Gas detection alarm method and system

Abstract

The invention relates to the technical field of data analysis, in particular to a gas detection alarm method and system.The method comprises the steps that a gas detection device matrix is arranged, and to-be-detected gas concentration data is collected; acquiring abnormal parameters of the to-be-detected gas concentration data according to the to-be-detected gas concentration data acquired by each gas every time and all the to-be-detected gas concentration data, and acquiring a reference abnormal index by combining the gas detection device at the corresponding moment; comparing the gas concentration abnormal parameter with the reference abnormal index to obtain a gas concentration deviation parameter; acquiring a contrast factor according to the to-be-detected gas concentration data of the gas detection device adjacent to the gas detection device, and acquiring a credibility factor of the to-be-detected gas concentration data in combination with the to-be-detected gas concentration data; and according to the data abnormal parameter, the gas concentration deviation parameter and the credibility factor, obtaining an early warning parameter, and setting an early warning threshold value to detect and alarm the to-be-detected gas. According to the invention, the abnormal condition of the gas concentration can be more accurately judged.

Description

Technical Field

[0001] This invention relates to the field of data analysis technology, specifically to a gas detection alarm method and system. Background Technology

[0002] Pipeline gas leak detection and alarm systems are of paramount importance in oilfield surface engineering. They enable timely detection of leaks, preventing safety accidents and environmental pollution caused by gas leaks. A timely alarm system allows for rapid repair and emergency response, ensuring the safety of workers and the surrounding environment, and guaranteeing the normal operation and production of oilfield surface projects. Common gases requiring monitoring in oilfield surface engineering operations include methane, hydrogen sulfide, and carbon monoxide. These gases are toxic, and exceeding safe concentrations can harm workers' health. Therefore, pipeline gas leak detection and alarm systems play a crucial role in oilfield surface engineering.

[0003] Traditional gas detection devices issue warnings based on fixed gas concentration thresholds. However, temperature variations can affect the measurement accuracy of these devices. High temperatures decrease sensitivity because the movement of gas molecules accelerates, potentially affecting sensor accuracy and leading to lower-than-expected gas concentration readings. Low temperatures slow down chemical reactions within the detector, such as oxidation and reduction reactions, thus impacting sensitivity and response speed. Therefore, relying on fixed gas concentration thresholds for gas concentration detection and warnings is inaccurate. Summary of the Invention

[0004] This invention provides a gas detection alarm method and system to solve the problem of inaccurate gas concentration detection and early warning in the prior art using fixed gas concentration thresholds.

[0005] The gas detection alarm method and system of the present invention adopts the following technical solution: In a first aspect, the present invention provides a gas detection alarm method, the method comprising the following steps: Arrange a gas detection device matrix to collect the concentration data of the gas to be detected; Based on the gas concentration data acquired by each gas detection device each time and the total gas concentration data acquired by that gas detection device, abnormal parameters of the gas concentration data acquired by each gas detection device each time are obtained; based on the abnormal parameters of the gas concentration data acquired by each gas detection device at the same time, the benchmark abnormal index of the gas concentration acquired by each gas detection device at the corresponding time is obtained. The gas concentration deviation parameter is obtained based on the abnormal gas concentration parameter detected each time and the benchmark abnormality index corresponding to the gas concentration; the comparison factor corresponding to the gas concentration data collected by each gas detection device at each time is obtained based on the gas concentration data collected by the gas detection devices in the neighborhood of each gas detection device at each time; the confidence factor of each gas concentration data is obtained based on the difference between the gas concentration data collected by each gas detection device each time and its corresponding comparison factor. The warning parameters for each gas concentration to be detected are obtained based on the data anomaly parameters, gas concentration deviation parameters, and confidence factors corresponding to each gas concentration data; the gas to be detected is then alarmed based on the warning parameters and warning thresholds.

[0006] Furthermore, the specific method for obtaining the abnormal parameters of the gas concentration data acquired by each gas detection device each time, based on the gas concentration data acquired by each gas detection device each time and all gas concentration data acquired by that gas detection device, includes the following:

[0007] In the formula, This indicates an abnormal parameter in the concentration data of the z-th gas to be detected obtained by the c-th gas detection device. This represents the concentration data of the z-th gas to be detected obtained by the c-th gas detection device. This represents the concentration data of the i-th gas to be detected acquired by the c-th gas detection device, t represents the duration of gas concentration collection in days, and T represents the time interval between gas concentration collections in minutes. This indicates the number of times the concentration data of the gas to be detected is collected within the time range of collection duration t.

[0008] Furthermore, the specific method for obtaining the benchmark anomaly index of the gas concentration at the corresponding moment for each gas detection device based on the abnormal parameters of the gas concentration data obtained by each gas detection device at the same time is as follows:

[0009] In the formula, This represents the baseline anomaly index corresponding to the concentration of the z-th gas to be detected by the c-th gas detection device. This represents the abnormal parameter of the z-th gas concentration data obtained by j gas detection devices, and N represents the number of gas detection devices.

[0010] Furthermore, the specific method for obtaining the gas concentration deviation parameter based on each detected gas concentration anomaly parameter and the corresponding benchmark anomaly index includes:

[0011] In the formula, This represents the gas concentration deviation parameter corresponding to the z-th gas concentration of the c-th gas detection device. This represents the baseline anomaly index corresponding to the concentration of the z-th gas to be detected by the c-th gas detection device. This indicates an abnormal parameter in the concentration data of the z-th gas to be detected obtained by the c-th gas detection device. This means calculating the absolute value of the difference between the abnormal parameter corresponding to each gas concentration data collected by each gas detection device and the benchmark abnormal index corresponding to the gas concentration, and recording the maximum and minimum values ​​of the absolute value. Then, it calculates the absolute value of the difference between the abnormal parameter of the z-th gas concentration data of the c-th gas detection device and the benchmark abnormal index of the corresponding gas concentration, and maps the absolute value to the range of 0-1 according to the recorded maximum and minimum values.

[0012] Furthermore, the specific method for obtaining the comparison factor corresponding to the concentration data of the gas to be detected collected by each gas detection device at each moment based on the concentration data of the gas to be detected collected by the neighboring gas detection devices at each moment includes: Select a neighboring gas detection device and calculate the mean value of the gas concentration data collected by all neighboring gas detection devices in the z-th time for the c-th gas detection device. This mean value is denoted as the comparison factor corresponding to the z-th gas concentration data of the c-th gas detection device, and is denoted as . .

[0013] Furthermore, the specific method for obtaining the reliability factor of each gas concentration data based on the difference between the gas concentration data collected by each gas detection device each time and its corresponding comparison factor includes:

[0014] In the formula, This represents the confidence factor corresponding to the concentration of the z-th gas to be detected by the c-th gas detection device. This represents the comparison factor corresponding to the z-th concentration data of the gas to be detected by the c-th gas detection device. This represents the concentration data of the z-th gas to be detected obtained by the c-th gas detection device.

[0015] Furthermore, the specific method for obtaining the early warning parameter for each gas concentration based on the data anomaly parameter, gas concentration deviation parameter, and confidence factor corresponding to each gas concentration data to be detected includes:

[0016] In the formula, This represents the warning parameter corresponding to the concentration of the z-th gas to be detected by the c-th gas detection device. This indicates an abnormal parameter in the concentration data of the z-th gas to be detected obtained by the c-th gas detection device. This represents the gas concentration deviation parameter corresponding to the z-th gas concentration of the c-th gas detection device. This represents the confidence factor corresponding to the concentration of the z-th gas to be detected by the c-th gas detection device.

[0017] Furthermore, the specific method for detecting and alarming the gas to be detected based on the gas warning parameters and warning threshold is as follows: After each collection of gas concentration data, the gas detection device calculates the corresponding warning parameter and compares it with the warning threshold. When the warning parameter is greater than or equal to the warning threshold, the gas detection device issues a local voice alarm and uploads the abnormal information to the control room and mobile APP via wireless communication to display the alarm, notifying management personnel and maintenance technicians to handle the leak fault on site in a timely manner.

[0018] Furthermore, the specific method for selecting the neighborhood gas detection device is as follows: The neighboring gas detection device of a gas detection device refers to a 3*3 matrix with the spatial location of the gas detection device as the center, and each other gas detection device in the matrix is ​​denoted as a neighboring gas detection device.

[0019] Furthermore, the specific method for arranging the gas detection device matrix and collecting the concentration data of the gas to be detected includes: The gas detection device sensor matrix is ​​arranged according to the preset distance L and the number of gas detection devices N, and the gas concentration detected by each gas detection device in the matrix is ​​recorded and collected at preset time intervals T.

[0020] In a second aspect, the present invention provides a gas detection alarm system, comprising a gas detection device, an anomaly index calculation module, a reliability calculation module, and an alarm module. The data acquisition module is set up in a matrix in different areas to collect the concentration data of the gas to be detected in different areas. The anomaly index calculation module obtains the anomaly parameters of the gas concentration data obtained by each gas detection device each time based on the gas concentration data of the gas to be detected obtained by each gas detection device and all gas concentration data of the gas to be detected obtained by the gas detection device; and obtains the benchmark anomaly index of the gas concentration data of the gas to be detected obtained by each gas detection device at the corresponding time based on the anomaly parameters of the gas concentration data of the gas to be detected obtained by each gas detection device at the same time. The credibility calculation module obtains the gas concentration deviation parameter based on the gas concentration anomaly parameter detected each time and the benchmark anomaly index corresponding to the gas concentration; obtains the comparison factor corresponding to the gas concentration data collected by each gas detection device at each time based on the gas concentration data collected by the neighboring gas detection devices at each time; and obtains the credibility factor of each gas concentration data based on the difference between the gas concentration data collected by each gas detection device each time and its corresponding comparison factor. The alarm module obtains the early warning parameters for each gas concentration based on the data anomaly parameters, gas concentration deviation parameters, and confidence factors corresponding to each gas concentration data to be detected; and alarms are triggered for the gas to be detected based on the early warning parameters and early warning thresholds.

[0021] In a third aspect, a computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the gas detection alarm method described above.

[0022] In a fourth aspect, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described gas detection alarm method.

[0023] The beneficial effects of the technical solution of the present invention are: This invention provides a gas detection alarm method. By comparing the concentration data of the gas to be detected detected by each gas detection device with the trend of the concentration change of the gas to be detected in the environment, the degree of abnormality of the gas concentration is determined. Then, by combining the concentration changes of the gas to be detected by all gas detection devices in the environment to eliminate the influence of temperature on the measured concentration of the gas to be detected, and by comparing the gas concentration distribution measured by gas detection devices at different spatial locations based on the diffusion characteristics of the gas, the reliability of the gas concentration data is determined. A threshold is selected to comprehensively judge the abnormality of the gas concentration. This method can more accurately judge the abnormality of the gas concentration and can quickly take measures for repair and emergency treatment, ensuring the safety of personnel and the surrounding environment. Attached Figure Description To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a flowchart illustrating the steps of a gas detection alarm method according to an embodiment of the present invention. Detailed Implementation

[0025] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following detailed description, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a gas detection alarm method proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0026] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0027] The specific scheme of a gas detection alarm method provided by the present invention will be described in detail below with reference to the accompanying drawings.

[0028] Example 1 Please see Figure 1 This application describes the detection of carbon monoxide gas in detail, illustrating a flowchart of a gas detection alarm method according to an embodiment of the present invention. The method includes the following steps: Step S001: Arrange a matrix of gas detection devices and use the gas detection devices to collect carbon monoxide concentration data in different areas.

[0029] It should be noted that the gas detection devices are evenly distributed throughout the oilfield surface engineering operation area to facilitate monitoring personnel in quickly and accurately understanding the carbon monoxide gas concentration in different areas. A matrix arrangement clearly presents the gas concentration data at each detection point, enabling monitoring personnel to promptly identify anomalies and take appropriate measures to ensure the safety of personnel and equipment. Furthermore, the matrix arrangement improves the usability of the gas detection devices. Therefore, this step requires arranging the device matrix and collecting carbon monoxide gas concentration data from the devices sequentially, setting a time interval T = 1 minute, a data collection duration t = 1 day, a device spacing L = 50m, and a number of gas detection devices N = 100. This embodiment does not specifically limit the time interval T, the number of gas detection devices N, the spacing L, or the data collection duration t; the values ​​of T and L in other embodiments depend on the specific implementation.

[0030] Specifically, a gas detection sensor matrix is ​​arranged according to the preset distance L between gas detection devices and the number N of gas detection devices, and the gas concentration detected by each gas detection device in the matrix is ​​recorded and collected at preset time intervals T.

[0031] Step S002: Based on the carbon monoxide concentration data acquired by each gas detection device each time and all carbon monoxide concentration data acquired by that gas detection device, obtain the abnormal parameters of the carbon monoxide concentration data acquired by each gas detection device each time; based on the abnormal parameters of the carbon monoxide concentration data acquired by each gas detection device at the same time, obtain the benchmark abnormal index of the carbon monoxide concentration acquired by each gas detection device at the corresponding time.

[0032] It should be noted that the carbon monoxide concentration in the environment is relatively stable under normal circumstances. However, changes in temperature and carbon monoxide concentration can affect the carbon monoxide concentration detected by gas detection devices. During operation, if the carbon monoxide concentration detected by a gas detection device deviates more from the normal level, it indicates that the probability of carbon monoxide leakage in the area where the gas detection device is located is greater at that measurement moment.

[0033] Specifically, based on the carbon monoxide concentration data acquired by each gas detection device each time and all carbon monoxide concentration data acquired by that gas detection device, the formula for obtaining the abnormal parameter of the carbon monoxide concentration data acquired by each gas detection device each time is as follows:

[0034] In the formula, This indicates an abnormal parameter in the z-th carbon monoxide concentration data obtained by the c-th gas detection device. This represents the z-th carbon monoxide concentration data obtained by the c-th gas detection device. This represents the i-th carbon monoxide concentration data acquired by the c-th gas detection device, t represents the duration of carbon monoxide concentration collection in days, and T represents the time interval between carbon monoxide concentration collections in minutes. This indicates the number of times carbon monoxide concentration data was collected within the time range of collection duration t.

[0035] It should be noted that, according to the above method, abnormal parameters of each carbon monoxide concentration data obtained by each gas detection device can be obtained. The abnormal parameters are obtained based on the difference between each carbon monoxide concentration data and the average value of all carbon monoxide concentration data obtained by the corresponding gas detection device. If the abnormal parameter of the carbon monoxide concentration data is larger, it means that the difference between the carbon monoxide concentration data and the average value of all carbon monoxide concentration data obtained by the corresponding gas detection device is greater. In other words, the more the carbon monoxide concentration deviates from the general variation of carbon monoxide concentration in the area where the corresponding gas detection device is located, the greater the probability of the carbon monoxide concentration being abnormal.

[0036] It should be further noted that the deviation of the carbon monoxide concentration detected by the gas detection device from the general level may be due to the influence of temperature changes. If the temperature change causes the carbon monoxide concentration to deviate from the general variation of carbon monoxide concentration in the area where the gas detection device is located, the probability of the carbon monoxide concentration being abnormal is relatively low. This is because higher temperatures will cause the movement of gas molecules to accelerate, affecting the accuracy of the sensor. Therefore, this step needs to determine the degree to which each carbon monoxide concentration data is affected by temperature changes. The higher the degree to which the carbon monoxide concentration is affected by temperature changes, the lower the probability of the carbon monoxide data being abnormal.

[0037] Specifically, the formula for obtaining the baseline anomaly index of carbon monoxide concentration for each gas detection device at the corresponding time moment, based on the abnormal parameters of the carbon monoxide concentration data obtained by each gas detection device at the same time, is as follows:

[0038] In the formula, This represents the baseline anomaly index corresponding to the z-th carbon monoxide concentration of the c-th gas detection device. This represents the abnormal parameter of the z-th carbon monoxide concentration data obtained by j gas detection devices, and N represents the number of gas detection devices.

[0039] It should be noted that temperature changes have the same impact on carbon monoxide concentration, and the frequency of data collection by gas detection devices in the work area is the same. Therefore, this step uses the average distribution of abnormal parameters of carbon monoxide concentration data collected by each gas detection device at a certain data collection time as a benchmark to represent the degree to which carbon monoxide concentration is affected by temperature during the operation. The larger the abnormality index, the higher the corresponding collection time.

[0040] Step S003: Obtain the gas concentration deviation parameter based on the gas concentration anomaly parameter detected each time and the benchmark anomaly index corresponding to the gas concentration; obtain the comparison factor corresponding to the carbon monoxide concentration data collected by each gas detection device at each time based on the carbon monoxide concentration data collected by each gas detection device in the neighborhood at each time; obtain the confidence factor of each carbon monoxide concentration data based on the difference between the carbon monoxide concentration data collected by each gas detection device each time and its corresponding comparison factor.

[0041] It should be noted that if a gas detection device detects an abnormal gas concentration parameter that deviates more from its corresponding baseline abnormality index, it indicates that the carbon monoxide concentration deviates from the general variation of carbon monoxide concentration in the area where the gas detection device is located.

[0042] Specifically, the formula for obtaining the gas concentration deviation parameter based on each detected abnormal gas concentration parameter and the corresponding baseline abnormality index is as follows:

[0043] In the formula, This represents the gas concentration deviation parameter corresponding to the z-th carbon monoxide concentration of the c-th gas detection device. This represents the baseline anomaly index corresponding to the z-th carbon monoxide concentration of the c-th gas detection device. This indicates an abnormal parameter in the z-th carbon monoxide concentration data obtained by the c-th gas detection device. This means calculating the absolute value of the difference between the abnormal parameter corresponding to each carbon monoxide concentration data collected by each gas detection device and the benchmark abnormal index corresponding to that carbon monoxide concentration, and recording the maximum and minimum values ​​of the absolute value. Then, it calculates the absolute value of the difference between the abnormal parameter of the z-th carbon monoxide concentration data of the c-th gas detection device and the benchmark abnormal index of the corresponding carbon monoxide concentration, and maps this absolute value to the range of 0-1 according to the recorded range of the maximum and minimum values.

[0044] The above method is used to obtain the gas concentration deviation parameter corresponding to each carbon monoxide concentration data collected by each gas detection device. The larger the deviation parameter, the greater the probability that the carbon monoxide concentration deviates from the general variation of carbon monoxide concentration in the area where the gas detection device is located, and the greater the probability that the carbon monoxide concentration is abnormal.

[0045] It should be noted that gas molecules can move freely in the air and diffuse to other areas. If a gas detection device measures an abnormal carbon monoxide concentration while surrounding gas detection devices at the same time measure a relatively normal carbon monoxide concentration, it may be due to a malfunction of the device itself. In this case, the reliability of the abnormal carbon monoxide concentration measured by the gas detection device is low. Therefore, this step compares the carbon monoxide concentration data collected by each gas detection device with the carbon monoxide concentrations measured by the eight surrounding gas detection devices at the same time to obtain the reliability of each carbon monoxide concentration data.

[0046] Specifically, the comparison factor corresponding to the carbon monoxide concentration data collected by each gas detection device at each time moment is obtained based on the carbon monoxide concentration data collected by neighboring gas detection devices at each time moment. The specific method is as follows: Select a neighboring gas detection device and calculate the mean of the carbon monoxide concentration data collected by all neighboring gas detection devices in the z-th time for the c-th gas detection device. This mean is denoted as the comparison factor corresponding to the z-th carbon monoxide concentration data of the c-th gas detection device, and is further denoted as [missing information]. .

[0047] It should be noted that the neighboring gas detection device of a gas detection device refers to a 3*3 matrix with the spatial location of the gas detection device as the center, and each other gas detection device in the matrix is ​​denoted as a neighboring gas detection device.

[0048] Furthermore, the reliability factor for each carbon monoxide concentration data is obtained based on the difference between the carbon monoxide concentration data collected by each gas detection device and its corresponding comparison factor. The specific formula is as follows:

[0049] In the formula, This represents the confidence factor corresponding to the z-th carbon monoxide concentration of the c-th gas detection device. This represents the comparison factor corresponding to the z-th carbon monoxide concentration data from the c-th gas detection device. This represents the z-th carbon monoxide concentration data obtained by the c-th gas detection device.

[0050] It should be noted that the greater the difference between the carbon monoxide concentration and the corresponding comparison factor, the greater the difference between the carbon monoxide concentration and the neighboring carbon monoxide concentration. Since gases are diffusive, the carbon monoxide concentration is generally similar to the neighboring carbon monoxide concentration. The greater the difference, the greater the probability of equipment malfunction. In this case, the reliability of the carbon monoxide concentration data is low, that is, the reliability factor is small. The reliability factor of each carbon monoxide concentration data is obtained according to the above method.

[0051] Step S004: Obtain each carbon monoxide concentration warning parameter based on the data anomaly parameter, gas concentration deviation parameter, and confidence factor corresponding to each carbon monoxide concentration data; issue a carbon monoxide detection alarm based on the carbon monoxide warning parameter and warning threshold.

[0052] It should be noted that the above process obtains the data anomaly parameters, gas concentration deviation parameters, and confidence factors corresponding to each carbon monoxide concentration data, and can obtain carbon monoxide early warning parameters.

[0053] Specifically, the formula for obtaining the early warning parameter for each carbon monoxide concentration based on the data anomaly parameter, gas concentration deviation parameter, and confidence factor corresponding to each carbon monoxide concentration data is as follows:

[0054] In the formula, This represents the warning parameter corresponding to the z-th carbon monoxide concentration of the c-th gas detection device. This indicates an abnormal parameter in the z-th carbon monoxide concentration data obtained by the c-th gas detection device. This represents the gas concentration deviation parameter corresponding to the z-th carbon monoxide concentration of the c-th gas detection device. This represents the confidence factor corresponding to the z-th carbon monoxide concentration of the c-th gas detection device.

[0055] It should be noted that the larger the abnormal parameter of carbon monoxide concentration data, the greater the probability of carbon monoxide concentration abnormality. The larger the gas concentration deviation parameter corresponding to the carbon monoxide concentration, the greater the deviation of the carbon monoxide concentration from the general variation of carbon monoxide concentration in the area where the gas detection device is located. The greater the probability of carbon monoxide concentration abnormality, the larger the confidence factor, the smaller the probability that the data abnormality is affected by the gas detection device abnormality, and the higher the confidence of the data abnormality. Therefore, the larger the data abnormality parameter, gas concentration deviation parameter and confidence factor corresponding to carbon monoxide concentration data, the higher the degree of data abnormality and the larger the carbon monoxide warning parameter.

[0056] It should be further noted that carbon monoxide concentration warnings require selecting a warning parameter as a threshold and comparing it with each measured carbon monoxide warning parameter to determine the appropriate threshold. This implementation does not impose specific limitations on the value of the warning threshold; the value of the warning threshold depends on the implementation situation.

[0057] Specifically, the method for issuing a carbon monoxide detection alarm based on carbon monoxide warning parameters and warning thresholds is as follows: After each collection of carbon monoxide concentration data, the gas detection device calculates the corresponding warning parameter and compares it with the warning threshold. When the warning parameter is greater than or equal to the warning threshold, the gas detection device issues a local voice alarm and uploads the abnormal information to the control room and mobile APP via wireless communication to display the alarm, notifying management personnel and maintenance technicians to handle the leak fault on site in a timely manner.

[0058] This invention determines the degree of carbon monoxide concentration anomaly by comparing the carbon monoxide concentration data detected by each gas detection device with the trend of carbon monoxide concentration changes in the environment. It then combines the carbon monoxide concentration changes of all gas detection devices in the environment to eliminate the influence of temperature on the measured carbon monoxide concentration. Based on the diffusion characteristics of the gas, it compares the gas concentration distribution measured by gas detection devices at different spatial locations to determine the reliability of the gas concentration data. By selecting a threshold to comprehensively judge the abnormal situation of carbon monoxide concentration, it can more accurately judge the abnormal situation of gas concentration, and take rapid measures for repair and emergency treatment to ensure the safety of personnel and the surrounding environment.

[0059] In another embodiment of the present invention, a gas detection alarm system is provided, including a gas detection device, an anomaly index calculation module, a reliability calculation module and an alarm module; The data acquisition module is set up in a matrix in different areas to collect the concentration data of the gas to be detected in different areas. The anomaly index calculation module obtains the anomaly parameters of the gas concentration data obtained by each gas detection device each time based on the gas concentration data of the gas to be detected obtained by each gas detection device and all gas concentration data of the gas to be detected obtained by the gas detection device; and obtains the benchmark anomaly index of the gas concentration data of the gas to be detected obtained by each gas detection device at the corresponding time based on the anomaly parameters of the gas concentration data of the gas to be detected obtained by each gas detection device at the same time. The credibility calculation module obtains the gas concentration deviation parameter based on the gas concentration anomaly parameter detected each time and the benchmark anomaly index corresponding to the gas concentration; obtains the comparison factor corresponding to the gas concentration data collected by each gas detection device at each time based on the gas concentration data collected by the neighboring gas detection devices at each time; and obtains the credibility factor of each gas concentration data based on the difference between the gas concentration data collected by each gas detection device each time and its corresponding comparison factor. The alarm module obtains the early warning parameters for each gas concentration based on the data anomaly parameters, gas concentration deviation parameters, and confidence factors corresponding to each gas concentration data to be detected; and alarms are triggered for the gas to be detected based on the early warning parameters and early warning thresholds.

[0060] In another embodiment of the present invention, a terminal device is provided, comprising a processor and a memory. The memory stores a computer program, the computer program including program instructions, and the processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), or field-programmable gate arrays (FPGAs). Gate Array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc., are the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions to realize corresponding method flows or corresponding functions; the processor described in this embodiment of the invention can be used for the operation of a gas detection alarm method, including the following steps: acquiring gas concentration data to be detected in different areas; acquiring abnormal parameters of the gas concentration data to be detected acquired by each gas detection device each time based on the gas concentration data to be detected acquired by each gas detection device and all gas concentration data to be detected acquired by that gas detection device each time; acquiring the abnormal parameters of the gas concentration data to be detected acquired by each gas detection device at the same time to obtain the corresponding parameters of the gas concentration data to be detected acquired by each gas detection device at the same time. Each gas detection device acquires a baseline anomaly index for the gas concentration to be detected at any given time; based on the gas concentration anomaly parameter detected each time and the corresponding baseline anomaly index, a gas concentration deviation parameter is acquired; based on the gas concentration data collected by neighboring gas detection devices at each time, a comparison factor corresponding to the gas concentration data collected by each gas detection device at each time is acquired; based on the difference between the gas concentration data collected by each gas detection device each time and its corresponding comparison factor, a reliability factor for each gas concentration data to be detected is acquired; based on the data anomaly parameter, gas concentration deviation parameter, and reliability factor corresponding to each gas concentration data to be detected, a warning parameter for each gas concentration to be detected is acquired; and an alarm is triggered for the gas to be detected based on the warning parameter and warning threshold.

[0061] In another embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory). This computer-readable storage medium is a memory device in a terminal device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and extended storage media supported by the terminal device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device.

[0062] One or more instructions stored in the computer-readable storage medium can be loaded and executed by the processor to implement the corresponding steps of the gas detection alarm method in the above embodiments; one or more instructions in the computer-readable storage medium are loaded by the processor and executed as follows: acquiring gas concentration data of different regions; acquiring abnormal parameters of gas concentration data acquired by each gas detection device each time based on the gas concentration data acquired by each gas detection device and all gas concentration data acquired by the gas detection device; acquiring the benchmark abnormal index of gas concentration acquired by each gas detection device at the corresponding time based on the abnormal parameters of gas concentration data acquired by each gas detection device at the same time. The gas concentration deviation parameter is obtained based on the abnormal gas concentration parameters detected each time and the corresponding benchmark abnormality index; the comparison factor corresponding to the gas concentration data collected by each gas detection device at each time moment is obtained based on the gas concentration data collected by each gas detection device in the vicinity of each gas detection device at each time moment; the confidence factor of each gas concentration data is obtained based on the difference between the gas concentration data collected by each gas detection device each time and its corresponding comparison factor; the warning parameter of each gas concentration is obtained based on the data abnormality parameter, gas concentration deviation parameter and confidence factor corresponding to each gas concentration data; and the gas detection alarm is triggered based on the gas detection warning parameter and the warning threshold.

[0063] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0064] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0065] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0066] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0067] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A gas detection alarm method, characterized in that, The method includes the following steps: A gas detection device with a matrix configuration collects concentration data of the gas to be detected in different areas. Based on the gas concentration data acquired by each gas detection device each time and the total gas concentration data acquired by that gas detection device, abnormal parameters of the gas concentration data acquired by each gas detection device each time are obtained; based on the abnormal parameters of the gas concentration data acquired by each gas detection device at the same time, the benchmark abnormal index of the gas concentration acquired by each gas detection device at the corresponding time is obtained. The gas concentration deviation parameter is obtained based on the abnormal gas concentration parameter detected each time and the benchmark abnormality index corresponding to the gas concentration; the comparison factor corresponding to the gas concentration data collected by each gas detection device at each time is obtained based on the gas concentration data collected by the gas detection devices in the neighborhood of each gas detection device at each time; the confidence factor of each gas concentration data is obtained based on the difference between the gas concentration data collected by each gas detection device each time and its corresponding comparison factor. The warning parameters for each gas concentration to be detected are obtained based on the data anomaly parameters, gas concentration deviation parameters, and confidence factors corresponding to each gas concentration data; the gas to be detected is then alarmed based on the warning parameters and warning thresholds.

2. The gas detection alarm method according to claim 1, characterized in that, The specific method for obtaining abnormal parameters of the gas concentration data acquired by each gas detection device each time, based on the gas concentration data acquired by each gas detection device each time and all gas concentration data acquired by that gas detection device, includes the following: In the formula, This indicates an abnormal parameter in the concentration data of the z-th gas to be detected obtained by the c-th gas detection device. This represents the concentration data of the z-th gas to be detected obtained by the c-th gas detection device. This represents the concentration data of the i-th gas to be detected acquired by the c-th gas detection device, t represents the duration of gas concentration collection in days, and T represents the time interval between gas concentration collections in minutes. This indicates the number of times the concentration data of the gas to be detected is collected within the time range of collection duration t.

3. The gas detection alarm method according to claim 1, characterized in that, The method for obtaining the baseline anomaly index of the gas concentration at a corresponding moment for each gas detection device based on the abnormal parameters of the gas concentration data obtained by each gas detection device at the same time is as follows: In the formula, This represents the baseline anomaly index corresponding to the concentration of the z-th gas to be detected by the c-th gas detection device. This represents the abnormal parameter of the z-th gas concentration data obtained by j gas detection devices, and N represents the number of gas detection devices.

4. The gas detection alarm method according to claim 1, characterized in that, The specific method for obtaining the gas concentration deviation parameter based on each detected gas concentration anomaly parameter and the corresponding benchmark anomaly index is as follows: In the formula, This represents the gas concentration deviation parameter corresponding to the z-th gas concentration of the c-th gas detection device. This represents the baseline anomaly index corresponding to the concentration of the z-th gas to be detected by the c-th gas detection device. This indicates an abnormal parameter in the concentration data of the z-th gas to be detected obtained by the c-th gas detection device. This means calculating the absolute value of the difference between the abnormal parameter corresponding to each gas concentration data collected by each gas detection device and the benchmark abnormal index corresponding to the gas concentration, and recording the maximum and minimum values ​​of the absolute value. Then, it calculates the absolute value of the difference between the abnormal parameter of the z-th gas concentration data of the c-th gas detection device and the benchmark abnormal index of the corresponding gas concentration, and maps the absolute value to the range of 0-1 according to the recorded maximum and minimum values.

5. The gas detection alarm method according to claim 1, characterized in that, The specific method for obtaining the comparison factor corresponding to the gas concentration data collected by each gas detection device at each moment based on the gas concentration data collected by the neighboring gas detection devices at each moment is as follows: Select a neighboring gas detection device and calculate the mean value of the gas concentration data collected by all neighboring gas detection devices in the z-th time for the c-th gas detection device. This mean value is denoted as the comparison factor corresponding to the z-th gas concentration data of the c-th gas detection device, and is denoted as . .

6. The gas detection alarm method according to claim 1, characterized in that, The method for obtaining the reliability factor of each gas concentration data based on the difference between the gas concentration data collected by each gas detection device each time and its corresponding comparison factor includes the following specific methods: In the formula, This represents the confidence factor corresponding to the concentration of the z-th gas to be detected by the c-th gas detection device. This represents the comparison factor corresponding to the z-th concentration data of the gas to be detected by the c-th gas detection device. This represents the concentration data of the z-th gas to be detected obtained by the c-th gas detection device.

7. The gas detection alarm method according to claim 1, characterized in that, The specific method for obtaining the early warning parameter for each gas concentration based on the data anomaly parameter, gas concentration deviation parameter, and confidence factor corresponding to each gas concentration data to be detected includes: In the formula, This represents the warning parameter corresponding to the concentration of the z-th gas to be detected by the c-th gas detection device. This indicates an abnormal parameter in the concentration data of the z-th gas to be detected obtained by the c-th gas detection device. This represents the gas concentration deviation parameter corresponding to the z-th gas concentration of the c-th gas detection device. This represents the confidence factor corresponding to the concentration of the z-th gas to be detected by the c-th gas detection device.

8. The gas detection alarm method according to claim 1, characterized in that, The specific method for detecting and alarming the gas to be detected based on the gas's warning parameters and warning threshold is as follows: After each collection of gas concentration data, the gas detection device calculates the corresponding warning parameter and compares it with the warning threshold. When the warning parameter is greater than or equal to the warning threshold, the gas detection device issues a local voice alarm and uploads the abnormal information to the control room and mobile APP via wireless communication to display the alarm, notifying management personnel and maintenance technicians to handle the leak fault on site in a timely manner.

9. The gas detection alarm method according to claim 5, characterized in that, The specific method for selecting the neighborhood gas detection device is as follows: The neighboring gas detection device of a gas detection device refers to a 3*3 matrix with the spatial location of the gas detection device as the center, and each other gas detection device in the matrix is ​​denoted as a neighboring gas detection device.

10. A gas detection alarm system, characterized in that, It includes a gas detection device, an anomaly index calculation module, a reliability calculation module, and an alarm module; The data acquisition module is set up in a matrix in different areas to collect the concentration data of the gas to be detected in different areas. The anomaly index calculation module obtains the anomaly parameters of the gas concentration data obtained by each gas detection device each time based on the gas concentration data of the gas to be detected obtained by each gas detection device and all gas concentration data of the gas to be detected obtained by the gas detection device; and obtains the benchmark anomaly index of the gas concentration data of the gas to be detected obtained by each gas detection device at the corresponding time based on the anomaly parameters of the gas concentration data of the gas to be detected obtained by each gas detection device at the same time. The credibility calculation module obtains the gas concentration deviation parameter based on the gas concentration anomaly parameter detected each time and the benchmark anomaly index corresponding to the gas concentration; obtains the comparison factor corresponding to the gas concentration data collected by each gas detection device at each time based on the gas concentration data collected by the neighboring gas detection devices at each time; and obtains the credibility factor of each gas concentration data based on the difference between the gas concentration data collected by each gas detection device each time and its corresponding comparison factor. The alarm module obtains the early warning parameters for each gas concentration based on the data anomaly parameters, gas concentration deviation parameters, and confidence factors corresponding to each gas concentration data to be detected; and alarms are triggered for the gas to be detected based on the early warning parameters and early warning thresholds.

11. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the gas detection alarm method as described in any one of claims 1 to 9.

12. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the gas detection alarm method as described in any one of claims 1 to 9.

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