CN116602637B - Life safety monitoring, early warning and positioning system based on coal mining personnel - Google Patents

Life safety monitoring, early warning and positioning system based on coal mining personnel Download PDF

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CN116602637B
CN116602637B CN202310889159.2A CN202310889159A CN116602637B CN 116602637 B CN116602637 B CN 116602637B CN 202310889159 A CN202310889159 A CN 202310889159A CN 116602637 B CN116602637 B CN 116602637B
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uwb
data
value
positioning
health state
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CN116602637A (en
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宋庆爽
刘朋朋
王传晨
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Xiaoyun Coal Mine Of Jining Mining Industry Group Co ltd
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Xiaoyun Coal Mine Of Jining Mining Industry Group Co ltd
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
    • A61B5/02055—Simultaneously evaluating both cardiovascular condition and temperature
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
    • A61B5/0015—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by features of the telemetry system
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7203—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/74—Details of notification to user or communication with user or patient ; user input means
    • A61B5/746—Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH DRILLING; MINING
    • E21F—SAFETY DEVICES, TRANSPORT, FILLING-UP, RESCUE, VENTILATION, OR DRAINING IN OR OF MINES OR TUNNELS
    • E21F17/00—Methods or devices for use in mines or tunnels, not covered elsewhere
    • E21F17/18—Special adaptations of signalling or alarm devices
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
    • G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/20—Instruments for performing navigational calculations
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/50—Network services
    • H04L67/52—Network services specially adapted for the location of the user terminal
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H04W4/021—Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/33—Services specially adapted for particular environments, situations or purposes for indoor environments, e.g. buildings
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Abstract

The application discloses a life safety monitoring, early warning and positioning system based on coal mining personnel, and relates to the field of intelligent monitoring of the Internet of things. The system can monitor key indexes of physiological parameters of miners in real time, including heart rate, body temperature, blood oxygen saturation and the like, comprehensively know the safety condition of the miners, and adopts advanced data processing algorithms, including filtering denoising, calibration and data fusion operation. The system can give an alarm in time when an abnormal situation occurs to miners, so as to prompt emergency response and take proper measures. When an alarm is sent, the system can accurately position the specific position of a miner, and can rapidly rescue when an accident occurs, so that rescue efficiency is improved. The life safety monitoring, early warning and positioning system based on coal mining personnel has wide application prospect in the coal mine industry, can effectively improve the safety and emergency response capability of miners, and reduces the risk of accidents.

Description

Life safety monitoring, early warning and positioning system based on coal mining personnel
Technical Field
The application relates to the field of intelligent monitoring of the Internet of things, in particular to a life safety monitoring, early warning and positioning system based on coal mining personnel.
Background
With the continuous development of coal mining activities, the problem of life safety of miners is a focus of attention; in order to ensure the life safety of miners, the traditional coal mine safety monitoring method is no longer satisfactory.
At present, some coal mine safety monitoring systems are applied to actual production, and in the prior art, the application patent of patent number 2019106994691 discloses a coal mine safety monitoring system based on the Internet of things, environmental information is collected through a plurality of underground fixed monitoring terminals and a plurality of underground mobile monitoring terminals, and the environmental information is sent to a ground monitoring server through wireless communication of the Internet of things, so that underground danger is comprehensively detected, underground personnel are timely notified, and therefore the danger type and the danger source are known in advance, so that safety measures can be taken in advance.
The prior art has the following defects:
the existing system only focuses on monitoring of coal mine environments and lacks physiological parameter monitoring and positioning functions for miners; in addition, the early warning mechanism of the existing system is simpler and lacks of fine analysis and judgment capability; therefore, a life safety monitoring, early warning and positioning system based on coal mining personnel is needed to solve the limitations of the traditional method.
Disclosure of Invention
The application aims to provide a life safety monitoring, early warning and positioning system based on coal mining personnel, which aims to solve the defects in the background technology.
In order to achieve the above object, the present application provides the following technical solutions: a life safety monitoring, early warning and positioning system based on coal mining personnel comprises a data acquisition module, a positioning module, a data processing module, an early warning processing module, a communication module and a control center;
and a data acquisition module: when a miner works under a mine, the sensor equipment is worn, and the human body parameter data of the miner are acquired through various sensors; the module is mainly used for collecting various life and health indexes of a human body through various sensors; the sensor includes: a temperature sensor detector, a respiratory rate sensor, a heart rate sensor, a blood pressure sensor, a blood oxygen saturation sensor, and a water immersion sensor detector;
and a positioning module: the premise of normal operation of the positioning module is that a plurality of signal base stations are required to be deployed under a mine, and position information of miners is acquired through UWB positioning technology and an inertial navigation system;
and a data processing module: the system is used for receiving and processing the data acquired by the data acquisition module, and in the aspect of human health monitoring of miners, the system adopts an advanced algorithm to analyze and evaluate physiological parameters of the miners, including filtering, denoising and calibration operations; comprehensively analyzing the health state of the person through data fusion, and calculating and evaluating the health state; the positioning module is used for receiving the position information of the positioning module and fusing two positioning data;
the early warning processing module: the system is used for analyzing the life safety monitoring data of miners in real time, and identifying and extracting key features; performing anomaly detection and state judgment on the extracted features by using preset rules and algorithms to identify potential safety risks; when an abnormality or safety risk is detected, triggering corresponding early warning measures to draw attention of miners; meanwhile, the early warning information is sent to a control center or related staff, so that emergency rescue measures can be taken in time;
and a communication module: the system is used for transmitting the human health state data, the alarm information and the positioning information to a control center and related personnel;
and the control center: for receiving alarm and positioning information and then performing correlation processing and decision making;
the system adopts an advanced data processing algorithm; therefore, the physiological state of a mineworker can be monitored in time, the detection result accuracy is high, and early warning information is generated, so that the safety and the production efficiency of a coal mine are improved.
The data processing module construction comprises the following steps:
a) For each human parameter index, denoising the acquired numerical value by using a filtering algorithm, and calculating the filtered numerical value by using the following formula:
wherein y (N) is a filtered value at the nth time point, x [ N-k ] is an original value at the nth-k time point, k is increased from 0 to N-1 at maximum, and N is the number of the original values involved in the filtering algorithm; therefore, in the process of finding the y (N) value, x [ N ], x [ N-1], x [ N-2]. X [ N-n+1] are involved for N raw data values;
b) In order to map the acquired values into the actual value range for linear calibration; the filtered value y (n) requires a linear calibration to obtain the true data value t (n), using the following formula:
where t (n) is the true value of the nth time point, a is the scaling factor of the linear calibration, and b is the offset of the linear calibration; for linear calibration, some known data values and corresponding acquisition values need to be obtained in advance, and the optimal a and b are determined through linear regression or other fitting methods;
further, after the data processing module completes filtering denoising and calibration processing of each parameter index of the human body, the relation between the parameter index data and the health state of the human body is required to be established through SVR by the real data value t (n) from different sensors, and the calculation and evaluation of the health state are carried out, wherein the calculation formula of the SVR is as follows:
wherein S represents a health state, t i Is the true data value of the ith sensor, w i Is toThe weight of the sensor is calculated by SVR, and the real measured values of n sensors are included in the process of calculating the health state S; b is a bias term; the weight vector of the SVR model that has been trained is w= [0.3, 0.3, 0.4, 0.2, 0.2, 0.3]The bias term is b=1.2; threshold S of human health state 0 80, so if S ≡ S 0 Indicating that the health state of the human body is better; if S<S 0 Indicating poor health status of the human body.
Further, the positioning module constructs data comprising UWB technology measurement data and inertial navigation system measurement data; the data processing module measures the time difference TOA of the target position reaching the UWB base station through the UWB positioning technology, calculates the distance of the target, and the following distance calculation formula is shown:
D = (TOA * C) / 2
wherein D represents the distance between the target and the UWB base station; TOA represents the arrival time difference of the UWB signal received by the target; c represents the propagation speed of light in vacuum;
the accurate position of the target is calculated by using triangulation, and the formula is as follows:
(U X , U Y , U Z ) = Tri-angulation(D 1 , D 2 , D 3 , (X 1 , Y 1 , Z 1 ), (X 2 , Y 2 , Z 2 ), (X 3 , Y 3 , Z 3 ))
wherein D is 1 , D 2 , D 3 Representing the distance between the target and three UWB base stations; (X) 1 , Y 1 , Z 1 ), (X 2 , Y 2 , Z 2 ), (X 3 , Y 3 , Z 3 ) Representing the position coordinates of three UWB base stations; (U) X , U Y , U Z ) Representing the specific positioning position of the target calculated by UWB positioning technology; tri-analysis represents a function of triangulation calculation, which is calculated as follows:
assume that three UWB base stations are located at the coordinates (X 1 , Y 1 , Z 1 )，(X 2 , Y 2 , Z 2 )，(X 3 , Y 3 , Z 3 ) The target receives UWB signals transmitted by the three base stations, and the distances between the target and the three base stations are respectively D can be calculated through a formula of D= (TOA x C)/2 1 ，D 2 ，D 3 The method comprises the steps of carrying out a first treatment on the surface of the First, three equations are derived from the relationship between distance and coordinates:
(D 1 ) 2 = (U X - X 1 ) 2 + (U Y - Y 1 ) 2 + (U Z - Z 1 ) 2
(D 2 ) 2 = (U X - X 2 ) 2 + (U Y - Y 2 ) 2 + (U Z - Z 2 ) 2
(D 3 ) 2 = (U X - X 3 ) 2 + (U Y - Y 3 ) 2 + (U Z - Z 3 ) 2
by solving, the accurate position (U) of the target can be obtained X , U Y , U Z )。
Still further, the position integral calculation formula of the data processing module about the inertial navigation system is as follows:
wherein P (t) represents a position vector at the current time; p (t) 0 ) A position vector representing the last time; vt represents the velocity vector at the last moment; />Is represented at time interval t 0 , t]Integrating the velocity vector; for each direction X, Y, Z of the coordinate axis, the above formula needs to be expressed separately, so that the specific positioning position of the target can be determined as (P X ，P Y ，P Z ）。
Furthermore, the data processing module performs time alignment on the position data measured by the UWB technology and the position data measured by the inertial navigation system to ensure that the time stamps of the position data measured by the UWB technology and the position data measured by the inertial navigation system are consistent, and then performs fusion processing on the position data measured by the UWB technology and the position data measured by the inertial navigation system:
based on measurement accuracy and systematic error, UWB weights are calculated:
w_uwb = 1 / (1 + σ_uwb 2 )
based on the measurement accuracy and the system error, calculating inertial navigation weights:
w_inertial = exp(-σ_inertial 2 )
normalized UWB weights:
w_uwb_s = w_uwb / (w_uwb + w_inertial)
normalized inertial navigation weights:
w_inertial_s = w_inertial / (w_uwb + w_inertial)
fused position values:
P_fused = w_uwb_s * (U X , U Y , U Z ) + w_inertial_s * (P X , P Y , P Z )
where σ_uwb represents one standard deviation of the position accuracy of the position data measured by the UWB technology, and σ_inertial represents the standard deviation of the position accuracy of the position data measured by the inertial navigation system.
Further, the early warning processing module compares the human health state value S with a human health state threshold S 0 Comparing; if S ≡S 0 The human health state is better, the human health state data and the positioning information are reported to the control center, the alarm is not triggered, and the system keeps monitoring state; if S<S 0 The method indicates that the human health state is poor, the human health state data and the positioning information are reported to the control center, and an alarm is triggered at the same time; when the miner wears the sensing equipment insecurely or the equipment fails, the miner can actively trigger an alarm to inform a control center and related personnel to respond timely.
Furthermore, the communication module supports a wireless local area network communication mode, and realizes real-time data transmission, command issuing and information interaction.
Furthermore, the control center is composed of server equipment, a computer and mobile terminal equipment and is responsible for receiving data and information transmitted by the data acquisition module, the early warning processing module and the positioning module, and related personnel can make safety decisions and guides according to the alarm information and the positioning information.
In the technical scheme, the application has the following beneficial effects:
1. according to the application, through comprehensively collecting, processing and analyzing the data of the human health of the miners, the real-time monitoring and early warning of the safety state of the miners are realized, the safety and emergency response capability of the miners can be effectively improved, and the risk of accidents is reduced; advantages of the system include: and (3) overall monitoring: the system can monitor key indexes of physiological parameters of miners in real time, including heart rate, body temperature, blood oxygen saturation and the like, so as to comprehensively know the safety condition of the human body of the miners; early warning in time: the system can give an alarm in time when an abnormal situation occurs to a miner so as to prompt emergency response and take proper measures, thereby minimizing the possibility of accidents.
2. The positioning module can accurately position the specific position of the miner, and the positioning module is beneficial to rapidly positioning the position of the miner by using two positioning technologies, so that the miner can be rapidly rescued when an accident occurs, and the rescue efficiency is improved.
3. The application adopts a data processing module which adopts advanced data processing algorithm including operations such as filtering, denoising, calibration and the like; establishing the relation between human body characteristic data and health states through SVR by using real data values from different sensors, and calculating and evaluating the health states; through data analysis and evaluation, miners' health indexes can be generated, and scientific basis is provided for decision making.
4. The application has the characteristic of customization, can be configured and adjusted according to the requirements and special requirements of different coal mines, and the monitoring indexes, the early warning threshold values, the positioning requirements and the like of different coal mines can be customized according to actual conditions so as to meet the safety management requirements of specific coal mines.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments described in the present application, and other drawings may be obtained according to these drawings for a person having ordinary skill in the art.
FIG. 1 is a schematic diagram of a life safety monitoring, early warning and positioning system based on coal mining personnel according to an embodiment of the present application;
FIG. 2 is a workflow diagram of a life safety monitoring, early warning and positioning system based on coal mining personnel according to an embodiment of the present application;
fig. 3 is a UWB positioning schematic diagram of a life safety monitoring, early warning and positioning system based on coal mining personnel according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Example 1:
the embodiment provides a life safety monitoring, early warning and positioning system based on coal mining personnel, as shown in fig. 1, which mainly comprises:
the data acquisition module is used for wearing sensor equipment when a miner works under a mine, and acquiring human body parameter data of the miner through various sensors;
the data processing module is used for receiving and processing the data acquired by the data acquisition module, including filtering, denoising and calibration operations, and calculating and evaluating the health state through SVR;
the early warning processing module analyzes and judges according to the data calculated and evaluated by the data processing module, and gives an alarm when the health state value exceeds or is lower than a set safety threshold value;
the positioning module is used for calculating the actual position of a mineworker through a UWB positioning technology on the premise that a plurality of signal base stations are required to be deployed under a mine and then fusing the position information calculated by an inertial navigation system;
the communication module is used for transmitting the human health state data, the alarm information and the positioning information to the control center and related personnel;
the control center is used for receiving the alarm and positioning information and then carrying out relevant processing and decision making;
the system can monitor the physiological state of miners in time by adopting an advanced data processing algorithm, has higher accuracy of detection results, and further generates early warning information so as to improve the safety and production efficiency of coal mines.
Example 2:
for easy understanding, the following describes the workflow of the system in detail, referring to fig. 2, each miner wears special life safety monitoring equipment on a coal mining site, and the equipment comprises a data acquisition module, a positioning module, a data processing module, an early warning processing module and a communication module of the system;
1. data acquisition module
As a preferred scheme, the module functionally comprises body temperature detection, respiratory rate detection, heart rate detection, blood pressure detection, blood oxygen saturation detection and human epidermis sweat detection, whether sweat exists in a human body is detected by using a water immersion sensor detector, the human skin is detected by using an electrode based on a liquid conduction principle, and whether sweat exists in the human epidermis can be judged by the conductivity difference due to the difference of the conductivities of the skin and the sweat.
The data acquisition module comprises a plurality of types of sensors, the sensors are in contact with the body of a mineworker in a non-invasive mode, and each sensor is subjected to strict calibration and testing; the human body related information is an input of the data processing module.
2. Positioning module
The positioning module constructs the data including UWB technology measurement data and inertial navigation system measurement data, and the positioning information is the input of the data processing module.
3. Data processing module
As a preferred scheme, the module uses a filtering algorithm to denoise the acquired values for each index of the human parameter, and uses the following formula to calculate the filtered values:
wherein y (N) is a filtered value at the nth time point, x [ N-k ] is an original value at the nth-k time point, k is increased from 0 to N-1 at maximum, and N is the number of the original values involved in the filtering algorithm; therefore, in the process of finding the y (N) value, x [ N ], x [ N-1], x [ N-2]. X [ N-n+1] are involved for N raw data values;
the filtered value y (n) requires a linear calibration to obtain the true data value t (n), using the following formula:
where t (n) is the true value of the nth time point, a is the scaling factor of the linear calibration, and b is the offset of the linear calibration; for linear calibration, some known data values and corresponding acquisition values need to be obtained in advance, and the optimal a and b are determined through linear regression or other fitting methods;
after the data processing module completes filtering denoising and calibration processing of various parameter indexes of a human body, the relation between the parameter index data and the health state of the human body is established through SVR by the real data value t (n) from different sensors, and the calculation and evaluation of the health state are carried out, wherein the calculation formula of the SVR is as follows:
wherein S represents a health state, t i Is the true data value of the ith sensor, w i Is the weight of the corresponding sensor, and contains the real measured values of n sensors in the process of calculating the health state S by the SVR; b is a bias term; the weight vector of the SVR model that has been trained is w= [0.3, 0.3, 0.4, 0.2, 0.2, 0.3]The bias term is b=1.2; threshold S of human health state 0 80, so if S ≡ S 0 Indicating that the health state of the human body is better; if S<S 0 Indicating poor health status of the human body.
For the above scheme, the following is exemplified:
we have trained SVR models with weight vectors w= [0.3, 0.3, 0.4, 0.2, 0.2, 0.3]The bias term is b=1.2, there is now a new sample, the body temperature is t 1 =36.8, heart rate t 2 =80, respiratory rate t 3 =40, blood pressure t 4 =90, blood sample saturation t 5 =70, human epidermis humidity t 6 =30, next the sample is evaluated for health status using SVR model, with specific numbers taken for calculation:
first, the input feature t= [ t ] 1 , t 2 , t 3 , t 4 , t 5 , t 6 ] = [36.8, 80, 40, 90, 70, 30]And carrying out prediction of health state by taking an SVR formula:
= [0.3, 0.3, 0.4, 0.2, 0.2, 0.3]·[36.8, 80, 40, 90, 70, 30]+ 1.2
(0.3 * 36.8) + (0.3 * 80) + (0.4 * 40) + (0.2 * 90) + (0.2 * 70) + (0.3 * 30) + 1.2/>93.24
therefore, according to the prediction of the SVR model, the predicted value of the health state of the sample is 93.24, the threshold S of the health state of the human body 0 80, at this time S>80, the human body is in a healthy state, and no alarm is triggered.
As a preferred solution, referring to fig. 3, the UWB positioning technology calculates the target distance by measuring the time difference TOA of arrival at the UWB base station, and the following distance calculation formula is shown:
D = (TOA * C) / 2
wherein D represents the distance between the target and the UWB base station; TOA represents the arrival time difference of the UWB signal received by the target; c represents the propagation speed of light in vacuum;
using triangulation to calculate the exact location of a target is formulated as follows
(U X , U Y , U Z ) = Tri-angulation(D 1 , D 2 , D 3 , (X 1 , Y 1 , Z 1 ), (X 2 , Y 2 , Z 2 ), (X 3 , Y 3 , Z 3 ))
Wherein D is 1 , D 2 , D 3 Representing the distance between the target and three UWB base stations; (X) 1 , Y 1 , Z 1 ), (X 2 , Y 2 , Z 2 ), (X 3 , Y 3 , Z 3 ) Respectively representing the position coordinates of three UWB base stations; (U) X , U Y , U Z ) Representing the specific positioning position of the target calculated by UWB positioning technology; tri-analysis represents a function of triangulation calculation, which is calculated by the following way:
for the above UWB positioning scheme, the following is illustrated:
assume that three UWB base stations are located at the coordinates (X 1 , Y 1 , Z 1 )，(X 2 , Y 2 , Z 2 )，(X 3 , Y 3 , Z 3 ) The distance between the target and the three base stations can be calculated by the formula of D= (TOA x C)/2 when the target receives UWB signals transmitted by the three base stations, and the distance is D respectively 1 ，D 2 ，D 3 The method comprises the steps of carrying out a first treatment on the surface of the First, three equations are derived from the relationship between distance and coordinates:
(D 1 ) 2 = (U X - X 1 ) 2 + (U Y - Y 1 ) 2 + (U Z - Z 1 ) 2
(D 2 ) 2 = (U X - X 2 ) 2 + (U Y - Y 2 ) 2 + (U Z - Z 2 ) 2
(D 3 ) 2 = (U X - X 3 ) 2 + (U Y - Y 3 ) 2 + (U Z - Z 3 ) 2
by solving, the accurate position (U) of the target can be obtained X , U Y , U Z )。
As a preferable scheme, the inertial navigation system has a position integral calculation formula as follows:
wherein P (t) represents a position vector at the current time; p (t) 0 ) A position vector representing the last time; vt represents the velocity vector at the last moment; />Is represented at time interval t 0 , t]Integrating the velocity vector; for each direction X, Y, Z of the coordinate axis, the above formula needs to be expressed separately, so that the specific positioning position of the target can be determined as (P X ，P Y ，P Z ）。
As a preferable scheme, the data processing module performs time alignment on the position data measured by the UWB technology and the position data measured by the inertial navigation system, ensures that the time stamps of the position data measured by the UWB technology and the position data measured by the inertial navigation system are consistent, and then performs fusion processing on the position data measured by the UWB technology and the position data measured by the inertial navigation system:
based on measurement accuracy and systematic error, UWB weights are calculated:
w_uwb = 1 / (1 + σ_uwb 2 )
based on the measurement accuracy and the system error, calculating inertial navigation weights:
w_inertial = exp(-σ_inertial 2 )
normalized UWB weights:
w_uwb_s = w_uwb / (w_uwb + w_inertial)
normalized inertial navigation weights:
w_inertial_s = w_inertial / (w_uwb + w_inertial)
fused position values:
P_fused = w_uwb_s * (U X , U Y , U Z ) + w_inertial_s * (P X , P Y , P Z )
where σ_uwb represents one standard deviation of the position accuracy of the position data measured by the UWB technology, and σ_inertial represents the standard deviation of the position accuracy of the position data measured by the inertial navigation system.
4. Early warning processing module
The early warning processing module processes the human health state value S and the human health state threshold S 0 Comparing; if S ≡S 0 The human health state is better, the human health state data and the positioning information are reported to the control center, the alarm is not triggered, and the system keeps monitoring state; if S<S 0 The method indicates that the human health state is poor, the human health state data and the positioning information are reported to the control center, and an alarm is triggered at the same time;
when the miner wears the sensing equipment insecurely or the equipment fails, the miner can actively trigger an alarm to inform a control center and related personnel to respond timely;
in the example of not triggering an alarm, the system only sends the human health state data and the positioning information to the control center; in the example of triggering an alarm, the system not only transmits the human health status data and the positioning information to the control center, but also transmits the alarm information so that related personnel respond in time.
5. Communication module
The module is mainly used for sending miner data wearing special life safety monitoring equipment to the control center, the control center can send commands and interact information to miners, and the communication module uses a wireless local area network communication mode to realize real-time data transmission; according to the alarm information and the positioning information, related personnel can make security decisions and guidance.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional modules is illustrated, and in practical application, the above-described functional allocation may be performed by different functional modules according to needs, i.e. the internal structure of the system is divided into different functional modules to perform all or part of the functions described above.
The foregoing is only a preferred embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions easily contemplated by those skilled in the art within the scope of the present application should be included in the scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims (5)

1. A life safety monitoring, early warning and positioning system based on coal mining personnel is characterized in that: the data acquisition module comprises a temperature sensor, a respiratory rate detection sensor, a heart rate detection sensor, a blood pressure measurement sensor, a blood oxygen saturation detection sensor and a human epidermis humidity sensor, and is used for respectively acquiring a body temperature value, a respiratory rate value, a heart rate value, a blood pressure value, a blood oxygen saturation value and a human epidermis humidity value of a mineworker;
the data processing module construction comprises the following steps:
a) For each human parameter index, denoising the acquired numerical value by using a filtering algorithm, and calculating the filtered numerical value by using the following formula:
wherein y (N) is a filtered value at the nth time point, x [ N-k ] is an original value at the nth-k time point, k is increased from 0 to N-1 at maximum, and N is the number of the original values involved in the filtering algorithm; therefore, in the process of finding the y (N) value, x [ N ], x [ N-1], x [ N-2]. X [ N-n+1] are involved for N raw data values;
b) In order to map the acquired values into the actual value range for linear calibration; the filtered value y (n) requires a linear calibration to obtain the true data value t (n), using the following formula:
where t (n) is the true value of the nth time point, a is the scaling factor of the linear calibration, and b is the offset of the linear calibration; for linear calibration, some known data values and corresponding acquisition values need to be obtained in advance, and the optimal a and b are determined through linear regression or other fitting methods;
after the data processing module completes filtering denoising and calibration processing of various parameter indexes of a human body, the relation between the parameter index data and the health state of the human body is established through SVR by the real data value t (n) from different sensors, and the calculation and evaluation of the health state are carried out, wherein the calculation formula of the SVR is as follows:
wherein S represents a health state, t i Is the true data value of the ith sensor, w i Is the weight of the corresponding sensor, and contains the real measured values of n sensors in the process of calculating the health state S by the SVR; b is a bias term; the weight vector of the SVR model that has been trained is w= [0.3, 0.3, 0.4, 0.2, 0.2, 0.3]The bias term is b=1.2; threshold S of human health state 0 80, so if S ≡ S 0 Indicating that the health state of the human body is better; if S< S 0 Indicating that the health state of the human body is poor;
the data processing module analyzes the UWB positioning technology, calculates the target distance by measuring the time difference TOA reaching the UWB base station, and the following distance calculation formula is shown:
D = (TOA * C) / 2
wherein D represents the distance between the target and the UWB base station; TOA represents the arrival time difference of the UWB signal received by the target; c represents the propagation speed of light in vacuum; calculating an accurate position of the target by using the triangulation; the triangle positioning formula is as follows:
(U X , U Y , U Z ) = Tri-angulation(D 1 , D 2 , D 3 , (X 1 , Y 1 , Z 1 ), (X 2 , Y 2 , Z 2 ), (X 3 , Y 3 , Z 3 ) In D) 1 , D 2 , D 3 Representing the distance between the target and three UWB base stations; (X) 1 , Y 1 , Z 1 ), (X 2 , Y 2 , Z 2 ), (X 3 , Y 3 , Z 3 ) Respectively representing the position coordinates of three UWB base stations; (U) X , U Y , U Z ) Representing the specific positioning position of the target calculated by UWB positioning technology; tri-analysis represents a function of triangulation calculation, which is calculated as follows:
assume that three UWB base stations are located at the coordinates (X 1 , Y 1 , Z 1 )，(X 2 , Y 2 , Z 2 )，(X 3 , Y 3 , Z 3 ) The distance between the target and the three base stations can be calculated by the formula of D= (TOA x C)/2 when the target receives UWB signals transmitted by the three base stations, and the distance is D respectively 1 ，D 2 ，D 3 The method comprises the steps of carrying out a first treatment on the surface of the First, three equations are derived from the relationship between distance and coordinates:
(D 1 ) 2 = (U X - X 1 ) 2 + (U Y - Y 1 ) 2 + (U Z - Z 1 ) 2
(D 2 ) 2 = (U X - X 2 ) 2 + (U Y - Y 2 ) 2 + (U Z - Z 2 ) 2
(D 3 ) 2 = (U X - X 3 ) 2 + (U Y - Y 3 ) 2 + (U Z - Z 3 ) 2
by solving, the accurate position (U) of the target can be obtained X , U Y , U Z )；
The position integral calculation formula of the data processing module about the inertial navigation system is as follows:
wherein P (t) represents a position vector at the current time; p (t) 0 ) A position vector representing the last time; vt represents the velocity vector at the last moment;is represented at time interval t 0 , t]Integrating the velocity vector; for each direction X, Y, Z of the coordinate axis, the above formula needs to be expressed separately, so that the specific positioning position of the target can be determined as (P X ，P Y ，P Z ）。
2. The life safety monitoring, early warning and positioning system based on coal mining personnel according to claim 1, wherein: the data processing module is used for carrying out time alignment on the position data measured by the UWB technology and the position data measured by the inertial navigation system, ensuring that the time stamps of the position data measured by the UWB technology and the position data measured by the inertial navigation system are consistent, and then carrying out fusion processing on the position data measured by the UWB technology and the position data measured by the inertial navigation system:
based on measurement accuracy and systematic error, UWB weights are calculated:
w_uwb = 1 / (1 + σ_uwb 2 )
based on the measurement accuracy and the system error, calculating inertial navigation weights:
w_inertial = exp(-σ_inertial 2 )
normalized UWB weights:
w_uwb_s = w_uwb / (w_uwb + w_inertial)
normalized inertial navigation weights:
w_inertial_s = w_inertial / (w_uwb + w_inertial)
fused position values:
P_fused = w_uwb_s * (U X , U Y , U Z ) + w_inertial_s * (P X , P Y , P Z )
where σ_uwb represents one standard deviation of the position accuracy of the position data measured by the UWB technology, and σ_inertial represents the standard deviation of the position accuracy of the position data measured by the inertial navigation system.
3. The life safety monitoring, early warning and positioning system based on coal mining personnel according to claim 1, wherein: the early warning processing module processes the human health state value S and the human health state threshold S 0 Comparing; if S ≡S 0 The human health state is better, the human health state data and the positioning information are reported to the control center, the alarm is not triggered, and the system keeps monitoring state; if S< S 0 The method indicates that the human health state is poor, the human health state data and the positioning information are reported to the control center, and an alarm is triggered at the same time; when the miner wears the sensing equipment insecurely or the equipment fails, the miner can actively trigger an alarm to inform a control center and related personnel to respond timely.
4. A life safety monitoring, early warning and positioning system based on coal mining personnel according to claim 3, wherein: the communication module supports a wireless local area network communication mode, and realizes real-time data transmission, command issuing and information interaction.
5. A life safety monitoring, early warning and positioning system based on coal mining personnel according to claim 3, wherein: the control center is composed of server equipment, a computer and mobile terminal equipment, and is responsible for receiving data and information transmitted by the data acquisition module, the early warning processing module and the positioning module, and related personnel can make safety decisions and guidance according to the alarm information and the positioning information.
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