Fire-fighting simulation training system based on smoke heat tracking and positioning technology

Abstract

The invention belongs to the field of fire-fighting simulation training, relates to a data analysis technology, and aims to solve the problem that the ability defect of each fireman during simulation training cannot be analyzed from an individual perspective in the prior art, in particular to a fire-fighting simulation training system based on a smoke heat tracking and positioning technology, which comprises a simulation training platform, the simulation training platform is in communication connection with a parameter generation module, a training execution module, an optimization analysis module and a database; the parameter generation module is used for generating simulation training parameters for the fire-fighting simulation training field: setting a plurality of target task points in the fire-fighting simulation training field, and generating corresponding environment simulation parameters for the target task points; according to the invention, the simulation training parameters can be generated for the fire-fighting simulation training field, the corresponding and unique environment simulation parameters are generated for each target task point, and the environment parameters of the training field are set according to the environment simulation parameters, so that the environment diversity of the simulation training field is improved.

Description

Technical Field

[0001] The present invention belongs to the field of fire simulation training and relates to data analysis technology, in particular to a fire simulation training system based on smoke and heat tracking and positioning technology. Background Art

[0002] The fire simulation training system is used to simulate a real fire environment and improve the practical ability and psychological quality of firefighters. This method constructs a highly simulated training environment, including extreme conditions such as thick smoke and high temperature, so that firefighters can train in such an environment to improve their response ability and teamwork.

[0003] The invention patent with announcement number CN108806451B discloses a fire training simulation device, which simulates specific accident scenarios through wind source providers and heat source providers, so that trainees can be as close to actual operations as possible, greatly saving training costs and improving training efficiency; however, the device cannot analyze the ability deficiencies of each firefighter during simulation training from an individual perspective, nor can it analyze the environmental factors that cause the greatest interference to the firefighters in performing training tasks from an overall perspective. Therefore, it is impossible to capture the key points of daily training, resulting in poor results of simulation training.

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The purpose of the present invention is to provide a firefighting simulation training system based on smoke and heat tracking and positioning technology, which is used to solve the problem that the existing technology cannot analyze the ability deficiencies of each firefighter during simulation training from an individual perspective;

[0006] The technical problem to be solved by the present invention is: how to provide a fire simulation training system based on smoke and heat tracking and positioning technology that can analyze the ability deficiencies of each firefighter during simulation training from an individual perspective.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] The firefighting simulation training system based on smoke and heat tracking and positioning technology includes a simulation training platform, which is communicatively connected with a parameter generation module, a training execution module, an optimization analysis module and a database;

[0009] The parameter generation module is used to generate simulation training parameters for the fire simulation training site: a number of target task points are set in the fire simulation training site, and corresponding environmental simulation parameters are generated for the target task points, the environmental simulation parameters including environmental temperature, environmental smoke concentration and flame coverage;

[0010] The training execution module is used to perform simulation training on firefighters: mark the firefighters who are undergoing simulation training as training subjects, randomly assign L1 target task points to the training subjects and mark them as training tasks for the training subjects, set the training environment of the training site according to the environmental simulation parameters of the target task points, and then the training subjects depart from the starting point to the target task points and return after completing the tasks, and obtain the execution efficiency value of the training subjects performing the corresponding training tasks; after the training subjects complete all the training tasks, calculate the average value of the execution efficiency values ​​of the training subjects corresponding to all the training tasks and mark it as the basic training value of the training subjects, calculate the variance of the execution efficiency values ​​of the training subjects corresponding to all the training tasks and mark it as the strain training value of the training subjects; and judge whether the basic skills and strain ability of the training subjects meet the requirements through the basic training value and strain training value of the training subjects;

[0011] The optimization analysis module is used to optimize and analyze the daily training content of firefighters.

[0012] Furthermore, the ambient temperature, ambient smoke concentration and flame coverage are values ​​randomly selected from the test environment range, test smoke concentration range and test flame coverage range respectively; the flame coverage is the ratio of the flame coverage area to the area of ​​the circular area obtained by drawing a circle with the target task point as the center and R1; the environmental simulation parameters of all target task points are sent to the training execution module through the simulation training platform.

[0013] Furthermore, the process of obtaining the execution efficiency value of the training object includes: marking the time between the time when the training object returns and the time when the training object departs as the execution time for the training object to perform the corresponding training task, marking the shortest path length value of the target task point relative to the starting point as the execution distance, and marking the ratio of the execution distance to the execution time as the execution efficiency value of the training object to perform the corresponding training task.

[0014] Furthermore, the specific process of determining whether the basic skills and adaptability of the training object meet the requirements includes: obtaining the basic training threshold and the adaptability training threshold through the database, and comparing the basic training value and the adaptability training value of the training object with the basic training threshold and the adaptability training threshold respectively: if the basic training value is greater than or equal to the basic training threshold, it is determined that the basic skills of the training object do not meet the requirements, and the corresponding training object is marked as a basic unqualified object, a basic training signal is generated, and the basic training signal is sent to the mobile phone terminal of the basic unqualified object through the simulation training platform; if the basic training value is less than the basic training threshold and the adaptability training value is less than the adaptability training threshold, it is determined that the basic skills and adaptability of the training object both meet the requirements; if the basic training value is less than the basic training threshold and the adaptability training value is greater than or equal to the adaptability training threshold, it is determined that the adaptability of the training object does not meet the requirements, the corresponding training object is marked as a adaptability unqualified object, a adaptability training signal is generated, and the adaptability training signal is sent to the mobile phone terminal of the adaptability unqualified object through the simulation training platform.

[0015] Furthermore, the specific process of the optimization analysis module optimizing and analyzing the daily training content of firefighters includes: extracting the environmental simulation parameters of the unqualified strain objects and constructing a strain optimization set, comparing the strain optimization set with all the environmental simulation parameters to obtain the temperature impact value, smoke impact value and flame impact value, marking the environmental parameter corresponding to the maximum value among the temperature impact value, smoke impact value and flame impact value as the key training parameter, and sending the key training parameter to the mobile terminal of the manager through the simulation training platform.

[0016] Furthermore, the process of obtaining the strain optimization set includes: arranging the training tasks corresponding to the unqualified strain objects in order of execution efficiency values ​​from small to large, marking the environmental simulation parameters of the target task points corresponding to the top L2 training tasks as the strain optimization parameters of the unqualified strain objects, and forming a strain optimization set with the strain optimization parameters of all unqualified strain objects.

[0017] Furthermore, the process of obtaining the temperature influence value, the smoke influence value and the flame influence value includes: sorting all environmental simulation parameters according to the environmental temperature from low to high, the environmental smoke concentration from low to high, and the flame coverage from low to high to obtain the temperature influence sequence, the smoke influence sequence and the flame influence sequence, summing up and averaging the corresponding serial numbers of all elements in the strain optimization set in the corresponding temperature influence sequence to obtain the temperature influence value, summing up and averaging the corresponding serial numbers of all elements in the strain optimization set in the corresponding smoke influence sequence to obtain the smoke influence value, and summing up and averaging the corresponding serial numbers of all elements in the strain optimization set in the corresponding flame influence sequence to obtain the flame influence value.

[0018] Furthermore, the working method of the fire simulation training system based on smoke and heat tracking positioning technology includes the following steps:

[0019] Step 1: Generate simulation training parameters for the fire simulation training site: set a number of target task points in the fire simulation training site, and generate corresponding environmental simulation parameters for the target task points;

[0020] Step 2: Conduct simulation training for firefighters and determine whether the basic skills and adaptability of the training subjects meet the requirements;

[0021] Step 3: Optimize and analyze the daily training content of firefighters and mark key training parameters.

[0022] The present invention has the following beneficial effects:

[0023] 1. The parameter generation module can generate simulation training parameters for the fire simulation training site, generate corresponding and unique environmental simulation parameters for each target task point, and set the environmental parameters of the training site according to the environmental simulation parameters, thereby improving the environmental diversity of the simulation training site;

[0024] 2. The training execution module can be used to conduct simulated training for firefighters. After the training subjects complete all training tasks, the execution efficiency values ​​corresponding to all training tasks are numerically calculated to obtain the basic training value and the strain training value. Based on the basic training value and the strain training value, the basic skills and strain ability of the training personnel are fed back. In the event of an abnormality, targeted daily training is conducted for the training personnel to improve their comprehensive quality.

[0025] 3. The training analysis module can be used to optimize and analyze the daily training content of firefighters, extract the training tasks of those who fail to meet the response requirements, and then analyze the sequence numbers of the strain optimization set in the environmental parameter influence sequence, extract the environmental factors that have the highest impact on execution efficiency as a whole, and provide key training directions for subsequent daily training tasks. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] 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 will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0027] Figure 1 is a system block diagram of Embodiment 1 of the present invention;

[0028] Figure 2 This is a flow chart of the method of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0029] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only 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 creative work are within the scope of protection of the present invention.

[0030] Embodiment 1: Figure 1 As shown, the fire simulation training system based on smoke and heat tracking and positioning technology includes a simulation training platform, which is communicatively connected with a parameter generation module, a training execution module, an optimization analysis module and a database.

[0031] The parameter generation module is used to generate simulation training parameters for the fire simulation training site: several target task points are set in the fire simulation training site, and corresponding environmental simulation parameters are generated for the target task points. The environmental simulation parameters include ambient temperature, ambient smoke concentration and flame coverage.

[0032] The ambient temperature, ambient smoke concentration and flame coverage are values ​​randomly selected from the test environment range, test smoke concentration range and test flame coverage range respectively; the flame coverage is the ratio of the flame coverage area to the area of ​​the circular area obtained by drawing a circle with the target task point as the center and R1; the environmental simulation parameters of all target task points are sent to the training execution module through the simulation training platform; simulation training parameters are generated for the fire simulation training site, corresponding and unique environmental simulation parameters are generated for each target task point, and the environmental parameters of the training site are set according to the environmental simulation parameters, thereby improving the environmental diversity of the simulation training site.

[0033] The training execution module is used to conduct simulation training for firefighters: the firefighters undergoing simulation training are marked as training subjects, L1 target task points are randomly assigned to the training subjects and marked as training tasks for the training subjects, the training environment of the training site is set according to the environmental simulation parameters of the target task points, and then the training subjects depart from the starting point to the target task point and return after completing the task, the time between the time when the training subjects return and the time when the training subjects depart is marked as the execution time of the training subjects performing the corresponding training tasks, the shortest travel path length value of the target task point relative to the starting point is marked as the execution distance, and the ratio of the execution distance to the execution time is marked as the execution efficiency value of the training subjects performing the corresponding training tasks;

[0034] After the training object completes all training tasks, the average of the execution efficiency values ​​of the training object corresponding to all training tasks is calculated and marked as the basic training value of the training object, and the variance of the execution efficiency values ​​of the training object corresponding to all training tasks is calculated and marked as the strain training value of the training object.

[0035] The basic training threshold and the strain training threshold are obtained through the database, and the basic training value and the strain training value of the training object are compared with the basic training threshold and the strain training threshold respectively:

[0036] If the basic training value is greater than or equal to the basic training threshold, it is determined that the basic skills of the training object do not meet the requirements, the corresponding training object is marked as a basic unqualified object, a basic training signal is generated and sent to the mobile terminal of the basic unqualified object through the simulation training platform;

[0037] If the basic training value is less than the basic training threshold and the strain training value is less than the strain training threshold, it is determined that the basic skills and strain ability of the training object meet the requirements;

[0038] If the basic training value is less than the basic training threshold and the strain training value is greater than or equal to the strain training threshold, it is determined that the strain ability of the training object does not meet the requirements, the corresponding training object is marked as an unqualified strain object, a strain training signal is generated and the strain training signal is sent to the mobile terminal of the unqualified strain object through the simulation training platform; the firefighters are subjected to simulation training, and after the training objects complete all training tasks, the execution efficiency values ​​corresponding to all training tasks are numerically calculated to obtain the basic training value and the strain training value, so as to provide feedback on the basic skills and strain ability of the training personnel according to the basic training value and the strain training value, and carry out targeted daily training for the training personnel in abnormal situations to improve the comprehensive quality of the training personnel.

[0039] The optimization analysis module is used to optimize and analyze the daily training content of firefighters: the training tasks corresponding to the unqualified strain objects are arranged in order of execution efficiency value from small to large, and the environmental simulation parameters of the target task points corresponding to the top L2 training tasks are marked as the strain optimization parameters of the unqualified strain objects. The strain optimization parameters of all unqualified strain objects constitute the strain optimization set.

[0040] All environmental simulation parameters are sorted from low to high according to the environmental temperature, from low to high according to the environmental smoke concentration, and from low to high according to the flame coverage, to obtain the temperature influence sequence, the smoke influence sequence, and the flame influence sequence. The corresponding serial numbers of all elements in the strain optimization set in the corresponding temperature influence sequence are summed and averaged to obtain the temperature influence value, the corresponding serial numbers of all elements in the strain optimization set in the corresponding smoke influence sequence are summed and averaged to obtain the smoke influence value, and the corresponding serial numbers of all elements in the strain optimization set in the corresponding flame influence sequence are summed and averaged to obtain the flame influence value. The environmental parameter corresponding to the maximum value among the temperature influence value, the smoke influence value, and the flame influence value is marked as the key training parameter, and the key training parameter is sent to the mobile phone terminal of the manager through the simulation training platform; the daily training content of firefighters is optimized and analyzed, the training tasks of unqualified objects are extracted, and then the serial numbers of the strain optimization set in the environmental parameter influence sequence are analyzed to extract the environmental factors with the highest degree of influence on execution efficiency as a whole, thereby providing key training directions for subsequent daily training tasks.

[0041] Embodiment 2: Figure 2 As shown, the firefighting simulation training method based on smoke and heat tracking positioning technology includes the following steps:

[0042] Step 1: Generate simulation training parameters for the fire simulation training site: set a number of target task points in the fire simulation training site, and generate corresponding environmental simulation parameters for the target task points;

[0043] Step 2: Conduct simulation training for firefighters: mark the firefighters who are undergoing simulation training as training subjects, randomly assign L1 target task points to the training subjects and mark them as training tasks for the training subjects, obtain the basic training value and the strain training value when the training subjects complete all the training tasks, and judge whether the basic skills and strain ability of the training subjects meet the requirements through the basic training value and the strain training value;

[0044] Step 3: Optimize and analyze the daily training content of firefighters and form a strain optimization set. Calculate the sequence numbers of the elements in the strain optimization set in the temperature influence sequence, smoke influence sequence and flame influence sequence to obtain the temperature influence value, smoke influence value and flame influence value. Mark the key training parameters by the values ​​of the temperature influence value, smoke influence value and flame influence value.

[0045] The fire simulation training system based on smoke and heat tracking and positioning technology sets several target task points in the fire simulation training site when working, and generates corresponding environmental simulation parameters for the target task points; marks the firefighters undergoing simulation training as training objects, randomly assigns L1 target task points to the training objects and marks them as training tasks for the training objects, obtains the basic training values ​​and strain training values ​​of the training objects when they complete all training tasks, and judges whether the basic skills and strain capabilities of the training objects meet the requirements through the basic training values ​​and strain training values; optimizes and analyzes the daily training content of firefighters and forms a strain optimization set, calculates the sequence numbers of the elements in the strain optimization set in the temperature influence sequence, smoke influence sequence and flame influence sequence to obtain the temperature influence value, smoke influence value and flame influence value, and marks the key training parameters through the values ​​of the temperature influence value, smoke influence value and flame influence value.

[0046] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0047] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0048] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. Firefighting simulation training system based on smoke and heat tracking and positioning technology, characterized by: It includes a simulation training platform, which is communicatively connected with a parameter generation module, a training execution module, an optimization analysis module and a database; The parameter generation module is used to generate simulation training parameters for the fire simulation training site: a number of target task points are set in the fire simulation training site, and corresponding environmental simulation parameters are generated for the target task points, the environmental simulation parameters including environmental temperature, environmental smoke concentration and flame coverage; The training execution module is used to perform simulation training on firefighters: mark the firefighters who are undergoing simulation training as training subjects, randomly assign L1 target task points to the training subjects and mark them as training tasks for the training subjects, set the training environment of the training site according to the environmental simulation parameters of the target task points, and then the training subjects depart from the starting point to the target task points and return after completing the task, and obtain the execution efficiency value of the training subjects performing the corresponding training tasks; After the training object completes all training tasks, the average of the execution efficiency values ​​of the training object corresponding to all training tasks is calculated and marked as the basic training value of the training object, and the variance of the execution efficiency values ​​of the training object corresponding to all training tasks is calculated and marked as the strain training value of the training object; Judging whether the basic skills and adaptability of the training object meet the requirements through the basic training value and adaptability training value of the training object; The optimization analysis module is used to optimize and analyze the daily training content of firefighters.

2. The firefighting simulation training system based on smoke and heat tracking and positioning technology according to claim 1 is characterized in that: The ambient temperature, ambient smoke concentration and flame coverage are values ​​randomly selected from the test environment range, test smoke concentration range and test flame coverage range respectively; the flame coverage is the ratio of the flame coverage area to the area of ​​the circular area obtained by drawing a circle with the target task point as the center and R1 as the center; the environmental simulation parameters of all target task points are sent to the training execution module through the simulation training platform.

3. The firefighting simulation training system based on smoke and heat tracking and positioning technology according to claim 2 is characterized in that: The process of obtaining the execution efficiency value of the training object includes: marking the time between the time when the training object returns and the time when the training object departs as the execution time for the training object to perform the corresponding training task, marking the shortest path length value of the target task point relative to the starting point as the execution distance, and marking the ratio of the execution distance to the execution time as the execution efficiency value of the training object to perform the corresponding training task.

4. The firefighting simulation training system based on smoke and heat tracking and positioning technology according to claim 3 is characterized in that: The specific process of judging whether the basic skills and adaptability of the training object meet the requirements includes: obtaining the basic training threshold and the adaptability training threshold through the database, and comparing the basic training value and the adaptability training value of the training object with the basic training threshold and the adaptability training threshold respectively: if the basic training value is greater than or equal to the basic training threshold, it is judged that the basic skills of the training object do not meet the requirements, and the corresponding training object is marked as a basic unqualified object, a basic training signal is generated, and the basic training signal is sent to the mobile terminal of the basic unqualified object through the simulation training platform; if the basic training value is less than the basic training threshold and the adaptability training value is less than the adaptability training threshold, it is judged that the basic skills and adaptability of the training object both meet the requirements; if the basic training value is less than the basic training threshold and the adaptability training value is greater than or equal to the adaptability training threshold, it is judged that the adaptability of the training object does not meet the requirements, the corresponding training object is marked as a adaptability unqualified object, a adaptability training signal is generated, and the adaptability training signal is sent to the mobile terminal of the adaptability unqualified object through the simulation training platform.

5. The firefighting simulation training system based on smoke and heat tracking and positioning technology according to claim 4 is characterized in that: The specific process of the optimization analysis module to optimize and analyze the daily training content of firefighters includes: extracting the environmental simulation parameters of the unqualified strain objects and constructing a strain optimization set, comparing the strain optimization set with all environmental simulation parameters to obtain temperature impact values, smoke impact values ​​and flame impact values, marking the environmental parameters corresponding to the maximum values ​​among the temperature impact values, smoke impact values ​​and flame impact values ​​as key training parameters, and sending the key training parameters to the mobile phone terminals of managers through the simulation training platform.

6. The firefighting simulation training system based on smoke and heat tracking and positioning technology according to claim 5 is characterized in that: The process of obtaining the strain optimization set includes: arranging the training tasks corresponding to the unqualified strain objects in order of execution efficiency values ​​from small to large, marking the environmental simulation parameters of the target task points corresponding to the top L2 training tasks as the strain optimization parameters of the unqualified strain objects, and forming a strain optimization set from the strain optimization parameters of all unqualified strain objects.

7. The firefighting simulation training system based on smoke and heat tracking and positioning technology according to claim 6 is characterized in that: The process of obtaining the temperature influence value, smoke influence value and flame influence value includes: sorting all environmental simulation parameters according to the environmental temperature from low to high, the environmental smoke concentration from low to high, and the flame coverage from low to high to obtain the temperature influence sequence, the smoke influence sequence and the flame influence sequence, summing up and averaging the corresponding serial numbers of all elements in the strain optimization set in the corresponding temperature influence sequence to obtain the temperature influence value, summing up and averaging the corresponding serial numbers of all elements in the strain optimization set in the corresponding smoke influence sequence to obtain the smoke influence value, and summing up and averaging the corresponding serial numbers of all elements in the strain optimization set in the corresponding flame influence sequence to obtain the flame influence value.

8. The firefighting simulation training system based on smoke and heat tracking and positioning technology according to any one of claims 1 to 7, characterized in that: The working method of the fire simulation training system based on smoke and heat tracking positioning technology includes the following steps: Step 1: Generate simulation training parameters for the fire simulation training site: set a number of target task points in the fire simulation training site, and generate corresponding environmental simulation parameters for the target task points; Step 2: Conduct simulation training for firefighters and determine whether the basic skills and adaptability of the training subjects meet the requirements; Step 3: Optimize and analyze the daily training content of firefighters and mark key training parameters.

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