A laboratory hazardous gas leakage monitoring method and system

Abstract

The present application relates to the technical field of laboratory safety monitoring, and discloses a laboratory dangerous gas leakage monitoring method and system, which comprises the following steps: configuring an electronic identity tag for dangerous gas related articles and deploying a read-write device in an operation area, automatically generating a time-limited temporary operation voucher when the articles enter the operation area; monitoring the environmental concentration in real time through a gas sensor, and first checking whether there is a matching voucher when an anomaly is detected to distinguish between normal operation and abnormal leakage; if it is abnormal leakage, a warning is triggered, and at the same time, a nearby sensor is woken up to verify the concentration gradient to locate the leakage source; through the dynamic coupling mechanism of the operation voucher and the area sensor, the present application distinguishes between controlled release and accidental leakage, improves the balance between sensitivity and false alarm rate of the traditional threshold alarm, and at the same time, combines near-field gradient verification and airflow sudden change adaptive strategy to improve the accuracy of leakage detection and system robustness.

Description

Technical Field

[0001] This invention relates to a method and system for monitoring hazardous gas leaks in laboratories, belonging to the field of laboratory safety monitoring technology. Background Technology

[0002] Current laboratory gas monitoring mainly relies on fixed threshold alarm systems. These systems deploy a network of gas sensors to monitor environmental concentrations in real time, triggering an alarm when the detected value exceeds a preset threshold. This indiscriminate alarm mode has inherent drawbacks: on the one hand, setting a low threshold is necessary to detect trace leaks, leading to false alarms caused by frequent normal experimental operations such as reagent handling; on the other hand, while raising the threshold reduces false alarms, it may miss slowly accumulating dangerous leaks.

[0003] Existing attempts to improve the system include using multi-sensor data fusion or machine learning algorithms to optimize thresholds, but none of these have solved the main problem—the system lacks the contextual judgment ability to distinguish between controlled releases and accidental leaks. Specifically, existing technologies have the following main limitations: 1. They cannot establish a logical association between gas concentration signals and experimental operations; 2. They lack adaptability to environmental disturbances such as sudden airflow disturbances; 3. The problem of decreased monitoring reliability due to sensor performance degradation has not been addressed by the system. Therefore, how to construct an intelligent monitoring system with operational context awareness capabilities, achieving essential differentiation of leak events while ensuring high detection sensitivity, has become the technical problem to be solved by this invention. Summary of the Invention

[0004] This invention provides a method and system for monitoring hazardous gas leaks in laboratories. Its main purpose is to solve the core technical problem that existing monitoring systems lack the ability to judge operational context, making it impossible to distinguish between controlled releases and accidental leaks, resulting in a trade-off between false alarm rates and false alarm rates.

[0005] To achieve the above objectives, the present invention provides a method for monitoring hazardous gas leaks in a laboratory, the method comprising the following steps:

[0006] Equip laboratory items used for handling hazardous gases with electronic identification tags and deploy tag reading and writing devices in the handling areas of these items.

[0007] When the hazardous gas is used in the operation area, the tag reading and writing device automatically reads the identity information of the electronic identification tag and generates a temporary operation certificate with a predetermined validity period based on the identity information and the operation area information.

[0008] The gas concentration in the environment is monitored in real time by gas sensors, and the area where the gas sensors are located is obtained; when the gas concentration detected by any gas sensor exceeds the first concentration threshold, it is determined whether there is a valid temporary operation certificate that completely matches the area information of the gas sensor and the type of gas detected.

[0009] If a valid temporary operation certificate exists that perfectly matches the information of the gas sensor's location and the type of gas detected, the concentration increase will be determined as a normal operation, will not trigger a Level 1 warning, and the data will be recorded.

[0010] If there is no valid temporary operating certificate that perfectly matches the information of the gas sensor’s location and the type of gas detected, the concentration increase will be judged as an abnormal leak and a level one warning will be triggered.

[0011] Regardless of the existence of a valid temporary operating certificate, once any gas sensor detects a gas concentration higher than the second concentration threshold, and the second concentration threshold is higher than the first concentration threshold and defined as a high-risk concentration that poses an immediate threat to human health, the highest level alarm will be triggered immediately.

[0012] Preferably, after triggering a Level 1 warning, the method further includes the following steps: sending a wake-up command to at least one nearby gas sensor in a dormant state around the gas sensor that triggered the Level 1 warning; the woken nearby gas sensor performs a concentration measurement and returns a concentration reading; comparing the concentration reading of the gas sensor that triggered the Level 1 warning with the concentration reading of the woken nearby gas sensor, and when the ratio of the two is greater than a preset concentration gradient threshold, determining the source location of the abnormal leak or the reliability of the Level 1 warning.

[0013] Preferably, after triggering the Level 1 warning, before sending a wake-up command to the nearby gas sensor, the following steps are also included: real-time acquisition of physical state signals indicating a sudden change in the macroscopic airflow state in the laboratory; when the physical state signal indicates that the macroscopic airflow is in a sudden change state, within a predetermined time period, suspending the execution of the logic that triggers the Level 1 warning if there is no valid temporary operation certificate that completely matches the information of the gas sensor's location area and the detected gas type.

[0014] Preferably, the electronic identification tag is a passive UHF radio frequency identification electronic tag.

[0015] Preferably, when comparing the concentration reading of the gas sensor that triggered the first-level warning with the concentration reading of the nearby gas sensor that was awakened, if both concentration readings are lower than a preset verification threshold or the spatial distribution of the concentration readings does not meet the predetermined spatial gradient characteristics, the system temporarily suspends the alarm and enters a continuous observation mode.

[0016] Preferably, the method further includes the following steps: within a predetermined maintenance cycle, the instruction system actively releases a standardized dose of probe material near the target gas sensor; acquires the response data of the target gas sensor to the probe material, including the response time from receiving the probe material signal to the peak reading and the peak height; calculates the current performance status of the target gas sensor by comparing it with pre-stored benchmark response data, the performance status being the time delay deviation rate and sensitivity attenuation rate; and, based on the performance status, adjusts the first concentration threshold of the target gas sensor used to determine whether a valid temporary operating certificate exists using a preset compensation algorithm, or adjusts its weighting factor in near-field verification.

[0017] Preferably, the method further includes: recording the communication delay from receiving a wake-up command to returning a concentration measurement value from a nearby gas sensor; calculating the wireless communication interference intensity in the area where the nearby gas sensor is located based on the deviation, trend, and magnitude of the communication delay from a preset reference delay within a predetermined observation period, according to preset judgment rules, and generating a physical interference zone marker based on the interference intensity; when transmitting a first-level warning or the highest-level alarm information, prioritizing the selection of nodes in non-interference areas for information routing or instructing gas sensors located in the physical interference zone to increase the number of information retransmissions based on the physical interference zone marker.

[0018] Preferably, the generation of temporary operation credentials and the context decision of alarms are both executed by a lightweight edge computing gateway. The lightweight edge computing gateway integrates a rule engine, which judges and processes the temporary operation credentials and gas sensor data according to a preset set of logical rules, and outputs alarm decision instructions to control the execution of alarm logic.

[0019] A laboratory hazardous gas leak monitoring system, the system comprising:

[0020] The tag reading and writing device is used to automatically read the identity information of the electronic identification tag configured on the hazardous gas when the hazardous gas is used in the operation area;

[0021] A gas sensor is used to monitor the gas concentration in the environment in real time and acquire information about the area where the gas sensor is located; an edge computing gateway communicates with the tag reader / writer and the gas sensor, and the edge computing gateway includes:

[0022] The voucher generation module is used to generate temporary operation vouchers with a predetermined validity period based on identity information and item operation area information.

[0023] The concentration judgment module is used to determine whether there is a valid temporary operation certificate that completely matches the information of the area where the gas sensor is located and the type of gas detected when the gas concentration detected by any gas sensor exceeds the first concentration threshold.

[0024] The alarm decision module is used to determine that if there is a valid temporary operation certificate that perfectly matches the information of the gas sensor's location and the type of gas detected, the concentration increase is determined to be caused by normal operation, and no first-level warning is triggered, and the data is recorded; if there is no valid temporary operation certificate that perfectly matches the information of the gas sensor's location and the type of gas detected, the concentration increase is determined to be an abnormal leak, and a first-level warning is triggered; and regardless of whether there is a valid temporary operation certificate, once the gas concentration detected by any gas sensor is higher than the second concentration threshold, and the second concentration threshold is higher than the first concentration threshold and defined as a high-risk concentration that poses an immediate hazard to the human body, the highest level alarm is immediately triggered.

[0025] Compared with the prior art, the beneficial effects of the present invention are:

[0026] 1. When a gas sensor detects an abnormal concentration, the system first verifies whether there is a matching valid operation certificate in the area. If a certificate exists, it indicates that the gas originates from the currently authorized operation, and the system automatically classifies it as a safety event. If no matching certificate exists, it is determined to be an abnormal leak. This mechanism, based on dual verification of operation context and physical location, distinguishes between controlled release and accidental leakage in principle, avoiding the inherent contradiction between sensitivity and false alarm rate in traditional threshold alarms, and making it possible to accurately detect early trace leaks. After triggering a first-level warning, the system wakes up nearby dormant sensors to compare concentrations. By analyzing the concentration gradient relationship between the trigger point and nearby points, if the concentration at the trigger point is significantly higher than that at nearby points, the system can infer the location of the leak source and verify the effectiveness of the warning. This mechanism does not rely on complex diffusion models, but is based on the physical law of natural decay of gas concentration in space, and achieves preliminary location of the leak source and secondary filtering of false alarms with simple hardware coordination.

[0027] 2. When doors and windows are opened or forced ventilation is started, the reed switch marks the sudden airflow event in real time. The system then automatically enters the conservative monitoring mode: suspends the determination of unlicensed gases based on spatial logic, increases the gradient threshold of near-field verification, and strengthens data recording. This logic switching mechanism based on physical event triggering avoids misjudgment in the state of chaotic airflow. After the environment stabilizes, it seamlessly resumes the high-sensitivity mode, ensuring the robustness of decision-making under complex working conditions.

[0028] 3. The system periodically releases standardized detection substances, such as trace amounts of ethanol, into the target sensor. By analyzing the response time and peak value changes, the sensor delay deviation rate and sensitivity decay rate are derived. This implicit performance indicator is used in real time to dynamically compensate alarm thresholds or adjust sensor weights. This closed loop of active detection-state inversion-parameter correction enables the system to have self-maintenance capabilities and ensures the long-term effectiveness of the core monitoring logic. Attached Figure Description

[0029] Figure 1 This is a schematic diagram of the laboratory hazardous gas leakage monitoring method and system of the present invention;

[0030] Figure 2 This is a graph showing the change of the concentration gradient ratio R of chloroform leakage in the laboratory of this invention over time.

[0031] Figure 3 This is an interactive flowchart of the laboratory hazardous gas leak monitoring system of the present invention.

[0032] The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0033] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention are described in detail. Obviously, the described embodiments are only some embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of this invention.

[0034] This application discloses a laboratory hazardous gas leak monitoring method and system, whose overall architecture mainly consists of three core components operating in concert: first, electronic identification tags embedded in hazardous gas-related items and tag reading and writing devices deployed in specific item operation areas; second, a distributed gas sensor network deployed in the laboratory for real-time monitoring of ambient gas concentration; and third, a lightweight edge computing gateway responsible for data fusion and decision arbitration. The gateway communicates with the aforementioned tag reading and writing devices and gas sensors via wireless or wired means, and acts as the intelligent hub of the system, performing the generation of temporary operation credentials, contextual matching judgment of gas concentration and operation credentials, and the final decision logic for graded alarms.

[0035] In existing laboratory safety monitoring practices, a fundamental challenge lies in the inability to establish a direct logical correlation between environmental gas concentration signals and specific experimental operations. This limitation makes it difficult for monitoring systems to distinguish between controlled gas releases from normal experiments and accidental hazardous leaks, resulting in a trade-off between false alarm and false negative rates. To address this challenge, the core procedure of this invention begins by equipping each item used for hazardous gases, such as high-pressure gas cylinders or highly volatile reagent bottles, with a passive ultra-high frequency radio frequency identification (RFID) tag. This tag stores the item's globally unique identification information. Correspondingly, tag reading and writing devices are deployed in all areas where related material handling may occur, such as inside fume hoods, dedicated lab benches, or reagent weighing areas. When a hazardous gas item carrying an electronic identification tag is moved into the effective electromagnetic induction field of any item handling area, that area... The tag reading and writing device is activated, automatically completing the contactless reading of the electronic identity tag's identity information and immediately transmitting this identity information along with its own regional location information to the edge computing gateway. Upon receiving the data packet, the credential generation module within the edge computing gateway calculates and generates a temporary operation credential with a specific validity period based on a preset calculation model, taking into account the chemical type of the materials used for the hazardous gas, the environmental ventilation properties of the current operation area, and the established standard experimental procedure duration. The data structure of this credential includes at least the operation area information, the corresponding gas type, and a start and end timestamp. The establishment of this procedure ensures that any compliant experimental operation is digitally authorized and registered by the system at the beginning of the action, providing crucial contextual basis for subsequent interpretation of gas concentration signals, thus laying a solid foundation in principle for distinguishing between controlled release and accidental leakage.

[0036] In the generation of temporary operation vouchers, their predetermined validity period is... The determination is based on a linear weighted model. The results of the calculation, among which Defined as the baseline duration to ensure the minimum safe operating time, it is usually set at 60 seconds; The quantification coefficient characterizing the inherent risk of a type of hazardous gas is determined by consulting the toxicity classification and explosion limits of each gas in the hazardous chemicals catalogue, and then normalizing it to a range of 1 to 10 using a risk assessment matrix. For example, the value of the highly toxic gas hydrogen chloride... The value is 9, and it is a non-toxic, non-flammable gas called nitrogen. =1; To quantify the ventilation efficiency of the handling area, the value is determined by measuring the average face velocity (in meters per second) in different areas of the laboratory using an anemometer and combining this with testing the number of air changes per hour (in times per hour) using a tracer gas (e.g., sulfur hexafluoride). The combined result is then normalized to a range of 1 to 5. For example, inside a fume hood... 5. Ordinary open experimental platform It is 2; Defined as based on sensor performance degradation, through time delay deviation rate and sensitivity attenuation rate The calculated risk correction factor is derived from the following formula: ,in and For pre-defined weighting coefficients, such as ; These are the weighting factors for each item. They are determined through iterative solutions using a genetic algorithm within a large-scale simulation environment encompassing thousands of simulated scenarios (covering different gas types, ventilation conditions in operating areas, and sensor aging levels). The objective function is to minimize the false alarm rate and the false negative rate, with operational convenience as a constraint, to arrive at the optimal solution set. For example, in a specific laboratory environment... This procedure ensures that the generation of the validity period of the certificate has a clear quantitative basis and engineering adjustment process.

[0037] Given that authorized operating credentials alone are insufficient to address all security scenarios, the system must establish a robust logic capable of dynamically determining gas concentration signals to effectively filter environmental interference while ensuring high sensitivity. To this end, the gas sensors within the system, which can be electrochemical or semiconductor gas sensors, are configured to continuously monitor the gas concentration in their surrounding microenvironment in real time and transmit the concentration readings. The sensor periodically reports its own regional information to the edge computing gateway; the gateway's concentration judgment module processes these data streams in real time, and its built-in rule engine executes a dual threshold comparison logic: when the concentration value reported by any sensor... When the concentration first exceeds a preset lower threshold, the system does not immediately trigger an alarm. Instead, it first searches the certificate database for a temporary operation certificate that perfectly matches the sensor's location and the currently detected gas type, and whose timestamp is still within the valid window. If such a matching certificate is found, the alarm decision module classifies the concentration increase event as a normal operation and does not trigger a Level 1 warning, but only records and archives it as operation process data. Conversely, if no matching certificate is found, the event is initially classified as an abnormal leak and a Level 1 warning is immediately triggered. However, regardless of whether a valid temporary operation certificate exists, once the gas concentration detected by any gas sensor exceeds a certain threshold, the system will immediately issue an alarm. If the concentration exceeds a second concentration threshold, which is defined as a high-risk concentration that can cause immediate harm to the human body, the system will bypass all context judgment logic and directly trigger the highest level alarm to ensure a rapid response speed in extremely dangerous situations. Through this judgment mechanism based on the dynamic coupling of operation credentials and dual concentration thresholds, the system can accurately identify trace, slow early leaks in most scenarios, while exempting benign concentration fluctuations caused by normal experimental operations, thus improving the accuracy of alarms and the robustness of system decision-making.

[0038] Furthermore, after a Level 1 warning is triggered, to further confirm the authenticity of the leak and preliminarily locate the leak source, the system is configured to execute a proximity-based verification procedure. This procedure is designed to address false alarms that may occur from a single sensor due to its own malfunction or local airflow eddies. Simultaneously, while sending an alarm signal to the area triggering the Level 1 warning, the edge computing gateway sends a forced wake-up command to at least one nearby gas sensor in a dormant or low-power state. Upon receiving the command, the awakened nearby sensor immediately performs a high-precision concentration measurement and records the reading. The system then returns to the gateway; the system subsequently sends the initial alarm sensor concentration reading. Concentration readings from nearby sensors that were activated When comparing the two, the ratio of the two... When the concentration gradient exceeds a preset threshold based on a gas diffusion model, the source of the abnormal leak can be confirmed to be near the initial alarm sensor, thus confirming the effectiveness of the first-level warning. As a supplementary constraint to this procedure, if, during comparison, the concentration readings of both sensors are below a preset validity verification threshold, or the spatial distribution of their concentration readings does not meet the established spatial gradient characteristics (e.g., the concentration at neighboring points is higher), the system will temporarily suspend the alarm and enter a continuous observation mode to perform intensive monitoring of the area. This near-field gradient verification mechanism utilizes the physical law of natural diffusion and decay of gas in space, adding an effective false alarm filtering and leak location method to the system with low communication and computational overhead.

[0039] The concentration gradient threshold used in near-field gradient validation is set through a rigorous offline calibration procedure. This procedure involves precisely releasing a specific type of target gas at a known and stable rate (e.g., 0.01 L / min) within a target operating area equipped with gas sensors, using a miniature flow controller. Gas concentration readings are simultaneously recorded at an initial alarm sensor and at least one nearby dormant sensor. This process is repeated under various typical airflow patterns to collect a large amount of data. Ratio data; through statistical analysis of these experimental data, including plotting ROC curves to evaluate the true positive rate and false positive rate at different thresholds, the optimal ratio that can distinguish between local leakage and long-distance diffusion is finally determined. This ratio is set as the concentration gradient threshold for subsequent verification of the first-level warning by the system. For example, in the chloroform leakage scenario, this threshold is 3.5. When the macroscopic airflow physical state signal indicates a sudden change, the system dynamically adjusts the gradient threshold to 1.5 times the original value. This adjustment is maintained until the airflow returns to a stable state, determined by the physical state sensor signal remaining unchanged for 30 consecutive seconds. This dynamic adjustment strategy ensures the robustness of the system's decision-making under environmental disturbances.

[0040] Considering that in a laboratory environment, the sudden opening and closing of doors and windows or the start and stop of a forced ventilation system can cause severe disturbances in the macroscopic airflow, which can quickly lead to chaotic and disordered gas concentration distribution, thus interfering with the aforementioned judgment logic based on a stable diffusion model, the system also integrates an adaptive strategy for sudden airflow changes. This involves installing physical state sensors, such as reed switches, at key locations in the laboratory, such as door frames, window frames, and fume hood regulating valves, to instantly reflect their opening and closing states. These sensors acquire physical state signals indicating sudden changes in the macroscopic airflow state in real time. When the system receives such signals indicating a sudden change in the macroscopic airflow, its rule engine... Within a predetermined time period, such as 30 to 90 seconds, the system will automatically pause execution of its core logic, which triggers a level-one warning if no matching credentials are found. This is because during this period, the gas in a certain area may have been carried in by turbulence from normal operations at a distance. In this conservative monitoring mode, the system will correspondingly increase the gradient threshold used for near-field verification and strengthen the recording of concentration data at each point. Once the physical state signal returns to stability, the system will automatically and seamlessly switch back to the original high-sensitivity monitoring mode. This dynamic degradation and recovery mechanism based on decision-making logic triggered by physical events ensures the reliability of the system's decisions under complex operating conditions and avoids misjudgments caused by drastic environmental changes.

[0041] To maintain the long-term monitoring effectiveness and data reliability of the entire monitoring system, a closed-loop sensor self-diagnosis and compensation correction mechanism is built-in to combat the inevitable performance degradation of sensors due to long-term operation. During predetermined system maintenance cycles, such as the scheduled quarterly maintenance window, the system can automatically or under administrator command release a standardized dose of harmless detection substance near a target gas sensor via a miniature piezoelectric pump or electrically controlled valve. The system then accurately records and acquires the complete dynamic response data of the target sensor to this standard detection substance, with key indicators including the response time from receiving the detection substance signal to reaching the peak reading. and the final peak height By comparing these real-time measured data with the reference response data pre-stored at the sensor's factory or recorded during the last calibration, the system can calculate the sensor's current performance parameters, specifically the time delay deviation rate. and sensitivity attenuation rate These parameters are then input into a preset compensation algorithm, which dynamically adjusts the first concentration threshold used by the sensor for judgment based on the attenuation rate, or adjusts its weight factor in the near-field verification multi-point data fusion algorithm. This closed-loop workflow of active detection-state inversion-parameter correction enables the system to have self-maintenance capabilities, actively identify and quantify the performance drift of the core sensing element, and eliminate its adverse effects on monitoring accuracy through algorithm compensation, thereby ensuring the long-term stability and effectiveness of the core monitoring logic of the entire system.

[0042] The sensor's self-diagnosis and compensation correction mechanism relies on the system precisely releasing a standardized dose of the detection substance, such as 50 ppm ethanol gas (0.5 ml) to the vicinity of the target gas sensor via a miniature piezoelectric pump within a predetermined maintenance cycle, for example, once per quarter. This dose does not affect the laboratory environment and does not cause long-term damage to the sensor. The system accurately records the sensor's response time from receiving the detection substance signal to the peak reading. and final peak height These data were then compared with the baseline response time recorded by the sensor during initial installation. and benchmark peak height By comparing the results, the time delay deviation rate was calculated. and sensitivity attenuation rate Based on the calculated performance status, the system makes a compensatory adjustment to the first concentration threshold of the sensor, and the new threshold... ,in, This is a compensation coefficient, the value of which is determined experimentally to ensure that when the sensor sensitivity decreases... When the threshold is lowered accordingly. To maintain detection capabilities, for example, when If a threshold reduction is required... ,but Furthermore, the weighting factor of this sensor in near-field verification is also dynamically adjusted according to its performance degradation rate, specifically as follows: ,in For example, the weight decay coefficient. This closed-loop mechanism achieves continuous calibration of sensor performance through automated procedures, ensuring the long-term stability and accuracy of the monitoring system.

[0043] Finally, to ensure the system can reliably transmit critical alarm information even in complex electromagnetic environments, it is also configured to have passive sensing capabilities for wireless communication channel quality. During routine communication tasks such as waking up nearby sensors and transmitting data back, the system continuously records the complete communication delay of each nearby gas sensor node from receiving the wake-up command to successfully returning the concentration measurement value. By analyzing the deviation of this communication delay from a preset baseline delay within a predetermined observation period, its trend over time, and the short-term jitter amplitude, the system can, based on a set of preset judgment rules, inversely calculate the wireless communication interference intensity in the area where the nearby sensor is located, and... This generates dynamic physical interference zone markers. When the system needs to transmit high-priority Level 1 early warning or highest-level alarm information, its routing logic will actively query the marker map, prioritizing nodes in non-interference areas for information relay and routing, or directly instructing gas sensor nodes located in marked physical interference zones to actively increase the number of information retransmissions when sending alarm information until a confirmation acknowledgment is received from the upper layer. This mechanism transforms the byproduct data of communication latency into an effective insight into the network environment status and applies it to the reliability assurance strategy for critical information transmission, thereby further enhancing the overall system's survivability and execution capability in harsh environments.

[0044] Example 1: This example aims to deploy and simulate the aforementioned technical solution in a practical application scenario. Specifically, in a high-throughput drug development laboratory environment, multiple fume hoods are deployed side by side along the wall. Different researchers may conduct different chemical experiments in adjacent fume hoods simultaneously. This scenario poses a severe challenge to the gas monitoring system, namely, how to effectively detect weak and unexpected dangerous gas leaks without interfering with normal and authorized experiments. At a certain moment, Researcher A completes a predetermined operation in fume hood A and leaves a bottle of chloroform reagent with an electronic identification tag inside the hood. The predetermined temporary operation certificate expires on time after the operation. However, the valve of the reagent bottle has a minor defect and begins to leak chloroform gas at a slow rate. At the same time, Researcher B is in the adjacent fume hood B, using a bottle of ether reagent with the same electronic identification tag to perform a compliant operation. The system has generated a valid temporary ether operation certificate for Researcher B in the area of ​​fume hood B.

[0045] As time passed, the concentration of chloroform gas in fume hood A slowly accumulated and eventually exceeded the system's preset first concentration threshold. At this point, the gas sensor deployed in fume hood A reported this threshold-exceeding event to the edge computing gateway. Upon receiving the signal, the gateway's concentration judgment module immediately initiated the context decision procedure. It first searched the valid credential database to check if there was a valid temporary operation credential matching the location of fume hood A and the type of chloroform gas. The query result was no. Based on this judgment of exceeding the threshold without a credential, the alarm decision module characterized this event as an abnormal leak and triggered a level one warning. The execution of this procedure first transformed an indiscriminate physical concentration signal into a logical event with unauthorized attributes.

[0046] At the moment the Level 1 warning was triggered, the system collaboratively initiated the near-field gradient verification procedure. The edge computing gateway issued a wake-up command to the nearby gas sensors around fume hood A, including those located between fume hoods A and B. After being woken up, the readings of these nearby sensors were simultaneously affected by the trace amounts of chloroform leaked from fume hood A and the ether released during normal operation of fume hood B. However, when the system performed concentration gradient calculations, it was based on gas type, and it used the chloroform concentration reading from the sensor in fume hood A. Chloroform concentration readings from adjacent sensors Comparing the two, since the leak source is inside fume hood A, the ratio of the two is... The concentration gradient was much higher than the preset threshold, thus confirming the existence of a real, localized leak source in fume hood A. Meanwhile, the ether concentration increase event in fume hood B, due to the existence of a perfectly matching and valid temporary operating certificate, was consistently judged as normal operation by the system and did not generate any interference signals. This dynamic coupling of the temporary operating certificate mechanism and the near-field gradient verification mechanism allows the system to not only distinguish between authorized and unauthorized gas releases, but also to perform secondary verification of the authenticity and source of unauthorized signals through the concentration distribution characteristics of the physical space. This resolves the inherent contradiction between high sensitivity and high false alarm rate in traditional monitoring technologies.

[0047] Ultimately, instead of issuing a blanket or indiscriminate alarm, the system illuminated a red warning light on the control panel of fume hood A and sent a precise alarm message via the network to the laboratory safety administrator's terminal. This message clearly indicated the specific location of the leak, the type of gas, and the nature of the event, enabling safety personnel to intervene quickly and accurately. Meanwhile, the normal experimental workflow of researcher B in fume hood B remained unaffected, and the overall operational efficiency of the laboratory was maintained. This result demonstrates that the technical solution of this invention, by introducing the logical dimension of operational authorization, transforms the traditional gas concentration monitoring problem from a purely physical signal measurement problem into an abnormal behavior auditing problem based on the location-substance-time-authorization quadruple. This allows previously difficult-to-distinguish or mixed-up danger signals and background noise to be effectively decoupled and identified within the new judgment framework.

[0048] Example 2: To objectively verify the actual effectiveness of the technical solution of the present invention in distinguishing between real trace leaks and authorized operation interference under complex working conditions, a verification test described in this example was designed and executed. The purpose of the test is to quantitatively evaluate the accuracy and selectivity of the alarm decision of the system in parallel authorized and unauthorized gas release event scenarios with spatial proximity. This scenario directly corresponds to the most challenging false alarm and missed alarm risk points in practical applications.

[0049] The experiment was conducted in a sealed environment chamber with a volume of 15 cubic meters. The chamber contained two simulated object handling areas, 1.5 meters apart, labeled Area A and Area B. Each area was equipped with a tag reading / writing device and a high-precision electrochemical gas sensor for a specific gas type, denoted as sensor A and sensor B, respectively. With sensors Additionally, a similar adjacent gas sensor is deployed at the geometric center of both regions. Used for gradient verification; the entire system is uniformly controlled by a lightweight edge computing gateway; to ensure the engineering rationality of the experimental conditions, the setting of key parameters follows a rigorous decision-making logic chain. Taking the determination of the first concentration threshold as an example, its setting needs to balance the sensitivity of early detection with the stability against environmental noise. Its value is defined as a weighted sum of the sensor's inherent baseline noise and the short-term exposure limit of the target gas. Specifically, in this experiment, for chloroform gas, its short-term exposure limit is 10 ppm, the sensor baseline noise is 0.5 ppm, and a sensitivity factor is set. If the value is 0.15, then its first concentration threshold is determined to be... Similarly, the concentration gradient threshold used for near-field gradient verification is set to balance the accuracy of leak source location with the reliability of the verification process. After offline calibration, under the current sensor layout, it was confirmed that the minimum concentration ratio caused by local leakage is greater than 5.0. Therefore, a concentration gradient threshold with redundant fault tolerance space is set to 3.5.

[0050] The experiment proceeded in the following sequence: At all times, the background inside the environmental chamber is clean; At a specified time, an ether reagent bottle equipped with an electronic identification tag is placed in area B. The system immediately reads the tag and generates a temporary operation certificate valid for ether in area B for 5 minutes. Simultaneously, the system releases ether into area B at a stable rate via the mass flow controller, maintaining its concentration at the sensor level. The concentration quickly reaches and remains at approximately 50 ppm; At a specified time, an independent mass flow controller is activated in region A to simulate an undocumented and slow chloroform leak, with the leak rate precisely controlled so that the chloroform concentration reaches a threshold of 2.0 ppm after approximately 120 seconds. Throughout the process, the system continuously records readings from all sensors and the internal decision-making state of the edge computing gateway. At a certain time, the system captured a set of key state data that are typical and representative, as shown in Table 1.

[0051] Table 1: For System key status data table at the second.

[0052]

[0053] As shown in Table 1, in Seconds, sensor The chloroform reading of 2.1 ppm exceeded the first concentration threshold of 2.0 ppm for the first time. Because the system could not find a matching temporary operating certificate, it immediately classified the event as a Level 1 warning and triggered near-field gradient verification. Meanwhile, the ether event in area B, with a concentration as high as 51.3 ppm, was correctly identified as a normal operation by the system because it had a valid certificate, and no alarm interference occurred. Furthermore, the system compared... and The concentration gradient ratio was calculated from the chloroform readings. The value is 5.25, which is significantly greater than the preset concentration gradient threshold of 3.5. This confirms the locality and authenticity of the leak source at the physical level, and ultimately outputs a precise alarm decision for area A. The recorded data of this process shows that the inherent collaborative mechanism of this solution, namely the temporary operation certificate mechanism, firstly removes the interference of authorized operation from the logical level, enabling the system to focus on the unlicensed signal. Subsequently, the near-field gradient verification mechanism provides spatial dimension evidence for the unlicensed signal from the physical level.

[0054] Example 3: This example combines Figures 1 to 3 This paper describes the implementation of a method and system for monitoring hazardous gas leaks in a laboratory. Figure 1 At the on-site perception and interaction layer, hazardous gas items are equipped with electronic identification tags, and tag reading and writing devices are deployed in the operating area. When a hazardous gas item enters the operating area, the tag reading and writing device automatically reads the identification information of the electronic identification tag and transmits it to the edge computing gateway. Gas sensors monitor the ambient gas concentration in real time and obtain its location information, transmitting the concentration reading to the edge computing gateway. At the edge computing and decision-making layer, the concentration data acquisition module is responsible for acquiring sensor readings and location. The voucher generation module generates a time-sensitive temporary operation voucher based on the item's identification information and the operating area information. If a matching valid voucher exists, the module verifies the context of the operation authorization. If yes, it is determined to be a normal operation, the data is recorded, and no warning is issued; otherwise, a level one warning is triggered. The system detects an abnormal leak and determines that the concentration exceeds the first threshold. Regardless of valid evidence, once the concentration exceeds the second threshold (high-risk concentration), the system will immediately trigger the highest-level alarm to ensure immediate response at high-risk concentrations. Furthermore, the system includes a closed-loop self-diagnosis and compensation correction mechanism. This mechanism actively detects and corrects sensor performance degradation and dynamically compensates for the first concentration threshold / adjusts the weights. In the system response and adaptation layer, after triggering the first-level warning, the system enters the near-field gradient verification stage, waking up nearby sensors to compare concentrations and locate the source. Subsequently, it checks if the gradient exceeds the threshold to verify the authenticity and locality of the leak. If so, the leak source is confirmed, an alarm is triggered, and the precise location is sent. If not, the alarm is temporarily suspended, and the system enters continuous observation mode.

[0055] like Figure 2The graph shows the trend of the concentration gradient ratio R over time (seconds), where the horizontal axis represents time (from 160 seconds to 200 seconds) and the vertical axis represents the concentration gradient ratio. The solid line in the graph represents the real-time measured value of the concentration gradient ratio R, while the dashed line represents the preset gradient threshold (3.5). During the experiment, the chloroform leak started at T=60 seconds and reached the first concentration threshold of 2.0 ppm after about 120 seconds (i.e., around T=180 seconds). At T=185 seconds, the chloroform reading of sensor SA reached 2.1 ppm, triggering near-field gradient verification and calculating the concentration gradient ratio R to be 5.25. As can be seen from the graph, starting from about 170 seconds, the concentration gradient ratio R gradually increased and exceeded the gradient threshold of 3.5, reaching 5.25 at T=185 seconds, which is clearly greater than the preset threshold, thus confirming the locality and authenticity of the leak source.

[0056] like Figure 3 First, the operator moves items with RFID tags into the operating area. The RFID tag sends its ID (gas type / chloroform) to the reader. After the reader identifies the tag in area B + chloroform, it transmits the information to the edge gateway. The edge gateway calculates the validity period (based on the gas cylinder type / ventilation level) and generates a certificate (valid for 300 seconds). This certificate information can be synchronized to the database. At the same time, gas sensors continuously monitor the gas concentration in the environment in parallel. When a concentration data (area B: chloroform 2.1ppm) is detected, it is transmitted to the edge gateway. The edge gateway verifies the certificate (area B + chloroform). If the certificate is valid, the operation log is recorded in the database. If the certificate is invalid, the edge gateway issues a level 1 warning (code E102) and requests neighbor verification. When an anomaly occurs, tag reading failure or certificate generation timeout may occur.

[0057] Example 4: In a semiconductor manufacturing laboratory where the monitoring system of this invention has been deployed and has been running continuously for more than twelve months, a specific gas sensor located in the etching area experienced irreversible chemical aging of its sensing element due to long-term exposure to trace amounts of corrosion products. This resulted in a slower response speed and decreased sensitivity. This gradual performance degradation poses a hidden risk to the reliability of the monitoring system. If not corrected, it may lead to a de facto increase in the detection threshold for slow leaks, or distorted spatiotemporal data output due to response delay during near-field gradient verification, thereby causing missed detections or false alarms.

[0058] To address systemic risks caused by hardware aging, the invention incorporates a closed-loop self-diagnostic mechanism activated during a predetermined maintenance cycle of the sensor. The system instructs a calibration unit located near the sensor to precisely release a standardized dose of probe material and begin recording the sensor's response curve. The system extracts two key performance indicators from the response curve: the response time from signal reception to peak reading. and peak height The edge computing gateway then retrieves the reference response time from its stored initial calibration database of the sensor. Compared with the benchmark peak height And perform a quantitative evaluation of the performance status according to the following procedures: First, calculate the delay deviation rate. Secondly, calculate the sensitivity attenuation rate. These two dimensionless parameters objectively describe the degree to which the sensor's current performance deviates from its ideal state.

[0059] Based on the calculated performance status parameters, a compensation algorithm within the edge computing gateway is triggered to adaptively adjust the monitoring logic of the sensor. This compensation algorithm includes a set of preset rules, one of which is based on the sensitivity attenuation rate. If the concentration exceeds a preset threshold of 20%, the system will correspondingly reduce the weighting factor of this sensor in any future multi-point collaborative analysis, such as near-field gradient verification, to reduce the interference of its poor data on the overall decision-making. Secondly, the system will dynamically compensate for the sensor's first concentration threshold, based on a sensitivity decay rate. The relevant compensation function, i.e., the new threshold, is set as the first concentration threshold. ,in A pre-calibrated compensation coefficient is used to moderately reduce the alarm threshold of aging sensors to offset the loss of detection capability caused by decreased sensitivity. This complete closed loop of active detection, state inversion, and parameter correction enables the system to autonomously identify and adapt to the performance evolution of its physical layer hardware, thereby maintaining the long-term effectiveness of the monitoring logic.

[0060] Furthermore, the aforementioned pre-defined computational model for generating temporary operation credentials can, in its specific implementation, also integrate sensor health status information for risk adjustment; specifically, the predetermined validity period of the temporary operation credentials... It can be determined by a linear weighted model, i.e. ;in, and These are quantitative coefficients characterizing the gas hazard level and the ventilation conditions of the operating area, respectively. This is based on the health status of the sensors in that area, i.e., based on... and The calculated risk correction factor, and , , These are the weighting factors for each item; thus, the worse the sensor health status of a region, the higher its risk correction factor. The larger the value, the shorter the validity period of the generated temporary operation certificate. This forces operations to be carried out under stricter time monitoring, thereby compensating for the hardware aging effect from another dimension of risk management.

[0061] Example 5: When the monitoring system of this invention is first deployed in a new laboratory environment or after replacing any gas sensor therein, to ensure the baseline accuracy of all subsequent monitoring and diagnostic functions, the system is configured to first execute a set of pre-deployment calibration procedures. In this procedure, the system administrator places the system in a specific debugging mode through the maintenance interface and specifies the newly created sensors that need to be initialized one by one. For each specified target sensor, the edge computing gateway instructs its adjacent calibration unit to release a standardized dose of probe material and fully record the response time and peak height of the new sensor to this standard excitation. These two initial measurements are then stored in the gateway's database and associated with the sensor's unique identifier, serving as the baseline response time for performance degradation calculations during its subsequent lifecycle. Compared with the benchmark peak height The execution of this procedure establishes a digital profile of the initial health status for each individual sensing element, thereby providing a raw benchmark for accurate comparison and non-speculation for subsequent closed-loop self-diagnostic mechanisms.

[0062] Furthermore, to ensure that the calculation model used to generate the validity period of temporary operating certificates has an objective basis, the various quantitative coefficients it relies on were systematically constructed and filled through a series of offline calibration experiments before system deployment; specifically, the coefficients used to characterize the gas hazard level... It is a quantitative value calculated by releasing each target gas in a controlled standard environment and measuring multiple physicochemical parameters such as its diffusion rate and emission tendency, and then comprehensively calculating it through a risk assessment matrix; while the coefficient characterizing the properties of the operating area of ​​the item... This is a risk index assigned after standardized testing of the air exchange efficiency and airflow organization patterns of different types of fume hoods or isolation control boxes; ultimately, the various weighting factors in the model... , and The optimal balance between ensuring safety redundancy and maintaining operational convenience was determined through iterative optimization of algorithms in large-scale simulations covering thousands of different gases, regions, and sensor aging levels. This entire set of offline calibration and data filling procedures ensures that every parameter of the calculation model has its own physical or statistical source to support it, thereby guaranteeing the scientific nature and consistency of the system's decision-making in practical applications.

[0063] Example 6: When the monitoring system of this invention is first deployed in a new laboratory environment or after replacing any gas sensor therein, to ensure the baseline accuracy of all subsequent monitoring and diagnostic functions, the system is configured to first execute a set of pre-deployment calibration procedures. In this procedure, the system administrator places the system in a specific debugging mode through the maintenance interface and specifies the newly created sensors that need to be initialized one by one. For each specified target sensor, the edge computing gateway instructs its adjacent calibration unit to release a standardized dose of probe material and fully record the response time and peak height of the new sensor to this standard excitation. These two initial measurements are then stored in the gateway's database and associated with the sensor's unique identifier, serving as the baseline response time for performance degradation calculations during its subsequent lifecycle. Compared with the benchmark peak height The execution of this procedure establishes a digital profile of the initial health status of each individual sensing element, thereby providing a raw, non-speculated benchmark for accurate comparison in subsequent closed-loop self-diagnostic mechanisms.

[0064] Furthermore, to ensure that the calculation model used to generate the validity period of temporary operating certificates has an objective basis, the various quantitative coefficients it relies on were systematically constructed and filled through a series of offline calibration experiments before system deployment; specifically, the coefficients used to characterize the gas hazard level... It is a quantitative value calculated by releasing each target gas in a controlled standard environment and measuring multiple physicochemical parameters such as its diffusion rate and emission tendency, and then comprehensively calculating it through a risk assessment matrix; while the coefficient characterizing the properties of the operating area of ​​the item... This is a risk index assigned after standardized testing of the air exchange efficiency and airflow organization patterns of different types of fume hoods or isolation control boxes; ultimately, the various weighting factors in the model... , and The optimal balance between ensuring safety redundancy and maintaining operational convenience was determined through iterative optimization of algorithms in large-scale simulations covering thousands of different gases, regions, and sensor aging levels. This entire set of offline calibration and data filling procedures ensures that every parameter of the calculation model has its own physical or statistical source, thereby guaranteeing the scientific nature and consistency of the system's decision-making in practical applications. All of these are extended implementation methods known to those skilled in the art.

[0065] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0066] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for monitoring hazardous gas leaks in a laboratory, characterized in that, The method includes the following steps: Equip laboratory items used for handling hazardous gases with electronic identification tags and deploy tag reading and writing devices in the handling areas of these items. When the hazardous gas is used in the operation area, the tag reading and writing device automatically reads the identity information of the electronic identification tag and generates a temporary operation certificate with a predetermined validity period based on the identity information and the operation area information. The gas concentration in the environment is monitored in real time by gas sensors, and the area where the gas sensors are located is obtained; when the gas concentration detected by any gas sensor exceeds the first concentration threshold, it is determined whether there is a valid temporary operation certificate that completely matches the area information of the gas sensor and the type of gas detected. If a valid temporary operation certificate exists that perfectly matches the information of the gas sensor's location and the type of gas detected, the concentration increase will be determined as a normal operation, will not trigger a Level 1 warning, and the data will be recorded. If there is no valid temporary operating certificate that perfectly matches the information of the gas sensor’s location and the type of gas detected, the concentration increase will be judged as an abnormal leak and a level one warning will be triggered. Regardless of the existence of a valid temporary operating certificate, once any gas sensor detects a gas concentration higher than the second concentration threshold, and the second concentration threshold is higher than the first concentration threshold and defined as a high-risk concentration that poses an immediate threat to human health, the highest level alarm will be triggered immediately.

2. The laboratory hazardous gas leakage monitoring method according to claim 1, characterized in that, After triggering a Level 1 warning, the following steps are also included: sending a wake-up command to at least one nearby gas sensor that is in a dormant state around the gas sensor that triggered the Level 1 warning; the awakened nearby gas sensor performs a concentration measurement and returns a concentration reading; comparing the concentration reading of the gas sensor that triggered the Level 1 warning with the concentration reading of the awakened nearby gas sensor, and when the ratio of the two is greater than a preset concentration gradient threshold, determining the source location of the abnormal leak or the reliability of the Level 1 warning.

3. The laboratory hazardous gas leakage monitoring method according to claim 2, characterized in that, After triggering the Level 1 warning, before sending a wake-up command to the nearby gas sensors, the following steps are also included: real-time acquisition of physical state signals indicating a sudden change in the macroscopic airflow state in the laboratory; when the physical state signal indicates that the macroscopic airflow is in a sudden change state, within a predetermined time period, suspending the execution of the logic that triggers the Level 1 warning if there is no valid temporary operation certificate that completely matches the information of the gas sensor's location area and the type of gas detected.

4. The laboratory hazardous gas leakage monitoring method according to claim 1, characterized in that, The electronic identification tag is a passive UHF radio frequency identification electronic tag.

5. A method for monitoring laboratory hazardous gas leaks according to claim 2, characterized in that, When comparing the concentration reading of the gas sensor that triggered the first-level warning with the concentration reading of the nearby gas sensor that was awakened, if both concentration readings are lower than the preset verification threshold or the spatial distribution of the concentration readings does not meet the predetermined spatial gradient characteristics, the system will temporarily suspend the alarm and enter the continuous observation mode.

6. The laboratory hazardous gas leakage monitoring method according to claim 1, characterized in that, It also includes the following steps: Within a predetermined maintenance cycle, the command system actively releases a standardized dose of probe material near the target gas sensor; acquires the target gas sensor's response data to the probe material, including the response time from receiving the probe material signal to the peak reading and the peak height; calculates the current performance status of the target gas sensor by comparing it with pre-stored baseline response data, which includes the delay deviation rate and sensitivity attenuation rate; based on the performance status, adjusts the first concentration threshold used by the target gas sensor to determine the existence of a valid temporary operating certificate or adjusts its weighting factor in near-field verification using a preset compensation algorithm.

7. A method for monitoring laboratory hazardous gas leaks according to claim 2, characterized in that, The method also includes: recording the communication delay from receiving a wake-up command to returning a concentration measurement value from a nearby gas sensor; calculating the wireless communication interference intensity in the area where the nearby gas sensor is located based on the deviation, trend, and magnitude of the communication delay from the preset baseline delay within a predetermined observation period, according to preset judgment rules, and generating a physical interference zone marker based on the interference intensity; when transmitting first-level warning or highest-level alarm information, prioritizing the selection of nodes in non-interference areas for information routing or instructing gas sensors located in the physical interference zone to increase the number of information retransmissions based on the physical interference zone marker.

8. The laboratory hazardous gas leakage monitoring method according to claim 1, characterized in that, The generation of temporary operation credentials and the context decision-making of alarms are both executed by the lightweight edge computing gateway. The lightweight edge computing gateway integrates a rule engine, which judges and processes the temporary operation credentials and gas sensor data according to a preset set of logical rules, and outputs alarm decision instructions to control the execution of alarm logic.

9. A laboratory hazardous gas leak monitoring system, characterized in that, The system includes: The tag reading and writing device is used to automatically read the identity information of the electronic identification tag configured on the hazardous gas when the hazardous gas is used in the operation area; A gas sensor is used to monitor the gas concentration in the environment in real time and acquire information about the area where the gas sensor is located; an edge computing gateway communicates with the tag reader / writer and the gas sensor, and the edge computing gateway includes: The voucher generation module is used to generate temporary operation vouchers with a predetermined validity period based on identity information and item operation area information. The concentration judgment module is used to determine whether there is a valid temporary operation certificate that completely matches the information of the area where the gas sensor is located and the type of gas detected when the gas concentration detected by any gas sensor exceeds the first concentration threshold. The alarm decision module is used to determine that if there is a valid temporary operation certificate that perfectly matches the information of the gas sensor's location and the type of gas detected, the concentration increase is determined to be caused by normal operation, and no first-level warning is triggered, and the data is recorded; if there is no valid temporary operation certificate that perfectly matches the information of the gas sensor's location and the type of gas detected, the concentration increase is determined to be an abnormal leak, and a first-level warning is triggered; and regardless of whether there is a valid temporary operation certificate, once the gas concentration detected by any gas sensor is higher than the second concentration threshold, and the second concentration threshold is higher than the first concentration threshold and defined as a high-risk concentration that poses an immediate hazard to the human body, the highest level alarm is immediately triggered.

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