CN117422425B - On-site potential safety hazard management method and system based on instant messaging - Google Patents

Abstract

The present invention discloses a method and system for managing on-site safety hazards based on instant messaging: based on the monitoring data of the first device, it is determined whether the first device has an abnormality, if an abnormality occurs, the type of safety hazard is identified, a topological route for troubleshooting and the content of the hidden danger troubleshooting of each detection node are generated, and then the safety hazard, the topological route for troubleshooting and the content of the hidden danger troubleshooting of each detection node are sent to the instant messaging client of the regional person in charge of the area where the first device is located, and the regional person in charge makes an instruction. When a positive instruction is obtained, the abnormality handling personnel who handles the safety hazard will check the safety hazard, and send the inspection result to the instant messaging client of the regional person in charge. When a negative instruction is obtained, the potential failure risk of the first device is calculated and sent to the instant messaging client of the regional person in charge. The technical solution of the present invention reduces the cost of safety hazard management and improves the efficiency of on-site hidden danger troubleshooting, governance and rectification.

Description

A method and system for managing on-site safety hazards based on instant messaging

Technical Field

The present invention belongs to the field of communication technology, and in particular relates to an on-site safety hazard management method and system based on instant messaging.

Background technique

At present, the scale of construction projects such as domestic building construction projects, rail transit projects, municipal projects, road and bridge projects is large. The inspection of safety and quality hazards mainly relies on inspections by safety working groups, or monitoring by back-end personnel through video surveillance and manual safety work inspections. Not only is the work intensity high, but the human factor has a great influence when conducting safety hazard inspections, resulting in low identification efficiency and accuracy.

With the development of digital and intelligent technology, it is an important research direction to protect production safety through information technology, improve production safety benefits, and reduce the risk of safety accidents. In the prior art, for example, Chinese patent application CN112488376A discloses a method and system for the control of safety hazards at the work site, which obtains the location area information and safety hazard content data of the location where the safety hazard exists, obtains the operation safety information matching the location area information according to the location area information, and extracts the characteristics of the safety hazard content data according to the preset identification method according to the type of the safety hazard content data, obtains the safety hazard characteristic data, and matches the safety hazard characteristic data with the operation safety information to determine the safety hazard result. This method determines whether there is a safety hazard by matching the safety hazard characteristic data with the operation safety information, and does not analyze and investigate the cause of the safety hazard based on the judgment result, so the safety hazard control is not comprehensive enough. Another example is China's application CN116486343A, which discloses a method for identifying safety hazards at infrastructure sites. It configures the types of safety hazards that need to be monitored and identified and the corresponding safety hazard identification strategies; obtains the monitoring area image, configures the areas involved in the monitoring area image and the types of safety hazards involved; obtains the real-time monitoring area image, and uses the safety hazard identification strategy to match and analyze the safety hazards involved in the real-time monitoring area image; and communicates the analysis results of the identified safety hazards to the monitoring and early warning terminal. This method notifies the monitoring and early warning terminal of the results after identifying the safety hazards, which will cause problems such as low efficiency in the implementation of the management system and decreasing effectiveness when communicating layer by layer.

Therefore, it is an urgent problem to provide an on-site safety hazard management method and system based on instant messaging to reduce the cost of safety hazard rectification and management, reduce distrust in safety hazard investigation and management, make on-site safety hazard handling more transparent and convenient, establish a responsibility implementation mechanism, and improve the efficiency of on-site hazard investigation, management and rectification.

Summary of the invention

In response to the above-mentioned technical problems, the present invention provides an on-site safety hazard management method and system based on instant messaging.

In a first aspect, the present invention provides a method for managing on-site safety hazards based on instant messaging, the method comprising:

Step 1: The on-site safety management platform obtains monitoring data of the first device, and determines whether an abnormality occurs in the first device based on the monitoring data;

Step 2: If the first device is abnormal, the on-site safety management platform identifies the safety hazard of the first device and generates a hazard investigation topology route and hazard investigation content for each detection node;

Step 3: search the first personnel information table based on the location information of the first device, obtain the information of the regional person in charge of the area where the first device is located, and then send the safety hazard, the hazard investigation topological route and the hazard investigation content of each detection node to the instant messaging client of the regional person in charge, and the regional person in charge will issue instructions on the hazard investigation topological route and the hazard investigation content of each detection node;

Step 4: If a positive reply is received, proceed to step 5; if a negative reply is received, proceed to step 6;

Step 5: search the second personnel information table based on the location information and the safety hazard, obtain the information of the exception handling personnel who handles the safety hazard, and have the exception handling personnel check the safety hazard. After the check is completed, send the check result to the instant messaging client of the regional person in charge;

Step 6: Calculate the potential failure risk of the first device and send it to the instant messaging client of the regional manager.

Specifically, in step 1, judging whether an abnormality occurs in the first device based on the monitoring data includes:

Step 11: Obtain the nth monitoring data in the monitoring data, extract M monitoring data related to the nth monitoring data from the monitoring data, and calculate the estimated monitoring value of the nth monitoring device based on the M monitoring data. The calculation formula is:

,

Among them, EV _n is the estimated monitoring value of the nth monitoring device, is the parameter weight coefficient, AV _m is the mth monitoring data among M monitoring data, k is a natural number, A is a constant, n is a positive integer from 1 to N, N is the total number of monitoring data, M is the total number of monitoring data related to the nth monitoring data, and the nth monitoring device is the monitoring device that obtains the nth monitoring data;

Step 12: Calculate the monitoring accuracy of the nth monitoring device at the current moment based on the nth monitoring data and the estimated monitoring value of the nth monitoring device. The calculation formula is:

,

Wherein, _ACn is the monitoring accuracy of the nth monitoring device at the current moment, and _AVn is the nth monitoring data;

Step 13, obtaining N1 monitoring accuracies of the nth monitoring device within the first preset time from the first storage module, and determining whether the data state of the nth monitoring data is fluctuating, if so, determining the data state of the nth monitoring data as fluctuating, and then proceeding to step 15; if not, proceeding to step 14, wherein the N1 monitoring accuracies include the monitoring accuracy of the nth monitoring device at the current moment;

Step 14, calculating the number of N1 monitoring accuracies that are greater than or equal to the first preset value, if the number is greater than or equal to the second preset value, determining that the data state of the nth monitoring data is normal, if the number is less than the second preset value, determining that the data state of the nth monitoring data is abnormal;

Step 15, after traversing all monitoring data, if there is monitoring data with abnormal data status, determine that the first device is abnormal; if not, determine whether there is monitoring data with fluctuating data status; if so, determine that there is fluctuation in the first device; otherwise, determine that the first device is normal.

Specifically, in step 13, determining whether the data state of the nth monitoring data is fluctuating includes:

Step 131, obtaining N1 monitoring data of the nth monitoring device within a first preset time, wherein the N1 monitoring data include the nth monitoring data;

Step 132, respectively calculating the difference between the nth monitoring data and other monitoring data in N1 monitoring data, and calculating the first root mean square error of N1 monitoring accuracy of the nth monitoring device;

Step 133: When any difference is greater than the first root mean square error, it is determined that the data state of the nth monitoring data is fluctuation.

Specifically, when the number of times the first device is determined to fluctuate within the second preset time is greater than or equal to a third preset value, it is determined that the first device is abnormal.

Specifically, based on the abnormal monitoring data of the first device, the potential safety hazard is determined. In step 2, generating a potential safety hazard troubleshooting topology route includes:

Step 21, searching the second storage module based on the safety hazard, obtaining abnormal diagnosis information corresponding to the safety hazard, wherein the abnormal diagnosis information is a layered set of detection items, the first layer is the safety hazard, the detection item connected to any detection item of the i-th layer and the i-1-th layer is the abnormal cause of any detection item, the number of detection items connected to the i-th layer and the p-th detection item of the i-1-th layer is TI _i,p , wherein i is a positive integer greater than or equal to 2, p is a positive integer greater than or equal to 1, and TI _i,p is a positive integer greater than or equal to 1;

Step 22: Obtain all detection items in the abnormal diagnosis information, and generate a topological route set including all detection steps, wherein a detection node in each topological route corresponds to a detection item;

Step 23: Calculate the inspection cost of each topological route respectively, and use the topological route with the minimum inspection cost as the hidden danger inspection topological route.

Specifically, the first position of the exception handling personnel is obtained. In step 23, the troubleshooting cost calculation method of each topological route is:

Step 231, obtaining the g-th topological route in the topological route set, and then obtaining the second position of each detection node in the g-th topological route, where g is a positive integer from 1 to G, and G is the total number of all topological routes in the topological route set;

Step 232: Calculate the distance from the exception handling personnel to the initial node of the g-th topological route, and calculate the distance between any two connected detection nodes in the g-th topological route;

Step 233: Obtain the initial node of the g-th topological route, and calculate the route cost at the initial node. The calculation formula is:

,

in, and/> is the parameter weight coefficient, PC _r is the route cost at the initial node, D _t,r is the distance from the abnormality handler to the initial node, and MC _r is the detection cost of the initial node;

Step 234: Obtain the qth detection node of the gth topological route, and calculate the route cost at the qth detection node. The calculation formula is:

,

Wherein, PC _q is the route cost at the qth detection node, D _q-1,q is the distance from the q-1th detection node to the qth detection node, MC _q is the detection cost of the qth detection node, PC _q-1 is the route cost at the q-1th detection node, q is a positive integer from 2 to Q, Q is the total number of detection nodes of the gth topological route, and the first detection node of the gth topological route is the initial node;

Step 235: determine whether the qth detection node is a leaf node. If not, set q=q+1 and return to step 234. If yes, obtain the probability of an abnormality occurring at the qth detection node. Calculate the branch inspection cost at the qth detection node based on the probability of an abnormality occurring at the qth detection node and the route cost at the qth detection node. The calculation formula is:

,

Where, CI _q is the branch inspection cost at the qth detection node, PA _q is the probability of an abnormality occurring at the qth detection node,

Then determine whether q is equal to Q. If not, set q=q+1 and return to step 234. If yes, proceed to step 236.

Step 236: After traversing all detection nodes in the g-th topological route, calculate the inspection cost of the g-th topological route. The calculation formula is:

,

Among them, PC _g is the inspection cost of the g-th topological route, j is a positive integer from 1 to J, J is the total number of leaf nodes in the g-th topological route, and CI _j is the branch inspection cost at the j-th leaf node.

Specifically, in step 5, the safety hazard investigation by the exception handling personnel includes:

Step 51: Obtain the initial node of the hidden danger investigation topology route, and define the initial node as an analysis node;

Step 52: determine whether the analysis node is a leaf node. If not, proceed to step 53; if so, proceed to step 55;

Step 53: Obtain the first operation content corresponding to the detection item at the analysis node, send the location of the analysis node and the first operation content to the instant messaging client of the exception handling personnel, and obtain the detection result;

Step 54: According to the detection result, a detection node corresponding to the detection result is selected from the lower layer detection nodes connected to the analysis node as the detection node to be analyzed, and the detection node to be analyzed is defined as the analysis node, and the process returns to step 52;

Step 55: determine that the detection item at the analysis node is the cause of the safety hazard, obtain the abnormal recovery operation content corresponding to the detection item at the analysis node, and send the location of the analysis node and the abnormal recovery operation content to the instant messaging client of the abnormality handler.

In a second aspect, the present invention further provides an on-site safety hazard management system based on instant messaging, the system comprising: a first device, a monitoring device, an on-site safety management platform and an instant messaging client, the monitoring device is used to collect monitoring data of the first device, and the on-site safety management platform comprises an abnormality judgment module, a route generation module, a troubleshooting instruction module, a hidden danger troubleshooting module and a risk calculation module;

An abnormality judgment module, used to obtain monitoring data of the first device, and judge whether an abnormality occurs in the first device based on the monitoring data;

A route generation module, used to identify the safety hazards of the first device when the first device is abnormal, and generate a hazard troubleshooting topology route and hazard troubleshooting content for each detection node;

The inspection and instruction module is used to search the first personnel information table based on the location information of the first device, obtain the information of the regional person in charge of the area where the first device is located, and then send the safety hazards, the hazard inspection topological route and the hazard inspection content of each detection node to the instant messaging client of the regional person in charge, and the regional person in charge will inspect and handle the hazard inspection topological route and the hazard inspection content of each detection node;

The hidden danger investigation module is used to search the second personnel information table based on the location information and the hidden dangers when a positive reply is received, and obtain the information of the exception handling personnel who handles the hidden dangers. The exception handling personnel will investigate the hidden dangers and send the investigation results to the instant messaging client of the regional person in charge after the investigation is completed;

The risk calculation module is used to calculate the potential failure risk of the first device when a negative reply is received, and send the calculated risk to the instant messaging client of the regional person in charge.

The present invention discloses a method and system for managing on-site safety hazards based on instant messaging. Based on the monitoring data of the first device, it is judged whether the first device is abnormal. By replacing manual monitoring with data analysis, the efficiency and accuracy of the hidden danger analysis are improved. If an abnormality occurs, the safety hazard of the first device is identified, and a hidden danger investigation topological route and hidden danger investigation content for each detection node are generated. The safety hazard, the hidden danger investigation topological route and the hidden danger investigation content for each detection node are sent to the instant messaging client of the regional person in charge of the area where the first device is located for approval. After the approval is passed, the abnormality handling personnel responsible for handling the safety hazard in the area where the first device is located are required to investigate the safety hazard. If the approval is not passed, the potential failure risk of the first device is sent to the instant messaging client of the regional person in charge to remind again. Through the technical solution of the present invention, the rectification and management costs of safety hazards can be reduced, the distrust of safety hazard investigation and management can be reduced, the on-site safety hazard handling can be made more transparent and convenient, and a good responsibility implementation mechanism can be established, thereby improving the on-site hidden danger investigation, management and rectification.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below. Obviously, the drawings in the following description are only embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on the provided drawings without creative work.

FIG1 is a flow chart of an on-site safety hazard management method based on instant messaging according to the present invention;

FIG2 is a schematic diagram of the structure of abnormal diagnosis information in an embodiment of the present invention;

FIG3a is a schematic diagram of a first structure of a topology circuit according to an embodiment of the present invention;

FIG3b is a schematic diagram of a second structure of a topology circuit according to an embodiment of the present invention;

FIG. 4 is a schematic structural diagram of an on-site safety hazard management system based on instant messaging according to the present invention.

Detailed ways

In order to make the purpose, technical scheme and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. Obviously, the specific embodiments described herein are only used to explain the present invention and are part of the embodiments of the present invention, rather than all of 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.

It should be noted that if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

FIG1 is a flow chart of an embodiment of a method for managing potential safety hazards on site based on instant messaging provided by the present invention, and the flow chart specifically includes:

Step 1: The on-site safety management platform obtains monitoring data of the first device, and determines whether an abnormality occurs in the first device based on the monitoring data.

Exemplarily, the first device is a monitoring target for potential safety hazards monitoring, including electronic and electrical equipment, building facilities, etc.

Specifically, in step 1, judging whether an abnormality occurs in the first device based on the monitoring data includes:

Step 11: Obtain the nth monitoring data in the monitoring data, extract M monitoring data related to the nth monitoring data from the monitoring data, and calculate the estimated monitoring value of the nth monitoring device based on the M monitoring data. The calculation formula is:

,

Among them, EVn is the estimated monitoring value of the nth monitoring device, is the parameter weight coefficient, AVm is the mth monitoring data among M monitoring data, k is a natural number, A is a constant, n is a positive integer from 1 to N, N is the total number of monitoring data, M is the total number of monitoring data related to the nth monitoring data, and the nth monitoring device is the monitoring device that obtains the nth monitoring data.

Step 12: Calculate the monitoring accuracy of the nth monitoring device at the current moment based on the nth monitoring data and the estimated monitoring value of the nth monitoring device. The calculation formula is:

,

Among them, ACn is the monitoring accuracy of the nth monitoring device at the current moment, and AVn is the nth monitoring data.

Step 13, obtain N1 monitoring accuracies of the nth monitoring device within the first preset time from the first storage module, and determine whether the data state of the nth monitoring data is fluctuating. If so, determine the data state of the nth monitoring data as fluctuating, and then enter step 15; if not, enter step 14, wherein the N1 monitoring accuracies include the monitoring accuracy of the nth monitoring device at the current moment.

Step 14, calculate the number of N1 monitoring accuracies that are greater than or equal to the first preset value. If the number is greater than or equal to the second preset value, the data state of the nth monitoring data is determined to be normal; if the number is less than the second preset value, the data state of the nth monitoring data is determined to be abnormal.

Step 15, after traversing all monitoring data, if there is monitoring data with abnormal data status, determine that the first device is abnormal; if not, determine whether there is monitoring data with fluctuating data status; if so, determine that there is fluctuation in the first device; otherwise, determine that the first device is normal.

The total number N of monitoring data, the first preset time, the first preset value and the second preset value are set according to the experience of technical personnel in this field or according to the actual application scenario, and the embodiments of the present application are not limited to this.

There are multiple monitoring devices for the same monitoring target, and the monitoring target is monitored from multiple angles. Therefore, there is a certain correlation between the monitoring data obtained by each monitoring device. According to the technical solution of the present invention, for any monitoring device, the estimated monitoring value of the monitoring device is calculated on the basis of considering the causal relationship between its monitoring data and other monitoring data, and then the monitoring accuracy of the nth monitoring device at the current moment is calculated based on the estimated monitoring value and the actual monitoring data. Finally, it is judged whether the monitoring data of the monitoring device is abnormal based on the number of monitoring accuracies greater than or equal to the first preset value within the first preset time, thereby improving the accuracy of data abnormality judgment. Before judging whether the monitoring data is normal or abnormal, first judge whether the monitoring data has fluctuations (i.e., noise). If it is fluctuating data, no normal or abnormal judgment is made, and the monitoring data is defined as fluctuation. If it is not fluctuating data, normal or abnormal judgment is made, further improving the accuracy of normal and abnormal judgment.

Exemplarily, the monitoring device is a sensor.

Preferably, the calculation formula for the estimated monitoring value for any monitoring device is trained in advance and stored in the storage module in association with the identification of the monitoring device.

Preferably, after acquiring the monitoring data, any monitoring data, the time when the monitoring data is acquired, the estimated monitoring value corresponding to the monitoring data, and the monitoring accuracy are stored correspondingly.

As a preferred technical solution of the present invention, in step 1, judging whether an abnormality occurs in the first device based on the monitoring data includes:

Obtain the nth monitoring data in the monitoring data, extract M monitoring data related to the nth monitoring data from the monitoring data, and calculate the estimated monitoring value of the nth monitoring device based on the M monitoring data. The calculation formula is:

,

Among them, EVn is the estimated monitoring value of the nth monitoring device, is the parameter weight coefficient, AVm is the mth monitoring data among M monitoring data, k is a natural number, A is a constant, n is a positive integer from 1 to N, N is the total number of monitoring data, M is the total number of monitoring data related to the nth monitoring data, and the nth monitoring device is the monitoring device that obtains the nth monitoring data;

The monitoring accuracy of the nth monitoring device at the current moment is calculated based on the nth monitoring data and the estimated monitoring value of the nth monitoring device. The calculation formula is:

,

Among them, ACn is the monitoring accuracy of the nth monitoring device at the current moment, and AVn is the nth monitoring data;

Obtaining N1 monitoring accuracies of the nth monitoring device within the first preset time from the first storage module, calculating the number of the N1 monitoring accuracies that are greater than or equal to the first preset value, and if the number is greater than or equal to the second preset value, determining that the data state of the nth monitoring data is normal; if the number is less than the second preset value, determining that the data state of the nth monitoring data is abnormal, wherein the N1 monitoring accuracies include the monitoring accuracy of the nth monitoring device at the current moment;

After traversing all monitoring data, if there is monitoring data with an abnormal data status, it is determined that the first device is abnormal, otherwise it is determined that the first device is normal.

In this preferred technical solution, normal fluctuations are not taken into account, and whether the monitoring data of the monitoring device is abnormal is judged only based on the number of monitoring accuracies greater than or equal to the first preset value within the first preset time.

Specifically, in step 13, determining whether the data state of the nth monitoring data is fluctuating includes:

Step 131, obtaining N1 monitoring data of the nth monitoring device within a first preset time, wherein the N1 monitoring data include the nth monitoring data;

Step 132, respectively calculating the difference between the nth monitoring data and other monitoring data in N1 monitoring data, and calculating the first root mean square error of N1 monitoring accuracies of the nth monitoring device;

Step 133: When any difference is greater than the first root mean square error, it is determined that the data state of the nth monitoring data is fluctuation.

Specifically, when the number of times the first device is determined to fluctuate within the second preset time is greater than or equal to a third preset value, it is determined that the first device is abnormal.

Step 2: If the first device is abnormal, the on-site safety management platform identifies the safety hazard of the first device and generates a hazard investigation topology route and hazard investigation content for each detection node.

Specifically, based on the abnormal monitoring data of the first device, the potential safety hazard is determined. In step 2, generating a potential safety hazard troubleshooting topology route includes:

Step 21. Search the second storage module based on the safety hazard to obtain abnormal diagnosis information corresponding to the safety hazard, wherein the abnormal diagnosis information is a layered set of detection items, the first layer is the safety hazard, the detection item connected to any detection item of the i-th layer and the i-1-th layer is the abnormal cause of any detection item, and the number of detection items connected to the i-th layer and the p-th detection item of the i-1-th layer is TI _i,p , wherein i is a positive integer greater than or equal to 2, p is a positive integer greater than or equal to 1, and TI _i,p is a positive integer greater than or equal to 1.

Step 22: Obtain all detection items in the abnormal diagnosis information, and generate a topological route set including all detection steps, wherein a detection node in each topological route corresponds to a detection item.

Step 23: Calculate the inspection cost of each topological route respectively, and use the topological route with the minimum inspection cost as the hidden danger inspection topological route.

As shown in Figure 2, the technical solution of the present invention is explained by taking the abnormal diagnosis information as 3 layers as an example. The first layer is the safety hazard (safety hazard name/safety hazard type/safety hazard type), and the second layer contains two branches, detection item 1 and detection item 2, wherein detection item 1 contains three branches, detection item 11, detection item 12 and detection item 13 (detection item 11, detection item 12 and detection item 13 are located in the third layer), and detection item 2 has no branches. All detection items in the abnormal diagnosis information include detection item 1, detection item 2, detection item 11, detection item 12 and detection item 13. The abnormal causes of the above-mentioned safety hazards are detection item 1 and detection item 2, and the abnormal causes of detection item 1 are detection item 11, detection item 12 and detection item 13. Therefore, when generating the topological line, detection item 1 can be detected, or detection item 11, detection item 12 and detection item 13 can be detected directly without detecting detection item 1.

As shown in FIG. 3 a , the generation of the topology line is described by taking the initial detection node as the detection item 11 as an example. Take detection item 11 as the initial node (i.e., the first detection node). When the detection result of the detection item of the initial node is true, the detection node is transferred to the second detection node (leaf node), and the detection item corresponding to the second detection node is detection item 11 (since the second detection node is a leaf node, if the detection result of the detection item of the initial node is true, detection item 11 is the abnormal cause of the safety hazard). When the detection result of the detection item of the initial node is false, the detection node is transferred to the third detection node (non-leaf node), and the detection item corresponding to the third detection node is detection item 2; when the detection result of the detection item of the third detection node is true, the detection node is transferred to the fourth detection node (leaf node), and the detection item corresponding to the fourth detection node is detection item 2; when the detection result of the detection item of the third detection node is false, the detection node is transferred to the fifth detection node (non-leaf node), and the detection item corresponding to the fifth detection node is detection item 12; when the detection result of the detection item of the fifth detection node is true, the detection node is transferred to the sixth detection node (leaf node), and the detection item corresponding to the sixth detection node is detection item 12; when the detection result of the detection item of the fifth detection node is false, the detection node is transferred to the seventh detection node (leaf node), and the detection item corresponding to the seventh detection node is detection item 13.

As shown in FIG. 3 b , the generation of the topology line is described by taking the initial detection node as detection item 1 as an example. Take detection item 1 as the initial node (i.e., the first detection node). When the detection result of the detection item of the initial node is true, transfer to the second detection node (non-leaf node), and the detection item corresponding to the second detection node is detection item 11. When the detection result of the detection item of the initial node is false, transfer to the third detection node (leaf node), and the detection item corresponding to the third detection node is detection item 2 (since the third detection node is a leaf node, if the detection result of the detection item of the initial node is true, detection item 2 is the abnormal cause of the safety hazard); when the detection result of the detection item of the second detection node is true, transfer to the fourth detection node (leaf node), and the detection item corresponding to the fourth detection node is detection item 11. When the detection result of the detection item of the second detection node is false, transfer to the fifth detection node (non-leaf node), and the detection item corresponding to the fifth detection node is detection item 12; when the detection result of the detection item of the fifth detection node is true, transfer to the sixth detection node (leaf node), and the detection item corresponding to the sixth detection node is detection item 12. When the detection result of the detection item of the fifth detection node is false, transfer to the seventh detection node (leaf node), and the detection item corresponding to the seventh detection node is detection item 13. The topological line may also use detection item 2 or detection item 12 as the initial node.

Specifically, the first position of the exception handling personnel is obtained. In step 23, the troubleshooting cost calculation method of each topological route is:

Step 231: obtain the g-th topological route in the topological route set, and then obtain the second position of each detection node in the g-th topological route, where g is a positive integer from 1 to G, and G is the total number of all topological routes in the topological route set.

Step 232: Calculate the distance from the exception handling personnel to the initial node of the g-th topological route, and calculate the distance between any two connected detection nodes in the g-th topological route.

Step 233: Obtain the initial node of the g-th topological route, and calculate the route cost at the initial node. The calculation formula is:

,

in, and/> is the parameter weight coefficient, PC _r is the route cost at the initial node, D _t,r is the distance from the exception handler to the initial node, and MC _r is the detection cost of the initial node.

Step 234: Obtain the qth detection node of the gth topological route, and calculate the route cost at the qth detection node. The calculation formula is:

,

Among them, PC _q is the route cost at the qth detection node, D _q-1,q is the distance from the q-1th detection node to the qth detection node, MC _q is the detection cost of the qth detection node, PC _q-1 is the route cost at the q-1th detection node, q is a positive integer from 2 to Q, Q is the total number of detection nodes on the gth topological route, and the first detection node of the gth topological route is the initial node.

Step 235: determine whether the qth detection node is a leaf node. If not, set q=q+1 and return to step 234. If yes, obtain the probability of an abnormality occurring at the qth detection node. Calculate the branch inspection cost at the qth detection node based on the probability of an abnormality occurring at the qth detection node and the route cost at the qth detection node. The calculation formula is:

,

Where, CI _q is the branch inspection cost at the qth detection node, PA _q is the probability of an abnormality occurring at the qth detection node,

Then determine whether q is equal to Q. If not, set q=q+1 and return to step 234. If so, go to step 236.

Step 236: After traversing all detection nodes in the g-th topological route, calculate the inspection cost of the g-th topological route. The calculation formula is:

,

Among them, PC _g is the inspection cost of the g-th topological route, j is a positive integer from 1 to J, J is the total number of leaf nodes in the g-th topological route, and CI _j is the branch inspection cost at the j-th leaf node.

When calculating the inspection cost of each topological route, the distance from the exception handling personnel to the initial node of the topological route, the distance between each detection node, the detection cost of each detection node and the probability of an abnormality in the detection item corresponding to each node are taken into consideration. This ensures that safety hazards are promptly and quickly inspected while reducing the cost of safety hazard inspection and the cost of safety hazard rectification.

Step 3. Search the first personnel information table based on the location information of the first device to obtain the information of the regional person in charge of the area where the first device is located, and then send the safety hazards, hazard inspection topology routes and hazard inspection contents of each detection node to the instant messaging client of the regional person in charge. The regional person in charge will instruct on the hazard inspection topology routes and hazard inspection contents of each detection node.

Preferably, the topological lines are sorted according to the inspection cost of each topological line, the first N2 topological lines are selected, the probability of failure of each detection node on each topological line and the time of the last inspection are respectively marked, and the marked first N2 topological lines are sent to the regional person in charge, who selects the topological line for hidden danger inspection.

Step 4: If you get a positive response, go to step 5; if you get a negative response, go to step 6.

Step 5: Search the second personnel information table based on the location information and safety hazards to obtain the information of the exception handling personnel who handle the safety hazards. The exception handling personnel will check the safety hazards and send the results to the instant messaging client of the regional manager after the check is completed.

Preferably, the troubleshooting results include the causes of the potential safety hazard and the operation results of the exception handling personnel.

According to the technical solution of the present invention, the location of the first device is first obtained, and based on the location, the information of the regional person in charge of the area where the first device is located is obtained. The regional person in charge approves the hidden danger investigation topological route and the hidden danger investigation content of each detection node. After approval, the abnormal handling personnel who handle the above-mentioned safety hazards in the area where the first device is located will investigate the safety hazards, thereby establishing a good responsibility implementation mechanism and improving the on-site hidden danger investigation, management and rectification.

Specifically, in step 5, the safety hazard investigation by the exception handling personnel includes:

Step 51: Obtain the initial node of the hidden danger investigation topology route, and define the initial node as an analysis node.

Step 52: determine whether the analysis node is a leaf node. If not, proceed to step 53; if so, proceed to step 55.

Step 53: Obtain the first operation content corresponding to the detection item at the analysis node, send the location of the analysis node and the first operation content to the instant messaging client of the exception handling personnel, and obtain the detection result.

Step 54 , according to the detection result, select a detection node corresponding to the detection result from the lower layer detection nodes connected to the analysis node as the detection node to be analyzed, define the detection node to be analyzed as the analysis node, and return to step 52 .

Step 55: determine that the detection item at the analysis node is the cause of the safety hazard, obtain the abnormal recovery operation content corresponding to the detection item at the analysis node, and send the location of the analysis node and the abnormal recovery operation content to the instant messaging client of the abnormality handler.

After the exception handling personnel moves to the analysis node, they perform a detection based on the first operation content corresponding to the analysis node and feed back the detection result (true or false) to the on-site safety management platform. The on-site safety management platform sends the location of the next node to be analyzed and the first operation content corresponding to the node to be analyzed to the exception handling personnel's instant messaging client along the hidden danger investigation topology route based on the detection result. This confirmation is repeated until the abnormal cause causing the safety hazard is found. Subsequently, the safety hazard is rectified and restored according to the abnormal recovery operation content at the abnormal cause.

According to the technical solution of the present invention, the next node to be detected and the operation content are allocated based on the detection results of the exception handling personnel, which can achieve zero-distance and refined guidance on the handling of on-site safety hazards, making the handling of on-site safety hazards more convenient and clear.

Step 6: Calculate the potential failure risk of the first device and send it to the instant messaging client of the regional manager.

Exemplarily, the potential failure risk of the first device is calculated according to the economic loss and impact caused by the failure of the first device.

Fig. 4 is a schematic diagram of the structure of an embodiment of an on-site safety hazard management system based on instant messaging provided by the present invention. As shown in Fig. 4, the system includes: a first device 10, a monitoring device 20, an on-site safety management platform 30 and an instant messaging client 40, the monitoring device 20 is used to collect monitoring data of the first device 10, and the on-site safety management platform 30 includes an abnormality judgment module 301, a route generation module 302, a troubleshooting instruction module 303, a hidden danger troubleshooting module 304 and a risk calculation module 305.

The abnormality determination module 301 is used to obtain monitoring data of the first device 10 and determine whether an abnormality occurs in the first device based on the monitoring data.

The route generation module 302 is used to identify the safety hazards of the first device 10 when the first device 10 is abnormal, and generate a hazard troubleshooting topology route and hazard troubleshooting content for each detection node.

The inspection and approval module 303 is used to search the first personnel information table based on the location information of the first device 10, obtain the information of the regional person in charge of the area where the first device is located, and then send the safety hazards, hazard inspection topological routes and hazard inspection contents of each detection node to the instant messaging client 40 of the regional person in charge, who will approve the hazard inspection topological routes and hazard inspection contents of each detection node.

The hidden danger investigation module 304 is used to search the second personnel information table based on the location information and the safety hazard when a positive reply is received, and obtain the information of the exception handling personnel who handles the safety hazard. The exception handling personnel will investigate the safety hazard. After the investigation is completed, the investigation results will be sent to the instant messaging client of the area manager.

The risk calculation module 305 is used to calculate the potential failure risk of the first device 10 when a negative reply is received, and send the calculated risk to the instant messaging client 40 of the regional person in charge.

It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have strict order restrictions, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the above-mentioned program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and/or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

The above-mentioned embodiments only express the preferred implementation mode of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims (6)

1. A method for managing potential safety hazards on site based on instant messaging, comprising the following steps: Step 1: The on-site safety management platform obtains monitoring data of a first device, and determines whether an abnormality occurs in the first device based on the monitoring data; Step 2: If the first device is abnormal, the on-site safety management platform identifies the safety hazard of the first device and generates a hazard troubleshooting topology route and hazard troubleshooting content for each detection node; Step 3: searching the first personnel information table based on the location information of the first device, obtaining the information of the regional person in charge of the area where the first device is located, and then sending the safety hazard, the hazard investigation topological route, and the hazard investigation content of each detection node to the instant messaging client of the regional person in charge, and the regional person in charge shall approve and process the hazard investigation topological route and the hazard investigation content of each detection node; Step 4: If a positive reply is received, proceed to step 5; if a negative reply is received, proceed to step 6; Step 5: searching the second personnel information table based on the location information and the potential safety hazard, obtaining the information of the exception handling personnel who handles the potential safety hazard, and having the exception handling personnel check the potential safety hazard. After the check is completed, the check result is sent to the instant messaging client of the person in charge of the area; Step 6: Calculate the potential failure risk of the first device and send it to the instant messaging client of the regional person in charge; The potential safety hazard is determined based on abnormal monitoring data of the first device. In step 2, generating a potential safety hazard troubleshooting topology route includes: Step 21, searching the second storage module based on the safety hazard to obtain abnormal diagnosis information corresponding to the safety hazard, wherein the abnormal diagnosis information is a layered set of detection items, the first layer is the safety hazard, the detection item connected to any detection item of the i-th layer and the i-1-th layer is the abnormal cause of any of the detection items, the number of detection items connected to the i-th layer and the p-th detection item of the i-1-th layer is TI _i,p , wherein i is a positive integer greater than or equal to 2, p is a positive integer greater than or equal to 1, and TI _i,p is a positive integer greater than or equal to 1; Step 22: Obtain all detection items in the abnormal diagnosis information, and generate a topological route set including all detection steps, wherein one detection node in each topological route corresponds to one detection item; Step 23: Calculate the troubleshooting cost of each topological route respectively, and use the topological route with the minimum troubleshooting cost as the hidden danger troubleshooting topological route; The first position of the exception handling personnel is obtained. In step 23, the method for calculating the troubleshooting cost of each topological route is: Step 231, obtaining the g-th topological route in the topological route set, and then obtaining the second position of each detection node in the g-th topological route, wherein g is a positive integer from 1 to G, and G is the total number of all topological routes in the topological route set; Step 232: Calculate the distance from the exception handling personnel to the initial node of the g-th topological route, and calculate the distance between any two connected detection nodes in the g-th topological route; Step 233: Obtain the initial node of the g-th topological route, and calculate the route cost at the initial node. The calculation formula is: , Wherein, and are parameter weight coefficients, PC _r is the route cost at the initial node, D _t,r is the distance from the exception handling personnel to the initial node, and MC _r is the detection cost of the initial node; Step 234: Obtain the qth detection node of the gth topological route, and calculate the route cost at the qth detection node. The calculation formula is: , Wherein, PC _q is the route cost at the qth detection node, D _q-1,q is the distance from the q-1th detection node to the qth detection node, MC _q is the detection cost of the qth detection node, PC _q-1 is the route cost at the q-1th detection node, q is a positive integer from 2 to Q, Q is the total number of detection nodes of the gth topological route, and the first detection node of the gth topological route is the initial node; Step 235: determine whether the qth detection node is a leaf node. If not, set q=q+1 and return to step 234. If yes, obtain the probability of an abnormality occurring at the qth detection node. Calculate the branch inspection cost at the qth detection node based on the probability of an abnormality occurring at the qth detection node and the route cost at the qth detection node. The calculation formula is: , Wherein, CI _q is the branch inspection cost at the qth detection node, PA _q is the probability of abnormality occurring at the qth detection node, Then determine whether q is equal to Q. If not, set q=q+1 and return to step 234. If yes, proceed to step 236. Step 236: After traversing all detection nodes in the g-th topological route, calculate the inspection cost of the g-th topological route, and the calculation formula is: , Among them, PC _g is the inspection cost of the g-th topological route, j is a positive integer from 1 to J, J is the total number of leaf nodes in the g-th topological route, and CI _j is the branch inspection cost at the j-th leaf node. 2. The on-site safety hazard management method based on instant messaging according to claim 1, characterized in that in step 1, judging whether an abnormality occurs in the first device based on the monitoring data comprises: Step 11: Obtain the nth monitoring data from the monitoring data, extract M monitoring data related to the nth monitoring data from the monitoring data, and calculate the estimated monitoring value of the nth monitoring device based on the M monitoring data. The calculation formula is: , Wherein, EV _n is the estimated monitoring value of the nth monitoring device, is the parameter weight coefficient, AV _m is the mth monitoring data among the M monitoring data, k is a natural number, A is a constant, n is a positive integer from 1 to N, N is the total number of the monitoring data, M is the total number of monitoring data related to the nth monitoring data, and the nth monitoring device is the monitoring device that obtains the nth monitoring data; Step 12: Calculate the monitoring accuracy of the nth monitoring device at the current moment based on the nth monitoring data and the estimated monitoring value of the nth monitoring device. The calculation formula is: , Wherein, _ACn is the monitoring accuracy of the nth monitoring device at the current moment, and _AVn is the nth monitoring data; Step 13, obtaining N1 monitoring accuracies of the nth monitoring device within the first preset time from the first storage module, and determining whether the data state of the nth monitoring data is fluctuating, if so, determining the data state of the nth monitoring data as fluctuating, and then proceeding to step 15; if not, proceeding to step 14, wherein the N1 monitoring accuracies include the monitoring accuracy of the nth monitoring device at the current moment; Step 14, calculating the number of the N1 monitoring accuracies that are greater than or equal to a first preset value, and if the number is greater than or equal to a second preset value, determining that the data state of the nth monitoring data is normal; if the number is less than the second preset value, determining that the data state of the nth monitoring data is abnormal; Step 15. After traversing all monitoring data, if there is monitoring data with abnormal data status, determine that the first device is abnormal. If not, determine whether there is monitoring data with fluctuating data status. If so, determine that there is fluctuation in the first device. Otherwise, determine that the first device is normal. 3. The on-site safety hazard management method based on instant messaging according to claim 2, characterized in that in step 13, the step of determining whether the data state of the nth monitoring data is fluctuating comprises: Step 131: Acquire N1 monitoring data of the nth monitoring device within the first preset time, wherein the N1 monitoring data include the nth monitoring data; Step 132, respectively calculating the difference between the nth monitoring data and other monitoring data in the N1 monitoring data, and calculating the first root mean square error of the N1 monitoring accuracies of the nth monitoring device; Step 133: When any of the differences is greater than the first root mean square error, determine that the data state of the nth monitoring data is fluctuation. 4. According to the on-site safety hazard management method based on instant messaging in claim 2, it is characterized in that when the number of times the first device is judged to fluctuate within the second preset time is greater than or equal to a third preset value, it is determined that the first device has an abnormality. 5. The on-site safety hazard management method based on instant messaging according to claim 1, characterized in that in step 5, the abnormality handling personnel troubleshooting the safety hazard comprises: Step 51: Obtain the initial node of the hidden danger investigation topology route, and define the initial node as an analysis node; Step 52: determine whether the analysis node is a leaf node. If not, proceed to step 53; if so, proceed to step 55; Step 53: obtaining a first operation content corresponding to the detection item at the analysis node, sending the location of the analysis node and the first operation content to the instant messaging client of the exception handling personnel, and obtaining the detection result; Step 54: According to the detection result, select a detection node corresponding to the detection result from lower-layer detection nodes connected to the analysis node as the detection node to be analyzed, define the detection node to be analyzed as the analysis node, and return to step 52; Step 55: determine that the detection item at the analysis node is the cause of the safety hazard, obtain the abnormal recovery operation content corresponding to the detection item at the analysis node, and send the location of the analysis node and the abnormal recovery operation content to the instant messaging client of the abnormality handler. 6. An on-site safety hazard management system based on instant messaging, used to implement the on-site safety hazard management method based on instant messaging as described in any one of claims 1 to 5, characterized in that it comprises: a first device, a monitoring device, an on-site safety management platform and an instant messaging client, the monitoring device is used to collect monitoring data of the first device, and the on-site safety management platform comprises an abnormality judgment module, a route generation module, a troubleshooting instruction module, a hidden danger troubleshooting module and a risk calculation module; The abnormality judgment module is used to obtain the monitoring data of the first device and judge whether an abnormality occurs in the first device based on the monitoring data; The route generation module is used to identify the safety hazards of the first device when the first device is abnormal, and generate a hazard troubleshooting topology route and hazard troubleshooting content for each detection node; The inspection and approval module is used to search the first personnel information table based on the location information of the first device, obtain the information of the regional person in charge of the area where the first device is located, and then send the safety hazard, the hazard inspection topological route and the hazard inspection content of each detection node to the instant messaging client of the regional person in charge, and the regional person in charge will inspect and process the hazard inspection topological route and the hazard inspection content of each detection node; The hidden danger investigation module is used to search the second personnel information table based on the location information and the safety hidden danger when a positive reply is received, obtain the information of the exception handling personnel who handles the safety hidden danger, and the exception handling personnel investigates the safety hidden danger. After the investigation is completed, the investigation result is sent to the instant messaging client of the regional person in charge; The risk calculation module is used to calculate the potential failure risk of the first device when a negative reply is received, and send the calculated risk to the instant messaging client of the regional person in charge; Determining the potential safety hazard based on abnormal monitoring data of the first device, generating a potential safety hazard troubleshooting topology route includes: Step 21, searching the second storage module based on the safety hazard to obtain abnormal diagnosis information corresponding to the safety hazard, wherein the abnormal diagnosis information is a layered set of detection items, the first layer is the safety hazard, the detection item connected to any detection item of the i-th layer and the i-1-th layer is the abnormal cause of any of the detection items, the number of detection items connected to the i-th layer and the p-th detection item of the i-1-th layer is TI _i,p , wherein i is a positive integer greater than or equal to 2, p is a positive integer greater than or equal to 1, and TI _i,p is a positive integer greater than or equal to 1; Step 22: Obtain all detection items in the abnormal diagnosis information, and generate a topological route set including all detection steps, wherein one detection node in each topological route corresponds to one detection item; Step 23: Calculate the troubleshooting cost of each topological route respectively, and use the topological route with the minimum troubleshooting cost as the hidden danger troubleshooting topological route; The first position of the exception handling personnel is obtained. In step 23, the method for calculating the troubleshooting cost of each topological route is: Step 231, obtaining the g-th topological route in the topological route set, and then obtaining the second position of each detection node in the g-th topological route, wherein g is a positive integer from 1 to G, and G is the total number of all topological routes in the topological route set; Step 232: Calculate the distance from the exception handling personnel to the initial node of the g-th topological route, and calculate the distance between any two connected detection nodes in the g-th topological route; Step 233: Obtain the initial node of the g-th topological route, and calculate the route cost at the initial node. The calculation formula is: , Wherein, and are parameter weight coefficients, PC _r is the route cost at the initial node, D _t,r is the distance from the exception handling personnel to the initial node, and MC _r is the detection cost of the initial node; Step 234: Obtain the qth detection node of the gth topological route, and calculate the route cost at the qth detection node. The calculation formula is: , Wherein, PC _q is the route cost at the qth detection node, D _q-1,q is the distance from the q-1th detection node to the qth detection node, MC _q is the detection cost of the qth detection node, PC _q-1 is the route cost at the q-1th detection node, q is a positive integer from 2 to Q, Q is the total number of detection nodes of the gth topological route, and the first detection node of the gth topological route is the initial node; Step 235: determine whether the qth detection node is a leaf node. If not, set q=q+1 and return to step 234. If yes, obtain the probability of an abnormality occurring at the qth detection node. Calculate the branch inspection cost at the qth detection node based on the probability of an abnormality occurring at the qth detection node and the route cost at the qth detection node. The calculation formula is: , Wherein, CI _q is the branch inspection cost at the qth detection node, PA _q is the probability of abnormality occurring at the qth detection node, Then determine whether q is equal to Q. If not, set q=q+1 and return to step 234. If yes, proceed to step 236. Step 236: After traversing all detection nodes in the g-th topological route, calculate the inspection cost of the g-th topological route, and the calculation formula is: , Among them, PC _g is the inspection cost of the g-th topological route, j is a positive integer from 1 to J, J is the total number of leaf nodes in the g-th topological route, and CI _j is the branch inspection cost at the j-th leaf node.