Underground construction early warning and personnel safety evacuation guiding system

Abstract

According to the underground construction early warning and personnel safety evacuation guiding system, the safety risk identification module detects quality, environment and personnel sign parameters of underground construction and enters the safety risk evaluation module, parameter inspection and index prediction are carried out in combination with historical parameter indexes, predicted parameter indexes of different regions are obtained, a region parameter set is formed, and the safety of the underground construction is improved. The method comprises the following steps: calculating a danger coefficient, predicting the danger coefficient and a total construction danger coefficient, entering a safety risk early warning module, carrying out overall early warning, region early warning, grade early warning, group early warning and individual early warning according to the position of each region and the construction danger coefficient of the region, and carrying out targeted and grade safety detection early warning; the escape path guiding module selects a safe and short path for escape according to the structural layout of the safety channel and the early-warning dangerous area, and issues the sign sub-module and the evacuation indication system for dynamic guidance, so that rapid evacuation of the escape path can be optimized.

Description

Technical Field

[0001] The invention belongs to the technical field of underground construction, and in particular relates to an underground construction early warning and personnel safety evacuation guidance system. Background Art

[0002] Underground projects include underground houses, subways, highway tunnels, supermarkets and other construction projects. Due to the complex construction environment and great construction difficulty of underground projects, the construction period of underground projects is relatively long. Once collapse or fire occurs during the construction process, it is very easy to cause serious personal injury and huge property losses, and at the same time it will cause the construction period to be extended. Therefore, it can be seen that real-time monitoring of the construction safety of underground projects is extremely important.

[0003] At present, the monitoring of underground construction safety mainly tests the stability of underground construction buildings and the quality of the construction environment, and is equipped with safety passage guidance signs, lighting, fire extinguishing, ventilation and other equipment to ensure that construction workers can evacuate to safe exits according to guidance signs in the event of collapse or fire accidents. However, it cannot carry out targeted safety detection and early warning at different levels according to the hazard area and degree of hazard, nor can it optimize the escape route for rapid evacuation based on the density of construction workers and their vital signs. It cannot meet the current needs for comprehensive and highly reliable monitoring of underground construction safety and rapid evacuation. Summary of the invention

[0004] In view of the above situation, in order to overcome the defects of the prior art, the present invention provides an underground construction early warning and personnel safe evacuation guidance system, which can carry out targeted and graded safety detection and early warning according to the hazard area and degree of hazard, and can optimize the escape route for rapid evacuation according to the density and vital signs of construction personnel.

[0005] Its technical solution is to include a safety risk identification module, a safety risk assessment module, a safety risk warning module, and an escape route guidance module. The safety risk identification module includes a construction quality identification submodule, a construction environment submodule, and a construction personnel physical sign submodule. The construction quality identification submodule includes underground construction building fracture, settlement, tilt, pressure, and vibration parameter indicators. After the abnormal values ​​are eliminated, the change amount and change rate index of each parameter indicator are further calculated. The parameter indicators and the change amount and change rate index of each parameter indicator are changed, and the safety risk assessment module is actively entered under the sampling frequency of the change rate indicator.

[0006] The construction environment submodule includes temperature and humidity, smoke, PM2.5, oxygen concentration, methane concentration, and noise parameter indicators of the underground construction environment. When any of the weighted fusion of temperature and humidity and smoke, oxygen concentration, and methane concentration is abnormal, the safety risk assessment module is immediately and actively entered;

[0007] The construction worker's vital signs submodule includes blood oxygen, heart rate, heart rate, blood pressure, and respiratory parameter indicators. When the microprocessor determines that any of them is abnormal, an on-site sound and light alarm will be issued, and the safety risk assessment module will be entered through the GPS positioning and communication integrated module;

[0008] The security risk assessment module obtains the parameter indicators of the security risk identification module and the historical parameter indicators, normalizes them, builds a time series model, and performs parameter inspection and indicator prediction;

[0009] Obtain parameter indicators and historical parameter indicators of security risk identification modules in different regions and make parameter indicator predictions;

[0010] Obtain prediction parameter indicators for different regions, form a regional parameter set, and calculate the safety risk identification model.

[0011] The risk factor of each submodule of the block;

[0012] The total construction risk factor is obtained by weighted fusion of the risk factors of each submodule;

[0013] The safety risk warning module performs an overall warning based on the total construction risk factor;

[0014] According to the construction quality, the abnormal characteristic areas of the construction environment and the scope of impact, the corresponding areas and personnel are given graded warnings from strong to weak;

[0015] According to the common and individual abnormalities of construction workers' physical signs, group warning and dispersed warning are carried out;

[0016] The escape route guidance module selects a safe and short route for escape according to the structural layout of the safety passage and the warned dangerous area, and sends the construction personnel's vital sign sub-module and evacuation indication system to provide dynamic guidance.

[0017] The beneficial effects of the present invention are as follows: 1. By collecting the construction quality, construction environment and physical sign parameters of each underground area, testing each parameter and predicting the index, the parameter index prediction value is obtained, and then the risk coefficient and the predicted risk coefficient are obtained. The risk coefficient is firstly weighted and fused with the predicted risk coefficient of each submodule, and then the risk coefficient of each area after the first-level weighted fusion is subjected to the second-level weighted fusion to obtain the total construction risk coefficient of each area. According to the location of each area and the construction risk coefficient of the area, the distribution of the characteristic abnormal value is extracted to account for the proportion of the total area. When it reaches 85%, an overall warning is issued. When the discrete individual area is abnormal, the corresponding regional warning is issued;

[0018] When issuing regional warnings, the corresponding areas and personnel will be given level warnings from strong to weak according to the construction quality, abnormal characteristic areas of the construction environment and the scope of impact;

[0019] According to the common and individual abnormalities of the physical signs of construction workers, group warnings and individual warnings can be carried out. In this way, targeted and graded safety detection and warnings can be carried out according to the hazard area and hazard degree;

[0020] 2. According to the structural layout of the safety passage and the warned dangerous areas, choose a safe and short path for escape, and send the vital signs sub-module and evacuation indication system of the construction personnel who need to escape for dynamic guidance. It can optimize the escape path for rapid evacuation according to the density of construction personnel and vital signs. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a system block diagram of the present invention.

[0022] Figure 2 It is a flow chart of the steps of selecting a safe and short path for escape in the escape path guidance module of the present invention.

[0023] Figure 3 It is a flow chart of the steps of dynamic guidance in the escape route guidance module of the present invention. DETAILED DESCRIPTION

[0024] The technical solutions of various embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0025] The following is in conjunction with the instruction manual Figures 1 to 3 , the specific implementation modes of the present invention are further described in detail.

[0026] Embodiment 1, underground construction early warning and personnel safe evacuation guidance system, including safety risk identification module, safety risk assessment module, safety risk early warning module, escape path guidance module, the safety risk identification module includes construction quality identification submodule, construction environment submodule, construction personnel physical sign submodule, construction quality identification submodule is mainly used to detect the quality of underground construction buildings, arrange base points and detection points in advance, the layout of the detection points of this application is evenly arranged, the spacing between the detection points is 20m, including the detection of underground construction building fracture, settlement, inclination, pressure, vibration parameter index detection, after abnormal value removal, specifically, first filter the parameter value exceeding the range of the detection instrument, and then take the difference between the detection parameter value and the historical average value, and remove the abnormality if the standard deviation exceeds 3 times, and further calculate the change amount and change rate index of each parameter index, and the change amount is the periodic change amount △H i =H i -H i-1 , the change can also be the cumulative change Σ△H i =H i -H0, where △H iIndicates the change of monitoring points within a monitoring cycle, H i Indicates the monitoring value of the time, H i-1 Indicates the last monitoring value, Σ△H i It indicates the cumulative change from the first monitoring to the current monitoring, and the change rate is the periodic change rate b = periodic change △H i / period T, the current monitoring value, change amount, and change rate enter the security risk assessment module at the sampling frequency. Due to the high sampling frequency, the data volume is large and the processing burden is heavy. The low sampling frequency reduces the large data volume and the loss of important data. It is set to actively enter the security risk assessment module when the change rate index reaches the control value to adjust the sampling frequency. When the monitoring value and the change rate index reach the control value, the security risk assessment module can be actively entered immediately to reduce the data volume and avoid the loss of important data.

[0027] The construction environment submodule includes temperature and humidity, smoke, PM2.5, oxygen concentration, methane concentration, and noise parameter indicators of the underground construction environment. Since PM2.5 and noise reflect the air quality indicators in the construction environment, the former is that particulate matter at the construction site enters the human body through the respiratory tract, and the latter is that the noise at the construction site affects people's hearing, vision, and mood. Long-term exposure to them is harmful to human health. The safety risk assessment module is entered at the sampling frequency. Since fire, explosion, and oxygen can directly cause casualties and property losses, it is set that when any of the weighted fusion of temperature and humidity and smoke, oxygen concentration, and methane concentration is abnormal, that is, when the fire, oxygen, and explosion indicators reach 75% of the hazard value, the sampling frequency is immediately adjusted (for example, the sampling switch is triggered to turn on when abnormal, and the sampling frequency is adjusted) to actively enter the safety risk assessment module;

[0028] The construction worker vital signs submodule includes blood oxygen, heart rate, blood pressure, and respiratory parameter indicators. Specifically, a blood oxygen saturation sensor, a heart rate sensor, a blood pressure sensor, and a respiratory rate sensor can be used to collect the construction worker's blood oxygen saturation, blood pressure, heart rate, and respiratory rate vital signs. The microprocessor judges and monitors. When any indicator is abnormal, the sound and light alarm is driven to sound and light alarm on the spot. The safety risk assessment module is entered through the GPS positioning communication integrated module, and a Bluetooth module can be set to connect nearby construction workers. If someone sounds an on-site sound and light alarm, nearby personnel will automatically receive the alarm and rush to rescue in time. It can be integrated into a bracelet or a safety construction helmet;

[0029] The safety risk assessment module obtains the parameter indicators of the safety risk identification module and the historical parameter indicators, normalizes the data of different dimensions into a unified dimension, constructs the time series model ARMA, performs parameter test and indicator prediction, and the parameter test adopts variance analysis. By performing a significance test analysis on the difference between the detected parameter indicator and the mean of two or more nearby parameters, the reliability and effectiveness of the selected model are ensured, and the value of the future time point is accurately predicted. The specific process of indicator prediction is to use the exponential extrapolation method H i+1 =abt prediction value change trend, where H i+1 represents the trend value, a represents the intercept, b represents the periodic change rate, and t represents the time. Substitute the data to generate the predicted operating risk value, the predicted value H i+1 And it is corrected by the residual, where the residual is the difference between the historical predicted value and the actual value. According to the control value and the predicted value, the time rt to reach the control value is calculated, rt = (control value - predicted value) / ab i+1 When the control value is less than the sampling period, the sampling frequency is adjusted to facilitate timely acquisition of detection parameters, which can be fed back to the safety risk warning module for rapid response to warnings. i+1 represents the forecast period change rate;

[0030] Obtain parameter indicators and historical parameter indicators of security risk identification modules in different regions and make parameter indicator predictions;

[0031] Obtain prediction parameter indicators for different regions, form a regional parameter set, and calculate the safety risk identification model.

[0032] The danger coefficient of each submodule of the block is specifically as follows: the danger coefficient of the construction quality identification submodule sz=d+q+c+v+f, where d is the fracture coefficient, q is the inclination coefficient, c is the settlement coefficient, v is the pressure coefficient, and f is the vibration coefficient. Each coefficient is obtained by comparing each detection parameter + the change rate of each detection parameter with the safety value of each detection parameter. Similarly, the predicted danger coefficient is obtained based on the predicted value of each detection parameter, sz+1;

[0033] The hazard coefficient of the construction environment submodule is sh=sh1+sh2, where sh1 is the fire hazard coefficient and sh2 is the air quality coefficient. The fire hazard coefficient sh1 is obtained by weighted fusion of temperature, humidity and smoke, and then weighted average fusion of oxygen concentration and methane concentration, and then compared with the fire hazard value. Similarly, the predicted values ​​of each detection parameter are used to obtain the predicted hazard coefficient, sh+1;

[0034] The air quality coefficient sh2 is obtained by comparing PM2.5 and noise detection parameters with the safety values ​​of each detection parameter;

[0035] The risk coefficient SR of the construction personnel's physical sign submodule first cleans the blood oxygen, heart rate, heart rate, blood pressure, and respiratory parameter data; secondly, normalizes them and converts them into a unified dimension; finally, the Kalman filter is used to recursively estimate and fuse the parameter values ​​to obtain an estimated value, and the estimated value is compared with the normal value to obtain the risk coefficient SR;

[0036] The weighted fusion of the risk coefficients of each submodule is used to obtain the total construction risk coefficient of each area. The risk coefficients of each submodule are firstly weighted fused with the predicted risk coefficients of each submodule, and then the risk coefficients of each area after the first-level weighted fusion are weighted fused at the second level to obtain the total construction risk coefficient of each area. Specifically, in the first-level weighted fusion, the weights of construction quality, construction environment, and construction personnel physical signs are set to 50%, 50%, and 50% respectively. The fusion formula is = (construction quality x 50%+Construction environment x 50%) / N+physical signs of construction workers x 50%, where N is 1 when there is any abnormality in the construction quality or construction environment, otherwise it is 2. When there is any abnormality in the construction quality or construction environment and the physical signs of the construction personnel are abnormal, the risk factor is 100%. The secondary weighted fusion sets the weight according to the total number of areas, and adjusts the weight according to the location of the dangerous area, the density of the personnel in the area, and the impact caused, so as to adjust the total construction risk factor;

[0037] The safety risk warning module performs an overall warning based on the total construction risk factor. Specifically, according to the location of each area and the construction risk factor of the area, the distribution of characteristic abnormal values ​​is extracted to account for the proportion of the total area. When it reaches 85%, an overall warning is performed. When a discrete individual area is abnormal, a corresponding regional warning is performed;

[0038] When issuing regional warnings, the corresponding areas and personnel will be given level warnings from strong to weak according to the construction quality, abnormal characteristic areas of the construction environment and the scope of impact;

[0039] According to the common and individual abnormalities of the physical signs of construction workers, group warnings and individual warnings can be carried out. In this way, targeted and graded safety detection and warnings can be carried out according to the hazard area and hazard degree;

[0040] The escape route guidance module selects a safe and short route for escape according to the structural layout of the safety passage and the warned dangerous areas, and sends the vital sign sub-module and evacuation indication system of the construction personnel who need to escape for dynamic guidance. It can optimize the escape route for rapid evacuation according to the density and vital signs of the construction personnel.

[0041] Embodiment 2, based on embodiment 1, the escape path guidance module selects a safe and short path for escape according to the structural layout of the safety passage and the dangerous area warned, specifically:

[0042] Step 1, obtaining a structural layout diagram of an underground construction safety passage;

[0043] Step 2, obtain the type of warning and call the corresponding warning point;

[0044] Step 3: The highest level warning point is used as the starting point, and each safe exit is used as the target point. A neural network is used to plan a total of n optimal paths from the starting point to n target points with the affected range as the obstacle avoidance point to perform safe path planning;

[0045] Step 4: Based on step 3, calculate the time consumed for each path and select the path with the shortest time as the escape path for the construction workers. Specifically:

[0046] First, the speed-density empirical formula is used to calculate the movement speed ui of the construction workers.

[0047]

[0048] Where ui is the movement speed of the i-th construction worker in m / s, ρ is the crowd density of construction workers on each path, and the unit is personnel / m 2 ;

[0049] Secondly, the movement time TC is calculated through the path distance d, ui;

[0050] Next, the Togawa empirical formula is used to calculate the passage time TE of the emergency exit.

[0051]

[0052] Among them, NG is the total number of people evacuated from the safety exit, W is the width of the safety exit (m), and h is the personnel flow coefficient;

[0053] Finally, the total time consumed by each path is calculated, T = TC + TE, and the path with the smallest T is selected as the current optimal path and provided to the construction personnel, which is conducive to choosing a safe and short path for rapid escape.

[0054] Embodiment 3, based on Embodiment 2, the submodule for issuing the vital signs of construction personnel who need to escape and the evacuation indication system for dynamic guidance are specifically as follows:

[0055] Step 1: The escape route guidance module sends the optimal route to the construction worker vital sign submodule through sharing;

[0056] Step 2: The escape path guidance module sends the optimal path to the evacuation indication system through sharing;

[0057] Step 3: Construction workers are dynamically guided to evacuate according to the optimal path and signposts;

[0058] Step 4: Identify the walking behavior and GPS location information of the construction workers;

[0059] Step 5, using the TLC evaluation algorithm to determine whether the path is deviated;

[0060] Step 6: When deviation occurs, timely broadcast reminder;

[0061] Step 7: When construction workers walk on a non-optimal path, their identity information and GPS location information are transmitted to the safety risk assessment module for real-time tracking to obtain construction workers' dynamics in a timely manner.

[0062] Embodiment 4, based on embodiment 2, the construction worker vital sign submodule recognizes the walking behavior of the construction workers by using human infrared sensors and gyroscope sensors to distinguish the behavior of the construction workers and facilitate deviation analysis from the planned path.

[0063] When the present invention is used specifically: a safety risk identification module, a safety risk assessment module, a safety risk warning module, and an escape path guidance module are set. The safety risk identification module includes a construction quality identification submodule, a construction environment submodule, and a construction personnel vital sign submodule. The construction quality identification submodule is mainly used to detect the quality of underground construction buildings, including the detection of fracture, settlement, inclination, pressure, and vibration parameter indicators of underground construction buildings. After abnormal values ​​are eliminated, the change amount and change rate indicators of each parameter indicator are calculated, that is, the current monitoring value, change amount, and change rate are entered into the safety risk assessment module at the sampling frequency;

[0064] The construction environment submodule detects the temperature and humidity, smoke, PM2.5, oxygen concentration, methane concentration, and noise parameter indicators of the underground construction environment and enters the safety risk assessment module;

[0065] The construction worker's vital signs submodule collects the construction worker's blood oxygen saturation, blood pressure, heart rate, and respiratory rate vital signs. The microprocessor judges and monitors. When any indicator is abnormal, the sound and light alarm is driven to sound and light alarm on site, and the safety risk assessment module is entered through the GPS positioning communication integrated module.

[0066] The safety risk assessment module obtains the parameter indicators of the safety risk identification module and the historical parameter indicators. First, normalization is used to convert data of different dimensions into a unified dimension, and the time series model ARMA is constructed to perform parameter inspection and indicator prediction to obtain the predicted value. The time to reach the control value is calculated based on the control value and the predicted value. Secondly, the predicted parameter indicators of different regions are obtained to form a regional parameter set, and the risk coefficient and predicted risk coefficient of each submodule of the safety risk identification module are calculated. The risk coefficient is firstly weightedly fused with the predicted risk coefficient of each submodule, and then the risk coefficient of each region after the first-level weighted fusion is weightedly fused by the second-level weighted fusion. The total construction risk factor of each area is obtained, and the safety risk warning module is entered. According to the location of each area and the construction risk factor of the area, the distribution of characteristic abnormal values ​​is extracted to account for the proportion of the total area. When it reaches 85%, an overall warning is issued. When discrete individual areas are abnormal, corresponding regional warnings are issued. When regional warnings are issued, according to the construction quality, construction environment abnormal characteristic areas and the scope of the impact, the corresponding areas and personnel are graded from strong to weak. According to the common and individual abnormalities of the physical signs of the construction personnel, group warnings are issued and dispersed to individual warnings. In this way, targeted and graded safety detection and warnings can be carried out according to the hazard area and the degree of hazard;

[0067] Finally, the escape route guidance module selects a safe and short route for escape based on the structural layout of the safety passage and the warned dangerous areas, and sends the vital sign sub-module and evacuation indication system of the construction personnel who need to escape for dynamic guidance. It can optimize the escape route for rapid evacuation based on the density of construction personnel and their vital signs.

[0068] In summary, the above are only preferred embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. Underground construction early warning and personnel safety evacuation guidance system, including safety risk identification module, safety risk assessment module, safety risk early warning module, escape path guidance module, characterized in that: The safety risk identification module includes a construction quality identification submodule, a construction environment submodule, and a construction personnel physical sign submodule. The construction quality identification submodule includes underground construction building fracture, settlement, tilt, pressure, and vibration parameter indicators. After the abnormal values ​​are eliminated, the change amount and change rate index of each parameter indicator are further calculated. The parameter indicators and the change amount and change rate index of each parameter indicator are changed, and the safety risk assessment module is actively entered under the sampling frequency of the change rate indicator; The construction environment submodule includes temperature and humidity, smoke, PM2.5, oxygen concentration, methane concentration, and noise parameter indicators of the underground construction environment. When any of the weighted fusion of temperature and humidity and smoke, oxygen concentration, and methane concentration is abnormal, the safety risk assessment module is immediately and actively entered; The construction worker's vital signs submodule includes blood oxygen, heart rate, heart rate, blood pressure, and respiratory parameter indicators. When the microprocessor determines that any of them is abnormal, an on-site sound and light alarm will be issued, and the safety risk assessment module will be entered through the GPS positioning and communication integrated module; The security risk assessment module obtains the parameter indicators of the security risk identification module and the historical parameter indicators, normalizes them, builds a time series model, and performs parameter inspection and indicator prediction; Obtain parameter indicators and historical parameter indicators of security risk identification modules in different regions and make parameter indicator predictions; Obtain prediction parameter indicators for different regions, form a regional parameter set, and calculate the safety risk identification model. The risk coefficient of each submodule of the block; The risk coefficient of each submodule is weighted and integrated to obtain the total construction risk coefficient; The safety risk warning module performs an overall warning according to the total construction risk coefficient; According to the construction quality, the abnormal characteristic areas of the construction environment and the scope of impact, the corresponding areas and personnel are given graded warnings from strong to weak; According to the common and individual abnormalities of construction workers' physical signs, group warning and dispersed warning are carried out; The escape route guidance module selects a safe and short route for escape according to the structural layout of the safety passage and the warned dangerous area, and sends the construction personnel's vital sign sub-module and evacuation indication system to provide dynamic guidance.

2. The underground construction early warning and personnel safety evacuation guidance system according to claim 1 is characterized in that: The escape path guidance module selects a safe and short path for escape according to the structural layout of the safety passage and the dangerous area warned, specifically: Step 1, obtaining a structural layout diagram of an underground construction safety passage; Step 2, obtain the type of warning and call the corresponding warning point; Step 3: The highest level warning point is used as the starting point, and each safe exit is used as the target point. A neural network is used to plan a total of n optimal paths from the starting point to n target points with the affected range as the obstacle avoidance point to perform safe path planning; Step 4: Based on step 3, calculate the time consumed for each path and select the path with the shortest time as the escape path for the construction workers. Specifically: First, the speed-density empirical formula is used to calculate the movement speed of the construction workers. , in, For the The movement speed of the construction workers is m / s, is the crowd density of construction workers on each path, in units of people / m 2 ; Secondly, through the path distance d, , calculate the movement time TC; Next, the Togawa empirical formula is used to calculate the passage time TE of the emergency exit. Among them, NG is the total number of people evacuated from the safety exit, W is the width of the safety exit (m), and h is the personnel flow coefficient; Finally, the total time consumed by each path is calculated, T = TC + TE, and the path with the smallest T is selected as the current optimal path and provided to the construction personnel.

3. The underground construction early warning and personnel safety evacuation guidance system according to claim 2 is characterized in that: The specific steps of issuing the physical sign submodule of construction personnel who need to escape and the evacuation indication system for dynamic guidance are as follows: Step 1: The escape route guidance module sends the optimal route to the construction worker vital sign submodule through sharing; Step 2: The escape path guidance module sends the optimal path to the evacuation indication system through sharing; Step 3: Construction workers are dynamically guided to evacuate according to the optimal path and signposts; Step 4: Identify the walking behavior and GPS location information of the construction workers; Step 5, using the TLC evaluation algorithm to determine whether the path is deviated; Step 6: When deviation occurs, timely broadcast reminder; Step 7: When construction workers walk on a non-optimal path, their identity information and GPS location information are transmitted to the safety risk assessment module for real-time tracking.

4. The underground construction early warning and personnel safety evacuation guidance system according to claim 1 is characterized in that: The construction worker vital sign submodule recognizes the walking behavior of the construction workers by using human infrared sensors and gyroscope sensors.

5. The underground construction early warning and personnel safety evacuation guidance system according to claim 1 is characterized in that: The safety risk assessment module obtains prediction parameter indicators of different areas, forms a regional parameter set, and calculates the risk coefficient of each submodule of the safety risk identification module, specifically: the risk coefficient of the construction quality identification submodule sz=d+q+c+v+f, where d is the fracture coefficient, q is the tilt coefficient, c is the settlement coefficient, v is the pressure coefficient, and f is the vibration coefficient. Each coefficient is obtained by comparing each detection parameter + the change rate of each detection parameter with the safety value of each detection parameter; The hazard coefficient of the construction environment submodule is sh=sh1+sh2, where sh1 is the fire hazard coefficient and sh2 is the air quality coefficient. The fire hazard coefficient sh1 is obtained by weighted fusion of temperature, humidity and smoke, and then weighted average fusion of oxygen concentration and methane concentration, and then compared with the fire hazard value; The air quality coefficient sh2 is obtained by comparing the PM2.5 and noise detection parameters with the safety values ​​of each detection parameter; The risk coefficient SR of the construction personnel's vital signs submodule first cleans the blood oxygen, heart rate, heart rate, blood pressure, and respiratory parameter data; secondly, normalizes them and converts them into a unified dimension; finally, the Kalman filter is used to recursively estimate and fuse the parameter values ​​to obtain an estimated value, and the estimated value is compared with the normal value to obtain the risk coefficient SR.

Images