CN106617456B - Safety helmet safety monitoring method - Google Patents
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- CN106617456B CN106617456B CN201710000608.8A CN201710000608A CN106617456B CN 106617456 B CN106617456 B CN 106617456B CN 201710000608 A CN201710000608 A CN 201710000608A CN 106617456 B CN106617456 B CN 106617456B
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- 238000000034 method Methods 0.000 title claims abstract description 20
- 238000012544 monitoring process Methods 0.000 title claims abstract description 9
- 238000007499 fusion processing Methods 0.000 claims abstract description 34
- 238000004364 calculation method Methods 0.000 claims abstract description 27
- 238000006073 displacement reaction Methods 0.000 claims abstract description 23
- 238000004458 analytical method Methods 0.000 claims abstract description 13
- 230000004927 fusion Effects 0.000 claims abstract description 12
- 230000009471 action Effects 0.000 claims abstract description 8
- 230000001133 acceleration Effects 0.000 claims abstract description 6
- 230000008447 perception Effects 0.000 claims abstract description 4
- 238000005259 measurement Methods 0.000 claims description 10
- 238000013500 data storage Methods 0.000 claims description 3
- 238000012360 testing method Methods 0.000 claims description 3
- 230000001960 triggered effect Effects 0.000 claims description 3
- 238000012545 processing Methods 0.000 abstract description 5
- 238000005516 engineering process Methods 0.000 abstract description 2
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- 230000006870 function Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 210000005069 ears Anatomy 0.000 description 1
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Classifications
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- A—HUMAN NECESSITIES
- A42—HEADWEAR
- A42B—HATS; HEAD COVERINGS
- A42B3/00—Helmets; Helmet covers ; Other protective head coverings
- A42B3/04—Parts, details or accessories of helmets
- A42B3/0406—Accessories for helmets
- A42B3/0433—Detecting, signalling or lighting devices
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
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- General Physics & Mathematics (AREA)
- Helmets And Other Head Coverings (AREA)
Abstract
The invention discloses a safety helmet safety monitoring method, which comprises an embedded information fusion processing unit, wherein the embedded information fusion processing unit is respectively connected with a radio frequency authentication unit, a biological sensing unit, an elastic displacement unit, a three-dimensional posture unit, a mobile interconnection unit and an active alarm unit, and comprises a data interface module, an information analysis module, an information calculation module, a voice module and a storage module. The invention adopts a multi-sensor fusion technology to obtain information such as biological perception, pressure, displacement, three-dimensional acceleration and the like, and the embedded information fusion processing unit is used for receiving, analyzing, calculating and processing the information to rapidly judge whether the action of wearing the safety helmet by staff is correct. The safety helmet has the advantages that the safety helmet is standardized in use, the safety accidents caused by improper wearing are reduced, and the safety helmet has a wide market prospect in the safety field.
Description
Technical Field
The invention relates to the field of multi-sensor fusion monitoring, in particular to a safety helmet safety monitoring method.
Background
In places with potential safety hazards, for safety protection, the present personnel are required to wear safety helmets. The existing safety helmet researches are mainly divided into two categories: firstly, the protection characteristic of the safety helmet is perfected through material and appearance design; another type provides supervision and control of production sites and communication in dangerous situations by assistance of electronic products such as cameras and bluetooth. These two classes of research essentially provide safety protection for the helmet, but ignore the casualties caused by improper use of the helmet. Through statistics of a large number of accidents, 88% of the direct reasons for the occurrence of the accidents are due to unsafe behavior of people.
Disclosure of Invention
The invention aims to provide a safety monitoring method for a safety helmet, which is used for detecting and monitoring whether the safety helmet is worn correctly.
The invention adopts the following technical scheme to realize the aim of the invention:
the safety helmet safety monitoring method comprises an embedded information fusion processing unit, and is characterized in that the embedded information fusion processing unit is respectively connected with a radio frequency authentication unit, a biological sensing unit, an elastic displacement unit, a three-dimensional posture unit, a mobile interconnection unit and an active alarm unit, and comprises a data interface module, an information analysis module, an information calculation module, a voice module and a storage module, and the method comprises the following steps:
(1) The radio frequency authentication unit works independently, actively collects user information after starting, judges whether the user is a legal user, if so, judges the system state, if so, starts the whole device, informs the mobile interconnection unit and enters the working state, otherwise, the device is in the standby state; if the working time is judged to be in the off-duty state, the working time is recorded, the data storage backup is completed and is sent to the mobile interconnection unit, and then the whole device enters a standby state;
(2) The data interface module starts to acquire sensor information of each unit in real time after the device enters a working state;
(3) The information analysis module analyzes the transmitted interface information of various types, converts the interface information into a discrimination variable in a unified format, counts the results of multiple measurements in fixed time aiming at different modules, takes the average value of the results, and transmits the results to the information calculation module;
(4) After receiving the normalized discrimination variables, the information calculation module carries out threshold range judgment firstly, then carries out multidimensional sensing algorithm calculation and judges whether the safety helmet is worn correctly;
(5) Once the safety helmet is judged to be not worn correctly, a voice module in the safety helmet can send out an acousto-optic action to prompt a wearer to correct the wearing action of the safety helmet; meanwhile, the embedded information fusion unit records information, and then sends the information to the mobile interconnection unit after exceeding an alarm threshold value, and the mobile interconnection unit sends the alarm information to the remote control center;
(6) The active alarm unit works independently, and is actively triggered by the wearer in case of emergency or other occasions where the wearer judges that the alarm needs to be reported, the embedded information fusion unit triggers the customized information to be sent up, and the priority is set to be the highest.
As a further limitation of the technical scheme, the biological sensing unit comprises 1 pyroelectric infrared sensor and 2 infrared ranging sensors, wherein the pyroelectric sensor is positioned at the front side inside the crown, and the 2 infrared ranging sensors are positioned at two sides of the visor.
As a further limitation to the technical scheme, the elastic displacement unit comprises 1 film pressure sensor and 3 high-precision resistance strain gauges, wherein the film pressure sensor is positioned at the chin strap of the hat, and the 3 high-precision resistance strain gauges are distributed at the cap hoops.
As a further limitation of the present technical solution, the three-position gesture unit includes a three-axis sensor, and the three-axis sensor is located at the top inside the helmet.
As a further limitation to the technical scheme, the specific steps of the step (2) are as follows: firstly judging whether the information of the biological sensing unit is received or not, and further judging the information content, if the fact that the user wears the safety helmet is detected, starting to sample the infrared ranging information in the biological sensing module, the pressure sensor information in the elastic displacement module and the angular speed and acceleration information of the three-dimensional gesture module at regular time.
As a further limitation to the technical scheme, the embedded information fusion processing unit adopts a control processing chip MSP430, a pin 5 of the embedded information fusion processing unit is connected with the active alarm unit, a pin 13, a pin 14 and a pin 15 of the embedded information fusion processing unit are connected with the biological sensing unit, a pin 13 of the embedded information fusion processing unit is connected with a collector of a triode Q1, the collector of the triode Q1 is also connected with a power supply through a resistor R5, an emitter of the triode Q1 is grounded, a base of the triode Q1 is connected with one of the infrared ranging sensors through a resistor R3, a pin 14 of the embedded information fusion processing unit is connected with a collector of a triode Q2, a collector of the triode Q2 is also connected with a power supply through a resistor R7, an emitter of the triode Q2 is grounded, a base of the triode Q2 is connected with the other infrared ranging sensor through a resistor R6, and a base of the embedded information fusion processing unit is connected with the infrared sensor; the pin 33, the pin 34, the pin 35 and the pin 44 of the embedded information fusion processing unit are respectively connected with the film pressure sensor and 3 high-precision resistance strain gauges, the pin 36, the pin 37 and the pin 38 of the embedded information fusion processing unit are connected with the radio frequency authentication unit, the pin 39, the pin 40, the pin 41, the pin 42 and the pin 43 of the embedded information fusion processing unit are respectively connected with the pin 6, the pin 7, the pin 12, the pin 23 and the pin 24 of the triaxial sensor, and the pin 58, the pin 59 and the pin 60 of the embedded information fusion processing unit are connected with the mobile interconnection unit.
As a further limitation to the present technical solution, the multi-dimensional sensing algorithm in the step (4) includes the following steps: a) Firstly, two infrared distance measuring sensors test the safety helmet for a plurality of times, and by using a formula,and->Wherein x is i D for each measurement value i Deviation of measured value from average value->n is the observation times, the measurement times of each infrared ranging sensor is n/2 times, the average value and the average error are calculated, and the ranging average value +.>And average error delta r The method comprises the steps of carrying out a first treatment on the surface of the Average value +.about.two kinds of pressure sensors in elastic displacement module>And average error delta b1 、δ b2 The calculation formulas of the average value and the average error of the two types of pressure sensors are identical to those of the infrared ranging sensor, and the two types of pressure sensors are used for transmitting according to the two types of pressure sensorsDifferent weighting values of the sensor +.>According to the formula->And->Calculate the mean value of the elastic displacement module +.>And average error delta b The method comprises the steps of carrying out a first treatment on the surface of the Average value of X, Y, Z three-direction angular velocities of three-dimensional attitude module +.>And average error delta ωx 、δ ωy 、δ ωz Simultaneously weighting values which differ according to the three directions X, Y, Z +.> According to the formula: />Andthe average value of the three-dimensional attitude module can be finally obtained>And average error delta ω The method comprises the steps of carrying out a first treatment on the surface of the b) Each module calculates average error through the measured value, judges whether the safety helmet is correctly worn according to whether the average error is in the error range which is determined in advance by each module, if the average error is in the error range, the safety helmet is considered to be correct, the step c) is carried out for the next step of calculation, otherwise, the safety helmet is considered to be not correctly worn, and c) when the safety helmet is not correctly wornWhen the average errors of the modules are all within the respective error range, the calculation is performed according to the weight value of the infrared ranging module>Weight value of elastic displacement module +.>And three-dimensional gesture module weight value +.>Thereby calculating the state average value +.>And average error->And calculating the overall state average value and the overall average error of the safety helmet through overall analysis, judging whether the safety helmet is worn correctly, and if the overall average error exceeds the preset overall average error, judging that the safety helmet is not worn correctly.
Compared with the prior art, the invention has the advantages and positive effects that: the invention adopts a multi-sensor fusion technology to obtain information such as biological perception, pressure, displacement, three-dimensional acceleration and the like, and the embedded information fusion processing unit is used for receiving, analyzing, calculating and processing the information to rapidly judge whether the action of wearing the safety helmet by staff is correct. The invention has the alarm device, realizes the remote automatic and manual alarm functions, and has great effect on emergency. The safety helmet has the advantages that the safety helmet is standardized in use, the safety accidents caused by improper wearing are reduced, and the safety helmet has a wide market prospect in the safety field.
Drawings
FIG. 1 is a schematic top layer structure of a helmet according to a preferred embodiment of the present invention;
FIG. 2 is a schematic view of the visor structure of the helmet according to the preferred embodiment of the present invention;
FIG. 3 is a schematic view of the mandibular strap configuration of the helmet of the preferred embodiment of the present invention;
FIG. 4 is a block diagram showing the connection between the modules of the helmet according to the preferred embodiment of the present invention;
fig. 5 is a flow chart of the method of the present invention.
Fig. 6 is a circuit diagram of a radio frequency authentication unit.
Fig. 7 (1) (2) (3) is a circuit diagram of a biological sensing unit.
Fig. 8 (1) (2) (3) (4) is a circuit diagram of an elastic displacement unit.
Fig. 9 is a three-dimensional attitude unit circuit diagram.
Fig. 10 is a circuit diagram of an active alarm unit.
Fig. 11 is a circuit diagram of a mobile interconnect unit.
Fig. 12 is a circuit diagram of an embedded information fusion processing unit.
Wherein, 101, a radio frequency authentication unit, 102, a biological sensing unit, 103, an elastic displacement unit and 104 three-dimensional gesture units, 105, an active alarm unit, 106, a mobile interconnection unit, 107 and an embedded information fusion processing unit; for the embedded information fusion unit, the interior of the embedded information fusion unit can be divided into: 201. the system comprises a data interface module 202, an information analysis module 203, an information calculation module 204, a storage module 205 and a voice module.
Detailed Description
One embodiment of the present invention will be described in detail below with reference to the attached drawings, but it should be understood that the scope of the present invention is not limited by the embodiment.
As shown in fig. 1 to 12, the present invention includes an embedded information fusion processing unit 107, which is respectively connected to a biological sensing unit 102, an elastic displacement unit 103, a three-dimensional posture unit 104, and an active alarm unit 105.
The embedded information fusion processing unit 107 is also connected to the rf authentication unit 101.
The embedded information fusion processing unit 107 is also connected to the mobile interconnection unit 106.
The embedded information fusion processing unit 107 includes a data interface module, an information analysis module, an information calculation module, a voice module, and a storage module.
The radio frequency authentication unit 101 is composed of an RFID and an accessory circuit, and is used for authenticating the identity of a wearer, acquiring basic information, judging according to system state information and time information, and starting the whole device to enter a working state or a standby state.
The biological sensing unit 102 is composed of 1 pyroelectric infrared sensor, 2 infrared distance measuring sensors and an accessory circuit thereof, wherein the pyroelectric infrared sensor arranged at the front side inside the cap top is used for judging whether a wearer exists, and the 2 infrared distance measuring sensors arranged at the two sides of the cap peak are used for measuring the distance from the safety helmet to the ears of the wearer.
The elastic displacement unit 103 is respectively composed of 1 film pressure sensor, 3 BF350 high-precision resistance strain gauge and an accessory circuit, wherein the film pressure sensor is arranged at the chin strap, the pressure at the chin strap is detected, the BF350 high-precision resistance strain gauge is arranged at the helmet hoop of the helmet, and the head pressure information of the wearer of the helmet is measured. The three-dimensional attitude unit 104 is composed of an MPU6050 triaxial sensor and an accessory circuit thereof, is arranged at the inner top of the helmet, completes the measurement of dynamic angular velocity and acceleration information of the helmet, and acquires real-time data.
The active alarm unit 105 is composed of keys and interface circuits, is located above the visor of the helmet, and is used for an alarm function initiated by a wearer in emergency, and structurally adopts a back button for preventing false triggering.
The mobile interconnection unit 106 is formed by a GPRS module SIM900 and an accessory circuit thereof, and is located above the helmet visor, and is used for information interaction transmission, including transmitting authentication attendance information and whether the helmet is correctly worn to a monitoring center, and simultaneously transmitting customized information triggered by an active alarm module to an upper monitoring center.
The embedded information fusion unit 107 is composed of a control processing chip MSP430 and a corresponding circuit and is positioned above the helmet visor, wherein the data interface module is used for acquiring real-time sensor information; the information analysis module is used for completing sampling structure analysis of real-time perception data; the information calculation module calculates and analyzes the analyzed information according to algorithm rules so as to judge whether the safety helmet is worn correctly; the voice module carries out voice prompt on the person who is not correctly worn, and can selectively report information according to the system configuration; the storage module records basic information, timing sensor information and operation information of the wearer.
The embedded information fusion processing unit 107 adopts a control processing chip MSP430, a pin 5 of the embedded information fusion processing unit is connected with the active alarm unit 105, a pin 13, a pin 14 and a pin 15 of the embedded information fusion processing unit 107 are connected with the biological sensing unit 102, a pin 13 of the embedded information fusion processing unit 107 is connected with a collector of a triode Q1, the collector of the triode Q1 is also connected with a power supply through a resistor R5, an emitter of the triode Q1 is grounded, a base of the triode Q1 is connected with one of the infrared ranging sensors through a resistor R3, a pin 14 of the embedded information fusion processing unit is connected with a collector of a triode Q2, the collector of the triode Q2 is also connected with a power supply through a resistor R7, an emitter of the triode Q2 is grounded, a base of the triode Q2 is connected with the other infrared ranging sensor through a resistor R6, and a pin 15 of the embedded information fusion processing unit 107 is connected with the pyroelectric infrared sensor; the pin 33, the pin 34, the pin 35 and the pin 44 of the embedded information fusion processing unit 107 are respectively connected with the film pressure sensor and 3 high-precision resistance strain gauges, the pin 36, the pin 37 and the pin 38 of the embedded information fusion processing unit 107 are connected with the radio frequency authentication unit 101, the pin 39, the pin 40, the pin 41, the pin 42 and the pin 43 of the embedded information fusion processing unit 107 are respectively connected with the pin 6, the pin 7, the pin 12, the pin 23 and the pin 24 of the triaxial sensor, and the pin 58, the pin 59 and the pin 60 of the embedded information fusion processing unit 107 are connected with the mobile interconnection unit 106.
The method for judging whether the helmet is worn correctly is shown in fig. 5, and comprises the following steps:
step 1: the radio frequency authentication unit 101 works independently, actively collects user information after starting, judges whether the user is a legal user, if the user is the legal user, judges the system state according to the system information, the card swiping times and the time data, if the user is judged to be in a working state, the whole device is started, the mobile interconnection unit 106 is informed to enter the working state, and if the user is not in a standby state, the device is started; if the working state is judged to be the off-duty state, the working time is recorded, the data storage backup is completed and is sent to the mobile interconnection unit 106, and then the whole device enters a standby state.
Step 2: the data interface module starts to collect information of each interface sensor in real time after the device enters a working state, specifically, judges whether the information of the biological sensing unit 102 is received or not, and further judges information content, if the user is detected to wear the safety helmet, the data interface module starts to sample infrared ranging information in the biological sensing unit 102, pressure sensor information in the elastic displacement unit 103 and angular speed and acceleration information of the three-dimensional posture unit 104 at fixed time.
Step 3: the information analysis module analyzes the transmitted interface information of various different types, converts the interface information into a discrimination variable in a unified format, counts the results of multiple measurements in fixed time aiming at different modules, takes the average value of the results, and transmits the results to the information calculation module.
Step 4: after the information calculation module receives the normalized discrimination variables, the information calculation module performs multidimensional sensing algorithm calculation: a) Firstly, two infrared distance measuring sensors test the safety helmet for a plurality of times, and by using a formula,andwherein x is i D for each measurement value i Deviation of measured value from average value->n is the observation times, the measurement times of each infrared ranging sensor are n/2 times, and the calculation is performedAverage value and average error, distance measurement average value +.>And average error delta r The method comprises the steps of carrying out a first treatment on the surface of the Average value +.about.two kinds of pressure sensors in elastic displacement module>And average error delta b1 、δ b2 The calculation formula of the average value and the average error of the two types of pressure sensors is identical with that of the infrared ranging sensor, and the two types of pressure sensors are weighted according to different weights +.>According to the formula->And->Calculate the mean value of the elastic displacement module +.>And average error delta b The method comprises the steps of carrying out a first treatment on the surface of the Average value of X, Y, Z three-direction angular velocities of three-dimensional attitude module +.>And average error delta ωx 、δ ωy 、δ ωz Simultaneously weighting values which differ according to the three directions X, Y, Z +.> According to the formula: />Andthe average value of the three-dimensional attitude module can be finally obtained>And average error delta ω The method comprises the steps of carrying out a first treatment on the surface of the b) Each module calculates average error through measured value, judges whether the helmet is correctly worn according to whether the average error is in the error range determined by each module in advance, if so, the helmet is considered to be correct, and then c) the next step of calculation is carried out, otherwise, the helmet is considered to be incorrectly worn, c) when the average error of each module obtained by the calculation is in the error range, the weight value of the infrared ranging module is calculated according to the weight value of the infrared ranging module>Weight value of elastic displacement module +.>And three-dimensional gesture module weight value +.>Thereby calculating the state average value +.>And average error->And calculating the overall state average value and the overall average error of the safety helmet through overall analysis, judging whether the safety helmet is worn correctly, and if the overall average error exceeds the preset overall average error, judging that the safety helmet is not worn correctly.
Step 5: once the safety helmet is judged to be not worn correctly, a voice module in the safety helmet can send out an acousto-optic action to prompt a wearer to correct the wearing action of the safety helmet; meanwhile, the embedded information fusion unit 107 records information, and then sends the information to the mobile interconnection unit 106 after exceeding an alarm threshold value, and the mobile interconnection unit 106 sends the alarm information to a remote control center.
Step 6: the active alarm unit 105 works independently, and in case of emergency or other situations where the wearer decides that the alarm needs to be reported, the wearer actively triggers the embedded information fusion unit 107 to trigger the custom information to be sent up, and this priority is set to be the highest.
The above description is of the preferred embodiments of the invention and is not intended to limit the scope of the invention. All equivalent changes and modifications made in accordance with the present invention shall be made in the light of the present invention.
Claims (1)
1. The safety helmet safety monitoring method comprises an embedded information fusion processing unit, and is characterized in that the embedded information fusion processing unit is respectively connected with a radio frequency authentication unit, a biological sensing unit, an elastic displacement unit, a three-dimensional posture unit, a mobile interconnection unit and an active alarm unit, and comprises a data interface module, an information analysis module, an information calculation module, a voice module and a storage module, and the method comprises the following steps:
(1) The radio frequency authentication unit works independently, actively collects user information after starting, judges whether the user is a legal user, if so, judges the system state, if so, starts the whole device, informs the mobile interconnection unit and enters the working state, otherwise, the device is in the standby state; if the working time is judged to be in the off-duty state, the working time is recorded, the data storage backup is completed and is sent to the mobile interconnection unit, and then the whole device enters a standby state;
(2) The data interface module starts to acquire sensor information of each unit in real time after the device enters a working state;
(3) The information analysis module analyzes the transmitted interface information of various types, converts the interface information into a discrimination variable in a unified format, counts the results of multiple measurements in fixed time aiming at different modules, takes the average value of the results, and transmits the results to the information calculation module;
(4) After receiving the normalized discrimination variables, the information calculation module carries out threshold range judgment firstly, then carries out multidimensional sensing algorithm calculation and judges whether the safety helmet is worn correctly;
(5) Once the safety helmet is judged to be not worn correctly, a voice module in the safety helmet can send out an acousto-optic action to prompt a wearer to correct the wearing action of the safety helmet; meanwhile, the embedded information fusion unit records information, and then sends the information to the mobile interconnection unit after exceeding an alarm threshold value, and the mobile interconnection unit sends the alarm information to the remote control center;
(6) The active alarm unit works independently, and is actively triggered by the wearer in case of emergency or other occasions when the wearer judges that the alarm needs to be reported, the embedded information fusion unit triggers the customized information to be sent upwards, and the priority is set to be the highest;
the biological sensing unit comprises 1 pyroelectric infrared sensor and 2 infrared ranging sensors, the pyroelectric sensor is positioned at the front side inside the crown, and the 2 infrared ranging sensors are positioned at two sides of the visor;
the elastic displacement unit comprises 1 film pressure sensor and 3 high-precision resistance strain gauges, wherein the film pressure sensor is positioned at the chin strap of the hat, and the 3 high-precision resistance strain gauges are distributed at the cap hoops;
the three-dimensional attitude unit comprises a three-axis sensor, and the three-axis sensor is positioned at the inner top of the helmet;
the specific steps of the step (2) are as follows:
firstly judging whether the information of the biological sensing unit is received or not, and further judging the information content, if the fact that the user wears the safety helmet is detected, starting to sample the infrared ranging information in the biological sensing module, the pressure sensor information in the elastic displacement module and the angular speed and acceleration information of the three-dimensional gesture module at regular time;
the multi-dimensional perception algorithm in the step (4) comprises the following calculation steps: a) Firstly, two infrared ranging sensors test the safety helmet for multiple times, and a formula is utilizedWhere xi is the measured value of each time, di is the deviation of the measured value from the mean value +.>N is the observation times, the measurement times of each infrared ranging sensor is n/2 times, the average value and the average error are calculated, and the ranging average value +.>And average error->The method comprises the steps of carrying out a first treatment on the surface of the Average value +.about.two kinds of pressure sensors in elastic displacement module>、/>And average error->、/>The calculation formula of the average value and the average error of the two types of pressure sensors is identical with that of the infrared ranging sensor, and the two types of pressure sensors are weighted according to different weights +.>、/>According to the formula->And->Calculating the average value of elastic displacement module +.>And average error->The method comprises the steps of carrying out a first treatment on the surface of the Average value of X, Y, Z three-direction angular velocities of three-dimensional attitude module +.>And average error->Simultaneously according to the weighted values of X, Y, Z in three different directions According to the formula: />And->The average value of the three-dimensional attitude module can be finally obtained>And average error->The method comprises the steps of carrying out a first treatment on the surface of the b) Each module calculates average error through measured value, and if the average error is within the error range, the module considers to be correct, and then proceeds to c) the next step of calculation, otherwise, the safety helmet is considered to be not worn correctly, c) when the average error of each module obtained by the calculation is within the respective error range, the module is judged to be correct according to the weight value of the infrared ranging module>Weight value of elastic displacement module +.>And three-dimensional gesture module weight value +.>Thereby calculating the state average value +.>And average error->And calculating the overall state average value and the overall average error of the safety helmet through overall analysis, judging whether the safety helmet is worn correctly, and if the overall average error exceeds the preset overall average error, judging that the safety helmet is not worn correctly.
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Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109953399A (en) * | 2017-12-26 | 2019-07-02 | 刘金 | A kind of intelligent safety helmet and intelligent control method |
| CN108646316A (en) * | 2018-05-02 | 2018-10-12 | 四川斐讯信息技术有限公司 | A kind of wearing state recognition methods of wearable device and wearable device |
| CN109542215B (en) * | 2018-10-09 | 2022-03-08 | 中国矿业大学 | Wearing monitoring method for safety helmet |
| CN109361902A (en) * | 2018-11-19 | 2019-02-19 | 河海大学 | A kind of intelligent safety helmet wearing monitoring system based on edge calculations |
| CN111273450B (en) * | 2020-04-14 | 2020-12-08 | 湖南翰坤实业有限公司 | VR experience helmet and balance adjusting method thereof |
| CN115171334A (en) * | 2022-06-30 | 2022-10-11 | 福建汇川物联网技术科技股份有限公司 | Safety helmet wearing supervision method and device, electronic equipment and storage medium |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102232645A (en) * | 2010-05-05 | 2011-11-09 | 曹磊 | High voltage warning safety helmet |
| CN102349720A (en) * | 2011-11-04 | 2012-02-15 | 江南大学 | Warning helmet |
| CN102450764A (en) * | 2010-10-28 | 2012-05-16 | 尚文建 | Novel high voltage alarm safety helmet |
| CN102793330A (en) * | 2011-05-24 | 2012-11-28 | 刘生科 | Novel alarming type safety helmet |
| CN202842494U (en) * | 2012-10-12 | 2013-04-03 | 大唐国际发电股份有限公司重庆分公司 | Intelligent safety helmet with functions of monitoring and personnel location |
| KR101581353B1 (en) * | 2015-05-22 | 2016-01-11 | 전상보 | Safety helmet |
| CN105701968A (en) * | 2014-11-17 | 2016-06-22 | 南通大学 | Wireless monitoring alarm system for welding operation |
-
2017
- 2017-01-03 CN CN201710000608.8A patent/CN106617456B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102232645A (en) * | 2010-05-05 | 2011-11-09 | 曹磊 | High voltage warning safety helmet |
| CN102450764A (en) * | 2010-10-28 | 2012-05-16 | 尚文建 | Novel high voltage alarm safety helmet |
| CN102793330A (en) * | 2011-05-24 | 2012-11-28 | 刘生科 | Novel alarming type safety helmet |
| CN102349720A (en) * | 2011-11-04 | 2012-02-15 | 江南大学 | Warning helmet |
| CN202842494U (en) * | 2012-10-12 | 2013-04-03 | 大唐国际发电股份有限公司重庆分公司 | Intelligent safety helmet with functions of monitoring and personnel location |
| CN105701968A (en) * | 2014-11-17 | 2016-06-22 | 南通大学 | Wireless monitoring alarm system for welding operation |
| KR101581353B1 (en) * | 2015-05-22 | 2016-01-11 | 전상보 | Safety helmet |
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| CN106617456A (en) | 2017-05-10 |
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