A data availability identification method and system for gas detectors

Abstract

The present invention is applicable to the field of data identification technology, and in particular, relates to a method and system for identifying data availability for gas detectors, including: extracting gas detection data according to the transportation direction of the gas transmission pipeline; intercepting the gas detection data based on the gas transmission speed, performing data alignment, and obtaining aligned detection data; constructing a multidimensional coordinate space, marking the aligned detection data in the multidimensional coordinate space, and obtaining a data space dot matrix; constructing a data space model, calculating the availability of the selected aligned detection data, and outputting the identification result. The present invention verifies the data detected by each gas detector based on the aligned gas detection data, verifies the stability of the gas data by constructing a multidimensional coordinate system and a space model, realizes the data validity detection of the gas detector, and can jointly detect the data stability of the gas detector to ensure the validity of the data.

Description

Technical Field

[0001] The present invention belongs to the technical field of data identification, and in particular relates to a method and system for identifying data availability for a gas detector. Background Art

[0002] A gas detector is a device used to detect the concentration of a specific gas in the environment. It is widely used in industrial safety, environmental monitoring, medical health and other fields. It monitors the presence and concentration of gases in real time through different sensing technologies (such as electrochemical, infrared, metal oxide semiconductor, etc.), providing accurate data to ensure safety and compliance. Gas detectors can be single gas detectors that specifically detect one gas, or multi-gas detectors that monitor multiple gases at the same time. They are suitable for various application scenarios, such as coal mine safety, air quality monitoring and laboratory analysis.

[0003] Existing gas detectors can monitor multiple types of gases at the same time, but as the usage time increases, the gas detectors will gradually age, which will affect the detection accuracy of the gas detectors. The existing technology lacks data availability detection methods for gas detectors and can only determine that the gas detector is abnormal when the data deviation is extremely large. In this case, there is a huge deviation in the previous statistical data, which greatly affects the monitoring effect. Summary of the invention

[0004] The purpose of the present invention is to provide a method for identifying data availability for gas detectors, aiming to solve the problem that the prior art lacks means for detecting data availability of gas detectors and can only determine that a gas detector is abnormal when its data deviation is extremely large.

[0005] The present invention is implemented as follows: a method for identifying data availability for a gas detector, the method for identifying data availability for a gas detector comprising:

[0006] According to the transportation direction of the gas transmission pipeline, the gas detection data of each gas detector is extracted one by one;

[0007] The gas detection data is intercepted based on the gas delivery speed, and data alignment is performed according to the intercepted interval detection data to obtain aligned detection data;

[0008] Constructing a multidimensional coordinate space, marking the alignment detection data in the multidimensional coordinate space to obtain a data space dot matrix, wherein the multidimensional coordinate space includes a time axis and multiple data axes, all the data axes are coplanar, and the time axis is perpendicular to all the data axes;

[0009] Each time a set of alignment detection data is selected, a data space model is built based on other alignment detection data, the availability of the selected alignment detection data is calculated, and the recognition result is output.

[0010] Preferably, the step of intercepting the gas detection data based on the gas delivery speed, and performing data alignment according to the intercepted interval detection data to obtain the aligned detection data specifically includes:

[0011] Obtaining the gas delivery speed, and determining the gas arrival time interval corresponding to each gas detector based on the gas delivery speed;

[0012] The corresponding gas detection data is intercepted based on the gas arrival time interval to obtain the interval detection data within the corresponding time interval;

[0013] Extract gas concentration data from interval detection data, compare gas concentration data corresponding to the same gas, calculate similarity, extract data with similarity higher than a preset value, and obtain aligned detection data.

[0014] Preferably, the step of constructing a multidimensional coordinate space, marking the alignment detection data in the multidimensional coordinate space, and obtaining a data space dot matrix specifically includes:

[0015] Constructing a multidimensional coordinate space, wherein the number of data axes in the multidimensional coordinate space is the same as the total number of gas types detected by the gas detector;

[0016] Mark each gas concentration data in the aligned detection data in the multi-dimensional coordinate space in chronological order to obtain the data plane dot matrix corresponding to each moment;

[0017] The centroid position of the data plane dot matrix is ​​calculated, and the centroid position and the corresponding time value are combined and marked in the multidimensional coordinate space to obtain the data space dot matrix.

[0018] Preferably, the step of selecting a group of alignment detection data each time, building a data space model based on other alignment detection data, calculating the availability of the selected alignment detection data, and outputting the recognition result specifically includes:

[0019] Each time a set of alignment detection data is selected, a data space model is generated according to the data space lattice corresponding to all other alignment detection data;

[0020] A data verification space curve is constructed based on the selected alignment detection data, and the length of the outer curve and the length of the inner curve are counted according to the data space model;

[0021] The ratio of the inner curve length to the outer curve length is calculated to obtain the data availability assessment value, and the recognition result is output according to the preset interval range.

[0022] Preferably, an availability prediction function is constructed according to the data availability evaluation value of each gas detector, the availability of the gas detector is predicted based on the availability prediction function, and a prediction result is generated.

[0023] Another object of the present invention is to provide a data availability identification system for a gas detector, the data availability identification system for a gas detector comprising:

[0024] A data acquisition module, used to extract gas detection data of each gas detector one by one according to the transportation direction of the gas transmission pipeline;

[0025] A data alignment module is used to intercept the gas detection data based on the gas delivery speed, and perform data alignment according to the intercepted interval detection data to obtain aligned detection data;

[0026] A data dot matrix construction module is used to construct a multi-dimensional coordinate space, mark the alignment detection data in the multi-dimensional coordinate space, and obtain a data space dot matrix, wherein the multi-dimensional coordinate space includes a time axis and multiple data axes, all the data axes are coplanar, and the time axis is perpendicular to all the data axes;

[0027] The availability recognition module is used to select a group of alignment detection data each time, build a data space model based on other alignment detection data, calculate the availability of the selected alignment detection data, and output the recognition result.

[0028] Preferably, the data alignment module includes:

[0029] A delivery speed acquisition unit, used to acquire the gas delivery speed, and determine the gas arrival time interval corresponding to each gas detector based on the gas delivery speed;

[0030] A data interception unit, used to intercept the corresponding gas detection data based on the gas arrival time interval to obtain the interval detection data within the corresponding time interval;

[0031] The detection data alignment unit is used to extract gas concentration data from the interval detection data, compare the gas concentration data corresponding to the same gas, calculate the similarity, extract data with a similarity higher than a preset value, and obtain aligned detection data.

[0032] Preferably, the data lattice construction module includes:

[0033] A multi-dimensional coordinate system construction unit, used for constructing a multi-dimensional coordinate space, wherein the number of data axes in the multi-dimensional coordinate space is the same as the total number of gas types detected by the gas detector;

[0034] A coordinate marking unit is used to mark each gas concentration data in the aligned detection data in a multi-dimensional coordinate space in chronological order to obtain a data plane dot matrix corresponding to each moment;

[0035] The dot matrix construction unit is used to calculate the centroid position of the data plane dot matrix, combine the centroid position and the corresponding time value, mark it in the multi-dimensional coordinate space, and obtain the data space dot matrix.

[0036] Preferably, the availability identification module includes:

[0037] A spatial model building unit, for selecting a set of alignment detection data each time, and generating a data space model according to data space lattices corresponding to all other alignment detection data;

[0038] A space curve construction unit, used to construct a data verification space curve based on the selected alignment detection data, and to count the length of the outer curve and the length of the inner curve according to the data space model;

[0039] The data evaluation unit is used to calculate the ratio of the inner curve length to the outer curve length, obtain the data availability evaluation value, and output the recognition result according to the preset interval range.

[0040] Preferably, an availability prediction function is constructed according to the data availability evaluation value of each gas detector, the availability of the gas detector is predicted based on the availability prediction function, and a prediction result is generated.

[0041] The data availability identification method for gas detectors provided by the present invention collects data from multiple gas detectors on a transmission pipeline, verifies the data detected by each gas detector based on the aligned gas detection data, and verifies the stability of the gas data by constructing a multi-dimensional coordinate system and a spatial model, thereby realizing data validity detection of the gas detectors, and can jointly detect the data stability of the gas detectors to ensure the validity of the data. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 A flow chart of a method for identifying data availability for a gas detector provided by an embodiment of the present invention;

[0043] Figure 2 A flowchart of the steps of intercepting gas detection data based on gas delivery speed, performing data alignment according to the intercepted interval detection data, and obtaining aligned detection data provided by an embodiment of the present invention;

[0044] Figure 3 A flowchart of the steps of constructing a multidimensional coordinate space, marking the alignment detection data in the multidimensional coordinate space, and obtaining a data space dot matrix provided by an embodiment of the present invention;

[0045] Figure 4A flowchart of the steps of selecting a set of alignment detection data each time, building a data space model based on other alignment detection data, calculating the availability of the selected alignment detection data, and outputting a recognition result provided by an embodiment of the present invention;

[0046] Figure 5 An architecture diagram of a data availability identification system for a gas detector provided by an embodiment of the present invention;

[0047] Figure 6 An architecture diagram of a data alignment module provided by an embodiment of the present invention;

[0048] Figure 7 An architectural diagram of a data lattice construction module provided by an embodiment of the present invention;

[0049] Figure 8 An architecture diagram of an availability identification module provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0051] like Figure 1 As shown in FIG. 1, a flow chart of a method for identifying data availability for a gas detector provided by an embodiment of the present invention, the method for identifying data availability for a gas detector comprising:

[0052] S100, extracting gas detection data of each gas detector one by one according to the transportation direction of the gas transmission pipeline.

[0053] In this step, the delivery direction of the gas transmission pipeline is obtained. The gas is transported by pipeline, such as natural gas, which is transported by natural gas pipeline. In order to monitor the delivery status of natural gas and detect whether there is any leakage, multiple gas detectors are usually installed continuously on the natural gas transmission pipeline. The gas concentration at the installation point can be detected by the gas detector. The gas detector can use a multi-gas sensor to monitor the concentration of multiple gases at the same time, or multiple single gas sensors can be installed at the same location. The effects of the two are the same. Taking natural gas as an example, methane accounts for about 70-95%, ethane accounts for about 0.5-10%, propane accounts for about 0.5-5%, butane accounts for about 0.1 to 0.3%, carbon dioxide accounts for about 0.1-3%, and other gases are negligible. During monitoring, one or more gases can be monitored to obtain gas detection data of the gas detector. In this embodiment, the gas detector is a multi-gas sensor that can monitor the concentration data of multiple gases at the same time.

[0054] S200, intercepting the gas detection data based on the gas delivery speed, and performing data alignment according to the intercepted interval detection data to obtain aligned detection data.

[0055] In this step, the gas detection data is intercepted based on the gas transmission speed. The gas transmission speed in the pipeline is unstable, so the transmission speed at each position may be inconsistent, but in general, the transmission speed of natural gas in the pipeline is within a certain range. When it is necessary to detect the data availability of the gas detector, the detection data of multiple consecutive gas detectors installed on the same pipeline are analyzed. For example, five gas detectors are installed in succession on the pipeline, which are A, B, C, D and E sensors in order, and the installation distance between two adjacent gas detectors is 5 kilometers. The time it takes for the gas to arrive at each gas detector is calculated according to the gas transmission speed, and the gas detection data of the corresponding time is intercepted to obtain the interval detection data. In order to further improve the detection accuracy, the gas concentration is analyzed to realize data alignment processing to obtain aligned detection data. The gas concentration data corresponding to the aligned detection data is the gas concentration data detected when the same section of gas passes through different gas detectors.

[0056] S300, constructing a multidimensional coordinate space, marking the alignment detection data in the multidimensional coordinate space, and obtaining a data space dot matrix, wherein the multidimensional coordinate space includes a time axis and multiple data axes, all the data axes are coplanar, and the time axis is perpendicular to all the data axes.

[0057] In this step, a multidimensional coordinate space is constructed. The multidimensional coordinate system includes multiple data axes. The data axis is used to record gas concentration data, and the time axis is used to record the time value of generating the above gas concentration data. All data axes are coplanar, the time axis is perpendicular to all data axes, and the angles between the data axes are equal. When marking data, first read the numerical value of each gas concentration, mark it on the data axis, and calculate the center of mass position of the marked point on each data axis. The position of the data detected by the gas sensor at the current moment in the multidimensional coordinate space is determined according to the center of mass position and the time value. The position is defined as the data characterization point. The position of the data characterization point corresponding to all moments is determined accordingly to obtain the data space dot matrix. When there are multiple gas detectors, then at the same moment, there will be multiple data characterization points corresponding, and the data characterization points at the same moment are in the same plane.

[0058] S400, each time a group of alignment detection data is selected, a data space model is constructed based on other alignment detection data, the availability of the selected alignment detection data is calculated, and a recognition result is output.

[0059] In this step, each time a group of aligned detection data is selected, when it is necessary to detect the data availability of a certain gas detector, such as five groups of gas detectors A, B, C, D and E, to detect the data availability of gas detector A, the data space lattices corresponding to the remaining four groups of gas detectors are selected, and a spatial model is constructed based on this, that is, the data space model. The data space model is a closed spatial structure, and then the data space lattice corresponding to the selected gas detector is called up, connected by a smooth curve, and then the curve length of the smooth curve within the data space model and the curve length outside the data space model are counted. The data availability is represented based on the ratio between the two groups of curve lengths. When the proportion of the curve length inside the data space model is greater than the preset value, it is determined that there is data available, otherwise it is determined that it is unavailable, and the recognition result is output.

[0060] like Figure 2 As shown, as a preferred embodiment of the present invention, the gas detection data is intercepted based on the gas delivery speed, and the data is aligned according to the intercepted interval detection data to obtain the aligned detection data, which specifically includes:

[0061] S201, obtaining a gas delivery speed, and determining a gas arrival time interval corresponding to each gas detector based on the gas delivery speed.

[0062] In this step, the gas transmission speed is obtained. The transmission speed V of natural gas in the pipeline is between 10 m / s and 20 m / s. When the pipeline diameter remains unchanged, the time length of the gas with a length of L in the pipeline passing through the first gas sensor is L / V. The time it takes for the gas with a length of L to reach the next gas detector can be calculated based on the distance between the gas detectors, the transmission speed V and the length L of the gas in the pipeline. Similarly, the time interval for the gas with a length of L to pass through each gas detector is obtained.

[0063] S202, intercepting corresponding gas detection data based on the gas arrival time interval to obtain interval detection data within the corresponding time interval.

[0064] In this step, the corresponding gas detection data is intercepted based on the gas arrival time interval. The time interval obtained by calculation can ensure that the detection data of the same gas passing through different gas detectors can be identified. Therefore, the corresponding gas detection data is intercepted according to the time interval to obtain the interval detection data.

[0065] S203, extracting gas concentration data from the interval detection data, comparing gas concentration data corresponding to the same gas, calculating similarity, extracting data with a similarity higher than a preset value, and obtaining aligned detection data.

[0066] In this step, the gas concentration data in the interval detection data is extracted. Since the gas delivery speed is not uniform, the time interval corresponding to the later gas detectors is larger. In order to determine the data of the same section of gas passing through different gas detectors, the similarity is calculated. Specifically, the gas concentration data corresponding to each gas detector is divided into multiple time slice data according to the preset time step. Five gas detectors correspond to 5 time slice data groups (including time slice data corresponding to multiple time steps). The overlap between the first time slice data group and the subsequent four time slice data groups is calculated, and the part with the highest overlap is selected to obtain the aligned detection data. That is, the gas concentration data corresponding to the subsequent four gas detectors is obtained based on this. Find the corresponding data in the measuring sensor, which is the aligned detection data. When calculating the similarity, if gas detector A contains 10 time slice data and gas detector B contains 20 time slice data, select 10 consecutive time slice data from the time slice data corresponding to B each time in order, and compare them with the time slice data corresponding to A. If the gas concentration difference in the time slice data used for comparison is within the preset range, the time slice data in B is determined to be a valid slice. If, among the 20 time slice data corresponding to B, the 5th to the 14th time slice data contain the most valid slices, the 5th to the 14th time slice data are selected as the aligned detection data corresponding to B.

[0067] like Figure 3 As shown, as a preferred embodiment of the present invention, the step of constructing a multidimensional coordinate space, marking the alignment detection data in the multidimensional coordinate space, and obtaining a data space dot matrix specifically includes:

[0068] S301, constructing a multidimensional coordinate space, wherein the number of data axes in the multidimensional coordinate space is the same as the total number of gas types detected by the gas detector.

[0069] In this step, a multidimensional coordinate space is constructed, and multiple data axes are constructed. All data axes are located in the same plane. In order to balance the spatial model, the scale ratios of the data axes are normalized, and 0-1 is used to represent the gas concentration. For example, the concentration range of gas a (expressed as volume percentage) is 1-5%, 0 represents the concentration of gas a is 1%, and 1 represents the volume percentage of gas a is 5%. The number of data axes in the multidimensional coordinate space is the same as the total number of gas types detected by the gas detector.

[0070] S302, marking each gas concentration data in the aligned detection data in a multi-dimensional coordinate space in chronological order to obtain a data plane dot matrix corresponding to each moment.

[0071] S303, calculating the centroid position of the data plane dot matrix, combining the centroid position and the corresponding time value, marking in the multi-dimensional coordinate space, and obtaining the data space dot matrix.

[0072] In this step, each gas concentration data in the aligned detection data is marked in the multi-dimensional coordinate space in chronological order. Taking gas detector A as an example, the concentration values ​​of each gas corresponding to the first time value are read and marked on the corresponding data axis. At this time, multiple data points will appear in the plane where the data axis is located. The center of mass of these data points is calculated to obtain the center of mass position. According to the position of the first time value on the time axis, the center of mass position is translated along the time axis to obtain the first spatial data point. The spatial data points corresponding to each time value are determined accordingly. Subsequently, the aligned detection data is switched to obtain the spatial data points corresponding to all gas detectors to obtain a data space dot matrix.

[0073] like Figure 4 As shown, as a preferred embodiment of the present invention, the steps of selecting a group of alignment detection data each time, building a data space model based on other alignment detection data, calculating the availability of the selected alignment detection data, and outputting the recognition result specifically include:

[0074] S401, each time a group of alignment detection data is selected, and a data space model is generated according to the data space lattices corresponding to all other alignment detection data.

[0075] In this step, a group of aligned detection data is selected each time. Specifically, which gas detector needs to be tested for availability is selected from the group of aligned detection data. For example, among the five groups of gas detectors ABCDE, gas detector A is selected, and a data space model is generated according to the data space lattice corresponding to the aligned detection data corresponding to BCDE. Specifically, a time value is selected, and the corresponding spatial data points in the data space lattice corresponding to the corresponding time value are retrieved. The spatial data points are connected with a smooth curve in a counterclockwise direction to obtain an enclosed area. Based on this, multiple enclosed areas are obtained, and two adjacent enclosed areas are lofted to obtain a data space model, such as two circular enclosed areas, which are then lofted to obtain a truncated cone.

[0076] S402, constructing a data verification space curve based on the selected alignment detection data, and counting the length of the outer curve and the length of the inner curve according to the data space model.

[0077] In this step, a data verification space curve is constructed based on the selected aligned detection data. The data verification space curve is the data representation obtained by the A gas detector. When it appears inside the data space model, it means that the gas concentration data obtained by this part of the detection is within the allowable range. Otherwise, it means that this part of the data is not within the allowable range. The outer curve length and the inner curve length are counted according to the data space model.

[0078] S403, calculating the ratio of the inner curve length to the outer curve length, obtaining a data availability evaluation value, and outputting a recognition result according to a preset interval range.

[0079] In this step, the ratio of the inner curve length to the outer curve length is calculated, and the ratio is used as the data availability evaluation value. The larger the data availability evaluation value, the stronger the data availability, and vice versa. An availability prediction function is constructed according to the data availability evaluation value, and the availability of the gas detector is predicted based on the availability prediction function, and a prediction result is generated. When the data availability evaluation value recorded in the prediction result is lower than the preset value, the relevant personnel are notified to perform inspection or maintenance.

[0080] like Figure 5 As shown, a data availability identification system for a gas detector provided by an embodiment of the present invention, the data availability identification system for a gas detector includes:

[0081] The data acquisition module 100 is used to extract the gas detection data of each gas detector one by one according to the transportation direction of the gas transmission pipeline.

[0082] In this system, the data acquisition module 100 obtains the delivery direction of the gas transmission pipeline. The gas is transported by pipeline, such as natural gas, which is transported by natural gas pipeline. In order to monitor the delivery status of natural gas and detect whether there is leakage, multiple gas detectors are usually installed continuously on the natural gas transmission pipeline. The gas concentration at the installation point can be detected by the gas detector. The gas detector can use a multi-gas sensor to monitor the concentration of multiple gases at the same time, or multiple single gas sensors can be installed at the same location. The effects of the two are the same. Taking natural gas as an example, methane accounts for about 70-95%, ethane accounts for about 0.5-10%, propane accounts for about 0.5-5%, butane accounts for about 0.1 to 0.3%, carbon dioxide accounts for about 0.1-3%, and other gases are negligible. During monitoring, one or more gases can be monitored to obtain gas detection data of the gas detector. In this embodiment, the gas detector is a multi-gas sensor that can monitor the concentration data of multiple gases at the same time.

[0083] The data alignment module 200 is used to intercept the gas detection data based on the gas delivery speed, and perform data alignment according to the intercepted interval detection data to obtain aligned detection data.

[0084] In this system, the data alignment module 200 intercepts the gas detection data based on the gas transmission speed. The gas transmission speed in the pipeline is unstable, so the transmission speed at each position may be inconsistent, but in general, the transmission speed of natural gas in the pipeline is within a certain range. When it is necessary to detect the data availability of the gas detector, the detection data of multiple consecutive gas detectors installed on the same pipeline are analyzed. For example, five gas detectors are installed in succession on the pipeline, which are A, B, C, D and E sensors in order, and the installation distance between two adjacent gas detectors is 5 kilometers. The time when the gas arrives at each gas detector is calculated according to the gas transmission speed, and the gas detection data of the corresponding time is intercepted to obtain the interval detection data. In order to further improve the detection accuracy, the gas concentration is analyzed to realize data alignment processing to obtain aligned detection data. The corresponding gas concentration data of the aligned detection data is the gas concentration data detected when the same section of gas passes through different gas detectors.

[0085] The data dot matrix construction module 300 is used to construct a multi-dimensional coordinate space, mark the alignment detection data in the multi-dimensional coordinate space, and obtain a data space dot matrix. The multi-dimensional coordinate space includes a time axis and multiple data axes, all data axes are coplanar, and the time axis is perpendicular to all data axes.

[0086] In this system, the data lattice construction module 300 constructs a multidimensional coordinate space. The multidimensional coordinate system includes multiple data axes. The data axis is used to record gas concentration data, and the time axis is used to record the time value of generating the above gas concentration data. All data axes are coplanar, the time axis is perpendicular to all data axes, and the angles between the data axes are equal. When marking data, first read the value of each gas concentration, mark it on the data axis, and calculate the center of mass position of the marked point on each data axis. The position of the data representation point detected by the gas sensor at the current moment in the coordinate space is determined according to the center of mass position and the time value. The position of the data representation point corresponding to all moments is determined accordingly to obtain the data space lattice. When there are multiple gas detectors, then at the same moment, there will be multiple data representation points corresponding, and the data representation points at the same moment are in the same plane.

[0087] The availability identification module 400 is used to select a group of alignment detection data each time, build a data space model based on other alignment detection data, calculate the availability of the selected alignment detection data, and output the identification result.

[0088] In this system, the availability identification module 400 selects a group of aligned detection data each time. When it is necessary to detect the data availability of a certain gas detector, such as five groups of gas detectors A, B, C, D and E, to detect the data availability of gas detector A, the data space lattices corresponding to the remaining four groups of gas detectors are selected, and a spatial model is constructed based on this, that is, the data space model. The data space model is a closed spatial structure, and then the data space lattices corresponding to the selected gas detectors are retrieved and connected through smooth curves. Then, the curve length of the smooth curve within the data space model and the curve length outside the data space model are counted, and the data availability is characterized based on the ratio between the two groups of curve lengths. When the proportion of the curve length inside the data space model is greater than the preset value, it is determined that the data is available, otherwise it is determined that it is unavailable, and the identification result is output.

[0089] like Figure 6 As shown, as a preferred embodiment of the present invention, the data alignment module 200 includes:

[0090] The delivery speed acquisition unit 201 is used to acquire the gas delivery speed and determine the gas arrival time interval corresponding to each gas detector based on the gas delivery speed.

[0091] In this module, the delivery speed acquisition unit 201 acquires the gas delivery speed. The delivery speed V of natural gas in the pipeline is between 10 m / s and 20 m / s. When the pipeline diameter remains unchanged, the time length for the gas with a length of L in the pipeline to pass through the first gas sensor is L / V. The time for the gas with a length of L to reach the next gas detector can be calculated based on the distance between the gas detectors, the delivery speed V and the length L of the gas in the pipeline. Similarly, the time interval for the gas with a length of L to pass through each gas detector is obtained.

[0092] The data interception unit 202 is used to intercept the corresponding gas detection data based on the gas arrival time interval to obtain the interval detection data in the corresponding time interval.

[0093] In this module, the data interception unit 202 intercepts the corresponding gas detection data based on the gas arrival time interval. The time interval obtained by calculation can ensure that the detection data of the same gas passing through different gas detectors can be identified. Therefore, the corresponding gas detection data is intercepted according to the time interval to obtain the interval detection data.

[0094] The detection data alignment unit 203 is used to extract gas concentration data from the interval detection data, compare the gas concentration data corresponding to the same gas, calculate the similarity, extract the data with a similarity higher than a preset value, and obtain the aligned detection data.

[0095] In this module, the detection data alignment unit 203 extracts the gas concentration data in the interval detection data. Since the gas transmission speed is not uniform, the time interval corresponding to the later gas detector is larger. In order to determine the data of the same section of gas passing through different gas detectors, the similarity is calculated. Specifically, the gas concentration data corresponding to each gas detector is divided into multiple time slice data according to a preset time step. Five gas detectors correspond to 5 time slice data groups (including time slice data corresponding to multiple time steps). The overlap between the first time slice data group and the subsequent four time slice data groups is calculated, and the part with the highest overlap is selected to obtain the aligned detection data. That is, based on this Find the corresponding data from the subsequent four detection sensors, which is the aligned detection data. When calculating the similarity, if gas detector A contains 10 time slice data and gas detector B contains 20 time slice data, select 10 consecutive time slice data from the time slice data corresponding to B each time in order, and compare them with the time slice data corresponding to A. If the gas concentration difference in the time slice data used for comparison is within the preset range, the time slice data in B is determined to be a valid slice. If, among the 20 time slice data corresponding to B, the 5th to the 14th time slice data contain the most valid slices, the 5th to the 14th time slice data are selected as the aligned detection data corresponding to B.

[0096] like Figure 7 As shown, as a preferred embodiment of the present invention, the data dot matrix construction module 300 includes:

[0097] The multi-dimensional coordinate system construction unit 301 is used to construct a multi-dimensional coordinate space, and the number of data axes in the multi-dimensional coordinate space is the same as the total number of gas types detected by the gas detector.

[0098] In this module, the multidimensional coordinate system construction unit 301 constructs a multidimensional coordinate space and multiple data axes. All data axes are located in the same plane. In order to balance the space model, the scale ratios of the data axes are normalized, and 0-1 is used to represent the gas concentration. For example, the concentration range of gas a (expressed as volume percentage) is 1-5%, 0 represents the concentration of gas a is 1%, and 1 represents the volume percentage of gas a is 5%. The number of data axes in the multidimensional coordinate space is the same as the total number of gas types detected by the gas detector.

[0099] The coordinate marking unit 302 is used to mark each gas concentration data in the aligned detection data in a multi-dimensional coordinate space in time sequence to obtain a data plane dot matrix corresponding to each moment.

[0100] The dot matrix construction unit 303 is used to calculate the centroid position of the data plane dot matrix, combine the centroid position and the corresponding time value, mark it in the multi-dimensional coordinate space, and obtain the data space dot matrix.

[0101] In this module, each gas concentration data in the aligned detection data is marked in the multidimensional coordinate space in chronological order. Taking gas detector A as an example, the concentration values ​​of each gas corresponding to the first time value are read and marked on the corresponding data axis. At this time, multiple data points will appear in the plane where the data axis is located. The center of mass of these data points is calculated to obtain the center of mass position. According to the position of the first time value on the time axis, the center of mass position is translated along the time axis to obtain the first spatial data point. The spatial data points corresponding to each time value are determined accordingly. Subsequently, the aligned detection data is switched to obtain the spatial data points corresponding to all gas detectors and the data space lattice is obtained.

[0102] like Figure 8 As shown, as a preferred embodiment of the present invention, the availability identification module 400 includes:

[0103] The space model building unit 401 is used to select a group of alignment detection data each time and generate a data space model according to the data space dot matrix corresponding to all other alignment detection data.

[0104] In this module, the space model construction unit 401 selects a group of aligned detection data each time. Specifically, which gas detector needs to be tested for availability is selected from the group of aligned detection data. For example, among the five groups of gas detectors ABCDE, gas detector A is selected, and a data space model is generated according to the data space lattice corresponding to the aligned detection data corresponding to BCDE. Specifically, a time value is selected, and the corresponding spatial data points in the data space lattice corresponding to the corresponding time value are retrieved, and the spatial data points are connected with a smooth curve in a counterclockwise direction to obtain an enclosed area. Based on this, multiple enclosed areas are obtained, and two adjacent enclosed areas are lofted to obtain a data space model, such as two circular enclosed areas, which are then lofted to obtain a truncated cone.

[0105] The space curve construction unit 402 is used to construct a data verification space curve based on the selected alignment detection data, and to count the length of the outer curve and the length of the inner curve according to the data space model.

[0106] In this module, the space curve construction unit 402 constructs a data verification space curve based on the selected aligned detection data. The data verification space curve is the data representation obtained by the A gas detector. When it appears inside the data space model, it means that the gas concentration data obtained by this part of the detection is within the allowable range. Otherwise, it means that this part of the data is not within the allowable range. The outer curve length and the inner curve length are counted according to the data space model.

[0107] The data evaluation unit 403 is used to calculate the ratio of the inner curve length to the outer curve length, obtain a data availability evaluation value, and output a recognition result according to a preset interval range.

[0108] In this module, the data evaluation unit 403 calculates the ratio of the inner curve length to the outer curve length, and uses the ratio as the data availability evaluation value. The larger the data availability evaluation value, the stronger the data availability, and vice versa. An availability prediction function is constructed according to the data availability evaluation value, and the availability of the gas detector is predicted based on the availability prediction function, and a prediction result is generated. When the data availability evaluation value recorded in the prediction result is lower than the preset value, the relevant personnel are notified to perform inspection or maintenance.

[0109] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for identifying data availability for a gas detector, characterized in that: The data availability identification method for a gas detector comprises: According to the transportation direction of the gas transmission pipeline, the gas detection data of each gas detector is extracted one by one; The gas detection data is intercepted based on the gas delivery speed, and data alignment is performed according to the intercepted interval detection data to obtain aligned detection data; Constructing a multidimensional coordinate space, marking the alignment detection data in the multidimensional coordinate space to obtain a data space dot matrix, wherein the multidimensional coordinate space includes a time axis and multiple data axes, all the data axes are coplanar, and the time axis is perpendicular to all the data axes; Each time a set of alignment detection data is selected, a data space model is constructed based on other alignment detection data, the availability of the selected alignment detection data is calculated, and the recognition result is output; The step of constructing a multidimensional coordinate space, marking the alignment detection data in the multidimensional coordinate space, and obtaining a data space dot matrix specifically includes: Constructing a multidimensional coordinate space, wherein the number of data axes in the multidimensional coordinate space is the same as the total number of gas types detected by the gas detector; Mark each gas concentration data in the aligned detection data in the multi-dimensional coordinate space in chronological order to obtain the data plane dot matrix corresponding to each moment; Calculate the centroid position of the data plane dot matrix, combine the centroid position and the corresponding time value, mark it in the multidimensional coordinate space, and obtain the data space dot matrix; The step of selecting a group of alignment detection data each time, building a data space model based on other alignment detection data, calculating the availability of the selected alignment detection data, and outputting the recognition result specifically includes: Each time a set of alignment detection data is selected, a data space model is generated according to the data space lattice corresponding to all other alignment detection data; A data verification space curve is constructed based on the selected alignment detection data, and the length of the outer curve and the length of the inner curve are counted according to the data space model; The ratio of the inner curve length to the outer curve length is calculated to obtain the data availability assessment value, and the recognition result is output according to the preset interval range.

2. The data availability identification method for a gas detector according to claim 1, characterized in that: The step of intercepting the gas detection data based on the gas delivery speed, and performing data alignment according to the intercepted interval detection data to obtain the aligned detection data specifically includes: Obtaining the gas delivery speed, and determining the gas arrival time interval corresponding to each gas detector based on the gas delivery speed; The corresponding gas detection data is intercepted based on the gas arrival time interval to obtain the interval detection data within the corresponding time interval; Extract gas concentration data from interval detection data, compare gas concentration data corresponding to the same gas, calculate similarity, extract data with similarity higher than a preset value, and obtain aligned detection data.

3. The data availability identification method for a gas detector according to claim 1, characterized in that: An availability prediction function is constructed according to the data availability evaluation value of each gas detector, the availability of the gas detector is predicted based on the availability prediction function, and a prediction result is generated.

4. A data availability identification system for a gas detector, characterized in that: The data availability identification system for a gas detector comprises: A data acquisition module, used to extract gas detection data of each gas detector one by one according to the transportation direction of the gas transmission pipeline; A data alignment module is used to intercept the gas detection data based on the gas delivery speed, and perform data alignment according to the intercepted interval detection data to obtain aligned detection data; A data dot matrix construction module is used to construct a multi-dimensional coordinate space, mark the alignment detection data in the multi-dimensional coordinate space, and obtain a data space dot matrix, wherein the multi-dimensional coordinate space includes a time axis and multiple data axes, all the data axes are coplanar, and the time axis is perpendicular to all the data axes; Availability identification module, used for selecting a set of alignment detection data each time, building a data space model based on other alignment detection data, calculating the availability of the selected alignment detection data, and outputting the identification result; The data lattice construction module comprises: A multi-dimensional coordinate system construction unit, used for constructing a multi-dimensional coordinate space, wherein the number of data axes in the multi-dimensional coordinate space is the same as the total number of gas types detected by the gas detector; A coordinate marking unit is used to mark each gas concentration data in the aligned detection data in a multi-dimensional coordinate space in chronological order to obtain a data plane dot matrix corresponding to each moment; A dot matrix construction unit is used to calculate the centroid position of the data plane dot matrix, combine the centroid position and the corresponding time value, mark it in the multi-dimensional coordinate space, and obtain the data space dot matrix; The availability identification module includes: A spatial model building unit, for selecting a set of alignment detection data each time, and generating a data space model according to data space lattices corresponding to all other alignment detection data; A space curve construction unit, used to construct a data verification space curve based on the selected alignment detection data, and to count the length of the outer curve and the length of the inner curve according to the data space model; The data evaluation unit is used to calculate the ratio of the inner curve length to the outer curve length, obtain the data availability evaluation value, and output the recognition result according to the preset interval range.

5. The data availability identification system for gas detectors according to claim 4, characterized in that: The data alignment module comprises: A delivery speed acquisition unit, used to acquire the gas delivery speed, and determine the gas arrival time interval corresponding to each gas detector based on the gas delivery speed; A data interception unit, used to intercept the corresponding gas detection data based on the gas arrival time interval to obtain the interval detection data within the corresponding time interval; The detection data alignment unit is used to extract gas concentration data from the interval detection data, compare the gas concentration data corresponding to the same gas, calculate the similarity, extract data with a similarity higher than a preset value, and obtain aligned detection data.

6. The data availability identification system for gas detectors according to claim 4, characterized in that: An availability prediction function is constructed according to the data availability evaluation value of each gas detector, the availability of the gas detector is predicted based on the availability prediction function, and a prediction result is generated.

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