A construction method of a work personnel safety education and training system

Abstract

The application provides a construction method of a work personnel safety education training system, and belongs to the technical field of education training, and comprises the following steps: collecting work environment data of a training enterprise in real time through an Internet of Things terminal, obtaining quality behaviors of work personnel performing work in the work environment, obtaining enterprise information of the training enterprise, analyzing training demand according to a quality ability graph of the enterprise information, and combining a preset training framework to design a safety education training system; obtaining enterprise requirements and industry standards of the training enterprise, and developing a course based on the safety education training system; establishing a training effect evaluation system according to a preset dimension, obtaining an evaluation result, and optimizing the safety education training system based on the evaluation result. The safety education training of the enterprise can be provided more targetedly.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of education and training, and particularly relates to a construction method of a safety education and training system for operating personnel. BACKGROUND

[0002] At present, with the continuous expansion of enterprise scale and the increasing complexity of business, large-scale group enterprises are facing increasingly severe challenges in safety production management. The traditional safety education and training mode generally has problems such as content fragmentation, single form, lack of pertinence, etc., and is difficult to meet the needs of the rapid development of enterprises. Although some enterprises have begun to try to use new technical means such as multimedia and virtual reality for safety training, but as a whole, a scientific, systematic and personalized education and training system has not yet been formed.

[0003] Therefore, the present application provides a construction method of a safety education and training system for operating personnel. SUMMARY

[0004] The present application provides a construction method of a safety education and training system for operating personnel to solve the technical problems existing in the prior art.

[0005] The present application provides a construction method of a safety education and training system for operating personnel, comprising:

[0006] Step 1: acquiring the operating environment data of the training enterprise and the quality behavior of the workers performing work in the operating environment through the Internet of Things terminal, and acquiring the enterprise information of the training enterprise, wherein the enterprise information includes the risk types and risk levels of different operating environments;

[0007] Step 2: analyzing the training demand according to the quality and ability graph of the enterprise information, and designing a safety education and training system in combination with a preset training framework, wherein the safety education and training system covers all key safety knowledge points in different operating environments;

[0008] Step 3: acquiring the enterprise requirements and industry standards of the training enterprise based on a preset database, and developing courses based on the safety education and training system;

[0009] Step 4: establishing a training effect evaluation system according to a preset dimension to obtain an evaluation result, wherein the evaluation result includes student satisfaction, theoretical examination results and practical operation examination results;

[0010] Step 5: optimizing the safety education and training system based on the evaluation result.

[0011] Preferably, the enterprise information of the training enterprise is acquired, comprising:

[0012] The operation environment data of the training enterprise is collected in real time through the Internet of Things terminal to generate a scene risk map, meanwhile, the quality behavior of the worker performing work in the operation environment is obtained to obtain quality characteristics, and a quality capability map is constructed;

[0013] The SOP file of the training enterprise under each operation is obtained, the SOP file is preprocessed, and key data is determined based on an industry dictionary of the industry of the training enterprise;

[0014] It is judged whether the key data involves high-risk equipment;

[0015] If it involves, the risk type under the corresponding operation environment is determined based on a risk trigger condition and in combination with the scene risk map and the quality capability map;

[0016] The risk coefficient of the corresponding operation environment is determined based on the risk type and a preset risk factor quantification table;

[0017] The risk type is determined according to the key data, and the risk coefficient is corrected based on the protective measures to obtain a risk level.

[0018] Preferably, the process of analyzing training needs comprises:

[0019] The scene risk map is divided into grids, and data labeling is performed to generate a plurality of unit scene grids;

[0020] The data of the unit scene grid is normalized based on a preset data category, and the normalized coefficient is weight allocated according to a weight dynamic allocation model;

[0021] The environment coefficient of the unit scene grid is calculated based on the normalized coefficient;

[0022]

[0023] wherein, the environment coefficient of the a-th unit scene grid is represented by a; the normalized coefficient of the i-th data category of the a-th unit scene grid is represented by ai; the weight of the i-th data category is represented by wi; the normalized coefficient of the j-th high-risk factor under the a-th unit scene grid is represented by aj; the high-risk risk coefficient is represented by n; and n represents the number of data categories. the number of high-risk factors existing in the high-risk combination is represented by m;

[0024] The overall environment coefficient of the scene risk map is calculated according to all the environment coefficients;

[0025]

[0026] wherein, represents the overall environmental coefficient; represents the Euclidean distance from the a-th unit scene grid to the k-th sensor; p represents the attenuation coefficient, which is 0.1; m represents the number of sensors; represents the total number of unit scene grids.

[0027] Preferably, the training needs are analyzed, including:

[0028] The personnel error probability of the operating personnel is analyzed based on the quality and ability diagram;

[0029] The risk score is calculated according to the overall environmental coefficient and the personnel error probability, and based on the risk type and the corresponding risk level;

[0030]

[0031] wherein, represents the risk score of the t-th risk type; represents the weight of the overall environmental coefficient; represents the risk value of the t-th risk type; represents the weight of the risk type; represents the average value of all personnel error probabilities involved in the t-th risk type; represents the weight of the personnel error probability; ln represents the logarithmic function;

[0032] The training needs are generated according to the risk scores of all risk types, and combined with the proportion layout of each risk type.

[0033] Preferably, the safety education and training system is designed, including:

[0034] A preset training framework is obtained;

[0035] The basic training content is analyzed according to the training needs;

[0036] The content of the basic training content is analyzed, and a training factor is set;

[0037] The preset training framework is filled according to the basic training content and the training factor, and the safety education and training system is generated.

[0038] Preferably, the enterprise requirements and industry standards of the training enterprise are obtained, and the course development is carried out based on the safety education and training system, including:

[0039] The enterprise requirements and the industry standards are strictly compared to determine the high strictness requirements;

[0040] Selecting theoretical courses and practical courses from a preset database according to the high strictness requirement and the safety education and training system;

[0041] Obtaining an operation flow of the practical course;

[0042] Binding the operation flow with a device model to obtain a standard operation flow;

[0043] Obtaining a historical accident case of the standard operation flow;

[0044] Injecting the historical accident case into the standardized operation flow to obtain a scenario course.

[0045] Preferably, the safety education and training system is optimized based on the evaluation result, including:

[0046] Obtaining the evaluation result of each worker;

[0047] Determining a first course with a student satisfaction degree lower than a preset student satisfaction degree according to all the student satisfaction degrees of each course;

[0048] Performing a first course analysis on the first course;

[0049] Optimizing the first course based on the first course analysis;

[0050] Performing a first error analysis on all the theoretical examination results to determine a first common error;

[0051] Positioning a second course based on the first common error;

[0052] Performing a second course analysis on the second course;

[0053] Optimizing the second course based on the second course analysis;

[0054] Performing a second error analysis on all the practical examination results to determine a second common error;

[0055] Positioning a third course based on the second common error;

[0056] Optimizing the third course according to the second common error.

[0057] Preferably, the personnel error probability of the worker is analyzed based on the quality and ability graph, including:

[0058]

[0059]

[0060] wherein, It represents the probability of personnel error Pt of the corresponding staff under the t-th risk type; represents the probability function; Represents the actual operating behavior of the corresponding staff under the t-th risk type based on the quality and ability diagram analysis Standard operating procedures Similarity function probability of danger; Indicates the total number of risk types that exist; sum represents the cumulative sum symbol.

[0061] Preferably, after optimizing the safety education and training system based on the evaluation results, the following steps are included:

[0062] The training behavior results of each staff member based on each working environment are obtained, and compared with the standard behavior in the optimized system to determine abnormal behavior and combine it with the characteristics of the operating personnel. The results are input into the behavior analysis model to obtain targeted training courses and sent to the user end of the staff. The targeted training courses are related to online learning, offline practice and simulation exercises.

[0063] Compared with the prior art, the present invention has the following advantages:

[0064] By obtaining the corporate information of training companies, analyzing training needs, designing a safety education and training system based on training needs, developing courses based on corporate requirements and industry standards, evaluating the training effectiveness of trained operators, and optimizing the safety education and training system based on the evaluation results, we provide a scientific safety education and training system that can provide more targeted safety education and training for enterprises. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction is given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0066] Figure 1 This is a flowchart of a method for constructing a safety education and training system for operating personnel provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0067] In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions in the present application will be described clearly and completely below in combination with the drawings in the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the protection scope of the present application.

[0068] The present application provides a construction method of a work personnel safety education and training system, as shown in the figure, comprising: Figure 1

[0069] Step 1: collecting work environment data of a training enterprise in real time through an Internet of Things terminal and obtaining quality behaviors of work personnel performing work under the work environment, and obtaining enterprise information of the training enterprise, wherein the enterprise information comprises risk types and risk levels of different work environments;

[0070] Step 2: analyzing training needs according to a quality and ability graph of the enterprise information, and designing a safety education and training system in combination with a preset training framework, wherein the safety education and training system covers all key safety knowledge points under different work environments;

[0071] Step 3: obtaining enterprise requirements and industry standards of the training enterprise based on a preset database, and developing courses based on the safety education and training system;

[0072] Step 4: establishing a training effect evaluation system according to preset dimensions, and obtaining evaluation results, wherein the evaluation results comprise student satisfaction, theoretical examination results and practical operation examination results;

[0073] Step 5: optimizing the safety education and training system based on the evaluation results.

[0074] In this embodiment, the Internet of Things terminal can be various sensors installed in a well, such as a gas sensor for monitoring gas concentration in real time, and a temperature and humidity sensor for monitoring temperature and humidity in the well.

[0075] In this embodiment, the work environment data: data reflecting physical and chemical conditions of a work site. Taking a chemical enterprise as an example, the physical environment data comprises temperature, pressure, noise, etc.; and the chemical environment data comprises toxic and harmful gas concentration, dust concentration, etc. For example, the temperature in a certain chemical workshop is kept at about 30℃ all the year round, the pressure is maintained at a certain value, and the concentration of benzene in the air needs to be strictly controlled within a safe range.

[0076] ​In this example, the quality behavior of workers refers to the knowledge, skills, experience, and behavior of workers in the work. For example, in construction enterprises, the educational level of workers, whether they have relevant professional qualification certificates, records of safety accidents in previous work, and the degree of standardization in actual operation all belong to quality behavior. A worker with many years of experience and a high-altitude operation certificate strictly fastens the safety belt and checks the operation equipment according to the operation procedures when working at high altitude, and his quality behavior is good.

[0077] In this example, the risk type refers to the types of dangers that may exist in the work environment. Common risk types include mechanical injury, fire and explosion, electric shock, poisoning and suffocation, etc. For example, in a machine shop, workers may be injured by being entangled in rotating parts when operating machine tools, which is a mechanical injury risk; in a gas station, there is a risk of fire and explosion due to the presence of a large amount of flammable gasoline.

[0078] In this example, the risk level is a comprehensive assessment of the likelihood of risk and the severity of consequences. Generally, it is divided into low, medium and high risk levels. Taking high-altitude work in construction as an example, if the workers strictly follow the safety regulations and have perfect protective measures, the probability of falling accidents is small, and even if accidents occur, the consequences are relatively controllable, so the risk level may be low risk; on the contrary, if the workers operate irregularly and have no protective measures, the probability of falling accidents is large and the consequences are serious, so the risk level is high risk.

[0079] In this example, the training needs are derived from the analysis of enterprise information, and the content that employees need to improve in terms of safety knowledge and skills. For example, through the analysis of the enterprise information of an electronic manufacturing enterprise, it is found that employees lack of anti-static operation, which can easily cause damage to electronic components due to static electricity, so anti-static operation training becomes a training need. The safety education and training system is a complete training plan designed to meet the training needs, including training objectives, training content, training methods, and training faculty. For example, a logistics enterprise, the goal of the safety education and training system may be to improve the safety awareness and operation skills of employees in the aspects of cargo handling, warehouse management, etc.; the training content covers the correct posture of cargo handling, the safe use of warehouse equipment, fire safety knowledge, etc.; the training method can combine online video learning with offline practical training; the training faculty can invite industry experts, safety management personnel within the enterprise, etc.

[0080] In this embodiment, enterprise requirements are rules and standards established by the enterprise itself to ensure the safety and efficiency of production and business activities. For example, a food processing enterprise requires employees to strictly wash their hands and disinfect before entering the workshop, wear work clothes, hats and masks that meet hygiene standards, and have clear quality and safety requirements for raw material procurement, processing technology, finished product inspection and other links in the production process. According to enterprise requirements, industry standards and safety education and training system, specific training courses are designed and written. Taking the power industry as an example, the developed courses may include power safety regulations interpretation course, through case analysis and article explanation, let employees understand the relevant laws and regulations of power industry; electrical equipment operation skill training course, through actual operation demonstration and simulation training, make employees master the correct operation method of electrical equipment.

[0081] In this embodiment, common preset dimensions include trainee satisfaction, theoretical examination results, practical operation examination results, etc. The overall feeling and evaluation of trainees on the training course. The opinions of trainees can be collected through questionnaire survey, such as asking trainees about their satisfaction with the practicality of training content, the teaching level of training instructors, training organization arrangement, etc. If 100 questionnaires are distributed after a fire safety training, and 80 questionnaires show that trainees are satisfied with the training content, then the trainee satisfaction can be roughly considered to be 80%. The result of evaluating the degree of trainees' mastery of theoretical knowledge through written examination, etc. For example, after the safety production laws and regulations training is completed, organize trainees to take an examination, the examination content includes the provisions of laws and regulations, case analysis, etc., according to the examination results of trainees to determine the theoretical examination results. The result of evaluating the degree of trainees' skill mastery in actual operation scene. For example, after welding skill training, let trainees perform actual welding operation, and the examiner scores according to the quality, speed, standard degree of welding, etc., to obtain the practical operation examination results.

[0082] In this embodiment, according to the training effect evaluation results, the safety education and training system is improved and perfected. For example, if it is found in the evaluation that the trainees' satisfaction with a certain course is low, and after analysis it is found that the training content is too dry, then the content of the course can be adjusted, some case analysis, interactive link, etc. can be added to improve the interest and practicality of the course; if the theoretical examination results show that the trainees do not master some knowledge points well, the explanation and practice of these knowledge points can be strengthened; if the practical operation examination results show that the trainees have problems in a certain operation link, the corresponding practical operation training project can be added.

[0083] In this embodiment, demand analysis: in-depth investigation of enterprise work environment, work type, personnel structure, etc., to clarify the specific needs and target groups of safety education and training.

[0084] System construction: based on the demand analysis results, design the education and training system framework including safety education theory knowledge, safety operation skills, emergency handling process and other multi-dimensional.

[0085] Course development: combined with the actual enterprise and industry standards, develop targeted, rich content, and various safety education and training courses, make full use of multimedia, virtual reality and other modern teaching methods.

[0086] Personalization: according to the characteristics of different posts and different types of workers, customize personalized training plans and content to ensure that the training is practical and meets the needs.

[0087] Implementation and supervision: implement the training plan through online learning, offline operation, simulation and other forms, and establish a perfect training effect evaluation and supervision mechanism.

[0088] Continuous improvement: according to the training effect feedback and enterprise development needs, continuously optimize and upgrade the safety education and training system to maintain its advanced nature and applicability.

[0089] The beneficial effects of the above technical solutions are: by obtaining enterprise information of a training enterprise, analyzing training needs, designing a safety education and training system according to training needs, developing courses based on enterprise requirements and industry standards, evaluating the training effect of workers after training, and optimizing the safety education and training system according to the evaluation results, a scientific safety education and training system is provided, which can provide more targeted safety education and training for enterprises.

[0090] The present application provides a kind of construction method of safety education and training system of worker, obtains the enterprise information of training enterprise, including:

[0091] The working environment data of the training enterprise is collected in real time through the Internet of Things terminal, and scene risk map is generated, and the quality characteristics of the quality behavior of the worker performing work in the working environment are obtained, and quality ability map is constructed;

[0092] Obtain the SOP file of the training enterprise under each operation, preprocess the SOP file, and determine the key data based on the industry dictionary of the industry of the training enterprise.

[0093] Determine whether the key data involves high-risk equipment.

[0094] If it involves, determine the risk type in the corresponding working environment based on the risk trigger condition and in combination with the scene risk map and the quality ability map.

[0095] Determine the risk coefficient of the corresponding working environment based on the risk type and the preset risk factor quantization table.

[0096] Determine the protective measures of the risk type according to the key data, and correct the risk coefficient based on the protective measures to obtain a risk level.

[0097] In this embodiment, the quality characteristics include the education background of the operation personnel, the HR system examination records, the VR training scores, the illegal operation logs, etc. The quality and ability graph is a pentagon graph or a hexagon graph constructed by numerically representing the learning ability, the operation ability, etc. based on the quality characteristics. Taking the operation personnel of an electronic factory as an example, the education background is mostly a college degree, the average performance score in the HR system examination records is 80 points, the average score in the VR training scores, such as the static protection operation training, is 75 points, and the illegal operation logs show that the average number of illegal operations of each person in the past half year is 3. Based on these, the quality and ability graph is constructed by numerically representing the learning ability, the operation ability, etc. For example, the learning ability value is 70 and the operation ability value is 75, and a pentagon graph is drawn to display the various abilities.

[0098] In this embodiment, the operation environment data includes physical environment data, chemical environment data, device status, space layout, etc. For example, in an automobile manufacturing workshop, the physical environment data includes a temperature of 25°C, a humidity of 50%, and a noise of 80 decibels; in the chemical environment data, the flammable gas concentration in a paint shop can be 5% LEL (lower explosive limit); in terms of device status, the vibration frequency of a welding robot is stable at a certain value, and some devices have a slight degree of corrosion; and in terms of space layout, the width of the escape passage is 1.5 meters, and the coverage rate of safety signs is 80%. Through these data, a scene risk graph is generated, and the welding area is covered with orange color due to the risks of high temperature and device operation.

[0099] In this embodiment, the pre-processing of the SOP file includes format conversion, extraction of pure text, paragraph segmentation, construction of a document structure tree based on title style recognition, and identification of key data in the table by using a CNN+BiLSTM model. The key data includes devices, actions, and inspection items, etc. For example, the SOP file of a part processing in a mechanical processing enterprise includes a series of operation processes from the collection of raw materials, machine tool debugging, part processing steps to finished product inspection. During pre-processing, it is first converted from PDF format to pure text, the paragraphs are segmented, and the key data is identified by using a CNN+BiLSTM model, such as the device is a lathe, the action is turning, and the inspection item includes size tolerance inspection, etc.

[0100] In this embodiment, the risk types include mechanical injury, chemical exposure, and high-altitude falling, etc. The risk level is obtained according to the initial risk coefficient and in combination with the protective measures. For example, the high-altitude falling risk coefficient is 0.8, the protective measures include binding a safety rope and multiple people working together, etc., the corrected risk coefficient is 0.5, and the risk level is general risk.

[0101] In this embodiment, the high-risk equipment is obtained from the equipment dictionary when generating the industry dictionary, for example, in the mining industry, high-risk equipment such as mine hoist and large fan; in the power industry, in addition to transformers and transmission towers, high-voltage switch cabinets also belong to high-risk equipment.

[0102] In this embodiment, the key data is a power transmission tower, which involves the risk of falling from a high altitude, and the trigger condition of the key data is determined to be "climbing" + "more than 2 meters", and if the trigger condition exists, the risk type is falling from a high altitude.

[0103] In this embodiment, the preset risk factor quantization table is set in advance based on the risk probability of different risks and the historical personnel casualty situation to set different risk coefficients.

[0104] In this embodiment, the risk level corresponds to the risk coefficient, and the risk coefficient 0.3 is low risk, general risk, high risk, extremely high risk, for example, the risk coefficient of falling from a high altitude is 0.8, the protective measures include binding a safety rope and multiple people working together, and the corrected risk coefficient is 0.5, and the risk level is general risk.

[0105] The beneficial effects of the above technical solutions are: by designing high-risk equipment for key data, determining the risk type based on the risk trigger condition, determining the risk coefficient according to the risk type and the preset risk factor quantization table, and correcting the risk coefficient according to the protective measures, the risk level is obtained, which provides a basis for subsequent calculation of risk score.

[0106] The present application provides a kind of construction method of work personnel safety education training system, in the process of analyzing training demand, including:

[0107] The scene risk graph is divided into grid, and data labeling is carried out, to generate a plurality of unit scene grids;

[0108] Based on the preset data category, the data of the unit scene grid is normalized, and the weight distribution model is used to weight the normalization coefficient;

[0109] Based on the normalization coefficient, the environmental coefficient of the unit scene grid is calculated;

[0110]

[0111] Wherein, The environmental coefficient of the a unit scene grid is represented as a; The normalization coefficient of the i data category of the a unit scene grid is represented as a; The weight of the i data category is represented as i; represents the normalized coefficient of the jth high-risk factor under the ath unit scene grid; represents the high-risk coefficient; n represents the number of data categories; represents the number of high-risk factors existing in the high-risk combination;

[0112] According to all environmental coefficients, the overall environmental coefficient of the scene risk map is calculated.

[0113]

[0114] wherein, represents the overall environmental coefficient; represents the Euclidean distance from the ath unit scene grid to the kth sensor; p represents the attenuation coefficient, which is 0.1; m represents the number of sensors; represents the total number of unit scene grids.

[0115] In this embodiment, the scene risk map is divided into a cubic grid with an edge length of 0.5 m. Data labeling includes spatial coordinates (X: 10, Y: 15, Z: 3) of each grid, temperature 22℃, and device risk index (forklift operating area risk index is 0.6) and other information.

[0116] In this embodiment, taking the chemical production workshop data as an example, the temperature range in the physical environment data may be 0-100℃, and the concentration range of a certain toxic gas in the chemical environment data may be 0-100ppm. The piecewise function method is used to process these data of different dimensions to the interval of 0-1, eliminating the dimensional difference, and facilitating subsequent analysis.

[0117] In this embodiment, in the pharmaceutical industry, due to strict requirements on the chemical environment, the weight of chemical environment data (such as drug raw material purity, workshop cleanliness, etc.) is higher than that of physical environment data (temperature, humidity, etc.). Based on the analytic hierarchy process, the weight of chemical environment data is determined to be 0.6, and the weight of physical environment data is determined to be 0.4.

[0118] In this embodiment, there are several high-risk factors in the high-risk combination.

[0119] In this embodiment, for the environmental coefficient, for example: the normalized coefficient of the physical environment data is 0.6 (temperature, humidity, etc. comprehensive), the normalized coefficient of the chemical environment data is 0.4 (harmful gas concentration, etc.), the weight of the physical environment data is 0.3, the weight of the chemical environment data is 0.7, and there is no high-risk factor. According to the formula, the environmental coefficient of the unit scene grid = 0.6×0.3+0.4×0.7=0.46.

[0120] In the embodiment, in the process of determining the overall environment coefficient, it is assumed that a factory has 5 sensors, the total number of unit scene grids is 100, the Euclidean distance from the first unit scene grid to the first sensor is 2 meters, the attenuation coefficient p is 0.1, and the overall environment coefficient is calculated according to the environment coefficient of each unit scene grid and related distance data according to the formula.

[0121] In the embodiment, in the job environment risk assessment, different data categories (such as physical environment data and chemical environment data) have different influences on the environmental risk, and by , the normalized coefficient (reflecting the actual risk degree of the category data) and the weight (reflecting the importance of the category data) of each data category are multiplied and accumulated, the influences of various conventional data categories on the environment can be comprehensively considered.

[0122] In the job environment, the high-risk factors have a great influence on the risk, the overall risk degree of the high-risk factors is measured, is the normalized coefficient of the high-risk factor, and the combined comprehensive action of the high-risk factor combination is considered by means of multiplication, is to reflect the order of different high-risk factors in combination.

[0123] In the actual job environment, the contribution of different unit scene grids to the overall environmental risk depends not only on the environment coefficient of the unit scene grid itself, but also on the position of the sensor. The farther away from the sensor, the greater the monitoring error or the smaller the risk propagation influence, and therefore , the environment coefficient of the unit scene grid is modified by the distance related term.

[0124] The beneficial effects of the above technical solutions are: the environmental risk conditions of the unit scene grid are comprehensively and accurately evaluated by considering the conventional factors and the high-risk factors, which is the basis for subsequent analysis of the job environment risk. By double summation calculation of all unit scene grids, the self-risk of each unit scene grid and the distance relationship with the sensor can be considered, and the overall environment coefficient of the entire scene risk map can be accurately obtained, which provides a reliable basis for subsequent risk scoring, training demand analysis and the like based on the overall environment.

[0125] The application provides a construction method of a job personnel safety education and training system, analyzes training demand, and comprises the following steps:

[0126] analyzing the personnel error probability of the job personnel based on the quality and ability graph;

[0127] performing risk scoring according to the overall environment coefficient, the personnel error probability, and based on the risk type and the corresponding risk level;

[0128]

[0129] wherein, a risk score of the tth risk type is represented by; a weight of the overall environment coefficient is represented by; a risk value of the tth risk type is represented by; a weight of the risk type is represented by; an average value of all personnel error probabilities involved in the tth risk type is represented by; a weight of the personnel error probability is represented by; ln represents a logarithmic function;

[0130] According to the risk scores of all risk types, and in combination with the proportion layout of each risk type, training needs are generated.

[0131] In this embodiment, the scene risk map is divided according to a cubic grid with an edge length of 0.5m, and the data labeling includes spatial coordinates, temperature, device danger index, etc.

[0132] In this embodiment, the preset data categories include physical environment data, chemical environment data, etc. The normalization processing is performed using a piecewise function method, with the purpose of eliminating dimensional differences.

[0133] In this embodiment, the weight dynamic allocation model is an industry-specific weight based on the analytic hierarchy process. For example, in the chemical industry, the weight of chemical environment data is higher than that of physical environment data, and both are directly usable values.

[0134] In this embodiment, a high-risk combination refers to the presence of explosion risk, scald risk, etc., for example, combustible gas 30% LEL and ventilation rate <0.5m / s, which is considered to have an explosion risk The default is 0.15.

[0135] In this embodiment, a multidimensional evaluation matrix is constructed according to the quality and ability graph, for example, The personnel error probability is predicted using an XGBoost model.

[0136] In this embodiment, =1.

[0137] In this embodiment, for risk types with a risk score greater than a preset score, the type of accident caused by the risk source is analyzed, the ability defects of the operating personnel are inversely deduced from the risk exposure, and training needs are generated.

[0138] The beneficial effects of the above technical solutions are: by normalizing the data of the cell scene and performing weight analysis, calculating the environment coefficient, further calculating the overall environment coefficient, calculating the risk score according to the overall environment coefficient, personnel error probability, risk type, and corresponding risk level, the accuracy of analyzing the risk score is improved, laying a foundation for subsequent determination of training needs.​​

[0139] The application provides a construction method of a work personnel safety education and training system, designs a safety education and training system, and comprises the following steps of:

[0140] obtaining a preset training framework;

[0141] analyzing basic training content according to the training demand;

[0142] performing content analysis on the basic training content, and setting a training factor;

[0143] filling the preset training framework according to the basic training content and the training factor, and generating the safety education and training system.

[0144] In this embodiment, the preset training framework is a general safety education and training structure template. For high-altitude work, it usually covers safety education theoretical knowledge, such as safety regulations and safety principles related to high-altitude work; safety operation skills, such as correct wearing of a safety belt, erection and use specifications of a scaffold; and emergency handling processes, including emergency rescue processes for high-altitude falling accidents and measures for responding to sudden severe weather.

[0145] In this embodiment, the knowledge and skills that work personnel need to master are deduced through analysis of training demands such as risk assessment of a high-altitude work scene and a current situation of work personnel. For example, if it is found that high-altitude work personnel do not pay enough attention to pre-work environment inspection, the basic training content will include how to check weather conditions of a work area, whether wind force meets work standards, whether a work platform is stable, and whether a protective fence is firm, and the like. For another example, considering safety risks of work personnel during high-altitude movement, the basic training content will also involve correct operation methods during movement, such as a standard process of using a fall arrester, and the like.

[0146] In this embodiment, the above basic training content is further analyzed. For example, for the basic training content of “correct wearing of a safety belt”, a training method in a training factor can adopt on-site demonstration plus actual operation practice, that is, a professional instructor first demonstrates in detail each step from selection, wearing to fastening of a safety belt, and then lets a student operate personally and gives guidance and correction; in terms of training time, 30 minutes of theoretical explanation and 1 hour of actual operation practice can be arranged to ensure that the student truly masters it. For another example, for “measures for responding to sudden severe weather during high-altitude work”, a training method can adopt case analysis combined with simulation practice, and training time is set to 1 hour of explanation of a case and 1.5 hours of emergency practice in a simulated severe weather scene.

[0147] In this embodiment, the basic training content of high-altitude operation, such as operation environment inspection, safety belt wearing, emergency measures, etc., is filled into the corresponding part of the preset training framework according to the training method and time determined by the training factor. In the safety education theory knowledge block, the high-altitude operation regulations, risk principles and the corresponding training time are added; in the safety operation skill block, the training method and time arrangement of the operation skills such as safety belt wearing and scaffold erection are put in; in the emergency handling process block, the arrangement of bad weather response, fall rescue and other drills is arranged.

[0148] The beneficial effects of the above technical solutions are: the basic training content is analyzed through training demand, and the training factor is set for the basic training content, and the safety education training system is constructed based on the preset training framework, and a safety education training system of all-around, multi-industry and multi-scene is constructed.

[0149] The present application provides a kind of construction method of safety education training system of operating personnel, obtains the enterprise requirement and industry standard of the training enterprise, and based on the safety education training system, course development includes:

[0150] The strictness of the enterprise requirement and the industry standard is compared, and high strictness requirement is determined;

[0151] According to the high strictness requirement and the safety education training system, select theory course and practical course from preset database;

[0152] The operation flow of the practical course is obtained;

[0153] The operation flow is bound with equipment model, and standard operation flow is obtained;

[0154] The historical accident case of the standard operation flow is obtained;

[0155] The historical accident case is injected into the standard operation flow, and a scenario course is obtained.

[0156] In this embodiment, taking a chemical enterprise as an example, the enterprise requires that the employees must be disinfected before entering the chemical production workshop, and the disinfection time is not less than 3 minutes; while the industry standard stipulates that the disinfection time is not less than 2 minutes. Through comparison, it is determined that "disinfection time not less than 3 minutes" is a high strictness requirement, and the safety production specifications, operation manual and other documents prepared by the enterprise, as well as the relevant national standards, industry association issued specifications and other materials are collected. Organize professional personnel to compare and analyze item by item, and clarify the more stringent provisions in the same production link or operation.

[0157] In this embodiment, still taking the chemical enterprise as an example, based on the high strictness requirement of “disinfection time not less than 3 minutes” and the part of safety standard for personnel entering the workshop in the constructed safety education and training system. From the preset database, select “chemical workshop personnel access safety theory” as the theoretical course, which includes the content of chemical workshop environmental risk, the importance of personnel protection, etc.; select “chemical workshop personnel disinfection operation” as the operation course, focusing on the demonstration and practice of correct disinfection process. Establish a preset database to store course resources by industry category, training theme, etc. According to the corresponding training module in the high strictness requirement and the safety education and training system, the keywords, application scenarios, etc. of the courses in the database are searched to filter out the matching theoretical courses and operation courses.

[0158] In this embodiment, for the “chemical workshop personnel disinfection operation” course, the operation process includes: first, the employee changes the special work clothes and work shoes in the dressing room; then, enter the disinfection channel, stand at the designated position, and start the full-body spray disinfection equipment; during the disinfection process, slowly rotate the body according to the specified action to ensure that all parts of the body can be disinfected; finally, after disinfection is completed, dry the body through the air shower room, and then enter the workshop. Refer to the original text description document, operation guide of the operation course, or demonstrate on site by a professional instructor and record the operation steps to compile a standard operation process document or video script.

[0159] In this embodiment, the modeling software is used to build models of the disinfection channel equipment, air shower room and other related equipment in the chemical workshop. Each step in the above disinfection operation process is interactively bound to the corresponding equipment model. For example, when demonstrating the “start the full-body spray disinfection equipment” step, the disinfection equipment in the model will display the opening process, spray range, etc. in the form of animation, forming a visual standard operation process animation. By using modeling technology and animation production software such as sMax, Maya, etc., the operation process and the equipment model are associated by writing script code or using the interactive functions provided by the software, so that the operation steps are dynamically presented on the model.

[0160] In this embodiment, in the history records of the chemical industry, a certain enterprise once caused a partial fire accident in the workshop due to the incomplete disinfection of employees, which brought external pollutants into the workshop and caused a chemical reaction. Collect detailed information of the accident, including the time, place, process, loss caused and cause analysis, etc. associated with the standard operation process of chemical workshop personnel disinfection. Through the channels of industry accident database, enterprise internal accident files, news reports, professional safety accident analysis reports, etc., collect historical accident cases related to the standard operation process, and select typical and educational cases for filing.

[0161] In this embodiment, the fire accident case is inserted on the basis of the animation of the standard operation process of the personnel disinfection in the chemical plant described above. For example, when the animation demonstrates the step of "incomplete employee disinfection", the picture or video clip of the accident case is popped up to show the chaotic scene of the accident site, the damage after the fire, etc., and the voice is added to explain the cause and consequence of the accident, emphasizing the importance of strictly following the disinfection operation process, forming a situational course. After the historical accident case materials are cut and processed using video editing software such as Adobe Premiere Pro, etc., they are reasonably embedded in the corresponding operation step node according to the logical order of the standard operation process, and elements such as narration and subtitles are added to make a complete situational course video.

[0162] The beneficial effects of the above technical solution are: by strictly comparing enterprise requirements and industry standards to determine high strictness requirements, and based on the safety education and training system, selecting theoretical courses and practical courses from the preset database, binding practical courses with equipment models to obtain standardized operation processes, and based on historical accident cases, obtaining situational courses, using multimedia digital technology to provide immersive learning experience for operating personnel.

[0163] The present application provides a construction method of an operating personnel safety education and training system, which optimizes the safety education and training system based on the evaluation results, comprising:

[0164] Obtaining the evaluation results of each operating personnel;

[0165] Determining a first course with a student satisfaction degree lower than a preset student satisfaction degree according to all the student satisfaction degrees of each course;

[0166] Performing a first course analysis on the first course;

[0167] Optimizing the first course based on the first course analysis;

[0168] Performing a first error analysis on all the theoretical examination results to determine a first common error;

[0169] Positioning a second course based on the first common error;

[0170] Performing a second course analysis on the second course;

[0171] Optimizing the second course based on the second course analysis;

[0172] Performing a second error analysis on all the practical examination results to determine a second common error;

[0173] Positioning a third course based on the second common error;

[0174] Optimize the third course according to the second common error.

[0175] In this embodiment, the preset student satisfaction is 3 stars, and the first course is less than 3 stars for more than 60% of the workers.

[0176] In this embodiment, the first course analysis is to extract and summarize the feedback of the workers on the first course into evaluation results of course time, course interest and the like.

[0177] In this embodiment, the optimization of the first course is to shorten or lengthen the course time, improve the course interest and the like according to the evaluation results of the course time, the course interest and the like.

[0178] In this embodiment, the first common error is a theoretical error made by more than a preset proportion of workers.

[0179] In this embodiment, the second course is a course corresponding to the first common error.

[0180] In this embodiment, the second course analysis is to determine the error cause of the knowledge point according to the face recognition of the workers in the learning video, and the error cause includes not understanding, not listening carefully and the like.

[0181] In this embodiment, the optimization of the second course is to optimize according to the error cause, for example, if the error cause is not understanding, then simplify the language and the like.

[0182] In this embodiment, the second common error is an operation error made by more than a preset proportion of workers.

[0183] In this embodiment, the third course is a course corresponding to the second common error.

[0184] In this embodiment, the optimization of the third course is to emphasize the error of the third course according to the operation error.

[0185] The beneficial effects of the above technical solutions are: by course analysis and optimization of the course lower than the preset student satisfaction, optimization of the course according to the common error of the theoretical examination result, and optimization of the course according to the common error of the practical operation examination result, the advanced nature and applicability of the safety education and training system can be maintained.

[0186] The present application provides a kind of construction method of worker safety education and training system, personnel error probability of the worker is analyzed based on the quality ability chart, comprising:

[0187]

[0188]

[0189] Among them, Pt represents the personnel error probability of the corresponding worker under the tth risk type; Pt represents the probability function; At represents the similarity function of the actual operation behavior of the corresponding worker under the tth risk type based on the aptitude ability map analysis to the standard operation behavior the risk probability of the similarity function; sum represents the total number of risk types present; sum represents the cumulative sum symbol.

[0190] In this embodiment, the standard operation behavior is pre-set, and the behaviors under different risk types are pre-set, which facilitates direct matching analysis.

[0191] In this embodiment, the deviation between the actual operation of the worker and the standard specification can be measured. For example, in chemical production, the standard operation behavior requires opening the valve in a specific order, and if there is an order error in the actual operation behavior, the function can reflect the risk probability brought by such difference, which is a basic element for evaluating the possibility of personnel error.

[0192] In this embodiment, the behavior performance of the worker under multiple different risk scenarios is considered, and the overall operation specification degree of the worker in a complex operation environment is comprehensively reflected. For example, in construction, the worker may face high-altitude operation, electrical operation, mechanical use and other risk types, and by accumulating the similarity functions under different risk types, the error probability of the worker in the entire work process can be comprehensively evaluated.

[0193] In this embodiment, the Pt is set to reasonably define the value range of the personnel error probability, avoiding the occurrence of unreasonable high or low probability values. In actual application, when At exceeds 1, Pt is uniformly set to 1, indicating that the personnel error probability is extremely high at this time, close to the inevitable error state; when At<1, Pt directly takes the value of At, accurately reflecting the state of relatively low but still possible error.

[0194] The beneficial effects of the above technical solutions are: the personnel error probability is calculated through a series of formulas, which can provide precise quantitative indicators for the operation personnel safety education and training system, and based on this, the training content can be more targetedly designed, the training focus can be determined, and the effectiveness and precision of the training can be improved.

[0195] The present application provides a construction method of an operation personnel safety education and training system, and after optimizing the safety education and training system based on the evaluation result, the method comprises:

[0196] ​The training behavior result of each worker under each working environment is obtained, and compared with the standard behavior in the optimized system to determine the abnormal behavior and combine the working personnel characteristics, input into the behavior analysis model to obtain the targeted training course and issue to the user end of the working personnel, wherein the targeted training course is related to online learning, offline operation and simulation.

[0197] In this embodiment, a monitoring camera is installed to record the working process of the worker in real time; a sensor is arranged to collect the operation data of the equipment, such as operation time, force, etc.; a field observer is arranged to regularly patrol and record the behavior of the working personnel. For example, in a mechanical processing workshop, the camera is used to record the hand movements of the worker when operating the machine tool, the sequence of starting and closing the equipment, etc.; the sensor is used to monitor the data such as the pressing time of the worker on the machine tool button.

[0198] The behavior analysis model is constructed by using artificial intelligence algorithm, which can analyze the causes of abnormal behavior and give countermeasures by comprehensively considering the personal characteristics of the working personnel such as age, education, work experience, skill level, and abnormal behavior data. The basic information of the working personnel is collected and input into the database; the abnormal behavior data is preprocessed and input into the model according to the format requirements. For example, in an electronic manufacturing enterprise, the information such as employee's working time, education certificate number, post skill examination score, etc. is sorted out and input into the deep learning model together with the abnormal behavior data of welding operation.

[0199] The targeted training course is to develop an online animation demonstration of the chemical leakage and diffusion process, and offline simulation leakage scene is built in the training base for the employee to operate.

[0200] The beneficial effects of the above technical solutions are: through comparison and analysis and determination of abnormal behavior, the abnormal behavior can be accurately located, which provides basis for targeted training, and the model is used to deeply analyze the root cause of abnormal behavior, which provides support for generating targeted courses. The course meets the needs of employees, improves training efficiency and effectiveness.

[0201] Finally, it should be pointed out that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for constructing a safety education and training system for operating personnel, characterized in that: include: Step 1: Using IoT terminals, collect real-time data on the training company's operating environment and the quality and behavior of staff working in the operating environment, thereby obtaining the company's corporate information, including the risk types and risk levels of different operating environments. The obtaining of the enterprise information of the training enterprise includes: collecting the operating environment data of the training enterprise in real time through an Internet of Things terminal to generate a scenario risk map; and simultaneously obtaining the quality behavior of the staff performing work in the operating environment to obtain quality characteristics and construct a quality capability map; Step 2: Analyze training needs based on the competency map of the enterprise information, and design a safety education and training system based on the preset training framework. The safety education and training system covers all key safety knowledge points in different operating environments. The process of analyzing training needs includes: dividing the scenario risk map into grids and performing data annotation to generate a plurality of unit scenario grids; Based on the preset data categories, the data of the unit scene grid is normalized, and the normalization coefficients are weighted according to the dynamic weight allocation model; Calculating an environment coefficient of the unit scene grid based on the normalized coefficient; in, represents the environmental coefficient of the a-th unit scene grid; Represents the normalization coefficient of the i-th data category of the a-th unit scene grid; represents the weight of the i-th data category; represents the normalized coefficient of the j-th high-risk factor under the a-th unit scenario grid; Indicates high risk coefficient; n indicates the number of data categories; Indicates the number of high-risk factors present in the high-risk combination; Calculate the overall environmental factor of the scenario risk map based on all environmental factors; in, represents the overall environmental factor; represents the Euclidean distance from the a-th unit scene grid to the k-th sensor; p represents the attenuation coefficient, which is 0.1; m represents the number of sensors; Indicates the total number of unit scene grids; The analyzing of training needs includes: analyzing the probability of human error of the operating personnel based on the quality and capability map; Calculate risk scores based on the overall environmental factor, probability of human error, risk type, and corresponding risk level; in, represents the risk score of the t-th risk type; Indicates the weight of the overall environmental coefficient; represents the risk value of the t-th risk type; The weight representing the risk type; represents the average probability of all human errors involved in the t-th risk type; represents the weight of the probability of human error; ln represents the logarithmic function; Generate training requirements based on the risk scores of all risk types and the proportion of each risk type; The analyzing the operator's error probability based on the quality capability graph includes: in, represents the probability of human error of the corresponding staff under the t-th risk type; represents the probability function; Represents the actual operating behavior of the corresponding staff under the t-th risk type based on the quality and ability diagram analysis Standard operating procedures Similarity function probability of danger; Indicates the total number of risk types that exist; sum indicates the cumulative sum symbol; Step 3: Obtain the enterprise requirements and industry standards of the training enterprise based on a preset database, and develop courses based on the safety education and training system; Step 4: Establish a training effectiveness evaluation system based on preset dimensions and obtain evaluation results, where the evaluation results include trainee satisfaction, theoretical assessment results, and practical assessment results; Step 5: Optimize the safety education and training system based on the evaluation results.

2. The method for constructing a safety education and training system for operating personnel according to claim 1, characterized in that: Obtain corporate information of training companies, including: Obtaining the SOP file of each operation of the training enterprise, pre-processing the SOP file, and determining key data based on the industry dictionary of the industry in which the training enterprise is located; Determine whether the critical data involves high-risk equipment; If involved, determine the risk type in the corresponding operating environment based on the risk trigger conditions and in combination with the scenario risk map and quality and capability map; Determine the risk factor of the corresponding operating environment based on the risk type and the preset risk factor quantitative table; Determine the protective measures for the risk type according to the key data, and modify the risk coefficient based on the protective measures to obtain the risk level.

3. The method for constructing a safety education and training system for operating personnel according to claim 1, characterized in that: Design a safety education and training system, including: Get preset training frameworks; Analyze basic training content based on the stated training needs; Conduct content analysis on the basic training content and set training factors; The preset training framework is filled in according to the basic training content and the training factors to generate the safety education and training system.

4. The method for constructing a safety education and training system for operating personnel according to claim 1, characterized in that: Obtain the enterprise requirements and industry standards of the training enterprise and develop courses based on the safety education and training system, including: Compare the strictness of the enterprise requirements and the industry standards to determine the most stringent requirements; Select theoretical courses and practical courses from a preset database according to the high stringency requirements and the safety education and training system; Obtain the operating procedures of the practical course; Binding the operation process to the device model to obtain a standard operation process; Obtain historical incident cases for the standard operating procedures; The historical accident cases are injected into the standard operating procedures to obtain situational courses.

5. The method for constructing a safety education and training system for operating personnel according to claim 1, characterized in that: Optimizing the safety education and training system based on the evaluation results, including: Obtaining the evaluation result of each operator; Determine the first course whose satisfaction level is lower than the preset student satisfaction level based on the satisfaction level of all students in each course; performing a first course analysis on the first course; Optimizing the first course based on the analysis of the first course; Performing a first error analysis on all the theoretical assessment results to determine a first common error; Locating a second course based on the first common error; conducting a second course analysis on the second course; optimizing the second course based on the analysis of the second course; Performing a second error analysis on all the practical examination results to determine the second common errors; Locate the third course based on the second common error; The third course is optimized according to the second common errors.

6. The method for constructing a safety education and training system for operating personnel according to claim 1, characterized in that: After optimizing the safety education and training system based on the evaluation results, the following steps are included: The training behavior results of each staff member based on each working environment are obtained, and compared with the standard behavior in the optimized system to determine abnormal behavior and combine it with the characteristics of the operating personnel. The results are input into the behavior analysis model to obtain targeted training courses and sent to the user end of the staff. The targeted training courses are related to online learning, offline practice and simulation exercises.

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