can detect potential risks in advance.

[0052] like Figure 2As shown, an early warning is issued for infrastructure line operations with risks. The specific analysis process is: if there is a risk in the infrastructure line operation, an early warning is issued for the infrastructure line operation with risks: the difference between the infrastructure line operation safety monitoring threshold and the infrastructure line operation safety analysis factor corresponding to the infrastructure line operation with risks is recorded as the infrastructure line operation safety deviation value; the infrastructure line operation safety deviation value is compared with the infrastructure line operation safety deviation warning value stored in the database; if the infrastructure line operation safety deviation value is not lower than the infrastructure line operation safety deviation warning value, a second-level early warning is issued for the infrastructure line operation with risks; if the infrastructure line operation safety deviation value is lower than the infrastructure line operation safety deviation warning value, a first-level early warning is issued for the infrastructure line operation with risks.

[0053] The safety deviation value of the infrastructure line operation is calculated and compared with the stored safety deviation warning value, and the risk is divided into primary and secondary warnings, realizing the quantitative distinction of the risk degree. This classification method can more accurately reflect the severity of the risk, allowing managers and operators to have a clearer understanding of the risk. When the safety deviation value is large (not lower than the safety deviation warning value), a secondary warning is issued, indicating that the risk is already serious and needs to be highly valued and more urgent measures should be taken; when the safety deviation value is small (lower than the safety deviation warning value), a primary warning is issued, indicating that the risk is relatively low, but it also needs attention and appropriate handling.

[0054] Different levels of early warning provide guidance for taking targeted response measures. Level 1 early warning only requires inspection or adjustment of local links, such as strengthening supervision of operators and performing simple maintenance on equipment; Level 2 early warning requires more stringent measures such as suspending some operations, comprehensively inspecting equipment, and re-evaluating environmental factors. This can avoid taking the same response approach to all risks and make safety measures more accurate and effective. The entire early warning process is based on the safety deviation early warning value stored in the database, which makes the early warning have a unified standard. Different infrastructure line operations or different operating periods can be warned according to this standard, avoiding early warning confusion caused by inconsistent human judgment standards.

[0055] In a specific embodiment, the ambient temperature of the infrastructure line is 25 degrees Celsius, the ambient humidity of the infrastructure line is 60%, the rated ambient temperature of the infrastructure line is 20 degrees Celsius, the rated ambient humidity of the infrastructure line is 50%, the measured carbon monoxide concentration of the infrastructure line environment is 5ppm, the sulfur dioxide concentration of the infrastructure line environment is 2ppm, the braking response time of the infrastructure line crane is 2 seconds, the operating power deviation rate of the infrastructure line crane motor is 0.1, the normal wearing ratio of the safety equipment of the infrastructure line operators is 0.8, the stay time of the infrastructure line operators in the dangerous area is 10 seconds, the body inclination angle of the infrastructure line operators is 10 degrees, and the deviation rate of the chin and chest angle of the infrastructure line operators is 0.05. At the same time, the rainfall in the geographical environment of the construction line is 50 mm, and its compensation factor is 0.8; the rock hardness of the geographical environment of the infrastructure line is 80 (dimensionless value), and its compensation factor is 1.2; the water level of the river channel in the geographical environment of the infrastructure line is 3 meters, and its compensation factor is 0.9.

[0056] After the data reception and verification is completed, the geographical environment characteristic signal of the infrastructure line is 0.107, the inclination of the infrastructure line tower is 2 degrees, and its compensation factor is 0.7; the corrosion area of ​​the infrastructure line tower accounts for 0.05, and its compensation factor is 1.1; the frequency of pollution flashover of the infrastructure line insulator is 0.02 times per day, and its compensation factor is 0.9. The infrastructure line operation characteristic factor is calculated to be 0.417, and the infrastructure line operation characteristic factor is stored as a specified label, which is compared with the set labels stored in the database to obtain the set label corresponding to the specified label, and the infrastructure line operation safety monitoring threshold corresponding to the set label stored in the database is 5.1.

[0057] The compensation factor of shw is 0.6, the compensation factor of shs is 0.7, the compensation factor of CON is 0.5, the compensation factor of SO2N is 0.4, the calculated environmental comfort index is 5.18, and the environmental harmful gas risk index is 0.61.

[0058] The compensation factor of zxy is 0.8, the compensation factor of qyg is 0.9, and the computing equipment failure prediction index is 2.01.

[0059] The compensation factor of cdb is 0.7, the compensation factor of wtl is 0.6, the compensation factor of sqx is 0.5, the compensation factor of jjp is 0.4, the abnormal behavior index of the operator is 0.70, and the abnormal posture index of the operator is 0.16.

[0060] The calculated infrastructure line operation safety analysis factor is 3.98, which is lower than the infrastructure line operation safety monitoring threshold of 5.1 for comparison, so there is a risk in the infrastructure line operation; the difference between the infrastructure line operation safety monitoring threshold and the infrastructure line operation safety analysis factor corresponding to the infrastructure line operation with risk is recorded as the infrastructure line operation safety deviation value of 1.12, and the infrastructure line operation safety deviation value is not lower than the infrastructure line operation safety deviation warning value of 1, then a second-level warning is issued for the infrastructure line operation with risk.

Claims

1. A safety monitoring and early warning system for infrastructure line operations, characterized in that: It includes sensor deployment module, data transmission module, geographic environment analysis module, safety monitoring threshold matching module, status data analysis module and infrastructure line operation risk judgment module, among which: The sensor deployment module deploys data acquisition sensors at the infrastructure line operation site based on the sensor deployment scheme stored in the database. The data acquisition sensors include GPS sensors, temperature and humidity sensors, harmful gas sensors, equipment operation status sensors, and video surveillance cameras; The data transmission module transmits the data collected by the data acquisition sensor to the data processing center in real time, and uses a data verification algorithm to determine whether the data needs to be retransmitted. The data received by the data processing center specifically includes infrastructure line operation environment status data, infrastructure line operation equipment status data, and infrastructure line operation personnel behavior data; The geographical environment analysis module analyzes the geographical environment factors of the infrastructure line to obtain the geographical environment characteristic signal of the infrastructure line; The safety monitoring threshold matching module analyzes the basic characteristics of the infrastructure line, combines the geographical environment characteristic signal of the infrastructure line, obtains the infrastructure line operation characteristic factor, and matches the infrastructure line operation safety monitoring threshold; The state data analysis module analyzes the infrastructure line operation environment state data, infrastructure line operation equipment state data, and infrastructure line operation personnel behavior data to obtain the infrastructure line operation safety analysis factor; The infrastructure line operation risk judgment module judges whether there is a risk in the infrastructure line operation based on the infrastructure line operation safety analysis factor and the infrastructure line operation safety monitoring threshold, and issues an early warning for the infrastructure line operation with risks.

2. The infrastructure line operation safety monitoring and early warning system according to claim 1 is characterized by: The specific analysis process of determining whether data needs to be retransmitted includes: The data verification algorithm is a cyclic redundancy check. For each transmitted data M, the CRC check code of the data M is calculated: Determine a generator polynomial G stored in a database; Get the number of binary digits of the data M to be sent, recorded as n bits, and the number of binary digits of the generating polynomial G is r+1 bits, where r is the degree of the generating polynomial stored in the database; Add r 0 bits after the data M to get the new data M1; Divide the data M1 by the generator polynomial G using modulo 2 division, and the remainder is the CRC check code. The CRC check code of data M is attached to the end of data M and sent together; The receiving end recalculates the CRC check code for the received data M and compares it with the CRC check code of the received data M to determine whether the data needs to be retransmitted: If they are consistent, the data does not need to be retransmitted; If they are inconsistent, the data needs to be retransmitted, and the sender is requested to resend the data.

3. The infrastructure line operation safety monitoring and early warning system according to claim 1 is characterized by: The analysis of the geographical environment factors of the infrastructure line is performed to obtain the characteristic signals of the geographical environment of the infrastructure line. The specific analysis process is as follows: Obtaining geographical environment factor data of infrastructure lines, which specifically include geographical environment rainfall of infrastructure lines, geographical environment rock hardness of infrastructure lines, and geographical environment river water level of infrastructure lines; Based on the acquired data of geographical environment factors of infrastructure lines, a comprehensive analysis is performed to obtain the geographical environment characteristic signals of infrastructure lines, and the geographical environment characteristic signals of infrastructure lines are used as the analysis basis for obtaining the characteristic factors of infrastructure line operation.

4. The infrastructure line operation safety monitoring and early warning system according to claim 1 is characterized by: The basic characteristics of the infrastructure line are analyzed, and the infrastructure line operation characteristic factors are obtained by combining the geographical environment characteristic signals of the infrastructure line. The specific analysis process is as follows: Obtain basic characteristic data of infrastructure lines, including the inclination of infrastructure line towers, the percentage of infrastructure line tower corrosion area, and the pollution flashover frequency of infrastructure line insulators; Based on the acquired basic characteristic data of the infrastructure line and combined with the characteristic signals of the geographical environment of the infrastructure line, a comprehensive analysis is conducted to obtain the characteristic factors of the infrastructure line operation. The characteristic factors of the infrastructure line operation are used as the analysis basis for matching the threshold value of the infrastructure line operation safety monitoring.

5. The infrastructure line operation safety monitoring and early warning system according to claim 4 is characterized by: The specific analysis process of the infrastructure line operation characteristic factor is as follows: ； In the formula, zyt is the characteristic factor of infrastructure line operation, dht is the characteristic signal of geographical environment of infrastructure line, qxd is the inclination of infrastructure line tower, gfs is the proportion of infrastructure line tower corrosion area, wsp is the pollution flashover frequency of infrastructure line insulator, is the compensation factor of the set qxd, is the compensation factor of the set gfs, is the compensation factor of the set wsp.

6. The infrastructure line operation safety monitoring and early warning system according to claim 4 is characterized by: The matching infrastructure line operation safety monitoring threshold, the specific analysis process is: The infrastructure line operation characteristic factor is stored as a specified label, the specified label is compared with each set label stored in the database, the set label corresponding to the specified label is obtained, and the infrastructure line operation safety monitoring threshold corresponding to the set label stored in the database is obtained.

7. The infrastructure line operation safety monitoring and early warning system according to claim 1 is characterized by: The infrastructure line operation environment status data, infrastructure line operation equipment status data, and infrastructure line operation personnel behavior data are analyzed to obtain the infrastructure line operation safety analysis factor. The specific analysis process is as follows: Analysis of infrastructure line operation environment status data: Obtain the infrastructure line ambient temperature shw, infrastructure line ambient humidity shs, infrastructure line rated ambient temperature ehw, and infrastructure line rated ambient humidity ehs; Comprehensively consider the infrastructure line ambient temperature, infrastructure line ambient humidity, infrastructure line rated ambient temperature, infrastructure line rated ambient humidity, and construct the environmental comfort index CI; ； In the formula, is the compensation factor of the set shw, is the compensation factor of the set shs; Obtain the carbon monoxide concentration CON and sulfur dioxide concentration SO2N of the infrastructure line environment; Comprehensively consider the carbon monoxide concentration and sulfur dioxide concentration in the infrastructure line environment to construct the environmental hazardous gas risk index HRI; ； In the formula, is the compensation factor of the set CON, is the compensation factor of the set SO2N; Analysis of infrastructure line operation equipment status data: Obtain the braking response time zxy of the infrastructure line crane and the operating power deviation rate qyg of the infrastructure line crane motor; The equipment failure prediction index GR is constructed by comprehensively considering the braking response time of the infrastructure line crane and the power deviation rate of the infrastructure line crane motor. ； In the formula, is the compensation factor of the set zxy, is the compensation factor of the set qyg, and e is a natural constant; Analysis of the behavior data of infrastructure line operators: Obtain the proportion of normal wearing of safety equipment by infrastructure line workers (cdb) and the length of time infrastructure line workers stay in dangerous areas (wtl); Taking into account the proportion of infrastructure line workers wearing safety equipment normally and the length of time they stay in dangerous areas, we construct the operator behavior abnormality index XYB. ； In the formula, is the compensation factor of the set cdb, is the compensation factor of the set wtl; Obtain the body inclination angle sqx of the infrastructure line operator and the deviation rate jjp of the angle between the chin and chest of the infrastructure line operator; Taking into account the body inclination angle of infrastructure line workers and the deviation rate of the angle between the chin and chest of infrastructure line workers, the operator posture abnormality index ZTB is constructed; ； In the formula, is the compensation factor of the set sqx, is the compensation factor of the set jjp; Based on the environmental comfort index, environmental harmful gas risk index, equipment failure prediction index, operator behavior abnormality index and operator posture abnormality index, a comprehensive analysis is conducted to obtain the infrastructure line operation safety analysis factor.

8. The infrastructure line operation safety monitoring and early warning system according to claim 7 is characterized by: The specific analysis process of the infrastructure line operation safety analysis factor is as follows: ； In the formula, It is the safety analysis factor of infrastructure line operation. Factor analysis for the working environment status, is the operating equipment status analysis factor, Analyze factors for operators.

9. The infrastructure line operation safety monitoring and early warning system according to claim 1 is characterized by: The infrastructure line operation safety analysis factor is combined with the infrastructure line operation safety monitoring threshold to determine whether there is a risk in the infrastructure line operation. The specific analysis process is as follows: Compare the infrastructure line operation safety analysis factor with the infrastructure line operation safety monitoring threshold; If the infrastructure line operation safety analysis factor is not lower than the infrastructure line operation safety monitoring threshold, there is no risk in the infrastructure line operation; If the infrastructure line operation safety analysis factor is lower than the infrastructure line operation safety monitoring threshold, there is a risk in the infrastructure line operation.

10. The infrastructure line operation safety monitoring and early warning system according to claim 9 is characterized by: The above mentioned and early warning of infrastructure line operations with risks are issued. The specific analysis process is as follows: If there is a risk in the infrastructure line operation, an early warning will be issued for the infrastructure line operation with risk: The difference between the infrastructure line operation safety monitoring threshold and the infrastructure line operation safety analysis factor corresponding to the infrastructure line operation with risk is recorded as the infrastructure line operation safety deviation value; Compare the infrastructure line operation safety deviation value with the infrastructure line operation safety deviation warning value stored in the database; If the safety deviation value of the infrastructure line operation is not lower than the safety deviation warning value of the infrastructure line operation, a second-level warning is issued for the infrastructure line operation with risks; If the safety deviation value of the infrastructure line operation is lower than the safety deviation warning value of the infrastructure line operation, a first-level warning will be issued for the infrastructure line operation with risks.

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