Underground special area early warning system

Abstract

The invention discloses an underground special area early warning system, which comprises an integrated system end, a static early warning monitoring hardware group and a dynamic early warning monitoring hardware group, and is characterized in that the static early warning monitoring hardware group is used for outputting a switching value signal to the integrated system end and carrying out sound-light alarm after a person enters an alarm area and generates a stay signal; static early warning monitoring hardware is arranged to output a switching value signal to an integrated system end and carry out sound-light alarm after a person enters an alarm area and generates a stay signal, and after the sound-light alarm, a dynamic early warning monitoring hardware group is used to capture a walking dynamic state after the person enters the alarm area. A risk rating is formed according to walking dynamic and static early warning monitoring hardware monitoring missing quantities and dynamic early warning monitoring hardware monitoring missing quantities, a current comparison digital value is finally formed according to the risk rating, and a corresponding early warning scheme is implemented by analyzing a difference point between the risk rating and a fixed value model. And the accuracy of an early warning signal emitted during early warning processing is ensured.

Description

Technical Field

[0001] The invention relates to the technical field of early warning systems, and in particular to an early warning system for special areas underground. Background Art

[0002] In order to prevent workers from illegally entering or staying in dangerous areas underground in coal mines, traditional intrusion systems mainly use sensor technology and electronic information technology to detect and indicate illegal entry or attempts to illegally enter the defense area, process alarm information, and issue alarm information. Although this type of intrusion warning system can complete real-time monitoring of dangerous demarcated areas, there are still the following specific problems:

[0003] 1. When workers frequently enter and exit dangerous areas, it is easy to trigger the early warning system identification signal multiple times, that is, it is easy to generate misjudgment signals after only passing through the dangerous area to the regular area, which is not conducive to the rating of early warning risks. The generated alarm prompt signal is too single, and workers cannot adjust their position or leave the dangerous area in time according to their own wrong behavior.

[0004] 2. The traditional early warning system arranges sensors at multiple points. Even if a single sensor receives a signal, it will directly respond to the intrusion state. When workers go back and forth in the dangerous area, the intrusion signal will still be triggered. Therefore, the verification method of the traditional early warning system is mainly to trigger the response state through multiple directional sensors at the same time, and then issue an early warning. It is impossible to issue corresponding early warning information based on the missing items when the sensor is triggered and the risk ratio of the corresponding area after the missing signal. The accuracy of the early warning processing is not ideal. For this reason, we propose an underground special area early warning system. Summary of the invention

[0005] The main purpose of the present invention is to provide an underground special area early warning system.

[0006] To achieve the above object, the technical solution adopted by the present invention is:

[0007] The underground special area early warning system includes an integrated system end, a static early warning monitoring hardware group and a dynamic early warning monitoring hardware group. The static early warning monitoring hardware is used to output a switch signal to the integrated system end and perform an audible and visual alarm after a person enters the alarm area and generates a stop signal. The dynamic early warning monitoring hardware group is used to capture the walking dynamics of a person after entering the alarm area, and to form a risk rating based on the walking dynamics, and to form a current comparison digital value based on the risk rating;

[0008] The static early warning monitoring hardware group and the dynamic early warning monitoring hardware group are both set up in the early warning area. There are several static early warning monitoring hardware groups, which are respectively arranged around the equipment in the early warning area, around the entrances and exits of the early warning area, and around the movable range of the warning area. After receiving the sound and light alarm signal, the integrated system end synchronously outputs a control signal to the dynamic early warning monitoring hardware group, and uses the dynamic early warning monitoring hardware group to verify in real time whether the personnel have left the alarm area after receiving the sound and light alarm signal.

[0009] A further improvement of the present invention is that the static early warning monitoring hardware group includes a programmable control box, a pyroelectric infrared sensor and an AI camera. The pyroelectric infrared sensor and the AI ​​camera are arranged in the early warning area to dual-item monitor whether the incoming personnel form missing items on the monitoring surface due to the reciprocating entry and exit of the warning area, and then verify the staying status of the incoming personnel inside the warning area.

[0010] A further improvement of the present invention is that the dynamic warning monitoring hardware group includes a wireless signal transmission module, a following signal processing module, a scanning recognition execution module, an image acquisition module and a tracking and control module. After the static warning monitoring hardware has confirmed the staying status of the entering person in the warning area, the wireless transmission module is used to upload the staying status information confirmed by the static warning monitoring hardware to the following signal processing unit. The following signal processing unit edits the operation information of the image acquisition module, the scanning recognition execution module and the tracking and control module according to the dynamic vanishing point of the person obtained by the static warning monitoring hardware. The tracking and control module drives the image acquisition module and the scanning recognition execution module along the dynamic vanishing point to perform dynamic approval and recognition, confirm the interval duration and frequency of the person entering and exiting the alarm area, and finally upload it to the system end, which forms a risk rating based on the dynamic data.

[0011] A further improvement of the present invention is that the method for using the underground special area early warning system comprises the following steps:

[0012] Step S1, obtaining risk parameter values ​​of dynamic intrusion and static stay in the restricted area, and constructing a first basic database model and a second basic database model according to the risk parameter values;

[0013] Step S2: setting a risk rating according to the risk parameter value, using the trigger threshold of the possible risk to determine the warning intensity, and establishing a fixed value model for comparing the risk rating;

[0014] Step S3, obtaining a comparison digital value according to a fixed value model of risk rating;

[0015] Step S4: Analyze the differences between the first basic database model and the second basic database model and the fixed value model of risk rating, and implement corresponding early warning plans according to the differences.

[0016] A further improvement of the present invention is that the method for using the underground special area early warning system includes editing the trigger number of the static early warning monitoring hardware group:

[0017] Set the number of pyro-infrared sensor locations in the static early warning monitoring hardware to U 1 , U 2 , U 3 and U 4 ...U n , set the AI ​​camera arrangement points in the static early warning monitoring hardware to several, and set them as V according to the number 1 、V 2 、V 3 and V 4 ...U n , which is used as a quick location number for the missing item on the system side;

[0018] Obtain the monitoring missing amount fluctuation range of the pyro infrared sensor and AI camera in the static early warning monitoring hardware, and set the missing amount toggle range in the pyro infrared sensor to M a 、M b 、M c ...M n , set the fluctuation range of the monitoring loss of the AI ​​camera to Z a , Z b , Z c ...Z n .

[0019] A further improvement of the present invention is that the method for using the underground special area early warning system further includes constructing a universal value for comparing the missing amount of intrusion risk, the steps of which are:

[0020] Substitute the fluctuation interval value of the pyroelectric infrared sensor and the conventional monitoring parameters into the following formula to obtain the general data, that is, the general data Where Nc is the calculated value, KU n Refers to U 1 , U 2 , U 3 and U 4 ...U n The non-alarm missing quantity during operation monitoring is substituted into the following formula to obtain the general data by substituting the monitoring missing quantity fluctuation range and conventional monitoring parameters of the AI ​​camera into the following formula, that is, the general data

[0021] According to the risk probability ratio of the pyro-infrared sensor and the AI ​​camera at each arrangement point when the monitoring is missing, the risk ratio of the pyro-infrared sensor missing is obtained. AI camera missing risk probability ratio The risk probability ratio is expressed as W o .

[0022] The missing option in the system-side positioning static early warning monitoring hardware number is substituted into the pyro-infrared sensor missing risk ratio AI camera missing risk probability ratio The final result is compared with the non-alarm missing quantity KU n The comparison constitutes a risk rating and a warning signal is generated by the integrated system.

[0023] Compared with the prior art, the present invention sets static early warning monitoring hardware to generate a stop signal after a person enters the alarm area, outputs a switch signal to the integrated system end and performs an audible and visual alarm, and captures the walking dynamics of the person after entering the alarm area through a dynamic early warning monitoring hardware group after the audible and visual alarm. A risk rating is formed according to the walking dynamics, the missing amount monitored by the static early warning monitoring hardware, and the missing amount monitored by the dynamic early warning monitoring hardware. Finally, the current comparison digital value is formed according to the risk rating. By analyzing the difference between the risk rating and the fixed value model, a corresponding early warning plan is implemented, thereby ensuring the accuracy of the early warning signal issued during the early warning processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a structural schematic diagram of the static early warning monitoring hardware group in the underground special area early warning system of the present invention.

[0025] Figure 2 It is a structural schematic diagram of the dynamic early warning monitoring hardware group in the underground special area early warning system of the present invention.

[0026] Figure 3 The figure is a flow chart of the underground special area early warning system of the present invention. DETAILED DESCRIPTION

[0027] The present invention is further described below in conjunction with specific embodiments, wherein the accompanying drawings are only used for exemplary descriptions and represent only schematic diagrams rather than actual drawings, and should not be understood as limitations on this patent. In order to better illustrate the specific embodiments of the present invention, some parts of the accompanying drawings may be omitted, enlarged or reduced, and do not represent the size of the actual product. For those skilled in the art, it is understandable that some well-known structures and their descriptions in the accompanying drawings may be omitted. Based on the specific embodiments of the present invention, all other specific embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0028] Example

[0029] See also Figure 1-Figure 3, the underground special area early warning system includes an integrated system end, a static early warning monitoring hardware group and a dynamic early warning monitoring hardware group. The static early warning monitoring hardware is used to output a switch signal to the integrated system end and make an audible and visual alarm after a person enters the alarm area and generates a stop signal. The dynamic early warning monitoring hardware group is used to capture the walking dynamics of a person after entering the alarm area, and to form a risk rating based on the walking dynamics, and to form a current comparison digital value based on the risk rating;

[0030] Furthermore, both the static early warning monitoring hardware group and the dynamic early warning monitoring hardware group are set up in the early warning area. There are several static early warning monitoring hardware groups, which are arranged around the equipment in the early warning area, around the entrances and exits of the early warning area, and around the movable range of the warning area. After receiving the sound and light alarm signal, the integrated system end synchronously outputs a control signal to the dynamic early warning monitoring hardware group, and uses the dynamic early warning monitoring hardware group to verify in real time whether the personnel have left the alarm area after receiving the sound and light alarm signal.

[0031] Furthermore, the static early warning monitoring hardware group includes a programmable control box, a pyroelectric infrared sensor and an AI camera. The pyroelectric infrared sensor and the AI ​​camera are set in the early warning area for dual monitoring to see whether the incoming personnel have formed missing items on the monitoring surface due to the reciprocating entry and exit of the warning area, and then verify the staying status of the incoming personnel in the warning area.

[0032] Furthermore, the dynamic warning monitoring hardware group includes a wireless signal transmission module, a following signal processing module, a scanning recognition execution module, an image acquisition module and a tracking and control module. After the static warning monitoring hardware has confirmed the staying status of the entering person inside the warning area, the wireless transmission module is used to upload the staying status information confirmed by the static warning monitoring hardware to the following signal processing unit. The following signal processing unit edits the operation information of the image acquisition module, the scanning recognition execution module and the tracking and control module according to the dynamic vanishing point of the person obtained by the static warning monitoring hardware. The tracking and control module drives the image acquisition module and the scanning recognition execution module along the dynamic vanishing point to perform dynamic approval and identification, confirm the interval duration and frequency of the person entering and leaving the alarm area, and finally upload it to the system end, which constructs a risk rating based on the dynamic data.

[0033] In this embodiment, in order to solve the problem that workers frequently enter and exit dangerous areas and easily trigger the early warning system identification signal multiple times, that is, only after the dangerous area is transitioned to the conventional area, it is easy to generate a misjudgment signal, which is not conducive to the rating of early warning risks, and the generated alarm prompt signal is too single, and the workers cannot adjust their positions or leave the dangerous area in time according to their own wrong behaviors, the present invention sets a static early warning monitoring hardware group and a dynamic early warning monitoring hardware group, and the static early warning monitoring hardware group once verifies whether the worker exists in the warning area to perform an early warning process, and after the early warning process, the infinite transmission module is used to upload the stay status information verified by the static early warning monitoring hardware to the following signal processing unit, and the following signal processing unit edits the operation information of the image acquisition module, the scanning recognition execution module and the tracking control module according to the dynamic vanishing point of the personnel obtained by the static early warning monitoring hardware, and the tracking control module drives the image acquisition module and the scanning recognition execution module along the dynamic vanishing point to perform dynamic verification and recognition, confirm the interval time and frequency of the personnel entering and exiting the alarm area, and finally upload it to the system end, and the system end forms a risk rating according to the dynamic data, thereby improving the accuracy of the early warning signal issued during the early warning process.

[0034] In this embodiment, after the pyro infrared sensors are arranged, when the underground personnel enter the effective monitoring range of the infrared probe, the infrared rays generated by the heat of the human body are converged by the Fresnel lens, stimulating the infrared receiver to generate a low-frequency signal, and then outputting a processing signal to the programmable control box, so that the programmable control box sends an early warning signal to the system end. Among them, the programmable control box can verify whether the workers are in the warning area once through the pyro infrared sensors and AI cameras after the arrangement points of the pyro infrared sensors and AI cameras are set, and send an early warning signal to the system end after obtaining the signal to remove people, and the system end sends an expulsion alarm signal. After that, the programmable control box analyzes the specific points triggered by the corresponding sorting editing number of the pyro infrared sensor or AI camera, and uploads it to the follow-up signal processing unit through the wireless signal transmission module in the dynamic early warning monitoring hardware group.

[0035] In this embodiment, a single-chip microcomputer is selected as the following signal processing unit. After the following signal processing unit obtains the specific point triggered by the sorting editing number of the pyro-infrared sensor or the AI ​​camera, it generates a corresponding control command, and then controls the tracking control module to drive the image acquisition module and the scanning recognition execution module to move along the dynamic vanishing point, so that the dynamic approval image acquisition module and the scanning recognition execution module check the specific point triggered by the sorting editing number and the dynamic vanishing point of the personnel, confirm the interval duration and frequency of the personnel entering and leaving the alarm area, and then upload the obtained interval duration and frequency of entering and leaving the alarm area to the system end, and the system end constructs a risk rating based on the dynamic data, thereby improving the accuracy of the warning signal issued during the warning processing.

[0036] Furthermore, the method for using the underground special area early warning system is characterized by comprising the following steps:

[0037] Step S1, obtaining risk parameter values ​​of dynamic intrusion and static stay in the restricted area, and constructing a first basic database model and a second basic database model according to the risk parameter values;

[0038] Step S2: setting a risk rating according to the risk parameter value, using the trigger threshold of the possible risk to determine the warning intensity, and establishing a fixed value model for comparing the risk rating;

[0039] Step S3, obtaining a comparison digital value according to a fixed value model of risk rating;

[0040] Step S4: Analyze the differences between the first basic database model and the second basic database model and the fixed value model of risk rating, and implement corresponding early warning plans according to the differences.

[0041] Furthermore, the method for using the underground special area early warning system also includes the following steps. First, edit the trigger number of the static early warning monitoring hardware group:

[0042] Set the number of pyro-infrared sensor locations in the static early warning monitoring hardware to U 1 , U 2 , U 3 and U 4 ...U n , set the AI ​​camera arrangement points in the static early warning monitoring hardware to several, and set them as V according to the number 1 、V 2 、V 3 and V 4 ...U n , which is used as a quick location number for the missing item on the system side;

[0043] Obtain the monitoring missing amount fluctuation range of the pyro infrared sensor and AI camera in the static early warning monitoring hardware, and set the missing amount toggle range in the pyro infrared sensor to M a 、M b 、M c ...M n , set the fluctuation range of the monitoring loss of the AI ​​camera to Z a , Z b , Z c ...Z n .

[0044] Secondly, a common value for comparing the missing amount of intrusion risk is constructed. The steps are:

[0045] Substitute the fluctuation interval value of the pyroelectric infrared sensor and the conventional monitoring parameters into the following formula to obtain the general data, that is, the general data Where Nc is the calculated value, KU n Refers to U 1 , U 2 , U 3 and U 4 ...U n The non-alarm missing quantity during operation monitoring is substituted into the following formula to obtain the general data by substituting the monitoring missing quantity fluctuation range and conventional monitoring parameters of the AI ​​camera into the following formula, that is, the general data

[0046] According to the risk probability ratio of the pyro-infrared sensor and the AI ​​camera at each arrangement point when the monitoring is missing, the risk ratio of the pyro-infrared sensor missing is obtained. AI camera missing risk probability ratio The risk probability ratio is expressed as W o .

[0047] The missing option in the system-side positioning static early warning monitoring hardware number is substituted into the pyro-infrared sensor missing risk ratio AI camera missing risk probability ratio The final result is compared with the non-alarm missing quantity KU n The comparison constitutes a risk rating and a warning signal is generated by the integrated system.

[0048] The working principle and usage method of the present invention are: by setting static early warning monitoring hardware to generate a stop signal after a person enters the alarm area, a switch signal is output to the integrated system end and an sound and light alarm is performed. After the sound and light alarm, the walking dynamics of the person after entering the alarm area is captured by the dynamic early warning monitoring hardware group, and a risk rating is formed according to the walking dynamics, the missing amount monitored by the static early warning monitoring hardware, and the missing amount monitored by the dynamic early warning monitoring hardware. Finally, a comparison digital value is formed according to the risk rating, and a corresponding early warning scheme is implemented by analyzing the difference between the risk rating and the fixed value model.

[0049] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. The underground special area early warning system is characterized by: It includes an integrated system end, a static early warning monitoring hardware group and a dynamic early warning monitoring hardware group. The static early warning monitoring hardware is used to output a switch signal to the integrated system end and make an audible and visual alarm after a person enters the alarm area and generates a stop signal. The dynamic early warning monitoring hardware group is used to capture the walking dynamics of a person after entering the alarm area, and to form a risk rating based on the walking dynamics, and to form a current comparison digital value based on the risk rating; The static early warning monitoring hardware group and the dynamic early warning monitoring hardware group are both set up in the early warning area. There are several static early warning monitoring hardware groups, which are respectively arranged around the equipment in the early warning area, around the entrances and exits of the early warning area, and around the movable range of the warning area. After receiving the sound and light alarm signal, the integrated system end synchronously outputs a control signal to the dynamic early warning monitoring hardware group, and uses the dynamic early warning monitoring hardware group to verify in real time whether the personnel have left the alarm area after receiving the sound and light alarm signal.

2. The underground special area early warning system according to claim 1 is characterized by: The static early warning monitoring hardware group includes a programmable control box, a pyroelectric infrared sensor and an AI camera. The pyroelectric infrared sensor and the AI ​​camera are arranged in the early warning area for dual-item monitoring to see whether the incoming personnel have formed missing items on the monitoring surface due to the reciprocating entry and exit of the warning area, and then verify the staying status of the incoming personnel inside the warning area.

3. The underground special area early warning system according to claim 1 is characterized by: The dynamic warning monitoring hardware group includes a wireless signal transmission module, a following signal processing module, a scanning recognition execution module, an image acquisition module and a tracking and control module. After the static warning monitoring hardware has confirmed the staying status of the entering person in the warning area, the wireless transmission module is used to upload the staying status information confirmed by the static warning monitoring hardware to the following signal processing unit. The following signal processing unit edits the operation information of the image acquisition module, the scanning recognition execution module and the tracking and control module according to the dynamic vanishing point of the person obtained by the static warning monitoring hardware. The tracking and control module drives the image acquisition module and the scanning recognition execution module along the dynamic vanishing point to perform dynamic approval and recognition, confirm the interval duration and frequency of the person entering and leaving the alarm area, and finally upload it to the system end, which forms a risk rating based on the dynamic data.

4. The method for using the underground special area early warning system according to claims 1-3 is characterized in that: The following steps are involved: Step S1, obtaining risk parameter values ​​of dynamic intrusion and static stay in the restricted area, and constructing a first basic database model and a second basic database model according to the risk parameter values; Step S2: setting a risk rating according to the risk parameter value, using the trigger threshold of the possible risk to determine the warning intensity, and establishing a fixed value model for comparing the risk rating; Step S3, obtaining a comparison digital value according to a fixed value model of risk rating; Step S4: Analyze the differences between the first basic database model and the second basic database model and the fixed value model of risk rating, and implement corresponding early warning plans according to the differences.

5. The method for using the underground special area early warning system according to claim 4 is characterized in that: Edit the trigger number of the static early warning monitoring hardware group, including, Set the number of pyro-infrared sensor locations in the static early warning monitoring hardware to U 1 , U 2 , U 3 and U 4 ...U n , set the AI ​​camera arrangement points in the static early warning monitoring hardware to several, and set them as V according to the number 1 、V 2 、V 3 and V 4 ...U n , which is used as a quick location number for the missing item on the system side; Obtain the monitoring missing amount fluctuation range of the pyro infrared sensor and AI camera in the static early warning monitoring hardware, and set the missing amount toggle range in the pyro infrared sensor to M a 、M b 、M c ...M n , set the fluctuation range of the monitoring loss of the AI ​​camera to Z a , Z b , Z c ...Z n .

6. The method for using the underground special area early warning system according to claim 4 is characterized by: It also includes constructing a universal value for comparing the missing amount of invasion risk, the steps of which are: Substitute the fluctuation interval value of the pyroelectric infrared sensor and the conventional monitoring parameters into the following formula to obtain the general data, that is, the general data Where Nc is the calculated value, KU n Refers to U 1 , U 2 , U 3 and U 4 ...U n The non-alarm missing quantity during operation monitoring is substituted into the following formula to obtain the general data by substituting the monitoring missing quantity fluctuation range and conventional monitoring parameters of the AI ​​camera into the following formula, that is, the general data According to the risk probability ratio of the pyro-infrared sensor and the AI ​​camera at each arrangement point when the monitoring is missing, the risk ratio of the pyro-infrared sensor missing is obtained. AI camera missing risk probability ratio The risk probability ratio is expressed as W o ; The missing option in the system-side positioning static early warning monitoring hardware number is substituted into the pyro-infrared sensor missing risk ratio AI camera missing risk probability ratio The final result is compared with the non-alarm missing quantity KU n The comparison constitutes a risk rating and a warning signal is generated by the integrated system.

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