Laboratory safety monitoring method and system based on multi-data fusion

Abstract

The invention provides a laboratory safety monitoring method and system based on multi-data fusion. The method comprises the steps that S1, a data acquisition module monitors and acquires environmental data in a laboratory in real time; environment data in a laboratory are preprocessed; performing weight distribution on the laboratory internal environment data and the manual alarm function triggering state, and introducing a comprehensive threat index; s2, calculating a comprehensive threat index according to the collected laboratory internal environment data, the manual alarm function trigger state and the weight; s3, judging a security threat level based on the comprehensive threat index; judging a security threat type based on the security threat level, the laboratory internal environment data and the manual alarm function triggering state; and S4, taking security countermeasures according to the security threat type. The comprehensive threat index can comprehensively reflect the safety condition in the laboratory; and safety countermeasures are taken for the safety threat type, so that the accuracy of safety condition identification and the pertinence and effectiveness of the countermeasures are improved, and personnel and property loss is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of laboratory safety, and particularly to a laboratory safety monitoring method and monitoring system based on multi-data fusion. Background Art

[0002] In the research and development and testing process of modern electronic devices, an electromagnetic compatibility (EMC) anechoic chamber is an indispensable facility, which is used to test the anti-interference ability and electromagnetic radiation level of devices in an electromagnetic environment, and its safety is crucial. Due to the presence of high-power electromagnetic devices, complex cable wiring, and a closed space environment in the anechoic chamber, once a fire, equipment failure, or other emergency occurs, it may cause serious damage to personnel and equipment. Therefore, the safety system of the EMC anechoic chamber must have a high degree of reliability and response speed to ensure the safety of personnel and equipment. Existing EMC anechoic chamber safety systems usually only include smoke monitoring and temperature monitoring functions to detect fire hazards in the anechoic chamber. However, these safety monitoring functions usually operate independently, lacking effective data fusion and intelligent decision-making capabilities, which limits the comprehensive judgment ability of the safety system and cannot accurately identify the risk sources. For example, when both smoke monitoring and temperature monitoring are triggered, the main risk source cannot be accurately identified, resulting in the anechoic chamber being unable to take effective safety response measures in the shortest time, thereby triggering serious safety accidents and causing significant losses to the lives and property of personnel in the EMC anechoic chamber. Summary of the Invention

[0003] One of the objectives of the present invention is to provide a laboratory safety monitoring method and monitoring system based on multi-data fusion to solve the problem in the prior art that the laboratory safety system cannot quickly judge the main fault source, resulting in the inability to take safety measures in a timely manner.

[0004] To achieve the above objective, the technical solutions adopted by the present invention are as follows:

[0005] A laboratory safety monitoring method based on multi-data fusion for real-time monitoring of the safety status in a laboratory, including the following steps:

[0006] S1. Use a data acquisition module including multiple sensors to real-time monitor and collect the environmental data in the laboratory, where the environmental data in the laboratory includes smoke concentration, temperature, carbon monoxide content, and humidity; perform preprocessing on the collected environmental data in the laboratory, including filtering, data calibration, time synchronization, and normalization;

[0007] Assign weights to the environmental data in the laboratory and the trigger status of the manual alarm function, and introduce a comprehensive threat index;

[0008] S2. Calculate the comprehensive threat index according to the collected environmental data in the laboratory and the trigger status of the manual alarm function, in combination with the weights.

[0009] S3. Introduce and judge the security threat level based on the comprehensive threat index. The security threat level includes high threat level, medium threat level, and low threat level;

[0010] Introduce and judge the security threat type based on the security threat level, the collected indoor environment data of the laboratory, and the triggering status of the manual alarm function. The security threat type includes fire threat, gas leakage threat, equipment overheating threat, and emergency of testers;

[0011] S4. Conduct security early warning according to the security threat type and take corresponding security response measures.

[0012] According to the above technical means, by using the comprehensive threat index to fuse the collected indoor environment data of the laboratory, it can comprehensively reflect the security status in the laboratory; by using the security threat level combined with the security threat type to judge the security status in the laboratory and take corresponding security response measures, it not only improves the accuracy of security status identification, but also improves the pertinence and effectiveness of security response measures, making the laboratory safe and able to avoid losses of personnel and property.

[0013] Further, in the step S1, the calculation formula of the comprehensive threat index is:

[0014]

[0015] In the formula: Y is the comprehensive threat index, W i is the weight of the i-th indoor environment data of the laboratory, X i is the normalized value of the i-th indoor environment data of the laboratory, and W5 and X5 are the weight and normalized value of the triggering status of the manual alarm function respectively;

[0016] Among them, the calculation formulas of the normalized values of the smoke concentration, temperature, carbon monoxide content, and humidity are:

[0017]

[0018] In the formula: x i is the indoor environment data of the laboratory collected by the i-th sensor, x imin is the minimum value of the range of the i-th sensor, and x imax is the threshold set for the i-th sensor;

[0019] The normalized value X5 of the triggering status of the manual alarm function is: when the triggering status of the manual alarm function is triggered, its normalized value is 1; when the triggering status of the manual alarm function is not triggered, its normalized value is 0.

[0020] According to the above technical means, the collected indoor environment data of the laboratory and the triggering status of the manual alarm function are normalized, eliminating the differences between the data and enabling comparison and calculation on the same scale; the weight distribution enables the calculation of the comprehensive threat index to meet the requirements of safety monitoring, improving the accuracy and reliability of the safety threat index in reflecting the safety status in the laboratory.

[0021] Further, the weight values of the indoor environment data of each laboratory and the triggering status of the manual alarm function are respectively: the weight W1 of the smoke concentration = 0.3, the weight W2 of the temperature = 0.25, the weight W3 of the carbon monoxide content = 0.20, the weight W4 of the humidity = 0.10, and the weight W5 of the triggering status of the manual alarm function = 0.15.

[0022] According to the above technical means, weights are assigned to the indoor environment data of the laboratory and the triggering status of the manual alarm function, making the calculation of the comprehensive threat index reliable and accurately reflecting the importance of the indoor environment data of the laboratory and the triggering status of the manual alarm function to the laboratory safety, which is conducive to accurately reflecting the safety status of the laboratory.

[0023] Further, the threshold set for the i-th sensor is specifically:

[0024] The threshold x of the smoke concentration 1max = 30 ppm; the threshold x of the temperature 2max = 50 °C; the threshold x of the carbon monoxide concentration 3max = 25 ppm; the threshold x of the humidity 4max = 100%.

[0025] According to the above technical means, by setting thresholds, it is beneficial to accurately identify the safety ranges of the smoke concentration, temperature, carbon monoxide concentration, and humidity in the laboratory, facilitating the normalized calculation of the smoke concentration, temperature, carbon monoxide concentration, and humidity and enabling their calculation on the same scale.

[0026] Further, in the S2 step, the specific safety threat level is: when the comprehensive threat index Y ∈ [0.8, 1], the safety threat level is a high threat level; when the comprehensive threat index Y ∈ [0.5, 0.8), the safety threat level is a medium threat level; when the comprehensive threat index Y ∈ [0, 0.5), the safety threat level is a low threat level.

[0027] According to the above technical means, by setting a clear range of the comprehensive threat index, it is possible to clearly distinguish the three threat levels of high threat level, medium threat level, and low threat level, making the judgment of the safety threat level accurate.

[0028] Further, in the S3 step:

[0029] When the security threat level is a high threat level:

[0030] When the smoke concentration collected by the data acquisition module ≥ 30 ppm, and the temperature collected by the data acquisition module ≥ 50 °C or the temperature rises at a rate of at least 5 °C per minute, it is determined as a fire threat;

[0031] When the carbon monoxide content collected by the data acquisition module ≥ 25 ppm, and the smoke concentration collected by the data acquisition module is less than 30 ppm, it is determined as a gas leakage threat;

[0032] When the security threat level is a medium threat level:

[0033] When the smoke concentration collected by the data acquisition module < 30 ppm, and the temperature collected by the data acquisition module ≥ 50 °C, it is determined as an equipment overheat threat;

[0034] When the trigger status of the manual alarm function is triggered, it is determined as a passenger emergency.

[0035] According to the above technical means, combining the security threat level and the collected indoor environment data of the laboratory and the trigger status of the manual alarm function to judge the type of security threat, which has accuracy and makes the security response measures targeted.

[0036] Furthermore, the security response measures specifically include:

[0037] When the type of security threat is determined as a fire threat: Immediately start the ventilation system to reduce the smoke concentration in the laboratory, make an emergency call to notify the test personnel, and guide the test personnel to evacuate through voice prompts and image prompts;

[0038] When the type of security threat is determined as a gas leakage threat: Immediately start the ventilation system to reduce the gas concentration and make an emergency call;

[0039] When the type of security threat is determined as an equipment overheat threat: Stop the operation of the equipment in the laboratory, send a maintenance request to the maintenance center, and display a warning through image information;

[0040] When the type of security threat is determined as a test personnel emergency: Make an emergency call, contact the monitoring center, and give voice prompts.

[0041] According to the above technical means, taking different security response measures for different types of security threats makes the security response measures targeted and effective.

[0042] Furthermore, the data calibration includes the following steps:

[0043] Laboratory calibration: In a laboratory environment, each of the sensors is calibrated using standard equipment to determine the reference value of each sensor;

[0044] Linear calibration: Combining multiple standard values measured by each standard equipment with multiple measurement values of each sensor to obtain the output value calibration formula for each sensor as: y i = k i x i + b i ;

[0045] In the formula: y i is the output value of the i-th sensor; x i is the measurement value of the i-th sensor; k i is the proportionality coefficient of the i-th sensor; b i is the offset of each of the sensors;

[0046] Among them:

[0047] In the formula: x ij is the j-th measurement value measured by the i-th sensor; y ij is the j-th standard value measured by the standard equipment corresponding to the i-th sensor; m i is the number of measurement values of the i-th sensor, and j ∈ [1, m i ;

[0048]

[0049] In the formula: x ij is the j-th measurement value measured by the i-th sensor; y ij is the j-th standard value measured by the standard equipment corresponding to the i-th sensor; k i is the proportionality coefficient of the i-th sensor; m i is the number of measurement values measured by the i-th sensor, and j ∈ [1, m i .

[0050] According to the above technical means, calibrating the sensor is beneficial to reducing the instrument error of the sensor. By linearly calibrating and further fitting the sensor measurement value and the standard value, the accuracy and reliability of the sensor output value can be improved.

[0051] The present invention also provides a laboratory safety monitoring system based on multi-data fusion. Based on any one of the above-mentioned laboratory safety monitoring methods based on multi-data fusion, it includes:

[0052] A data acquisition module for real-time monitoring and collecting the environmental data in the laboratory. The environmental data in the laboratory includes smoke concentration, temperature, carbon monoxide content, and humidity;

[0053] A data processing module for preprocessing the collected indoor environment data of the laboratory, and the preprocessing includes filtering, data calibration, time synchronization, and normalization;

[0054] A data fusion and judgment module for calculating a comprehensive threat index according to the indoor environment data of the laboratory and the weight of the manual alarm function trigger status, and judging the safety threat level according to the comprehensive threat index, and judging the safety threat type according to the indoor environment data and the manual alarm function trigger status;

[0055] A user interface for passengers to trigger a manual alarm;

[0056] A safety warning module for performing safety warnings according to the safety threat type, and taking safety response measures according to the safety threat level and the safety threat type;

[0057] A data storage module for storing the indoor environment data collected by the data collection module to form a log.

[0058] Further, the data collection module includes a smoke sensor, a temperature sensor, a carbon monoxide sensor, and a humidity sensor.

[0059] According to the above technical means, the real-time monitoring, warning and response of the laboratory safety status are realized, the monitoring accuracy, warning timeliness, effectiveness of response measures and management efficiency are improved, and a strong guarantee is provided for the safe operation of the laboratory.

[0060] The beneficial effects of the present invention are as follows:

[0061] 1. The method of the present invention uses the comprehensive threat index to fuse the collected indoor environment data of the laboratory, which can comprehensively reflect the safety status in the laboratory; using the safety threat level combined with the safety threat type to judge the safety status in the laboratory and take corresponding safety response measures not only improves the accuracy of safety status identification, but also improves the pertinence and effectiveness of safety response measures, making the laboratory safe and able to avoid losses of personnel and property.

[0062] 2. The system of the present invention realizes the real-time monitoring, warning and response of the laboratory safety status, improves the monitoring accuracy, warning timeliness, effectiveness of response measures and management efficiency, and provides a strong guarantee for the safe operation of the laboratory. Description of the Drawings

[0063] To more clearly illustrate the technical solutions in the embodiments of the present invention or in the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only partial embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0064] Figure 1 is a schematic flowchart of the laboratory safety monitoring method based on multi-data fusion of the present invention;

[0065] Figure 2 is a schematic diagram of the composition of the laboratory safety monitoring system based on multi-data fusion of the present invention. Detailed implementation manners

[0066] The following will describe the implementation manners of the present invention with reference to the accompanying drawings and preferred embodiments. The accompanying drawings are only for illustrative purposes and cannot be construed as limiting the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation manners. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be understood that the preferred embodiments are only for explaining the present invention and not for limiting the protection scope of the present invention.

[0067] As Figures 1 to 2 shown, this embodiment provides a laboratory safety monitoring method and system based on multi-data fusion for real-time monitoring of the safety status in the laboratory. As Figure 1 shown, the method includes the following steps:

[0068] S1. Use a data acquisition module containing multiple sensors to continuously monitor and collect the environmental data in the laboratory. The environmental data in the laboratory includes smoke concentration, temperature, carbon monoxide content, and humidity; preprocess the collected environmental data in the laboratory, including filtering, data calibration, time synchronization, and normalization;

[0069] Assign weights to the environmental data in the laboratory and the trigger status of the manual alarm function, and introduce a comprehensive threat index;

[0070] S2. Calculate the comprehensive threat index based on the collected environmental data in the laboratory and the trigger status of the manual alarm function, in combination with the weights;

[0071] S3. Introduce and determine the safety threat level based on the comprehensive threat index. The safety threat levels include high threat level, medium threat level, and low threat level;

[0072] Introduce and judge the type of security threat based on the security threat level, the collected indoor environment data of the laboratory, and the triggering status of the manual alarm function. The types of security threats include fire threat, gas leakage threat, equipment overheating threat, and emergency of testers.

[0073] S4. Conduct security early warning according to the type of security threat and take corresponding security response measures.

[0074] By fusing the collected indoor environment data of the laboratory using the comprehensive threat index, the security status of the laboratory can be comprehensively reflected. By combining the security threat level with the type of security threat to judge the security status of the laboratory and taking corresponding security response measures, not only the accuracy of security status identification is improved, but also the pertinence and effectiveness of security response measures are enhanced, making the laboratory safe and able to avoid losses of personnel and property.

[0075] In preprocessing, filter the original data collected by the sensors to remove noise interference and ensure the accuracy of the data; data calibration is used to eliminate errors caused by sensor accuracy or environmental factors; time synchronization is used to ensure that the data collected by all sensors are aligned in time to avoid misjudgment caused by time differences; normalization is to process data with different units so that they can be compared and calculated on the same dimension.

[0076] In this embodiment, in step S1, the calculation formula of the comprehensive threat index is:

[0077]

[0078] In the formula: Y is the comprehensive threat index, W i is the weight of the i-th indoor environment data of the laboratory, X i is the normalized value of the i-th indoor environment data of the laboratory, and W5 and X5 are the weight and normalized value of the triggering status of the manual alarm function respectively;

[0079] Among them, the calculation formulas of the normalized values of smoke concentration, temperature, carbon monoxide content, and humidity are:

[0080]

[0081] In the formula: x i is the indoor environment data of the laboratory collected by the i-th sensor, x imin is the minimum value of the range of the i-th sensor (0 in this embodiment), x imax is the threshold set for the i-th sensor;

[0082] The normalized value X5 of the manual alarm function trigger status is as follows: when the manual alarm function trigger status is triggered, its normalized value is 1; when the manual alarm function trigger status is not triggered, its normalized value is 0.

[0083] Normalizing the collected indoor environment data and the manual alarm function trigger status eliminates the differences between the data and enables comparison and calculation on the same scale; the weight assignment can make the calculation of the comprehensive threat index meet the requirements of safety monitoring, improving the accuracy and reliability of the safety threat index in reflecting the safety status of the laboratory.

[0084] In this embodiment, the weight values of each indoor environment data and the manual alarm function trigger status are as follows: the weight W1 of the smoke concentration = 0.3, the weight W2 of the temperature = 0.25, the weight W3 of the carbon monoxide content = 0.20, the weight W4 of the humidity = 0.10, and the weight W5 of the manual alarm function trigger status = 0.15. Assigning weights to the indoor environment data and the manual alarm function trigger status makes the calculation of the comprehensive threat index reliable and can accurately reflect the importance of the indoor environment data and the manual alarm function trigger status to the laboratory safety, which is beneficial to accurately reflecting the safety status of the laboratory. The above weight assignment is carried out according to the importance of the impact on laboratory safety (the greater the impact on laboratory safety, the higher the assigned weight), the real-time nature of the response (the data source that requires a quick response has a higher weight), and the reliability of the data. Among them, the smoke concentration is a direct indicator of fire and has the greatest impact on the safety of the laboratory; abnormal temperature may be a sign of fire or equipment failure and has the second greatest impact on the safety of the laboratory; the carbon monoxide concentration affects the personal safety of the testers in the laboratory and has a higher weight; the change in humidity has a relatively small impact on the safety of the laboratory but can reflect environmental abnormalities and has a lower weight; the manual alarm function is actively triggered by the tester, so the weight is medium.

[0085] In this embodiment, the threshold value set for the i-th sensor is specifically:

[0086] The threshold value x of the smoke concentration 1max = 30 ppm; the threshold value x of the temperature 2max = 50 °C; the threshold value x of the carbon monoxide concentration 3max = 25 ppm; the threshold value x of the humidity 4max= 100%. When the smoke concentration is higher than or equal to 30 ppm, it indicates that the smoke concentration in the laboratory is at a high level; when the temperature is greater than or equal to 50 °C, it indicates that the temperature in the laboratory has risen abnormally; when the carbon monoxide concentration is higher than or equal to 25 ppm, it indicates that the carbon monoxide concentration in the laboratory is at a high level; when the humidity is 100%, it indicates that the water vapor content in the air in the laboratory has reached the maximum value at the current temperature. By setting thresholds, it is beneficial to accurately identify the safety ranges of the smoke concentration, temperature, carbon monoxide concentration, and humidity in the laboratory, facilitating the normalized calculation of the smoke concentration, temperature, carbon monoxide concentration, and humidity, and enabling them to be calculated on the same scale.

[0087] In this embodiment, in step S2, the specific safety threat level is as follows: when the comprehensive threat index Y ∈ [0.8, 1], the safety threat level is a high threat level; when the comprehensive threat index Y ∈ [0.5, 0.8), the safety threat level is a medium threat level; when the comprehensive threat index Y ∈ [0, 0.5), the safety threat level is a low threat level. By setting a clear range of comprehensive threat indices, it is possible to clearly distinguish the three threat levels of high threat level, medium threat level, and low threat level, making the judgment of the safety threat level precise.

[0088] In this embodiment, in step S3:

[0089] When the safety threat level is a high threat level:

[0090] If the smoke concentration collected by the data acquisition module ≥ 30 ppm, and the temperature collected by the data acquisition module ≥ 50 °C or the temperature rises at a rate of at least 5 °C per minute, it is determined as a fire threat;

[0091] If the carbon monoxide content collected by the data acquisition module ≥ 25 ppm, and the smoke concentration collected by the data acquisition module is less than 30 ppm, it is determined as a gas leakage threat;

[0092] When the safety threat level is a medium threat level:

[0093] If the smoke concentration collected by the data acquisition module < 30 ppm, and the temperature collected by the data acquisition module ≥ 50 °C, it is determined as an equipment overheating threat;

[0094] When the trigger status of the manual alarm function is triggered, it is determined as a passenger emergency.

[0095] Combining the safety threat level with the collected environmental data in the laboratory and the trigger status of the manual alarm function to judge the type of safety threat has precision, making the safety response measures targeted.

[0096] In this embodiment, the safety response measures specifically include:

[0097] When the security threat type is determined to be a fire threat: Immediately activate the ventilation system to reduce the smoke concentration in the laboratory, make an emergency call to notify the testers, and guide the testers to evacuate through voice prompts and image prompts;

[0098] When the security threat type is determined to be a gas leakage threat: Immediately activate the ventilation system to reduce the gas concentration and make an emergency call;

[0099] When the security threat type is determined to be an equipment overheating threat: Stop the operation of the equipment in the laboratory, send a maintenance request to the maintenance center, and display a warning through image information;

[0100] When the security threat type is determined to be an emergency situation of the tester: Make an emergency call, contact the monitoring center, and give voice prompts.

[0101] Adopt different security response measures according to the security threat type, making the security response measures targeted and effective.

[0102] According to the severity and urgency of the impact of each security threat type on the laboratory, prioritize multiple security threat types: fire threat > gas leakage threat > equipment overheating threat > tester emergency situation. When implementing security response measures, execute the security response measures according to the priority ranking. It is worth mentioning that when the comprehensive threat index Y ∈ [0, 0.5), the threat level is a low threat level. At this time, each sensor continues to monitor the environmental data in the laboratory, and there is no need to immediately take security response measures.

[0103] In this embodiment, data calibration includes the following steps:

[0104] Laboratory calibration: In the laboratory environment, use standard equipment to calibrate each sensor to determine the reference value of each sensor;

[0105] Linear calibration: Combine the multiple standard values measured by each standard equipment with the multiple measured values of each sensor to obtain the output value calibration formula of each sensor as: y i =k i x i +b i ;

[0106] In the formula: y i is the output value of the i-th sensor; x i is the measured value of the i-th sensor; k i is the proportionality coefficient of the i-th sensor; b i is the offset of each sensor;

[0107] Among them:

[0108] In the formula: xij is the j-th measured value measured by the i-th sensor; y ij is the j-th standard value measured by the standard device corresponding to the i-th sensor; m i is the number of measured values of the i-th sensor, and j ∈ [1, m i ;

[0109]

[0110] In the formula: x ij is the j-th measured value measured by the i-th sensor; y ij is the j-th standard value measured by the standard device corresponding to the i-th sensor; k i is the proportionality coefficient of the i-th sensor; m i is the number of measured values measured by the i-th sensor, and j ∈ [1, m i .

[0111] Calibrating the sensor is beneficial to reducing the instrument error of the sensor. By further fitting the measured value and the standard value of the sensor through linear calibration, the accuracy and reliability of the output value of the sensor can be improved.

[0112] In this embodiment, a feedback mechanism is further included. During the process of laboratory safety monitoring, the data storage module stores the data collected by the sensor during the monitoring process and forms feedback data for data analysis and optimization and adjustment of the calculation of the comprehensive threat index in subsequent work.

[0113] This embodiment also provides a laboratory safety monitoring system based on multi-data fusion as shown in Figure 2 . A laboratory safety monitoring method based on multi-data fusion according to any one of the above includes:

[0114] A data acquisition module for real-time monitoring and acquisition of environmental data in the laboratory. The environmental data in the laboratory includes smoke concentration, temperature, carbon monoxide content, and humidity;

[0115] A data processing module for preprocessing the collected environmental data in the laboratory. The preprocessing includes filtering, data calibration, time synchronization, and normalization;

[0116] A data fusion and judgment module for calculating a comprehensive threat index according to the environmental data in the laboratory and the weight of the manual alarm function trigger status, and judging the safety threat level according to the comprehensive threat index and judging the safety threat type according to the environmental data in the laboratory and the manual alarm function trigger status;

[0117] A user interface for passengers to trigger a manual alarm;

[0118] A safety warning module, which is used to give safety warnings according to the types of safety threats and take safety response measures according to the safety threat levels and types of safety threats;

[0119] A data storage module, which is used to store the environmental data in the laboratory collected by the data collection module to form a log.

[0120] In this embodiment, the data collection module includes a smoke sensor, a temperature sensor, a carbon monoxide sensor and a humidity sensor.

[0121] In this embodiment, the tester can also perform manual one-key alarm and one-key cancel alarm through the user interface. The one-key alarm function enables the tester to quickly trigger an alarm when discovering a safety risk in the laboratory and immediately notify other staff that there is a safety risk or potential danger in the laboratory; after triggering the one-key alarm function, the system will immediately call the emergency rescue center and send the location information of the tester so that the rescue personnel can quickly arrive at the scene to take rescue measures; the one-key cancel alarm function is used to cancel when the tester accidentally touches the one-key alarm function.

[0122] The laboratory safety monitoring system uses multiple modules to achieve data collection, data processing, and human-computer interaction, realizing real-time monitoring, warning and response to the safety status of the laboratory, improving the monitoring accuracy, warning timeliness, effectiveness of response measures and management efficiency, and providing a strong guarantee for the safe operation of the laboratory. These sensors collect the smoke concentration, temperature, carbon monoxide content and humidity in the laboratory at a high frequency (such as collecting data once per second) and transmit the data to the data processing module and the data fusion and judgment module for processing in real time.

[0123] In this embodiment, the data fusion and judgment module, the user interface, the safety warning module and the data storage module are all communicatively linked to the core controller so as to issue response measure execution instructions to the safety warning module through the core controller.

[0124] It is worth mentioning that the laboratory in this embodiment refers to an EMC anechoic chamber, but the safety monitoring method and system in this embodiment are not limited to being used in an EMC anechoic chamber.

[0125] Obviously, the above embodiments of the present invention are only examples for clearly illustrating the present invention and are not limitations on the implementation manners of the present invention. For those of ordinary skill in the art, other different forms of changes or modifications can be made on the basis of the above description. It is not necessary and impossible to enumerate all the implementation manners here. Any modifications, equivalent replacements and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the claims of the present invention.

Claims

1. A laboratory safety monitoring method based on multi-data fusion, used for real-time monitoring of safety conditions in the laboratory, characterized in that: The following steps are involved: S1. Using a data acquisition module including multiple sensors to monitor and collect laboratory environment data in real time, the laboratory environment data includes smoke concentration, temperature, carbon monoxide content and humidity; preprocessing the collected laboratory environment data, including filtering, data calibration, time synchronization and normalization; Weights are assigned to laboratory environmental data and the trigger status of the manual alarm function, and a comprehensive threat index is introduced; S2. Calculate the comprehensive threat index based on the collected laboratory environment data and the trigger status of the manual alarm function and the weight; S3. Introduce and determine the security threat level based on the comprehensive threat index, where the security threat level includes a high threat level, a medium threat level, and a low threat level; Introducing and judging the type of security threat based on the security threat level, the collected laboratory environment data, and the triggering status of the manual alarm function, the security threat type including fire threat, gas leakage threat, equipment overheating threat, and tester emergency; S4. Issue a security warning based on the security threat type and take corresponding security response measures.

2. A laboratory safety monitoring method based on multi-data fusion according to claim 1, characterized in that: In the step S1, the calculation formula of the comprehensive threat index is: Where: Y is the comprehensive threat index, W i is the weight of the i-th laboratory environmental data, X i is the normalized value of the ith laboratory environmental data, W5 and X5 are the weight and normalized value of the triggering state of the manual alarm function respectively; The calculation formula for the normalized values ​​of smoke concentration, temperature, carbon monoxide content and humidity is: Where: x i is the laboratory environment data collected by the i-th sensor, x imin is the minimum value of the i-th sensor range, x imax The threshold set for the i-th sensor; The normalized value X5 of the manual alarm function trigger state is: when the manual alarm function trigger state is triggered, its normalized value is 1; when the manual alarm function trigger state is not triggered, its normalized value is 0.

3. A laboratory safety monitoring method based on multi-data fusion according to claim 2, characterized in that: The weight values ​​of the laboratory environmental data and the manual alarm function triggering status are: the weight of smoke concentration W1=0.3, the weight of temperature W2=0.25, the weight of carbon monoxide content W3=0.20, the weight of humidity W4=0.10, and the weight of manual alarm function triggering status W5=0.

15.

4. A laboratory safety monitoring method based on multi-data fusion according to claim 2 or 3, characterized in that: The threshold value set for the i-th sensor is specifically: The smoke concentration threshold x 1max =30ppm; the temperature threshold x 2max =50°C; the threshold value x of the carbon monoxide concentration 3max =25ppm; the humidity threshold x 4max =100%.

5. A laboratory safety monitoring method based on multi-data fusion according to claim 4, characterized in that: In the step S2, the security threat level is specifically: when the comprehensive threat index Y∈[0.8, 1], the security threat level is a high threat level; when the comprehensive threat index Y∈[0.5, 0.8), the security threat level is a medium threat level; when the comprehensive threat index Y∈[0, 0.5), the security threat level is a low threat level.

6. A laboratory safety monitoring method based on multi-data fusion according to claim 5, characterized in that: In the S3 step: When the security threat level is high: When the smoke concentration collected by the data collection module is ≥30ppm, and the temperature collected by the data collection module is ≥50°C or the temperature increases at a rate of at least 5°C per minute, it is determined to be a fire threat; When the carbon monoxide content collected by the data collection module is ≥25ppm, and the smoke concentration collected by the data collection module is less than 30ppm, it is determined to be a gas leakage threat; When the security threat level is medium threat level: When the smoke concentration collected by the data collection module is less than 30ppm, and the temperature collected by the data collection module is ≥50°C, it is determined to be a threat of equipment overheating; When the manual alarm function trigger state is triggered, it is determined to be a passenger emergency.

7. A laboratory safety monitoring method based on multi-data fusion according to claim 1, characterized in that: The safety countermeasures specifically include: When the security threat type is determined to be a fire threat: immediately start the ventilation system to reduce the smoke concentration in the laboratory, make an emergency call to notify the test personnel, and guide the test personnel to evacuate through voice prompts and image prompts; When the security threat type is determined to be a gas leakage threat: immediately start the ventilation system to reduce the gas concentration and make an emergency call; When the security threat type is determined to be a threat of equipment overheating: stopping the operation of the equipment in the laboratory, sending a maintenance request to the maintenance center, and displaying a warning through image information; When the security threat type is determined to be an emergency situation for the tester: an emergency call is made, the monitoring center is contacted, and a voice prompt is given.

8. A laboratory safety monitoring method based on multi-data fusion according to claim 1, characterized in that: The data calibration comprises the following steps: Laboratory calibration: In a laboratory environment, use standard equipment to calibrate each of the sensors to determine the reference value of each of the sensors; Linear calibration: Combining multiple standard values ​​measured by each standard device with multiple measurement values ​​of each sensor, the output value calibration formula of each sensor is: i =k i x i +b i ; Where: y i is the output value of the i-th sensor; x i is the measurement value of the i-th sensor; k i is the proportional coefficient of the i-th sensor; b i is the offset of each of the sensors; in: Where: x ij is the jth measurement value measured by the i-th sensor; y ij The jth standard value measured by the standard equipment corresponding to the i-th sensor; m i is the number of measurements of the ith sensor, and j∈[1, m i ]; Where: x ij is the jth measurement value measured by the i-th sensor; y ij k is the jth standard value measured by the standard equipment corresponding to the i-th sensor; i is the proportional coefficient of the i-th sensor; m i is the number of measurements taken by the i-th sensor, and j∈[1, m i ].

9. A laboratory safety monitoring system based on multi-data fusion, characterized in that: A laboratory safety monitoring method based on multi-data fusion according to any one of claims 1 to 8, comprising: Data acquisition module, used to monitor and collect laboratory environmental data in real time, including smoke concentration, temperature, carbon monoxide content and humidity; The data processing module is used to pre-process the collected laboratory environment data, including filtering, data calibration, time synchronization and normalization; A data fusion and judgment module is used to calculate a comprehensive threat index based on the weight of the laboratory environment data and the trigger status of the manual alarm function, and to judge the security threat level based on the comprehensive threat index, and to judge the security threat type based on the laboratory environment data and the trigger status of the manual alarm function; User interface for passengers to trigger manual alarms; A security warning module, used to issue a security warning according to the security threat type, and take security countermeasures according to the security threat level and the security threat type; The data storage module is used to store the laboratory environment data collected by the data collection module to form a log.

10. A laboratory safety monitoring system based on multi-data fusion according to claim 9, characterized in that: The data acquisition module includes a smoke sensor, a temperature sensor, a carbon monoxide sensor and a humidity sensor.

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