A kind of high-altitude operation anti-fall safety monitoring method and monitoring system

Abstract

The present invention discloses a method and system for monitoring fall prevention safety of aerial work, the method includes obtaining physiological sign data and operation behavior data of aerial work personnel, use status data of fall prevention devices and environmental data; determining human risk index, equipment risk index and environmental risk index; judging whether there is a situation where the risk value among human risk index, equipment risk index and environmental risk index is greater than a first preset threshold value; if so, triggering an alarm prompt and generating a first operation guide to push to the aerial work personnel; if not, determining the fall risk value according to the human risk index, equipment risk index and environmental risk index, and when it is greater than a second preset threshold value, triggering an alarm prompt and generating a second operation guide to push to the aerial work personnel. The present invention takes into account more comprehensive risk factors, so that the fall risk value can be accurately predicted, and different operation guides are provided for different risks, thereby improving the energy efficiency of aerial work safety monitoring.

Description

Technical Field

[0001] The present invention relates to the technical field of safety monitoring, and in particular to a high-altitude operation fall prevention safety monitoring method and a monitoring system. Background Art

[0002] Working at heights is an integral part of modern construction, maintenance, installation and overhaul industries, involving work in a variety of high-altitude environments such as building exteriors, bridges, towers, wind power facilities, and transmission lines. Due to the particularity of the working environment, workers working at heights face many safety challenges, among which falling accidents are one of the most common risks and the most deadly. According to statistics, falling accidents account for a considerable proportion of all accidents involving working at heights, posing a serious threat to the safety of personnel lives.

[0003] However, the current safety monitoring of high-altitude falls still mainly relies on manual supervision, such as regular safety inspections and whether personal protective equipment is worn properly. However, this method is not only costly and inefficient, but also has a slow response speed to sudden safety accidents or safety hazards, and there is a problem of delayed response. In addition, this method only considers a relatively single factor and ignores other potential risks, making the prediction of falling events inaccurate, and thus unable to more effectively monitor the safety of high-altitude operations to reduce the accident rate. Summary of the invention

[0004] In order to solve at least one of the technical problems mentioned above, the present invention provides a high-altitude work anti-fall safety monitoring method and monitoring system.

[0005] In a first aspect, the present invention provides a method for monitoring safety of falling prevention during high-altitude operations, the method comprising:

[0006] Obtain physiological sign data and work behavior data of personnel working at heights, usage status data of fall prevention devices, and environmental data;

[0007] Determine human risk indicators based on the physiological signs and work behavior data of workers working at heights, determine equipment risk indicators based on the use status data of fall protection devices, and determine environmental risk indicators based on environmental data;

[0008] Determine whether there is a risk value of any one of the human risk index, the equipment risk index, and the environmental risk index that is greater than the corresponding first preset threshold;

[0009] If yes, trigger an alarm prompt and generate a first operation guide, and push the first operation guide to the high-altitude operator;

[0010] If not, determine the falling risk value based on the human risk index, equipment risk index and environmental risk index to determine whether the falling risk value is greater than the second preset threshold; when the falling risk value is greater than the second preset threshold, trigger an alarm prompt and generate a second operation guide, and push the second operation guide to the high-altitude workers.

[0011] Preferably, the method of determining the human risk index based on the physiological sign data and work behavior data of the high-altitude workers includes:

[0012] Obtain the physiological sign data of workers working at heights, including heart rate, blood pressure, weight and height, and calculate the physiological sign risk based on the physiological sign data:

[0013] ;

[0014] In the formula, Indicates physiological risk. , , , Respectively represent the standardized heart rate, blood pressure, weight and height;

[0015] Obtain the work behavior data of high-altitude workers and calculate the work behavior risk based on the work behavior data:

[0016] ;

[0017] In the formula, Indicates the risk of operational behavior. Indicates the number of improper operations, satisfying Indicates improper operation; Indicates no improper operation; Indicates points for compliance with height work regulations. , Respectively represent weight factors; represents the base of natural logarithms;

[0018] Calculate human risk index based on physiological sign risk and operational behavior risk:

[0019] ;

[0020] In the formula, Represents anthropogenic risk indicator.

[0021] Preferably, determining the equipment risk index according to the usage status data of the fall prevention device includes:

[0022] Calculate the meshing degree of the gear and rack in the fall arrest device:

[0023] ;

[0024] In the formula, Represents the meshing index of the gear and rack, , represent the loss rates of gear and rack respectively, Indicates The actual contact area between the pitch gear and the rack; Indicates The ideal contact area between the pitch gear and the rack;

[0025] Calculate the suction force of the suction cup in the fall protection device:

[0026] ;

[0027] In the formula, Indicates the suction force of the suction cup. Indicates atmospheric pressure, Indicates the effective contact area between the bottom of the suction cup and the building. represents the effective contact radius;

[0028] The equipment risk index is determined based on the meshing degree of the gear and rack in the anti-fall device and the suction force of the suction cup:

[0029] ;

[0030] In the formula, Represents the equipment risk indicator, Indicates the meshing degree reference value, They respectively represent the weight of the person and the weight of the object carried by the fall prevention device.

[0031] Preferably, determining the environmental risk index according to the environmental data includes:

[0032] ;

[0033] In the formula, represents the environmental risk index, Represent the weight factors, Respectively represent the actual values ​​of temperature, humidity and wind speed in the current high-altitude operation; Respectively represent the reference values ​​of temperature, humidity and wind speed in the current high-altitude operation; It indicates any one or more of visibility deviation, snow thickness deviation, precipitation deviation and lightning risk.

[0034] Preferably, determining the fall risk value according to the human risk index, the equipment risk index and the environmental risk index includes:

[0035] Input the risk values ​​corresponding to the human risk index, equipment risk index and environmental risk index into a preset fall risk prediction model, and output the fall risk value;

[0036] The fall risk prediction model is obtained by training using any one of logistic regression, random forest, support vector machine or neural network models.

[0037] Preferably, generating the first operation instruction includes:

[0038] When the risk values ​​of two or more indicators among the human risk indicators, equipment risk indicators and environmental risk indicators are greater than the corresponding first preset thresholds, the risk levels of the indicators are prioritized;

[0039] Provide first operation guidance for different indicators in order of priority.

[0040] Preferably, generating the second operation instruction includes:

[0041] When the fall risk value is greater than a second preset threshold, the fall risk level is divided according to the difference between the fall risk value and the second preset threshold;

[0042] Different second operation instructions are matched according to different fall risk levels.

[0043] In a second aspect, the present invention further provides a high-altitude operation anti-fall safety monitoring system, the system comprising:

[0044] A data acquisition unit, used to acquire physiological sign data and work behavior data of personnel working at heights, use status data of anti-fall devices, and environmental data;

[0045] An index determination unit is used to determine the human risk index based on the physiological sign data and work behavior data of the height workers, determine the equipment risk index based on the use status data of the fall protection device, and determine the environmental risk index based on the environmental data;

[0046] An operation guide generating unit, used for judging whether a risk value of any one of the human risk index, the equipment risk index and the environmental risk index is greater than a corresponding first preset threshold value;

[0047] If yes, trigger an alarm prompt and generate a first operation guide, and push the first operation guide to the high-altitude operator;

[0048] If not, determine the falling risk value based on the human risk index, equipment risk index and environmental risk index to determine whether the falling risk value is greater than the second preset threshold; when the falling risk value is greater than the second preset threshold, trigger an alarm prompt and generate a second operation guide, and push the second operation guide to the high-altitude workers.

[0049] In a third aspect, the present invention further provides an electronic device comprising: a processor and a memory, wherein the memory is used to store computer program code, wherein the computer program code comprises computer instructions, and when the processor executes the computer instructions, the electronic device executes the method as described in the first aspect above and any possible implementation thereof.

[0050] In a fourth aspect, the present invention further provides a computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, wherein the computer program includes program instructions, and when the program instructions are executed by a processor of an electronic device, the processor executes the method as described in the first aspect above and any possible implementation thereof.

[0051] Compared with the prior art, the present invention has the following beneficial effects:

[0052] 1) The present invention takes into account multiple influencing factors, thereby conducting a comprehensive risk assessment of aerial work, including obtaining physiological sign data of aerial workers, including heart rate, blood pressure, weight and height to calculate physiological sign risks; calculating operational behavior risks based on operational behavior data: and then calculating human risk indicators based on physiological sign risks and operational behavior risks, so that the decline in working status caused by fatigue, disease or other physiological factors can be discovered in time, which helps to prevent accidents caused by physical exhaustion or poor health. By analyzing the operational norms of operators, such as movement trajectories, operating frequency and strength, it helps to identify improper operations or negligence and avoid the risk of falling due to human errors. Through the use status data of the anti-fall device, such as the meshing degree of the gear and the rack and the suction force of the suction cup, the equipment risk index is calculated, so that equipment problems can be effectively identified and the probability of safety accidents caused by equipment problems can be reduced. Through environmental data, including wind speed, temperature, humidity, etc., the safety of the working environment is evaluated to avoid aerial work under harsh conditions and reduce the risk of falling caused by environmental factors.

[0053] 2) The present invention provides a hierarchical early warning mechanism, which can distinguish different levels of risks by quantifying risks into numerical values ​​and setting thresholds of different levels, so as to achieve targeted early warning and intervention. A first preset threshold is set for human risk indicators, equipment risk indicators and environmental risk indicators. When any single risk indicator exceeds the first preset threshold, an alarm is triggered immediately, so that emergency situations such as sudden physical discomfort or equipment failure can be responded to quickly, ensuring that operators take timely measures to avoid serious consequences. The priorities of different risk indicators are taken into account when recommending operating instructions, so that operating personnel can be provided with operating guidance in a more scientific, reasonable and orderly manner, thereby reducing the accident rate.

[0054] 3) The fall risk value is obtained by comprehensively considering all risk indicators. The alarm is triggered only when the fall risk exceeds the second preset threshold, thus avoiding frequent false alarms, ensuring the accuracy and effectiveness of the alarm, and giving operators clear operating instructions. In addition, by classifying the fall risk into different levels and matching different second operating instructions according to different fall risk levels, it can also more effectively guide operators to protect themselves in emergencies and improve the safety of the operation process.

[0055] 4) The present invention enhances the emergency response capability of the aerial work site by providing timely feedback and clear and targeted operation instructions, helping operators to respond quickly and accurately and reduce the risk of falling. Through real-time monitoring and early warning, it can effectively prevent the occurrence of falling accidents, protect the lives of operators, reduce the downtime losses caused by accidents, and improve the safety and efficiency of the entire operation process.

[0056] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the background technology, the drawings required for use in the embodiments of the present invention or the background technology will be described below.

[0058] The drawings herein are incorporated into the specification and constitute a part of the specification. These drawings illustrate embodiments consistent with the present disclosure and are used to illustrate the technical solutions of the present disclosure together with the specification.

[0059] Figure 1 A schematic diagram of a flow chart of a high-altitude work fall prevention safety monitoring method provided by an embodiment of the present invention;

[0060] Figure 2 A schematic structural diagram of a high-altitude work anti-fall safety monitoring system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0061] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme 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, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0062] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices.

[0063] The term "and / or" herein is only a description of the association relationship of the associated objects, indicating that there may be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the term "at least one" herein represents any combination of at least two of any one or more of a plurality of. For example, including at least one of A, B, and C can represent including any one or more elements selected from the set consisting of A, B, and C.

[0064] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0065] In addition, in order to better illustrate the present invention, numerous specific details are provided in the following specific embodiments. It should be understood by those skilled in the art that the present invention can be implemented without certain specific details. In some examples, methods, means, components and circuits well known to those skilled in the art are not described in detail in order to highlight the subject matter of the present invention.

[0066] The current high-altitude work fall prevention safety monitoring still has problems such as incomplete monitoring coverage, low response speed, and unsatisfactory safety monitoring effect. To this end, the present invention provides a high-altitude work fall prevention safety monitoring method, which can analyze the high-altitude work risks from multiple aspects and match scientific operation guidelines for different risks, thereby reducing the incidence of falling accidents and improving the supervision efficiency.

[0067] See also Figure 1 , Figure 1 The following is a flow chart of a method for monitoring the safety of falling from a height during operation provided by an embodiment of the present invention. Figure 1 As shown, the method comprises the following steps:

[0068] S10. Acquire the physiological sign data and work behavior data of the personnel working at heights, the usage status data of the anti-fall device, and the environmental data.

[0069] In this embodiment, the physiological sign data mainly include heart rate, blood pressure, weight and height, among which weight and height can be confirmed by the identity information of the operator before the operation, while heart rate and blood pressure need to be obtained through the wearable device of the operator, such as a smart watch or a chest strap heart rate monitor. In some embodiments, the user's body temperature, blood oxygen saturation, and movement and posture changes can also be monitored. Body temperature and blood oxygen saturation can be collected by sensors, while movement and posture changes can be collected by accelerometers and gyroscopes. These sensors can be integrated into smart wearable devices, so as to achieve real-time monitoring of the physiological characteristics of the operator at work.

[0070] Operation behavior data can be monitored through accelerometers and gyroscopes or position trackers to obtain the location and movement trajectory of personnel. It can also be monitored through video surveillance and computer vision to analyze irregular operations during the operation. In order to obtain more comprehensive operation behavior data, pressure sensors can be used to monitor the strength and frequency of personnel operations, and tilt sensors can be used to detect the tilt angle of the work platform or personnel to prevent loss of balance.

[0071] The use status data of the anti-fall device mainly considers the adsorption force of the suction cup. The anti-fall device currently provided includes a suction cup. When using the device, the suction cup is adsorbed on the supporting structure of the building, and then the operator can complete the task at high altitude with the cooperation of the safety belt. Among them, the adsorption force of the suction cup can be measured by a pressure sensor, or obtained by calculating the effective contact area, and the loss rate of the equipment is mainly judged by the meshing degree of the rack and the gear.

[0072] The simplest way to obtain environmental data is to obtain it directly from a weather station, including environmental parameters such as wind speed, wind direction, temperature, humidity, etc. The weather station can also predict in advance the visibility deviation, snow thickness deviation, precipitation deviation, lightning risk and other adverse environments. Preferably, the noise level of the working environment can also be monitored through a noise sensor to arrange outdoor high-altitude work in a less noisy environment.

[0073] S20. Determine human risk indicators based on the physiological signs data and work behavior data of height workers, determine equipment risk indicators based on the usage status data of fall prevention devices, and determine environmental risk indicators based on environmental data.

[0074] In one embodiment, determining the human risk index based on the physiological sign data and work behavior data of the high-altitude workers includes:

[0075] Obtain the physiological sign data of workers working at heights, including heart rate, blood pressure, weight and height, and calculate the physiological sign risk based on the physiological sign data:

[0076] ;

[0077] In the formula, Indicates physiological risk. , , , Respectively represent the standardized heart rate, blood pressure, weight and height;

[0078] Obtain the work behavior data of high-altitude workers and calculate the work behavior risk based on the work behavior data:

[0079] ;

[0080] In the formula, Indicates the risk of operational behavior. Indicates the number of improper operations, satisfying Indicates improper operation; Indicates no improper operation; Indicates points for compliance with height work regulations. , Respectively represent weight factors; represents the base of natural logarithms;

[0081] Calculate human risk index based on physiological sign risk and operational behavior risk:

[0082] ;

[0083] In the formula, Represents anthropogenic risk indicator.

[0084] It should be noted that by considering multiple physiological indicators such as heart rate, blood pressure, weight and height, the physical condition of the operator and his ability to adapt to the environment are reflected. Through the natural logarithm function and standardization processing, the degree of deviation of physiological indicators from the normal range and their cumulative effect on risk can be captured.

[0085] The number of improper operations (M) and compliance scores (C) are introduced as measurement criteria, where the number of improper operations reflects irregular behavior, while the compliance score reflects the degree of compliance of operators with safety regulations. The exponential function and square root function highlight the amplification effect of improper operations on risks and the inhibitory effect of compliance with regulations on risks. Weight factor , The introduction of allows the relative importance of different risk factors to be adjusted according to specific circumstances, so that the model can adapt to the needs of different working environments and types of operations, and enhance the flexibility and applicability of the model. The final human risk index is determined by multiplying the physiological sign risk with the work behavior risk. This combination emphasizes the mutual influence between physiological signs and work behavior, that is, in the case of poor physiological condition, improper work behavior will significantly increase the risk of falling.

[0086] In one embodiment, determining the equipment risk index according to the usage status data of the fall prevention device includes:

[0087] Calculate the meshing degree of the gear and rack in the fall arrest device:

[0088] ;

[0089] In the formula, Represents the meshing index of the gear and rack, , represent the loss rates of gear and rack respectively, Indicates The actual contact area between the pitch gear and the rack; Indicates The ideal contact area between the pitch gear and the rack;

[0090] Calculate the suction force of the suction cup in the fall protection device:

[0091] ;

[0092] In the formula, Indicates the suction force of the suction cup. Indicates atmospheric pressure, Indicates the effective contact area between the bottom of the suction cup and the building. represents the effective contact radius;

[0093] The equipment risk index is determined based on the meshing degree of the gear and rack in the anti-fall device and the suction force of the suction cup:

[0094] ;

[0095] In the formula, Represents the equipment risk indicator, Indicates the meshing degree reference value, They respectively represent the weight of the person and the weight of the object carried by the fall prevention device.

[0096] In this embodiment, by calculating the ratio of the actual contact area to the ideal contact area and combining the loss rate of the gear and rack, the wear of the gear and rack in the anti-fall device can be quantitatively evaluated, potential mechanical failures can be discovered in time, and the risk of falling due to equipment aging or damage can be avoided. By combining the meshing deviation of the gear and rack with the difference between the suction cup adsorption force and load-bearing capacity, the overall performance of the anti-fall device can be comprehensively evaluated to ensure the safety of the device when carrying the weight of people and objects.

[0097] In one embodiment, determining the environmental risk indicator according to the environmental data includes:

[0098] ;

[0099] In the formula, represents the environmental risk index, Represent the weight factors, Respectively represent the actual values ​​of temperature, humidity and wind speed in the current high-altitude operation; Respectively represent the reference values ​​of temperature, humidity and wind speed in the current high-altitude operation; It indicates any one or more of visibility deviation, snow thickness deviation, precipitation deviation and lightning risk.

[0100] Low visibility affects workers' line of sight and increases the risk of collision and falling. Snow accumulation may affect the load-bearing capacity and stability of the work platform, increasing the risk of slipping or structural collapse. Precipitation may cause the work area to be slippery, reducing grip and stability. Thunderstorms not only directly threaten personnel safety, but may also damage equipment and interrupt operations. Therefore, when considering environmental risks, this embodiment not only considers the effects of temperature, humidity, and wind speed, but also introduces visibility deviation, snow thickness deviation, precipitation deviation, and lightning risk as compensation, thereby accurately assessing the impact of the environment on high-altitude operations.

[0101] S30, determining whether there is a risk value of any one of the human risk index, the equipment risk index, and the environmental risk index that is greater than a corresponding first preset threshold;

[0102] It is understandable that when any one of the three indicators of human risk index, equipment risk index and environmental risk index exceeds the corresponding first preset threshold, it will bring great hidden dangers. Therefore, it is necessary to set a safety range for each of these three indicators, that is, determine the first preset threshold. Once it is found that any indicator exceeds the first preset threshold, an alarm prompt is immediately triggered and the first operation guide is generated. Among them, the first preset threshold should include three values, namely, the safety reference values ​​corresponding to human risk, equipment risk and environmental risk.

[0103] S40: If yes, trigger an alarm prompt and generate a first operation guide, and push the first operation guide to the high-altitude operation personnel;

[0104] In one embodiment, generating the first operation instruction includes:

[0105] When the risk values ​​of two or more indicators among the human risk indicators, equipment risk indicators and environmental risk indicators are greater than the corresponding first preset thresholds, the risk levels of the indicators are prioritized;

[0106] Provide first operation guidance for different indicators in order of priority.

[0107] When there are two or more risk indicators with risk values ​​greater than their respective first preset thresholds, these indicators need to be prioritized. This is usually based on the severity and urgency of the risks, as well as their potential impact on operational safety. Once the risk level ranking is completed, operational guidelines can be generated in order of priority. These guidelines are designed to help operators or managers take actions to mitigate or eliminate the highest level of risks.

[0108] For example, if the equipment risk indicator shows that the equipment failure rate is abnormally high, and the environmental risk indicator shows that extreme weather conditions are approaching, and the risk values ​​of both exceed the preset threshold, the operational guidance may recommend:

[0109] First, inspect and repair the equipment, as equipment failure can immediately endanger the safety of operators.

[0110] Second, prepare for severe weather, which may include temporarily suspending operations until environmental conditions improve.

[0111] Therefore, this embodiment can ensure that when resources are limited, the risks that are most likely to cause major accidents are dealt with first, thereby effectively improving the safety and efficiency of operations.

[0112] S50. If not, determine the falling risk value according to the human risk index, equipment risk index and environmental risk index, and judge whether the falling risk value is greater than the second preset threshold value; when the falling risk value is greater than the second preset threshold value, trigger an alarm prompt and generate a second operation guide, and push the second operation guide to the high-altitude workers.

[0113] In one embodiment, determining the fall risk value according to the human risk index, the equipment risk index and the environmental risk index includes:

[0114] Input the risk values ​​corresponding to the human risk index, equipment risk index and environmental risk index into a preset fall risk prediction model, and output the fall risk value;

[0115] The fall risk prediction model is obtained by training using any one of logistic regression, random forest, support vector machine or neural network models.

[0116] Before training the model, a large amount of historical data needs to be collected. This data should contain information on all the risk indicators mentioned above, as well as records of known fall events. Generally, the data set should be large enough and representative enough to ensure the accuracy and generalization ability of the model.

[0117] In terms of model selection, you can choose one of the above models and use the prepared data set to train the model. The goal is to let the model learn how to predict the fall risk value from the input risk indicators. During the training process, the data set is usually divided into a training set and a test set to verify the performance of the model. After the model training is completed, it is necessary to use data that did not participate in the training to verify the accuracy and stability of the model. If the model performs poorly, it may be necessary to adjust the algorithm parameters or reconsider the data characteristics. You can also consider replacing other basic models for training.

[0118] Once the model is verified and meets satisfactory performance standards, it can be deployed in the actual operating environment, receiving risk indicator data in real time or periodically, and outputting fall risk values. Through this fall risk prediction model, the fall risk can be predicted quickly and accurately, so that high-risk situations can be identified in time, preventive measures can be taken, and the occurrence of fall accidents can be reduced.

[0119] In one embodiment, generating the second operation instruction includes:

[0120] When the fall risk value is greater than a second preset threshold, the fall risk level is divided according to the difference between the fall risk value and the second preset threshold;

[0121] Different second operation instructions are matched according to different fall risk levels.

[0122] In this embodiment, the difference between the fall risk value and the second preset threshold is calculated. According to the size of the difference, the fall risk level is divided into several levels, such as low, medium, and high. Further matching the operation instructions, for each risk level, there are corresponding operation instructions. For example, low risk may only require monitoring and slight adjustments; medium risk may require warnings to on-site personnel and increased inspection frequency; high risk may require immediate cessation of operations and evacuation of personnel until the risk is reduced. Finally, according to the matched risk level, the corresponding level of operation instructions are automatically or manually started. Operation instructions may include but are not limited to starting emergency procedures, adjusting work processes, enhancing protective measures, etc.

[0123] In summary, the monitoring method provided by the embodiment of the present invention can at least achieve the following effects:

[0124] 1) The present invention takes into account multiple influencing factors, thereby conducting a comprehensive risk assessment of aerial work, including obtaining physiological sign data of aerial workers, including heart rate, blood pressure, weight and height to calculate physiological sign risks; calculating operational behavior risks based on operational behavior data: and then calculating human risk indicators based on physiological sign risks and operational behavior risks, so that the decline in working status caused by fatigue, disease or other physiological factors can be discovered in time, which helps to prevent accidents caused by physical exhaustion or poor health. By analyzing the operational norms of operators, such as movement trajectories, operating frequency and strength, it helps to identify improper operations or negligence and avoid the risk of falling due to human errors. Through the use status data of the anti-fall device, such as the meshing degree of the gear and the rack and the suction force of the suction cup, the equipment risk index is calculated, so that equipment problems can be effectively identified and the probability of safety accidents caused by equipment problems can be reduced. Through environmental data, including wind speed, temperature, humidity, etc., the safety of the working environment is evaluated to avoid aerial work under harsh conditions and reduce the risk of falling caused by environmental factors.

[0125] 2) The present invention provides a hierarchical early warning mechanism, which can distinguish different levels of risks by quantifying risks into numerical values ​​and setting thresholds of different levels, so as to achieve targeted early warning and intervention. A first preset threshold is set for human risk indicators, equipment risk indicators and environmental risk indicators. When any single risk indicator exceeds the first preset threshold, an alarm is triggered immediately, so that emergency situations such as sudden physical discomfort or equipment failure can be responded to quickly, ensuring that operators take timely measures to avoid serious consequences. The priorities of different risk indicators are taken into account when recommending operating instructions, so that operating personnel can be provided with operating guidance in a more scientific, reasonable and orderly manner, thereby reducing the accident rate.

[0126] 3) The fall risk value is obtained by comprehensively considering all risk indicators. The alarm is triggered only when the fall risk exceeds the second preset threshold, thus avoiding frequent false alarms, ensuring the accuracy and effectiveness of the alarm, and giving operators clear operating instructions. In addition, by classifying the fall risk into different levels and matching different second operating instructions according to different fall risk levels, it can also more effectively guide operators to protect themselves in emergencies and improve the safety of the operation process.

[0127] 4) The present invention enhances the emergency response capability of the aerial work site by providing timely feedback and clear and targeted operation instructions, helping operators to respond quickly and accurately and reduce the risk of falling. Through real-time monitoring and early warning, it can effectively prevent the occurrence of falling accidents, protect the lives of operators, reduce the downtime losses caused by accidents, and improve the safety and efficiency of the entire operation process.

[0128] See also Figure 2 A certain embodiment of the present invention further provides a high-altitude operation anti-fall safety monitoring system, the system comprising:

[0129] The data acquisition unit 100 is used to acquire the physiological sign data and work behavior data of the high-altitude workers, the use status data of the anti-fall device, and the environmental data;

[0130] An index determination unit 200 is used to determine a human risk index based on the physiological sign data and work behavior data of the high-altitude workers, determine an equipment risk index based on the use status data of the anti-fall device, and determine an environmental risk index based on the environmental data;

[0131] The operation guide generating unit 300 is used to determine whether there is a risk value of any one of the human risk index, the equipment risk index and the environmental risk index greater than the corresponding first preset threshold value;

[0132] If yes, trigger an alarm prompt and generate a first operation guide, and push the first operation guide to the high-altitude operator;

[0133] If not, determine the falling risk value based on the human risk index, equipment risk index and environmental risk index to determine whether the falling risk value is greater than the second preset threshold; when the falling risk value is greater than the second preset threshold, trigger an alarm prompt and generate a second operation guide, and push the second operation guide to the high-altitude workers.

[0134] It can be understood that the functions or modules included in the system provided in this embodiment can be used to execute the method described in the above method embodiment. Its specific implementation can refer to the description of the above method embodiment. For the sake of brevity, it will not be repeated here.

[0135] The present invention also provides an electronic device, comprising: a processor and a memory, wherein the memory is used to store computer program code, the computer program code includes computer instructions, and when the processor executes the computer instructions, the electronic device executes a method as described in any possible implementation manner.

[0136] The present invention also provides a computer-readable storage medium, in which a computer program is stored. The computer program includes program instructions. When the program instructions are executed by a processor of an electronic device, the processor executes a method as described in any possible implementation manner.

[0137] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0138] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. Those skilled in the art can also clearly understand that the descriptions of the various embodiments of the present invention have different focuses. For the convenience and brevity of description, the same or similar parts may not be repeated in different embodiments. Therefore, for parts not described or not described in detail in a certain embodiment, refer to the records of other embodiments.

[0139] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0140] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a digital versatile disc (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)).

[0141] A person skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by a computer program to instruct the relevant hardware, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above-mentioned method embodiments. The aforementioned storage medium includes: a read-only memory (ROM) or a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

Claims

1. A method for monitoring safety of falling prevention during high-altitude operations, characterized in that: The method comprises: Obtain physiological sign data and work behavior data of personnel working at heights, usage status data of fall prevention devices, and environmental data; Determine human risk indicators based on the physiological signs and work behavior data of workers working at heights, determine equipment risk indicators based on the use status data of fall protection devices, and determine environmental risk indicators based on environmental data; The human risk index is determined based on the physiological sign data and work behavior data of the high-altitude workers, including: Obtain the physiological sign data of workers working at heights, including heart rate, blood pressure, weight and height, and calculate the physiological sign risk based on the physiological sign data: ； In the formula, Indicates physiological risk. , , , Respectively represent the standardized heart rate, blood pressure, weight and height; Obtain the work behavior data of high-altitude workers and calculate the work behavior risk based on the work behavior data: ； In the formula, Indicates the risk of operational behavior. Indicates the number of improper operations, satisfying Indicates improper operation; Indicates no improper operation; Indicates points for compliance with height work regulations. , Respectively represent weight factors; represents the base of natural logarithms; Calculate human risk index based on physiological sign risk and operational behavior risk: ； In the formula, Indicates human risk indicators; Determining the equipment risk index according to the usage status data of the fall prevention device includes: Calculate the meshing degree of the gear and rack in the fall arrest device: ； In the formula, Represents the meshing index of the gear and rack, , represent the loss rates of gear and rack respectively, Indicates The actual contact area between the pitch gear and the rack; Indicates Ideal contact area between the pitch gear and the rack; Calculate the suction force of the suction cup in the fall protection device: ； In the formula, Indicates the suction force of the suction cup. Indicates atmospheric pressure, Indicates the effective contact area between the bottom of the suction cup and the building. represents the effective contact radius; The equipment risk index is determined based on the meshing degree of the gear and rack in the anti-fall device and the suction force of the suction cup: ； In the formula, Represents the equipment risk indicator, Indicates the meshing degree reference value, They represent the weight of the person and the weight of the object carried by the fall protection device respectively; Determining environmental risk indicators based on environmental data includes: ； In the formula, Represents environmental risk indicators, They represent weight factors, Respectively represent the actual values ​​of temperature, humidity and wind speed in the current high-altitude operation; Respectively represent the reference values ​​of temperature, humidity and wind speed in the current high-altitude operation; Indicates any one or more of visibility deviation, snow thickness deviation, precipitation deviation and lightning risk; Determine whether there is a risk value of any one of the human risk index, the equipment risk index, and the environmental risk index that is greater than the corresponding first preset threshold; If yes, trigger an alarm prompt and generate a first operation guide, and push the first operation guide to the high-altitude operator; If not, determine the falling risk value based on the human risk index, equipment risk index and environmental risk index to determine whether the falling risk value is greater than the second preset threshold; when the falling risk value is greater than the second preset threshold, trigger an alarm prompt and generate a second operation guide, and push the second operation guide to the high-altitude workers.

2. The high-altitude work fall prevention safety monitoring method according to claim 1 is characterized in that: Determining the fall risk value according to the human risk index, the equipment risk index and the environmental risk index includes: Input the risk values ​​corresponding to the human risk index, equipment risk index and environmental risk index into a preset fall risk prediction model, and output the fall risk value; The fall risk prediction model is obtained by training using any one of logistic regression, random forest, support vector machine or neural network models.

3. The high-altitude work fall prevention safety monitoring method according to claim 1 is characterized in that: The generating of the first operation guide includes: When the risk values ​​of two or more indicators among the human risk indicators, equipment risk indicators and environmental risk indicators are greater than the corresponding first preset thresholds, the risk levels of the indicators are prioritized; Provide first operation guidance for different indicators in order of priority.

4. The high-altitude work fall prevention safety monitoring method according to claim 1 is characterized in that: The generating of the second operation guide comprises: When the fall risk value is greater than a second preset threshold, the fall risk level is divided according to the difference between the fall risk value and the second preset threshold; Different second operation instructions are matched according to different fall risk levels.

5. A high-altitude work anti-fall safety monitoring system, characterized in that: The system comprises: A data acquisition unit, used to acquire physiological sign data and work behavior data of personnel working at heights, use status data of anti-fall devices, and environmental data; An index determination unit is used to determine the human risk index based on the physiological sign data and work behavior data of the height workers, determine the equipment risk index based on the use status data of the fall protection device, and determine the environmental risk index based on the environmental data; The human risk index is determined based on the physiological sign data and work behavior data of the high-altitude workers, including: Obtain the physiological sign data of workers working at heights, including heart rate, blood pressure, weight and height, and calculate the physiological sign risk based on the physiological sign data: ； In the formula, Indicates physiological risk. , , , Respectively represent the standardized heart rate, blood pressure, weight and height; Obtain the work behavior data of high-altitude workers and calculate the work behavior risk based on the work behavior data: ； In the formula, Indicates the risk of operational behavior. Indicates the number of improper operations, satisfying Indicates improper operation; Indicates no improper operation; Indicates points for compliance with height work regulations. , Respectively represent weight factors; represents the base of natural logarithms; Calculate human risk index based on physiological sign risk and operational behavior risk: ； In the formula, Indicates human risk indicators; Determining the equipment risk index according to the usage status data of the fall prevention device includes: Calculate the meshing degree of the gear and rack in the fall arrest device: ； In the formula, Represents the meshing index of the gear and rack, , represent the loss rates of gear and rack respectively, Indicates The actual contact area between the pitch gear and the rack; Indicates Ideal contact area between the pitch gear and the rack; Calculate the suction force of the suction cup in the fall protection device: ； In the formula, Indicates the suction force of the suction cup. Indicates atmospheric pressure, Indicates the effective contact area between the bottom of the suction cup and the building. represents the effective contact radius; The equipment risk index is determined based on the meshing degree of the gear and rack in the anti-fall device and the suction force of the suction cup: ； In the formula, Represents the equipment risk indicator, Indicates the meshing degree reference value, They represent the weight of the person and the weight of the object carried by the fall protection device respectively; Determining environmental risk indicators based on environmental data includes: ； In the formula, Represents environmental risk indicators, They represent weight factors, Respectively represent the actual values ​​of temperature, humidity and wind speed in the current high-altitude operation; Respectively represent the reference values ​​of temperature, humidity and wind speed in the current high-altitude operation; Indicates any one or more of visibility deviation, snow thickness deviation, precipitation deviation and lightning risk; An operation guide generating unit, used for judging whether a risk value of any one of the human risk index, the equipment risk index and the environmental risk index is greater than a corresponding first preset threshold value; If yes, trigger an alarm prompt and generate a first operation guide, and push the first operation guide to the high-altitude operator; If not, determine the falling risk value based on the human risk index, equipment risk index and environmental risk index to determine whether the falling risk value is greater than the second preset threshold; when the falling risk value is greater than the second preset threshold, trigger an alarm prompt and generate a second operation guide, and push the second operation guide to the high-altitude workers.

6. An electronic device, characterized in that: include: A processor and a memory, wherein the memory is used to store computer program codes, wherein the computer program codes include computer instructions. When the processor executes the computer instructions, the electronic device executes the high-altitude work fall prevention safety monitoring method as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which includes program instructions. When the program instructions are executed by a processor of an electronic device, the processor executes the high-altitude work fall prevention safety monitoring method as described in any one of claims 1 to 4.

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