Underground worker safety tracking system based on intelligent safety helmet

Abstract

The invention discloses an underground worker safety tracking system based on an intelligent safety helmet, relates to the technical field of intelligent monitoring of production safety, and solves the technical problem that the influence of dangerous factors on underground workers is difficult to accurately monitor and analyze in real time. Potential safety hazards can be found in time by monitoring parameters such as positioning, gas concentration and oxygen content of underground workers in real time, the probability of accident occurrence is reduced, the action track of the underground workers is analyzed, track abnormal signals are generated when abnormal speed occurs, potential risks are further judged in combination with heart rate data, and the safety of the underground workers is improved. According to the intelligent safety helmet, the monitoring precision of the safety state of a worker is improved, early warning can be given out in time under dangerous conditions, the life safety of the worker is guaranteed, and the intelligent safety helmet integrates multiple functional units and is easy to operate. Operators can flexibly set parameters such as time t and threshold values according to actual conditions, and adaptability and practicability of the system are improved.

Description

Technical Field

[0001] The invention relates to the technical field of production safety intelligent monitoring, and in particular to a safety tracking system for underground workers based on intelligent safety helmets. Background Art

[0002] With the continuous development of science and technology, the safety requirements for underground operations are getting higher and higher. The emergence of smart helmets provides a new technical means for the safety tracking of underground workers. At present, high-precision positioning technology, sensor technology and wireless communication technology are constantly developing and maturing, providing technical support for the construction of underground worker safety tracking systems based on smart helmets.

[0003] According to the publication number CN116798183A, it is specifically a high-risk workstation safety monitoring method and device based on multi-target visual tracking, including: the Nth worker enters the high-risk workstation area, instantiates the Nth FDSST visual target tracker, and realizes multi-target tracking; the current worker starts the Nth FDSST visual target tracker by long pressing the touch control button at the set start position; all target trackers track each worker in the workstation area in real time, calculate and compare the size between the relevant filter response value corresponding to each target and the set value to determine whether an occlusion event occurs, and further start the particle filter tracking algorithm for the occluded target; when the worker enters the dangerous area, it is determined that the current worker's working status is high-risk, and the high-risk workstation safety monitoring system based on multi-target visual tracking issues an audible and visual prompt, and intervenes in the control system to terminate the equipment operation; when the worker wants to leave the work station, first enters the set end position, and long presses the touch end button to turn off the FDSST visual target tracker of the current target.

[0004] However, when some existing smart safety helmets are in use, due to the complex underground environment, it is difficult to accurately monitor and analyze the impact of these dangerous factors on underground workers in real time, and they have the disadvantages of low efficiency, poor accuracy, and difficulty in timely detection of potential dangers. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a safety tracking system for underground workers based on smart safety helmets, which solves the problem that it is difficult to accurately monitor and analyze the impact of these dangerous factors on underground workers in real time.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a safety tracking system for underground workers based on smart safety helmets, comprising: The positioning information analysis module analyzes the positioning safety of underground workers based on the positioning data of the worker information collection module, generates normal signals or abnormal signals for gas concentration and oxygen content, generates regional risk information or potential risk analysis signals based on the number of abnormal signals, calculates the underground safety risk index for the potential risk analysis signal and transmits it to the safety adaptive analysis module; The state information analysis module analyzes the acquired state parameters, generates a trajectory abnormality signal and a real-time speed analysis signal based on the movement trajectory of the underground workers, transmits the trajectory abnormality signal to the safety adaptive analysis module, generates danger information or normal information by calculating the speed ratio of the real-time speed analysis signal, and transmits it to the safety tracking information output module; The safety adaptive analysis module determines potential risks based on the periodic changes in the safety risk index, generates regional risk information or normal working information, and analyzes abnormal trajectory signals. It further analyzes the heart rate data of underground workers and generates danger information and warning information.

[0007] As a further solution of the present invention: it also includes a worker information collection module and a safety tracking information output module; The worker information collection module is used to obtain the positioning parameters and state parameters of the underground workers, and transmit the obtained positioning parameters to the positioning information analysis module, and transmit the state parameters to the state information analysis module; The safety tracking information output module is used to display the acquired warning information, risk information and normal information to the corresponding operators.

[0008] As a further solution of the present invention: the specific manner in which the positioning information analysis module generates normal signals and abnormal signals is: Get the location of underground workers in real time, select a worker as the analysis object, use its location as the origin to determine the corresponding area underground as the analysis area, obtain the gas concentration and oxygen content in the analysis area, and compare them with the normal indicators of gas concentration and oxygen content. If the gas concentration is greater than the normal standard, an abnormal signal is generated, and if it is less than the normal standard, a normal signal is generated. Similarly, the oxygen content is compared and a corresponding normal or abnormal signal is generated.

[0009] As a further solution of the present invention: the positioning information analysis module generates regional risk information and potential risk analysis signals, and calculates the underground safety risk index in the following specific manners: Determine the number of normal signals and abnormal signals. If the number of abnormal signals is not zero, generate regional risk information. If the number of abnormal signals is zero, generate a potential risk analysis signal and process it. Obtain the gas concentration in the analysis area as Nw, the oxygen content as No, and the dust concentration as Nf, and then substitute the obtained parameters into the formula The underground safety risk index SRI is calculated, where A is the adjustment coefficient and the specific value is set by the operator. In the formula, Nwmax, Nomax and Nfmax are the maximum safety thresholds of gas concentration, oxygen content and dust concentration respectively. At the same time, the generated underground safety risk index SRI is transmitted to the safety adaptive analysis module.

[0010] As a further solution of the present invention: the specific method in which the safety adaptive analysis module generates regional risk information and normal working information is: Set time t, and judge the change of underground safety risk index SRI of the analysis area within time t. If SRI increases, it means that there is potential risk in the analysis area over time, and regional risk information is generated. If SRI decreases, there is no potential risk in the analysis area, and normal working information is generated. The generated regional risk information and normal working information are transmitted to the safety tracking information output module.

[0011] As a further solution of the present invention: the specific manner in which the state information analysis module analyzes the state parameters is: Based on the real-time positioning of the underground workers, their real-time trajectory and the corresponding underground area are obtained, and the regional environmental information of the area is obtained, and the regional environmental information includes the normal walking speed. At the same time, the real-time speed of the underground workers is obtained and compared with the regional environment; If the speed is less than the regional environment, the action trajectory is determined to be abnormal, and a trajectory abnormality signal is generated and transmitted to the safety adaptive analysis module; if the speed is greater than the regional environment, a real-time speed analysis signal is generated and analyzed; Calculate the ratio of real-time speed to regional environment. The specific formula is speed ratio = real-time speed ÷ regional environment. Judge the obtained speed ratio. If the speed ratio is greater than the threshold, generate danger information. Otherwise, if the speed ratio is less than the threshold, generate normal information. At the same time, transmit the generated danger information and normal information to the safety tracking information output module.

[0012] As a further solution of the present invention: the specific method in which the safety adaptive analysis module analyzes the abnormal trajectory signal is: The time T from the time when the real-time speed becomes abnormal is taken as the trajectory abnormal time, and the heart rate data of the underground workers is obtained, and the change is analyzed and the change value is calculated, and compared with the normal range. The specific value of the normal range is set by the operator; If the change value is not within the normal range, a heart rate secondary analysis signal is generated and the secondary analysis signal is analyzed at the same time; if it is within the normal range, a warning message is generated.

[0013] As a further solution of the present invention: the specific method in which the safety adaptive analysis module analyzes the heart rate secondary analysis signal is: Get the duration corresponding to the abnormal change value. If the duration exceeds the preset time value, it means there is a risk and generates danger information. Otherwise, if the duration does not exceed the preset time value, it means that an early warning is needed and generates early warning information. At the same time, the early warning information and risk information are transmitted to the safety tracking information output module.

[0014] The present invention provides a safety tracking system for underground workers based on smart helmets. Compared with the prior art, it has the following beneficial effects: The present invention can timely discover potential safety hazards and reduce the probability of accidents by real-time monitoring of the positioning, gas concentration, oxygen content and other parameters of underground workers. It can also analyze the movement trajectory of underground workers, generate a trajectory abnormality signal when an abnormal speed occurs, and further judge the potential risks in combination with heart rate data, thereby improving the monitoring accuracy of the workers' safety status. In dangerous situations, early warnings can be issued in time to ensure the safety of workers' lives. The smart helmet integrates multiple functional units, including a positioning unit, a sensor unit, a communication unit and an audible and visual alarm unit, and is easy to operate. The operator can flexibly set parameters such as time t and threshold according to actual conditions, which improves the adaptability and practicality of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a block diagram of the system principle of the present invention; Figure 2 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] For example, see Figure 1 and Figure 2 The present application provides a safety tracking system for underground workers based on smart helmets, including: a worker information collection module, a positioning information analysis module, a state information analysis module, a safety adaptive analysis module and a safety tracking information output module. Figure 1 It can be known that all the above functional modules are electrically connected in one direction.

[0018] A worker information collection module, which is used to obtain the positioning parameters and state parameters of the underground workers, and transmit the obtained positioning parameters to the positioning information analysis module, and transmit the state parameters to the state information analysis module, wherein the positioning parameters specifically refer to the real-time positioning of the underground workers, and the state parameters represent the heart rate data corresponding to the underground workers, which are specifically obtained through the smart safety helmets worn by the underground workers. The smart safety helmets are composed of multiple functional units, specifically a positioning unit, a sensor module, a communication unit, and an audible and visual alarm unit; Positioning unit: Use high-precision positioning technology, such as GPS, Beidou or UWB, to determine the worker's location information in real time.

[0019] Sensor unit: includes acceleration sensors, gyroscopes, air pressure sensors, etc., used to monitor workers' motion status, posture and environmental parameters.

[0020] Communication unit: supports wireless communication technologies such as Wi-Fi, Bluetooth or LoRa to transmit data to the monitoring center.

[0021] Sound and light alarm unit: When encountering dangerous situations, it will send out sound and light alarm signals to alert workers and surrounding people.

[0022] Positioning information analysis module, which is used to analyze the positioning safety of underground workers based on the positioning data transmitted by the worker information collection module, and the specific analysis method is as follows: The real-time positioning of the underground workers is obtained, and one of the underground workers is obtained as the analysis object. At the same time, the real-time positioning of the analysis object is used as the origin to obtain the corresponding underground area, and the obtained underground area is recorded as the analysis area. Then, the gas concentration and oxygen content corresponding to the analysis area are obtained, and compared with the normal standards respectively. The normal standard here refers to the normal index of gas concentration and the normal index of oxygen content. If the gas concentration is greater than the normal standard, an abnormal signal is generated. On the contrary, if the gas concentration is less than the normal standard, a normal signal is generated. Similarly, the oxygen content is compared with the normal standard, and a normal signal and an abnormal signal are generated; In a specific example, suppose that in an underground working environment of a coal mine, worker A is selected as the analysis object. The real-time position of worker A is determined as (X1, Y1, Z1) through the positioning system. With this position as the origin, a spherical area with a radius of R is delineated as the analysis area. At this time, the detection equipment detects the gas concentration and oxygen content in the analysis area. It is known that the normal gas concentration index is N1%, and the normal oxygen content index is N2%.

[0023] If the gas concentration detected in the analysis area is N3% and N3>N1, the system will generate a gas concentration abnormality signal. If the detected oxygen content is N4%, when N4<N2, the system will generate an oxygen content abnormality signal.

[0024] The number of generated normal signals and abnormal signals is judged. When the number of abnormal signals is not zero, it means that both normal signals and abnormal signals exist, which means that there is a risk in the analysis area, and regional risk information is generated at the same time. On the contrary, when the number of abnormal signals is zero, it means that only normal signals exist, which means that there is no risk in the analysis area, and a potential risk analysis signal is generated and processed; Obtain the gas concentration in the analysis area as Nw, the oxygen content as No, and the dust concentration as Nf, and then substitute the obtained parameters into the formula The underground safety risk index SRI is calculated, where A is the adjustment coefficient, and the specific value is set by the operator. In the formula, Nwmax, Nomax and Nfmax are the maximum safety thresholds of gas concentration, oxygen content and dust concentration respectively. At the same time, the generated underground safety risk index SRI is transmitted to the safety adaptive analysis module; Safety adaptive analysis module, which is used to perform periodic analysis on the acquired underground safety risk index, and to generate corresponding potential risk judgment results by judging the change of underground safety risk index within the period, and the specific judgment method is as follows: The change of the downhole safety risk index SRI of the analysis area within the time t is judged and analyzed, and the specific value of the time t here is set by the operator, which can be one hour or two hours. If the downhole safety risk index SRI increases within the time t, it means that there will be potential risks in the analysis area with the change of time, and the regional risk information is generated at the same time. If the downhole safety risk index SRI decreases or remains unchanged within the time t, it means that there is no potential risk in the analysis area with the change of time, and normal working information is generated at the same time; The generated regional risk information and normal working information are further transmitted to the safety tracking information output module.

[0025] Safety tracking information output module, which is used to display the acquired regional risk information and normal working information to the corresponding operators.

[0026] Embodiment 2, as Embodiment 2 of the present invention, is implemented on the basis of Embodiment 1, and differs from Embodiment 1 in that: The state information analysis module is used to analyze the acquired state parameters by analyzing the movement trajectory of the underground workers. The specific analysis method is as follows: Based on the real-time positioning of the underground worker, the corresponding real-time trajectory is obtained, and the underground area corresponding to the real-time trajectory is obtained, and then the regional environment of the underground area is obtained, and the regional environment here represents the corresponding underground area terrain route and the corresponding normal walking speed. At the same time, the real-time speed of the underground worker is obtained, and the real-time speed is compared with the regional environment. If the real-time speed is less than the regional environment, it means that the movement trajectory of the underground worker is abnormal, and a trajectory abnormality signal is generated. On the contrary, if the real-time speed is greater than the regional environment, a real-time speed analysis signal is generated at the same time, and the trajectory abnormality signal is transmitted to the safety adaptive analysis module; In a specific example, in an underground operation scene in a coal mine, the real-time positioning of Worker A shows that he is located in a specific tunnel area. Through the collection of the environment of the area, it is learned that the terrain of this area is relatively flat, and the normal walking speed range is 30 to 40 meters per minute. At this time, the real-time speed of Worker A is monitored to be 25 meters per minute. Further comparison shows that the trajectory is abnormal and a trajectory abnormality signal is generated. For another example, Worker B is in another tunnel area, and the normal walking speed range of this area is also 30 to 40 meters per minute. The real-time speed of Worker B is monitored to be 45 meters per minute. At this time, the monitored speed exceeds the normal speed and requires further analysis.

[0027] The generated real-time speed analysis signal is analyzed, and the ratio of the real-time speed to the regional environment is calculated. The specific formula is speed ratio = real-time speed ÷ regional environment, and the obtained speed ratio is judged. If the speed ratio is greater than the threshold, and the specific value of the threshold here is set by the operator, in this application, the threshold is 1, then a dangerous information is generated, otherwise if the speed ratio is less than the threshold, normal information is generated, and the generated dangerous information and normal information are transmitted to the safety tracking information output module. Specifically, for example, there is a danger in the corresponding area, causing the speed of the underground workers to exceed the normal standard of the area.

[0028] Safety adaptive analysis module, which is used to analyze the acquired trajectory abnormal signals and danger information, and make a comprehensive judgment based on the corresponding status parameters of the underground workers.

[0029] For the trajectory abnormality signal, the trajectory abnormality time is obtained, and the trajectory abnormality time here means the time T from the start of the abnormality at the real-time speed. The heart rate data of the underground workers is obtained, and the change of the heart rate data during the trajectory abnormality time is analyzed. The change value of the heart rate data is calculated and compared with the normal range. If the change value is not within the normal range, a heart rate abnormality is generated, and a heart rate secondary analysis signal is generated. If the change value is within the normal range, an early warning message is generated; Assume that in a certain underground operation scenario, the real-time speed of an underground worker is abnormal. After the system receives the trajectory abnormality signal, it determines that the trajectory abnormality time is 30 minutes after the speed abnormality begins (T=30 minutes). During this period, the heart rate data of the worker is obtained. After analysis, it is found that in the first 10 minutes, the heart rate increased from 70 beats per minute to 90 beats per minute, and the calculated heart rate change value is 20 beats per minute. Assuming that the normal heart rate change value range is 0-15 beats per minute, since the change value exceeds the normal range, the system generates a heart rate abnormality prompt and generates a heart rate secondary analysis signal.

[0030] The generated heart rate secondary analysis signal is analyzed to obtain the duration corresponding to the abnormal change value. If the duration exceeds the preset time value, it indicates that there is a risk and generates danger information. Conversely, if the duration does not exceed the preset time value, it indicates that an early warning is needed and generates early warning information. At the same time, the early warning information and risk information are transmitted to the safety tracking information output module.

[0031] Further analysis found that this abnormal heart rate state lasted for 25 minutes, while the preset time value was 20 minutes. Since the duration exceeded the preset time value, the system determined that there was a risk and generated a danger message, such as "The worker's heart rate was abnormal for a long time, and he may face health risks or be in a dangerous environment. Rescue measures must be taken immediately."

[0032] The safety tracking information output module is used to display the acquired warning information, risk information and normal information to the corresponding operators.

[0033] Embodiment 3, as the embodiment 3 of the present invention, focuses on combining the implementation processes of embodiment 1 and embodiment 2 for implementation.

[0034] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0035] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. The underground worker safety tracking system based on smart helmets is characterized by: include: The positioning information analysis module analyzes the positioning safety of underground workers based on the positioning data of the worker information collection module, generates normal signals or abnormal signals for gas concentration and oxygen content, generates regional risk information or potential risk analysis signals based on the number of abnormal signals, calculates the underground safety risk index for the potential risk analysis signal and transmits it to the safety adaptive analysis module; The state information analysis module analyzes the acquired state parameters, generates a trajectory abnormality signal and a real-time speed analysis signal based on the movement trajectory of the underground workers, transmits the trajectory abnormality signal to the safety adaptive analysis module, generates danger information or normal information by calculating the speed ratio of the real-time speed analysis signal, and transmits it to the safety tracking information output module; The safety adaptive analysis module determines potential risks based on the periodic changes in the safety risk index, generates regional risk information or normal working information, and analyzes abnormal trajectory signals. It further analyzes the heart rate data of underground workers and generates danger information and warning information.

2. The underground worker safety tracking system based on the smart helmet according to claim 1 is characterized in that: It also includes a worker information collection module and a safety tracking information output module; The worker information collection module is used to obtain the positioning parameters and state parameters of the underground workers, and transmit the obtained positioning parameters to the positioning information analysis module, and transmit the state parameters to the state information analysis module; The safety tracking information output module is used to display the acquired warning information, risk information and normal information to the corresponding operators.

3. The underground worker safety tracking system based on the smart helmet according to claim 1 is characterized in that: The specific method for the positioning information analysis module to generate normal signals and abnormal signals is: Get the location of underground workers in real time, select a worker as the analysis object, use its location as the origin to determine the corresponding area underground as the analysis area, obtain the gas concentration and oxygen content in the analysis area, and compare them with the normal indicators of gas concentration and oxygen content. If the gas concentration is greater than the normal standard, an abnormal signal is generated, and if it is less than the normal standard, a normal signal is generated. Similarly, the oxygen content is compared and a corresponding normal or abnormal signal is generated.

4. The underground worker safety tracking system based on the smart helmet according to claim 1 is characterized in that: The specific method of the positioning information analysis module generating regional risk information and potential risk analysis signals and calculating the underground safety risk index is as follows: Determine the number of normal signals and abnormal signals. If the number of abnormal signals is not zero, generate regional risk information. If the number of abnormal signals is zero, generate a potential risk analysis signal and process it. Obtain the gas concentration in the analysis area as Nw, the oxygen content as No, and the dust concentration as Nf, and then substitute the obtained parameters into the formula The underground safety risk index SRI is calculated, where A is the adjustment coefficient and the specific value is set by the operator. In the formula, Nwmax, Nomax and Nfmax are the maximum safety thresholds of gas concentration, oxygen content and dust concentration respectively. At the same time, the generated underground safety risk index SRI is transmitted to the safety adaptive analysis module.

5. The underground worker safety tracking system based on the smart helmet according to claim 1 is characterized in that: The specific method of the safety adaptive analysis module to generate regional risk information and normal working information is as follows: Set time t, and judge the change of underground safety risk index SRI of the analysis area within time t. If SRI increases, it means that there is potential risk in the analysis area over time, and regional risk information is generated. If SRI decreases, there is no potential risk in the analysis area, and normal working information is generated. The generated regional risk information and normal working information are transmitted to the safety tracking information output module.

6. The underground worker safety tracking system based on the smart helmet according to claim 1 is characterized in that: The specific method in which the state information analysis module analyzes the state parameters is as follows: Based on the real-time positioning of the underground workers, their real-time trajectory and the corresponding underground area are obtained, and the regional environmental information of the area is obtained, and the regional environmental information includes the normal walking speed. At the same time, the real-time speed of the underground workers is obtained and compared with the regional environment; If the speed is less than the regional environment, the action trajectory is determined to be abnormal, and a trajectory abnormality signal is generated and transmitted to the safety adaptive analysis module; if the speed is greater than the regional environment, a real-time speed analysis signal is generated and analyzed; Calculate the ratio of real-time speed to regional environment. The specific formula is speed ratio = real-time speed ÷ regional environment. Judge the obtained speed ratio. If the speed ratio is greater than the threshold, generate danger information. Otherwise, if the speed ratio is less than the threshold, generate normal information. At the same time, transmit the generated danger information and normal information to the safety tracking information output module.

7. The underground worker safety tracking system based on the smart helmet according to claim 1 is characterized in that: The specific method in which the safety adaptive analysis module analyzes the trajectory abnormality signal is as follows: The time T from the time when the real-time speed becomes abnormal is taken as the trajectory abnormal time, and the heart rate data of the underground workers is obtained, and the change is analyzed and the change value is calculated, and compared with the normal range. The specific value of the normal range is set by the operator; If the change value is not within the normal range, a heart rate secondary analysis signal is generated and the secondary analysis signal is analyzed at the same time; if it is within the normal range, a warning message is generated.

8. The underground worker safety tracking system based on the smart helmet according to claim 7 is characterized in that: The specific method in which the safety adaptive analysis module analyzes the heart rate secondary analysis signal is as follows: Get the duration corresponding to the abnormal change value. If the duration exceeds the preset time value, it means there is a risk and generates danger information. Otherwise, if the duration does not exceed the preset time value, it means that an early warning is needed and generates early warning information. At the same time, the early warning information and risk information are transmitted to the safety tracking information output module.

Images