Combustible gas detection alarm method and system

Abstract

The invention relates to the technical field of alarm detection, in particular to a combustible gas detection alarm method and system. The method comprises the following steps: acquiring a preset neighborhood of each data point in a gas data segment acquired every day, and taking gas data in other gas data segments in the same acquisition time period as the preset neighborhood of the data point as a reference segment of the data point; calculating the closeness between the data point and each reference section; normalizing the product of the median of the closeness between the data point and each reference section and the cumulative sum of the closeness to obtain the credibility of the gas data in the preset neighborhood of the data point; obtaining the outlier degree of each data point through an ABOD algorithm, and normalizing the ratio of the outlier degree of the data point to the credibility of the gas data in the preset neighborhood as the correction dispersion of the data point; through the comparison result of the correction dispersion of the data points and the preset threshold value, combustible gas detection alarm is realized, and the accuracy of combustible gas detection alarm is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of alarm detection, and in particular to a combustible gas detection alarm method and system. Background Art

[0002] As a clean and efficient energy source, natural gas can be used in daily household cooking, hot water supply, etc. due to its environmental and economic characteristics. At the same time, natural gas is also flammable and explosive. Once it leaks in large quantities and encounters open flames or static sparks, it may cause fires or even explosions, affecting the safety of residents' lives.

[0003] In order to reduce hidden dangers and improve the safety of residents' lives, the prior art provides a variety of gas warning methods. For example, the patent application document with publication number CN118314701A discloses a gas safety monitoring and early warning device and method. The application includes a monitoring and early warning device, specifically including a gas detector, a safety shut-off valve, a sensor network, a communication channel, an intelligent gateway and a data master station; an alarm threshold is generated through an abnormal gas usage model, so as to analyze and evaluate the gas usage of each application scenario and monitor abnormalities; the gas transmission and distribution network fault point is located through the pipeline monitoring model and the alarm threshold, and the management personnel are displayed and warned.

[0004] The above-mentioned existing technology identifies abnormal gas data and issues early warnings through pipeline monitoring models and warning thresholds. However, gas data may fluctuate during daily gas use. If abnormal data is directly identified based on the warning threshold, false alarms or underreporting may occur, reducing the accuracy of combustible gas detection alarms.

[0005] Based on this, how to accurately implement combustible gas detection alarm is a problem that needs to be solved urgently by technical personnel in this field. Summary of the invention

[0006] In order to solve the technical problem of how to accurately implement combustible gas detection alarm, the present invention provides a combustible gas detection alarm method and system.

[0007] In a first aspect, the present invention provides a combustible gas detection alarm method, which adopts the following technical solution: The combustible gas detection alarm method comprises the following steps: Get the preset neighborhood of each data point in the gas data segment collected every day, and use the gas data in other gas data segments that are in the same collection time period as the preset neighborhood of the data point as the reference segment of the data point; obtain the proximity between the data point and each reference segment through the difference in the fitting value between the preset neighborhood of the data point and each reference segment: ; For the Data point and The proximity between the reference segments, , Respectively The preset neighborhood of the data point, The fitting function of the reference segment, , Respectively The initial collection time and the end collection time of the preset neighborhood of the data point, , Respectively The initial acquisition time and the end acquisition time of each reference segment, , Respectively The preset neighborhood of the data point, The range of the reference segment, is the absolute value; the product of the median of the proximity between the data point and each reference segment and the cumulative sum of the proximity is normalized to obtain the credibility of the gas data in the preset neighborhood of the data point; the outlier of each data point is obtained by the ABOD algorithm, and the ratio of the outlier of the data point to the credibility of the gas data in the preset neighborhood is normalized as the corrected discreteness of the data point; the combustible gas detection alarm is realized by comparing the corrected discreteness of the data point with the preset threshold.

[0008] The present invention can realize the detection and alarm of gas data by processing gas data through ABOD algorithm. In this process, the present invention takes into account that gas data will produce normal fluctuations during the use of gas, and directly obtains the discreteness of such data points based on the ABOD algorithm for abnormal identification, which may result in false alarms; based on this, the present invention obtains the possibility that the data point is normal gas concentration data by obtaining the degree of similarity between the data point and the gas data trend in the same acquisition time period, and corrects its discreteness based on the possibility that the data point is normal gas concentration data, which can effectively improve the accuracy of abnormal gas concentration data identification, thereby effectively improving the accuracy of combustible gas detection and early warning.

[0009] According to the combustible gas detection alarm method provided by the present invention, the preset neighborhood of each data point in the gas data segment collected every day is obtained, and before that, the gas concentration data obtained at each collection time is preprocessed as a data point to obtain the gas data segment.

[0010] The present invention takes into account the possibility of noise interference and the like in the originally collected gas data, and therefore improves the overall quality of the data through preprocessing.

[0011] According to the combustible gas detection alarm method provided by the present invention, the preset neighborhood acquisition method of the data point includes: obtaining the preset neighborhood length ; Take the data point as the end point and obtain the other data points as the preset neighborhood of this data point.

[0012] According to the combustible gas detection alarm method provided by the present invention, the outlier degree of each data point is obtained by the ABOD algorithm, including: vectorizing each data point; obtaining the variance or standard deviation of the angle between the data point and the gas data in a preset neighborhood for normalization processing to obtain the outlier degree of the data point.

[0013] The present invention processes a large amount of gas data in a short time through the ABOD algorithm, distinguishes abnormal data points that are significantly different from normal data points, and can output alarm results in real time.

[0014] According to the combustible gas detection alarm method provided by the present invention, the comparison result of the corrected discreteness of the data point and the preset threshold value includes: if the corrected discreteness of the data point is greater than the preset threshold value, then the data point is an abnormal data point; otherwise, the data point is a normal data point.

[0015] According to the combustible gas detection alarm method provided by the present invention, the combustible gas detection alarm is realized by comparing the corrected discreteness of the data point with the preset threshold, including: if the number of consecutive abnormal data points is greater than the preset number, the alarm device is activated; otherwise, the alarm device is not activated.

[0016] The present invention timely activates the alarm device to remind the user to handle the problem when the gas detection result is abnormal, which can effectively reduce safety hazards.

[0017] According to the combustible gas detection alarm method provided by the present invention, the combustible gas detection alarm is implemented, and then the abnormal data points in the gas data segment are associated with the corresponding collection time and stored.

[0018] The present invention takes into account that the normal operation of gas equipment plays an important role in user safety, and therefore stores abnormal gas data in association with the corresponding collection time to facilitate subsequent fault analysis and research by staff.

[0019] In a second aspect, the present invention provides a combustible gas detection alarm system, which adopts the following technical solution: A combustible gas detection alarm system comprises: a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the combustible gas detection alarm method is implemented.

[0020] By adopting the above technical solution, the above-mentioned combustible gas detection alarm method is generated into a computer program and stored in a memory so as to be loaded and executed by a processor, thereby making a terminal device based on the memory and the processor for easy use.

[0021] The present invention has the following technical effects: Based on the above technical solution, the present invention can realize the detection and alarm of gas data by processing gas data through ABOD algorithm when performing the detection and alarm of gas data. In this process, the present invention takes into account that the gas data will produce normal fluctuations in the process of using gas, and directly obtains the discreteness of such data points based on the ABOD algorithm for abnormal identification, which may result in false alarms; based on this, the present invention obtains the possibility that the data point is normal gas concentration data by obtaining the degree of similarity between the data point and the gas data trend in the same collection time period, and corrects its discreteness based on the possibility that the data point is normal gas concentration data, which can effectively improve the accuracy of abnormal gas concentration data identification, thereby effectively improving the accuracy of combustible gas detection and early warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] By reading the detailed description below with reference to the accompanying drawings, the above and other purposes, features and advantages of the exemplary embodiments of the present invention will become readily understood. In the accompanying drawings, several embodiments of the present invention are shown in an exemplary and non-restrictive manner, and the same or corresponding reference numerals represent the same or corresponding parts.

[0023] Figure 1 A schematic flow chart of a combustible gas detection and alarm method provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0025] It should be understood that when the terms "first", "second", etc. are used in the claims, descriptions, and drawings of the present invention, they are only used to distinguish different objects, rather than to describe a specific order. The terms "include" and "comprise" used in the description and claims of the present invention indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their collections.

[0026] As a clean and efficient energy source, natural gas can be used in daily household cooking, hot water supply, etc. due to its environmental and economic characteristics. At the same time, natural gas is also flammable and explosive. Once it leaks in large quantities and encounters open flames or static sparks, it may cause fires or even explosions, affecting the safety of residents' lives.

[0027] The Angle-Based Outlier Detection (ABOD) algorithm is an outlier measurement algorithm that determines whether a data point is an outlier by calculating the angle relationship between the data point and other points in the neighborhood. In combustible gas detection alarms, leakage events usually cause significant changes in the angle relationship between a data point and its neighboring data points. The algorithm can process a large amount of gas data in a short period of time, distinguish abnormal data points that are significantly different from normal data points, and output alarm results in real time.

[0028] Based on this, in order to reduce the hidden dangers of gas anomalies and improve the safety of residents' lives, an embodiment of the present invention discloses a combustible gas detection alarm method. This method uses the ABOD algorithm to process the collected gas data to identify abnormal data points, and outputs alarm results in real time, which can effectively improve the efficiency and accuracy of gas data processing.

[0029] For details, please see Figure 1 As shown, Figure 1 A flow chart of a combustible gas detection and alarm method provided in an embodiment of the present invention, the method specifically includes the following steps.

[0030] S1: Get the data points in the gas data segment collected every day.

[0031] For example, in an embodiment of the present invention, obtaining data points in a gas data segment collected every day includes: preprocessing the gas concentration data obtained at each collection time as a data point to obtain a gas data segment.

[0032] Among them, the preprocessing method can be data denoising, missing data interpolation, etc., which can be set according to actual needs.

[0033] Specifically, when collecting gas data, a highly sensitive combustible gas sensor can be installed in a fixed area such as a kitchen, and the collection frequency can be preset to collect gas concentration data in the environment.

[0034] The collection frequency may be once per minute, which may be set according to actual needs.

[0035] It is understandable that by collecting daily gas data on a daily basis to obtain gas data segments, we can clearly see the changes in residents' daily gas consumption. These data can reflect residents' gas usage habits and changing trends in different regions. If gas consumption suddenly increases or decreases significantly, there may be abnormal gas leakage.

[0036] After obtaining the gas concentration data in the environment based on the above steps, continue to perform the following steps.

[0037] S2: Obtain a preset neighborhood of each data point, and use the gas data in other gas data segments that are in the same collection time period as the preset neighborhood of the data point as the reference segment of the data point; obtain the proximity between the data point and each reference segment through the difference in fitting values ​​between the preset neighborhood of the data point and each reference segment.

[0038] Among them, the preset neighborhood length can be set to 10; the preset neighborhood length can be set according to actual needs, and the embodiment of the present invention does not impose too many restrictions on this.

[0039] It should be noted that by using the ABOD algorithm to process the collected gas data and identify abnormal data points, the alarm results of the gas data can be obtained. However, in the daily use of gas, there may be problems with incomplete gas combustion, which leads to the presence of gas components in the exhaust gas produced after combustion, causing fluctuations in the collected gas data. This fluctuation is controllable and indispensable. Compared with the gas concentration data when a gas leak occurs, this fluctuation is a normal fluctuation. If it is directly processed by the ABOD algorithm, such normal data fluctuations may be identified as abnormal data, resulting in false alarms and misreporting, reducing the accuracy of combustible gas detection alarms.

[0040] Based on this, the embodiment of the present invention obtains the degree of closeness between the current natural gas data and the previously collected gas data by analyzing the gas data characteristics between the preset neighborhood of each data point in the gas data segment collected on the day and the gas data collected in the same time period on other days. The higher the degree of closeness, the higher the similarity between the gas data characteristics in the preset neighborhood of the data point and the gas data characteristics in the reference segment.

[0041] For example, in an embodiment of the present invention, the method for obtaining the preset neighborhood of a data point includes: obtaining the preset neighborhood length ; Take the data point as the end point and obtain the other data points as the preset neighborhood of this data point.

[0042] In this way, by acquiring the historical data on the left side of the current data point as its preset neighborhood, the embodiment of the present invention can characterize the characteristic changes of the current data point through the historical gas data characteristics of the current data point on that day, and reduce the data waiting time.

[0043] For example, in an embodiment of the present invention, the method for obtaining a preset neighborhood of a data point further includes: obtaining a preset neighborhood length ; Get the values ​​on both sides of the data point other data points as the preset neighborhood of this data point.

[0044] It can be understood that the preset neighborhood of the current data point refers to other data points on the left or both sides of the current data point, so the preset neighborhood does not include the current data point itself.

[0045] After obtaining the preset neighborhood of each data point based on the above steps, continue to perform the following steps to calculate the proximity between the data point and each reference segment.

[0046] It should be further explained that the fitting curve can represent the changing trend of the gas data within a time period. If the combustible gas concentration in two time periods changes in the same direction over time, the areas enclosed by the two and the coordinate axis will be closer, and the difference in area will be smaller. At this time, the data in the two time periods are more likely to show similar trend changes.

[0047] Based on this, the embodiment of the present invention can obtain the degree of proximity between the data point and the reference segment by analyzing the degree of proximity of the fitting curve between the preset neighborhood of the data point and the reference segment.

[0048] Wherein, obtaining the fitting function of the preset neighborhood and the reference segment can be achieved by the least square method.

[0049] For example, in the embodiment of the present invention, the proximity between the data point and each reference segment is determined, and the specific relationship can be as follows: ; For the Data points and The proximity between the reference segments, For the The fitted function for a preset neighborhood of data points, For the The data point The fitting function of the reference segment, For the The initial collection time of a preset neighborhood of data points, For the The end time of the collection of the preset neighborhood of data points, For the The data point The initial acquisition time of the reference segment, For the The data point The end acquisition time of the reference segment, For the The range of the preset neighborhood of the data point, For the The data point The range of the reference segment, is the absolute value, is the integral symbol, is the differential symbol.

[0050] In the above formula, Indicates The fitted curve of the preset neighborhood of the data point and its The area enclosed by the fitting curves of the two reference segments on the time coordinate. The smaller the value, the more similar the combustible gas concentrations in the two time periods increase or decrease over time.

[0051] The range of the gas fluctuations in the data within the time period. Indicates The preset neighborhood of the data point is The smaller the value is, the more similar the numerical fluctuations of the data in the two time periods are.

[0052] In summary, if The preset neighborhood of the data point is The more similar the combustible gas concentration data change trends between the two reference sections and the more similar the numerical fluctuation ranges are, the higher the closeness of the combustible gas concentration data in the two time periods will be.

[0053] After obtaining the proximity between the data point and the corresponding reference segments based on the above formula, continue to perform the following steps.

[0054] S3: Normalize the product of the median of the proximity between the data point and each reference segment and the cumulative sum of the proximity to obtain the credibility of the gas data in the preset neighborhood of the data point.

[0055] It should be noted that based on the similarity of the change trend and fluctuation degree between the preset neighborhood of the above-mentioned analysis data point and the gas data in the same collection time period on other days, the closeness between the neighborhood gas data of the data point and the historical data can be obtained. However, different change patterns may appear in the actual operation of the gas equipment. For example, the user does not use gas according to the previous rules for a period of time. At this time, the closeness between the neighborhood time period at the current moment and the same time period on other days may be relatively low. If abnormal data is identified directly based on the closeness between the neighborhood time period at the current moment and the same time period on other days, such changes may be identified as abnormalities.

[0056] It should be further explained that even though the neighborhood time period at the current moment is less close to the same time period in other days, it is in line with normal fluctuations compared with the changes in the same time period in the entire history.

[0057] Based on this, the median of the proximity between the preset neighborhood of the data point and the reference segment obtained by the embodiment of the present invention reflects the majority of changes in historical data, and the credibility of the gas data in the preset neighborhood of the data point is obtained through the majority of changes in historical data and the overall change.

[0058] For example, in the embodiment of the present invention, the credibility of the gas data in the preset neighborhood of the data point is determined, and the specific details can be referred to the following relationship: ; For the The credibility of gas data in the preset neighborhood of data points is For the The median of the proximity of a data point to all reference segments, For the Data point and The proximity between the reference segments, is the number of reference segments, is the standard normalization function.

[0059] In the above formula, For the The cumulative sum of the proximity between the data point and all reference segments. The larger the value, the closer the The closer the change pattern of the gas data in the preset neighborhood of the data point is to the combustible gas concentration data in the corresponding reference segment.

[0060] On the basis of the above, if The larger the median of the proximity between the data point and all reference segments, the closer the It is not accidental that the gas data in the preset neighborhood of the data point is closer to the combustible gas concentration data in the corresponding reference segment. The gas data in the preset neighborhood of each data point conforms to normal changes, and the corresponding credibility is higher.

[0061] Based on the above formula, the The consistency of the change trend between the gas data in the preset neighborhood of the data point and the reference segment is obtained. After the credibility of the gas data in the neighborhood is preset by the data points, continue with the following steps.

[0062] S4: The outlier of each data point is obtained through the ABOD algorithm, and the ratio of the outlier of the data point to the credibility of the gas data in the preset neighborhood is normalized as the corrected discreteness of the data point; the combustible gas detection alarm is realized by comparing the corrected discreteness of the data point with the preset threshold.

[0063] It should be noted that after obtaining the credibility of the gas data of each data point based on the above steps, the outlier of the data point can be corrected based on the credibility of the gas data of each data point, so as to accurately obtain the true outlier of each data point and accurately realize abnormal warning of gas data.

[0064] For example, in an embodiment of the present invention, the outlier degree of each data point is obtained by the ABOD algorithm, including: vectorizing each data point; obtaining the variance or standard deviation of the angle between the data point and the gas data in a preset neighborhood for normalization to obtain the outlier degree of the data point.

[0065] The specific steps of obtaining the outlier degree of each data point through the ABOD algorithm can be implemented by the prior art, and will not be described in detail in the embodiment of the present invention.

[0066] It is understandable that the preset neighborhood of the current data point is composed of other data around the current data point, so the angle between the current data point and the gas data in the preset neighborhood is the angle between the current data point and other data points in the preset neighborhood.

[0067] For example, the outlier degree of the data point may also be normalized, which may be specifically set according to actual needs, and the embodiment of the present invention does not impose too many limitations here.

[0068] For example, in the embodiment of the present invention, the corrected discreteness of the data point is determined, and the specific details can be referred to the following relationship: ; For the The corrected dispersion of the data points, For the The dispersion of the data points, For the The credibility of gas data in the preset neighborhood of data points is is the standard normalization function.

[0069] In the above formula, The higher the credibility of the gas data in the preset neighborhood of a data point, the more it means that the change in the combustible gas concentration in the neighborhood period at the current moment conforms to the normal change. Therefore, it is necessary to reduce the outlier degree of the data point at the current moment to reduce the misjudgment of the data point at the current moment due to normal fluctuations.

[0070] After the corrected discreteness of each data point is obtained based on the above steps, abnormal data can be identified based on the corrected discreteness of the data point.

[0071] For example, in an embodiment of the present invention, the comparison result of the corrected discreteness of a data point and a preset threshold value includes: if the corrected discreteness of a data point is greater than the preset threshold value, the data point is an abnormal data point; otherwise, the data point is a normal data point.

[0072] The preset threshold may be set to 0.7; the preset threshold may be set specifically according to actual needs, and the embodiment of the present invention does not impose too many restrictions on this.

[0073] For example, in an embodiment of the present invention, a combustible gas detection alarm is realized by comparing the corrected discreteness of a data point with a preset threshold, including: if the number of consecutive abnormal data points is greater than a preset number, an alarm device is activated; otherwise, the alarm device is not activated.

[0074] Among them, the preset number can be set to 3; the preset number can be set according to actual needs, and the embodiment of the present invention does not impose too many restrictions on this.

[0075] For example, the warning device may be an audible warning signal or a light warning signal.

[0076] For example, in an embodiment of the present invention, a combustible gas detection alarm is implemented, and then the method further includes: storing abnormal data points in a gas data segment in association with corresponding collection times.

[0077] The present invention takes into account that the normal operation of gas equipment plays an important role in user safety, and therefore stores abnormal gas data in association with the corresponding collection time to facilitate subsequent fault analysis and research by staff.

[0078] Based on the above embodiments, the detection and early warning of combustible gas can be accurately achieved.

[0079] It can be seen that in the embodiment of the present invention, when realizing the detection and early warning of combustible gas, the preset neighborhood of each data point in the gas data segment collected every day can be obtained, and the gas data in other gas data segments that are in the same collection time period as the preset neighborhood of the data point is used as the reference segment of the data point; the proximity between the data point and each reference segment is obtained by the difference in fitting values ​​between the preset neighborhood of the data point and each reference segment; the product of the median of the proximity between the data point and each reference segment and the cumulative sum of the proximity is normalized to obtain the credibility of the gas data in the preset neighborhood of the data point; the outlier of each data point is obtained by the ABOD algorithm, and the ratio of the outlier of the data point to the credibility of the gas data in the preset neighborhood is normalized as the corrected discreteness of the data point; and the combustible gas detection alarm is realized by comparing the corrected discreteness of the data point with the preset threshold.

[0080] In this way, the embodiment of the present invention can realize the detection and alarm of gas data by processing gas data through the ABOD algorithm. In this process, the embodiment of the present invention takes into account that the gas data will produce normal fluctuations during the use of gas, and directly obtains the discreteness of such data points based on the ABOD algorithm for abnormal identification, which may result in false alarms; based on this, the embodiment of the present invention obtains the possibility that the data point is normal gas concentration data by obtaining the degree of similarity between the data point and the gas data trend in the same collection time period, and corrects its discreteness based on the possibility that the data point is normal gas concentration data, which can effectively improve the accuracy of abnormal gas concentration data identification, thereby effectively improving the accuracy of combustible gas detection and early warning.

[0081] The embodiment of the present invention further discloses a combustible gas detection alarm system, including a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the combustible gas detection alarm method provided by the present invention is implemented.

[0082] The above system also includes other components well known to those skilled in the art, such as a communication bus and a communication interface, and their configuration and functions are known in the art, so they will not be described in detail here.

[0083] In the present invention, the aforementioned memory may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, apparatus, or device. For example, a computer-readable storage medium may be any suitable magnetic storage medium or magneto-optical storage medium, such as a resistive random access memory RRAM, a dynamic random access memory DRAM, a static random access memory SRAM, an enhanced dynamic random access memory EDRAM, a high bandwidth memory HBM, a hybrid memory cube HMC, etc., or any other medium that can be used to store the required information and can be accessed by an application, a module, or both. Any such computer storage medium may be part of a device or accessible or connectable to a device.

[0084] Although this specification has shown and described a number of embodiments of the present invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art will conceive of many modifications, changes and alternatives without departing from the ideas and spirit of the present invention. It should be understood that in the practice of the present invention, various alternatives to the embodiments of the present invention described herein may be employed.

[0085] The above are all preferred embodiments of the present invention, and are not intended to limit the protection scope of the present invention. Therefore, any equivalent changes made based on the structure, shape, and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A combustible gas detection alarm method, characterized in that: include: Get the preset neighborhood of each data point in the gas data segment collected every day, and use the gas data in other gas data segments that are in the same collection time period as the preset neighborhood of the data point as the reference segment of the data point; obtain the proximity between the data point and each reference segment through the difference in the fitting value between the preset neighborhood of the data point and each reference segment: ； For the Data point and The proximity between the reference segments, , Respectively The preset neighborhood of the data point, The fitting function of the reference segment, , Respectively The initial collection time and the end collection time of the preset neighborhood of the data point, , Respectively The initial acquisition time and the end acquisition time of each reference segment, , Respectively The preset neighborhood of the data point, The range of the reference segment, is the absolute value; the product of the median of the proximity between the data point and each reference segment and the cumulative sum of the proximity is normalized to obtain the credibility of the gas data in the preset neighborhood of the data point; the outlier of each data point is obtained by the ABOD algorithm, and the ratio of the outlier of the data point to the credibility of the gas data in the preset neighborhood is normalized as the corrected discreteness of the data point; the combustible gas detection alarm is realized by comparing the corrected discreteness of the data point with the preset threshold.

2. The combustible gas detection alarm method according to claim 1, characterized in that: The step of obtaining the preset neighborhood of each data point in the gas data segment collected every day also includes: The gas concentration data obtained at each acquisition time is preprocessed as a data point to obtain a gas data segment.

3. The combustible gas detection alarm method according to claim 2, characterized in that: The preset neighborhood acquisition method of the data point includes: Get the preset neighborhood length ; Take the data point as the end point and get the value on the left side of the data point other data points as the preset neighborhood of this data point.

4. The combustible gas detection alarm method according to claim 1, characterized in that: The outlier degree of each data point is obtained by the ABOD algorithm, including: Each data point is vectorized; the variance or standard deviation of the angle between the data point and the gas data in the preset neighborhood is obtained for normalization to obtain the outlier degree of the data point.

5. The combustible gas detection alarm method according to claim 1, characterized in that: The comparison result of the modified discreteness of the data point and the preset threshold value includes: If the corrected discreteness of a data point is greater than a preset threshold, the data point is an abnormal data point; otherwise, the data point is a normal data point.

6. The combustible gas detection alarm method according to claim 5, characterized in that: The method of realizing combustible gas detection alarm by comparing the corrected discreteness of the data point with the preset threshold value includes: If the number of consecutive abnormal data points is greater than the preset number, the alarm device is activated; otherwise, the alarm device is not activated.

7. The combustible gas detection and alarm method according to claim 6, characterized in that: The method of realizing the combustible gas detection alarm further includes: The abnormal data points in the gas data segment are associated with the corresponding collection time and stored.

8. Combustible gas detection alarm system, characterized in that: include: A processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the combustible gas detection alarm method according to any one of claims 1 to 7 is implemented.

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