An environmental gas monitoring system and method based on a sensor network

Abstract

The application relates to the technical field of environment gas monitoring, in particular to an environment gas monitoring system and method based on a sensor network, which comprises an extended correlation chain construction module; the extended correlation chain construction module screens environment gas effective monitoring points in a to-be-measured region according to the obtained running state interference influence value corresponding to each gas sensor; and the extended correlation chain corresponding to each effective monitoring point in the to-be-measured region is constructed in combination with the relationship between the corresponding historical monitoring data between adjacent gas sensors at any position in the to-be-measured region. In the process of monitoring environment gas, the safety problem of the running state of the sensor network is considered, the monitoring result deviation caused by the environment information of the gas sensor is considered in the process, the screening of the effective monitoring points in the to-be-monitored region is realized, the corresponding extended correlation chain is constructed based on the screened effective monitoring points, and the supervision and early warning of the running state of the sensor network in the to-be-measured region are realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of environmental gas monitoring, in particular to an environmental gas monitoring system and method based on a sensor network. BACKGROUND

[0002] A gas sensor is a sensor used to detect the types, compositions and corresponding composition contents of gases present in the environment, and is widely used in industrial fields to identify and detect the content of toxic gases in the air, thereby achieving timely early warning of toxic gases. In actual use, people usually use multiple gas sensors to build a sensor network to effectively monitor toxic gases in the monitored area, avoid monitoring result deviations caused by accidental damage of the gas sensor, and also predict the diffusion of toxic gases, thereby reducing the impact of toxic gas diffusion on people.

[0003] The existing environmental gas monitoring system based on a sensor network usually directly analyzes the composition and diffusion area of toxic gases according to the monitoring results of the gas sensor, but does not consider the deviation of the monitoring results of the gas sensor itself, thereby failing to accurately select effective monitoring points in the monitored area and accurately screen the monitoring results. In addition, the monitoring of the running state of the gas sensor during use usually adopts a one-by-one inspection method, which cannot reduce the inspection range in advance, resulting in high inspection costs. Therefore, the existing environmental gas monitoring system based on a sensor network has great defects. SUMMARY

[0004] The present application aims to provide an environmental gas monitoring system and method based on a sensor network to solve the problems raised in the background.

[0005] To solve the above technical problems, the present application provides the following technical solution: an environmental gas monitoring method based on a sensor network, comprising the following steps:

[0006] S1, obtaining the positions of all gas sensors in the monitored area, numbering the obtained gas sensors, binding the obtained numbers with the corresponding gas sensor positions, and obtaining the environmental information within a preset radius around each sensor position; each gas sensor in the monitored area collects data at the same time every unit time, and the unit time and the preset radius are both constants preset in the database;

[0007] S2, analyzing the running state interference influence value of each gas sensor in the monitored area at the current time according to the historical monitoring data of each gas sensor in the monitored area and the environmental information corresponding to each gas sensor.

[0008] S3, screen the effective monitoring points of the environmental gas in the to-be-measured region according to the running state interference influence value corresponding to each gas sensor; and construct an expansion correlation chain corresponding to each effective monitoring point in the to-be-measured region by combining the relationship between the corresponding historical monitoring data between the adjacent gas sensors at any position in the to-be-measured region, wherein each expansion correlation chain contains an effective monitoring point, and each node in each expansion correlation chain corresponds to a gas sensor, and each node in each expansion correlation chain is taken as an element to construct a corresponding node set;

[0009] S4, obtain the union set of the node sets corresponding to each expansion correlation chain obtained in S3, and determine the running state of the sensor network in the to-be-measured region according to the comparison result of the number of elements in the obtained union set and the total number of gas sensors in the to-be-measured region, and generate a patrol inspection task for the sensor network for monitoring the environmental gas and feed back to the administrator in the case of abnormal running state.

[0010] Further, the number of the i-th gas sensor in the to-be-measured region is denoted as Ai in S1, and the position of the Ai corresponding gas sensor is denoted as Bi.

[0011] The environmental information includes a field intensity variation interval disturbed by a surrounding interference source and a dust accumulation speed in the air, the dust accumulation speed in the air is equal to the average accumulation thickness of the dust in the air within a preset radius range around the corresponding gas sensor position per unit time, and the field intensity disturbed by the surrounding interference source in the environmental information has differences in corresponding values at different times.

[0012] Further, the method for analyzing the running state interference influence value of each gas sensor in the to-be-measured region at the current time in S2 includes the following steps:

[0013] S21, obtain the aging coefficient corresponding to the i-th gas sensor in the to-be-measured region at the current time, denoted as Li, wherein the aging coefficient represents the ratio of the actual use time length of the current i-th gas sensor to the theoretical use time length of the i-th gas sensor, the theoretical use time length of the i-th gas sensor is equal to the average value of the actual service life of each gas sensor corresponding to the i-th gas sensor position replacement in the historical data, and the actual service life of the gas sensor is equal to the corresponding time length from the start of use to the replacement by a new gas sensor;

[0014] S22, obtain the environmental information corresponding to Ai, denoted as Ci;

[0015] S23, obtain the running state interference influence value of the i-th gas sensor in the to-be-measured region at the current time, denoted as Gi,

[0016] Gi=(Li+Cdi)·(1+Cgi)·eCcgi ,

[0017] Wherein, Cpgi represents the value corresponding to the midpoint of the field intensity variation interval of Ci interfered by the surrounding interference source, Ccgi represents the length of the field intensity variation interval of Ci interfered by the surrounding interference source, and Cdi represents the accumulation speed of dust in the air in Ci.

[0018] In the present application, e Ccgi The stability coefficient corresponding to the field intensity variation interval of Ci interfered by the surrounding interference source is analyzed; the influence value of the running state interference of the gas sensor is because the gas sensor may cause a large deviation in the monitoring result after being affected by the external environment. The commonly used gas sensor has a service life, and the specific service life may differ according to different use scenarios and use states. At the same time, in the use process of the gas sensor, dust in the air will gradually settle and adhere to the air inlet of the gas sensor, affecting the delivery of the monitored gas in the environment by the gas sensor, and further affecting the monitoring result of the gas sensor. After the gas sensor is affected by external electromagnetic interference, the monitoring signal of the gas sensor may fluctuate greatly, and the monitoring result may deviate greatly.

[0019] Further, in the S3, when the effective monitoring points of the environmental gas in the to-be-measured region are screened, the obtained running state interference influence value corresponding to each gas sensor is obtained, the obtained running state interference influence value corresponding to the gas sensor is compared with the state interference threshold value, and the state interference threshold value is a constant preset in the database,

[0020] The positions of all the gas sensors corresponding to the running state interference influence value in the to-be-measured region are less than or equal to the state interference threshold value are taken as the effective monitoring points of the environmental gas in the to-be-measured region.

[0021] In the present application, the effective monitoring points of the environmental gas are obtained for subsequent steps to obtain each expansion correlation chain, and each expansion correlation chain contains one or more effective monitoring points of the environmental gas.

[0022] Further, the method for constructing the expansion correlation chain corresponding to each effective monitoring point in the to-be-measured region in the S3 includes the following steps:

[0023] S31, the relationship between the corresponding historical monitoring data between the adjacent gas sensors at any position in the to-be-measured region is obtained, the obtained relationship is the relationship between the gas detection deviation rate and the running state interference influence deviation value, and different gas sensors with a distance between the positions of the gas sensors less than the distance preset in the database are determined as the adjacent gas sensors;

[0024] Let the number of any one gas sensor adjacent to the i-th gas sensor position be denoted as Ai, and the gas detection deviation rate between Ai and AI at any time point T in the historical data be denoted as PQ (Ai，AI) , the running state interference influence deviation value between Ai and AI at time point T in the historical data is denoted as PG (Ai，AI) , the PG (Ai，AI) is equal to the difference between the running state interference influence value corresponding to Ai and the running state interference influence value corresponding to AI at time T in the historical data; by default, the specifications of each gas sensor in the to-be-tested region are the same;

[0025]

[0026] Wherein, j1 represents the number of monitoring gas types corresponding to Ai and AI; β j represents the deviation conversion coefficient of the j-th gas monitored by the gas sensor, and β j is obtained by querying the database preset form; DAi j represents the monitoring result corresponding to the j-th gas in the monitoring result corresponding to Ai at time point T in the historical data; DAI j represents the monitoring result corresponding to the j-th gas in the monitoring result corresponding to AI at time point T in the historical data;

[0027] The correlation data pair corresponding to the monitoring data between Ai and AI at time point T is constructed and denoted as (PG (Ai，AI) , PQ (Ai，AI) ) ;

[0028] A plane rectangular coordinate system is constructed with o as the origin, the running state interference influence deviation value as the x-axis and the gas detection deviation rate as the y-axis. The coordinate points corresponding to each correlation data pair are marked in the plane rectangular coordinate system, and the coordinate points in the plane rectangular coordinate system are linearly fitted according to the linear regression equation formula. The function corresponding to the fitting result is taken as the relationship function between the historical monitoring data between Ai and AI in the to-be-tested region;

[0029] The average value of the distance between each marked point in the plane rectangular coordinate system and the fitting function is taken as the average deviation fluctuation value of the relationship between Ai and AI in the to-be-tested region;

[0030] S32, taking any one of the effective monitoring points of the gas as a starting node, obtaining any one of the gas sensors adjacent to the position of the gas sensor corresponding to the starting node and the starting node to form an extended relationship analysis pair, obtaining different extended relationship analysis pairs, each of the obtained extended relationship analysis pairs contains a gas sensor adjacent to the position of the starting node; each extended relationship analysis pair contains two elements, the first element is a node in the known extended correlation chain, and the second element is a gas sensor to be analyzed;

[0031] S33, respectively judging whether the second element in each extended relationship analysis pair is a node expanded by the first element on the extended correlation chain to which the first element belongs;

[0032] Obtain the relationship function between the corresponding historical monitoring data between the gas sensors corresponding to the first element and the second element, denoted as F(x); obtain the average deviation fluctuation value of the relationship between the gas sensors corresponding to the first element and the second element, denoted as R;

[0033] The gas detection deviation rate of the gas sensor corresponding to the first element and the second element in the corresponding monitoring data of the last obtained monitoring data is denoted as Zq, and the running state interference influence deviation value of the gas sensor corresponding to the first element and the second element in the corresponding monitoring data of the last obtained monitoring data is denoted as Zg;

[0034] The function value obtained after substituting Zg into x in F(x) is denoted as F(Zg);

[0035] When Zq belongs to [F(Zg)-R, F(Zg)+R], it is determined that the second element in the corresponding extended relationship analysis pair is a node expanded by the first element on the extended correlation chain to which the first element belongs, and the second element is added to the extended correlation chain to which the first element belongs.

[0036] When Zq does not belong to [F(Zg)-R, F(Zg)+R], it is determined that the second element in the corresponding extended relationship analysis pair is not a node expanded by the first element on the extended correlation chain to which the first element belongs.

[0037] S34, when the second element in the extended relationship analysis pair is a node expanded by the first element on the extended correlation chain, obtain all the gas sensors adjacent to the position of the second element in the corresponding extended analysis pair, and take the second element in the corresponding extended analysis pair as a node to construct different extended relationship analysis pairs, and jump to S33;

[0038] S35, when the second element in the extended relationship analysis pair is not a node expanded by the first element on the extended correlation chain, stop constructing the extended relationship analysis pair with the second element in the corresponding extended analysis pair as a node;

[0039] S36, when all nodes on the corresponding extended correlation chain and the gas sensor adjacent to the position of the corresponding node are analyzed, the corresponding extended correlation chain is output.

[0040] In the application, the relationship between the corresponding historical monitoring data between the gas sensors adjacent to any position in the to-be-measured region is obtained, in order to determine whether the second element in the extended relationship analysis pair is an extended node of the first element, and then generate a completed extended correlation chain; when the second element in the extended relationship analysis pair is an extended node of the first element, it is indicated that the data fluctuation of the second element meets the data change rule between the two, and the running state of the second element can be determined to be normal to a certain extent.

[0041] Further, when the number of elements in the obtained set is less than the total number of gas sensors in the to-be-measured region, it is determined that the running state of the sensor network for monitoring environmental gas in the to-be-measured region is abnormal; when the number of elements in the obtained set is equal to the total number of gas sensors in the to-be-measured region, it is determined that the running state of the sensor network for monitoring environmental gas in the to-be-measured region is normal.

[0042] The inspection and investigation task includes an inspection and investigation object in the sensor network for monitoring environmental gas, and the inspection and investigation object is a gas sensor in the to-be-measured region.

[0043] In the S4, the inspection and investigation object in the inspection and investigation task of the sensor network for monitoring environmental gas is obtained, and the inspection and investigation object is a gas sensor corresponding to a chain missing node and a chain abnormal end point respectively.

[0044] The gas sensor corresponding to the chain missing node is all the gas sensors in the to-be-measured region, which are not in the set of all nodes corresponding to the obtained respective extended correlation chains.

[0045] The gas sensor corresponding to the chain abnormal end point is a gas sensor corresponding to all nodes in the extended correlation chain, whose interference investigation correlation proportion is less than a preset value and is not an effective monitoring point; the interference investigation correlation proportion is equal to the quotient of the number of gas sensors adjacent to the position of the corresponding node and belonging to the node of the corresponding extended correlation chain divided by the total number of gas sensors adjacent to the position of the corresponding node.

[0046] An environmental gas monitoring system based on a sensor network, the system comprising the following modules:

[0047] The sensor data collection module acquires all gas sensor positions in the to-be-tested region, numbers the acquired gas sensors, binds the acquired numbers with the corresponding gas sensor positions, and acquires environmental information within a preset radius around each sensor position;

[0048] The running interference analysis module analyzes the running state interference influence value of each gas sensor in the to-be-tested region at the current time according to the historical monitoring data of each gas sensor in the to-be-tested region and the environmental information corresponding to each gas sensor.

[0049] The extended correlation chain construction module filters the effective monitoring points of environmental gas in the to-be-tested region according to the running state interference influence value of each gas sensor, and constructs the extended correlation chain corresponding to each effective monitoring point in the to-be-tested region in combination with the relationship between the corresponding historical monitoring data between the adjacent gas sensors at any position in the to-be-tested region.

[0050] The inspection and investigation task supervision module acquires the union set of the node sets corresponding to each extended correlation chain in the extended correlation chain construction module, judges the running state of the sensor network in the to-be-tested region according to the comparison result of the number of elements in the acquired union set and the total number of gas sensors in the to-be-tested region, generates the inspection and investigation task of the sensor network for monitoring environmental gas in the case of abnormal running state, and feeds back to the administrator.

[0051] Further, the extended correlation chain construction module includes an effective monitoring point filtering unit and a correlation chain construction unit,

[0052] The effective monitoring point filtering unit filters the effective monitoring points of environmental gas in the to-be-tested region according to the running state interference influence value of each gas sensor.

[0053] The correlation chain construction unit constructs the extended correlation chain corresponding to each effective monitoring point in the to-be-tested region in combination with the relationship between the corresponding historical monitoring data between the adjacent gas sensors at any position in the to-be-tested region.

[0054] Further, the inspection and investigation task supervision module includes a correlation chain union element analysis unit and an inspection and investigation task generation and feedback unit,

[0055] The correlation chain union element analysis unit acquires the union set of the node sets corresponding to each extended correlation chain in the extended correlation chain construction module.

[0056] The inspection and troubleshooting task generation feedback unit judges the sensor network operation state in the to-be-tested region according to a comparison result of the obtained number of elements and the total number of gas sensors in the to-be-tested region, and generates an inspection and troubleshooting task of the sensor network for monitoring the environmental gas and feeds back to the administrator in the case that the operation state is abnormal.

[0057] Compared with the prior art, the present application has the following beneficial effects: in the process of monitoring the environmental gas, the present application considers the operation state safety problem of the sensor network, considers the monitoring result deviation caused by the environmental information of the gas sensor in the process, realizes the screening of the effective monitoring points in the to-be-monitored region, and constructs the corresponding expansion correlation chain based on the screened effective monitoring points (starting points), and further realizes the supervision and early warning of the sensor network operation state in the to-be-tested region, and ensures the stability and accuracy of the sensor network. BRIEF DESCRIPTION OF DRAWINGS

[0058] The accompanying drawings are included to provide a further understanding of the present application, and constitute a part of the specification, illustrate the present application together with the embodiments thereof, and explain the technical solutions of the present application, but do not constitute a limitation on the present application. In the drawings:

[0059] Figure 1 is a flow diagram of an environmental gas monitoring method based on a sensor network according to the present application;

[0060] Figure 2 is a structural diagram of an environmental gas monitoring system based on a sensor network according to the present application. DETAILED DESCRIPTION

[0061] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0062] Please refer to Figure 1 The present application provides a technical solution: an environmental gas monitoring method based on a sensor network, which comprises the following steps:

[0063] S1, obtaining the positions of all gas sensors in a to-be-tested region, numbering the obtained gas sensors, binding the obtained numbers with the corresponding gas sensor positions, and obtaining the environmental information within a preset radius around each sensor position; each gas sensor in the to-be-tested region collects once at the same time every unit time, and the unit time and the preset radius are both constants pre-stored in a database;

[0064] The number of the i-th gas sensor in the to-be-tested region in the S1 is recorded as Ai; the position of the Ai corresponding gas sensor is recorded as Bi;

[0065] The environmental information includes a field intensity variation interval disturbed by a peripheral interference source and a dust accumulation speed in the air, the dust accumulation speed in the air is equal to an average accumulation thickness of the dust in the air within a preset radius range around the position of the corresponding gas sensor in a unit time, and the field intensity disturbed by the peripheral interference source in the environmental information has a difference in corresponding values at different times.

[0066] S2, according to the historical monitoring data of each gas sensor in the to-be-tested region and the environmental information corresponding to each gas sensor, analyzing an operating state interference influence value of each gas sensor in the to-be-tested region at the current time;

[0067] The method for analyzing the operating state interference influence value of each gas sensor in the to-be-tested region at the current time in the S2 includes the following steps:

[0068] S21, obtaining an aging coefficient corresponding to the i-th gas sensor in the to-be-tested region at the current time, recorded as Li, the aging coefficient represents a ratio of an actual use length of the current i-th gas sensor to a theoretical use length of the i-th gas sensor, the theoretical use length of the i-th gas sensor is equal to an average value of actual service lives corresponding to each gas sensor replaced by the i-th gas sensor position in the historical data, and the actual service life of the gas sensor is equal to a corresponding time length from the start of use to the replacement by a new gas sensor;

[0069] S22, obtaining the environmental information corresponding to Ai, recorded as Ci;

[0070] S23, obtaining an operating state interference influence value of the i-th gas sensor in the to-be-tested region at the current time, recorded as Gi,

[0071] Gi=(Li+Cdi)·(1+Cgi)·e Ccgi ,

[0072] Wherein, Cpgi represents a value corresponding to a midpoint of the field intensity variation interval disturbed by the peripheral interference source in Ci, Ccgi represents a length of the field intensity variation interval disturbed by the peripheral interference source in Ci, and Cdi represents the dust accumulation speed in the air in Ci.

[0073] S3, screening the effective monitoring points of the environmental gas in the to-be-measured area according to the obtained running state interference influence value corresponding to each gas sensor; constructing an extended correlation chain corresponding to each effective monitoring point in the to-be-measured area in combination with the relationship between the corresponding historical monitoring data between the adjacent gas sensors at any position in the to-be-measured area, each extended correlation chain containing the effective monitoring points and each node in each extended correlation chain corresponding to a gas sensor, and taking all the nodes in each extended correlation chain as an element to construct a corresponding node set;

[0074] In the S3, when the effective monitoring points of the environmental gas in the to-be-measured area are screened, the running state interference influence value corresponding to each gas sensor is obtained, and the running state interference influence value corresponding to the gas sensor is compared with a state interference threshold, the state interference threshold being a constant preset in the database,

[0075] The positions of all the gas sensors with the corresponding running state interference influence value less than or equal to the state interference threshold in the to-be-measured area are taken as the effective monitoring points of the environmental gas in the to-be-measured area.

[0076] In the embodiment, when the effective monitoring points of the environmental gas are screened, if there is no effective monitoring point of the environmental gas, the subsequent generated extended correlation chain is empty, that is, there is no corresponding extended correlation chain, and the subsequent inspection and investigation object of the inspection and investigation task is all the gas sensors in the to-be-measured area.

[0077] The method for constructing the extended correlation chain corresponding to each effective monitoring point in the to-be-measured area in the S3 includes the following steps:

[0078] S31, obtaining the relationship between the corresponding historical monitoring data between the adjacent gas sensors at any position in the to-be-measured area, the obtained relationship being the relationship between the gas detection deviation rate and the running state interference influence deviation value, and determining the different gas sensors with the distance between the positions of the gas sensors less than the distance preset in the database as the position-adjacent gas sensors;

[0079] Taking the number of any one gas sensor adjacent to the position of the ith gas sensor as AI, and taking the gas detection deviation rate between Ai and AI at any time point T in the historical data as PQ (Ai，AI) Taking the running state interference influence deviation value between Ai and AI at the time point T in the historical data as PG (Ai，AI) The PG (Ai，AI) is equal to the difference between the running state interference influence value corresponding to Ai and the running state interference influence value corresponding to AI at the time T in the historical data; by default, the specifications of the gas sensors in the to-be-measured area are the same;

[0080]

[0081] wherein, j1 represents the number of the monitoring gas species of the gas sensor corresponding to Ai and AI; β j represents the deviation conversion coefficient of the jth gas monitored by the gas sensor, and β j is obtained by querying the database preset form; DAi j represents the monitoring result of the jth gas in the monitoring result corresponding to Ai at time point T in the historical data; DAI j represents the monitoring result of the jth gas in the monitoring result corresponding to AI at time point T in the historical data;

[0082] In this embodiment, the monitoring result of each type of gas by the gas sensor is the concentration of the corresponding gas;

[0083] The correlation data pair corresponding to the monitoring data between Ai and AI at time point T is constructed, denoted as (PG (Ai，AI) , PQ (Ai，AI) );

[0084] A plane rectangular coordinate system is constructed with o as the origin, the running state interference influence deviation value as the x-axis and the gas detection deviation rate as the y-axis. The coordinate points corresponding to each correlation data pair are marked in the plane rectangular coordinate system, and the coordinate points in the plane rectangular coordinate system are linearly fitted according to the linear regression equation formula. The function corresponding to the fitting result is taken as the relationship function between the corresponding historical monitoring data between Ai and AI in the to-be-measured region;

[0085] The average value of the distance between each marked point in the plane rectangular coordinate system and the fitting function is taken as the average deviation fluctuation value of the relationship between Ai and AI in the to-be-measured region;

[0086] S32, taking any one gas effective monitoring point as a starting node, obtaining an extended relationship analysis pair composed of any one gas sensor adjacent to the gas sensor position corresponding to the starting node and the starting node, obtaining different extended relationship analysis pairs, each of which contains a gas sensor adjacent to the position of the starting node; each extended relationship analysis pair contains two elements, the first element is a node in the known extended correlation chain, and the second element is a gas sensor to be analyzed;

[0087] S33, respectively judging whether the second element in each extended relationship analysis pair is a node extended from the first element on the first element of the extended correlation chain;

[0088] Obtain the relationship function between the corresponding historical monitoring data between the gas sensors corresponding to the first element and the second element, denoted as F(x); obtain the average deviation fluctuation value of the relationship between the gas sensors corresponding to the first element and the second element, denoted as R;

[0089] Let the gas detection deviation rate of the gas sensor corresponding to the first element and the second element respectively in the latest acquired monitoring data correspond to Zq, and the running state interference influence deviation value of the gas sensor corresponding to the first element and the second element respectively in the latest acquired monitoring data correspond to Zg;

[0090] The function value obtained after substituting Zg into x in F(x) is recorded as F(Zg);

[0091] When Zq belongs to [F(Zg)-R, F(Zg)+R], it is determined that the second element is the node expanded by the first element on the expansion correlation chain to which the first element belongs in the corresponding expansion relationship analysis pair, and the second element is added to the expansion correlation chain to which the first element belongs;

[0092] When Zq does not belong to [F(Zg)-R, F(Zg)+R], it is determined that the second element is not the node expanded by the first element on the expansion correlation chain to which the first element belongs in the corresponding expansion relationship analysis pair;

[0093] S34, when the second element in the expansion relationship analysis pair is the node expanded by the first element on the expansion correlation chain, all gas sensors adjacent to the position of the second element in the corresponding expansion analysis pair are acquired, and the second element in the corresponding expansion analysis pair is taken as a node. Different expansion relationship analysis pairs are constructed, and jump to S33;

[0094] S35, when the second element in the expansion relationship analysis pair is not the node expanded by the first element on the expansion correlation chain, stop constructing the expansion relationship analysis pair with the second element in the corresponding expansion analysis pair as the node;

[0095] S36, when all nodes on the corresponding expansion correlation chain and the gas sensors adjacent to their positions construct the expansion relationship analysis pair, output the corresponding expansion correlation chain.

[0096] In this embodiment, the same gas sensor may have different results in the determination of the corresponding expansion nodes of different nodes in the same expansion correlation chain;

[0097] For example, there are two nodes of ethyl and propyl in the expansion correlation chain U, there is a gas sensor A, and the positions of the gas sensors corresponding to A are adjacent to the positions of the gas sensors corresponding to ethyl and propyl, respectively, the position of the gas sensor corresponding to ethyl is not adjacent to the position of the gas sensor corresponding to propyl,

[0098] If A is the expansion node of ethyl, if A is the expansion node of propyl,

[0099] Then the expansion correlation chain U contains nodes A, ethyl and propyl at the same time;

[0100] S4. Obtain the union of the node sets corresponding to each extended association chain obtained in S3. Based on the comparison between the number of elements in the obtained union and the total number of gas sensors in the area to be tested, determine the operating status of the sensor network in the area to be tested. If the operating status is abnormal, generate an inspection and troubleshooting task for the sensor network monitoring the ambient gas and report it to the administrator.

[0101] In step S4, when determining the operating status of the sensor network in the area to be tested, if the number of elements in the obtained union is less than the total number of gas sensors in the area to be tested, then the operating status of the sensor network monitoring the ambient gas in the area to be tested is determined to be abnormal; if the number of elements in the obtained union is equal to the total number of gas sensors in the area to be tested, then the operating status of the sensor network monitoring the ambient gas in the area to be tested is determined to be normal.

[0102] The inspection and investigation task includes the inspection and investigation objects in the sensor network that monitors ambient gases, and the inspection and investigation objects are the gas sensors in the area to be measured;

[0103] When the inspection and investigation objects are obtained in the inspection and investigation task of the sensor network for monitoring ambient gases in S4, the inspection and investigation objects are the gas sensors corresponding to the missing nodes and abnormal endpoints of the chain, respectively.

[0104] The gas sensors corresponding to the missing nodes in the chain are all gas sensors in the area to be tested that are not included in the union of the sets of nodes corresponding to each of the obtained extended association chains.

[0105] The gas sensors corresponding to the abnormal endpoints of the chain are the gas sensors corresponding to all nodes in the extended association chain whose interference investigation association ratio is less than a preset value and which are not effective monitoring points; the interference investigation association ratio is equal to the quotient of the number of gas sensors that are adjacent to the corresponding node and belong to the extended association chain node of the corresponding node divided by the total number of gas sensors that are adjacent to the corresponding node.

[0106] like Figure 2 As shown, an environmental gas monitoring system based on a sensor network includes the following modules:

[0107] The sensor data acquisition module acquires the locations of all gas sensors in the area to be measured, assigns numbers to the gas sensors, binds the assigned numbers to the corresponding gas sensor locations, and acquires environmental information within a preset radius around each sensor location.

[0108] running interference analysis module, the running interference analysis module analyzes the running state interference influence value of each gas sensor in the to-be-tested region according to historical monitoring data of each gas sensor in the to-be-tested region and corresponding environmental information of each gas sensor;

[0109] The extended correlation chain construction module screens the effective monitoring points of environmental gas in the to-be-tested region according to the running state interference influence value of each gas sensor, and constructs the extended correlation chain corresponding to each effective monitoring point in the to-be-tested region in combination with the relationship between the corresponding historical monitoring data between the adjacent gas sensors at any position in the to-be-tested region.

[0110] The inspection and investigation task supervision module obtains the union set of the node sets corresponding to each extended correlation chain obtained in the extended correlation chain construction module, judges the running state of the sensor network in the to-be-tested region according to the comparison result of the number of elements in the obtained union set and the total number of gas sensors in the to-be-tested region, and generates the inspection and investigation task of the sensor network for monitoring environmental gas and feeds back to the administrator in the case of abnormal running state.

[0111] The extended correlation chain construction module includes an effective monitoring point screening unit and a correlation chain construction unit,

[0112] The effective monitoring point screening unit screens the effective monitoring points of environmental gas in the to-be-tested region according to the running state interference influence value of each gas sensor.

[0113] The correlation chain construction unit constructs the extended correlation chain corresponding to each effective monitoring point in the to-be-tested region in combination with the relationship between the corresponding historical monitoring data between the adjacent gas sensors at any position in the to-be-tested region.

[0114] The inspection and investigation task supervision module includes a correlation chain union element analysis unit and an inspection and investigation task generation and feedback unit,

[0115] The correlation chain union element analysis unit obtains the union set of the node sets corresponding to each extended correlation chain obtained in the extended correlation chain construction module.

[0116] The inspection and investigation task generation and feedback unit judges the running state of the sensor network in the to-be-tested region according to the comparison result of the number of elements in the obtained union set and the total number of gas sensors in the to-be-tested region, and generates the inspection and investigation task of the sensor network for monitoring environmental gas and feeds back to the administrator in the case of abnormal running state.

[0117] It is to be noted that, in the present text, relational terms such as first and second and the like can be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus.

[0118] Finally, it should be noted that the above-mentioned only constitutes the preferred embodiments of the present application and is not intended to limit the present application. Although the present application has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications, equivalent replacements, improvements and the like of the technical solutions described in the foregoing embodiments can still be made. Any modifications, equivalent replacements, improvements and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. An environmental gas monitoring method based on sensor networks, characterized in that, The method includes the following steps: S1. Obtain the locations of all gas sensors in the area to be tested, number the obtained gas sensors, bind the obtained numbers to the corresponding gas sensor locations, and obtain the environmental information within a preset radius around each sensor location; each gas sensor in the area to be tested collects data once at a time interval, and the time interval and preset radius are both constants preset in the database. S2. Based on the historical monitoring data of each gas sensor in the test area and the environmental information corresponding to each gas sensor, analyze the impact value of the operating status interference on each gas sensor in the test area at the current time. S3. Based on the obtained operating status interference impact value of each gas sensor, select the effective monitoring points of environmental gas in the area to be tested; combine the relationship between the historical monitoring data of adjacent gas sensors in any position in the area to be tested, construct the extended association chain corresponding to each effective monitoring point in the area to be tested, each extended association chain contains an effective monitoring point, and each node in each extended association chain corresponds to a gas sensor, and construct the corresponding node set with all nodes in each extended association chain as an element. S4. Obtain the union of the node sets corresponding to each extended association chain obtained in S3. Based on the comparison between the number of elements in the union and the total number of gas sensors in the area to be tested, determine the operating status of the sensor network in the area to be tested. If the operating status is abnormal, generate an inspection and troubleshooting task for the sensor network monitoring the ambient gas and report it to the administrator. The method for analyzing the impact of operational state interference on each gas sensor within the test area at the current time in step S2 includes the following steps: S21. Obtain the aging coefficient of the i-th gas sensor in the test area at the current time, denoted as Li. The aging coefficient represents the ratio of the actual usage time of the i-th gas sensor to the theoretical usage time of the i-th gas sensor. The theoretical usage time of the i-th gas sensor is equal to the average of the actual lifespans of each gas sensor replaced by the i-th gas sensor in the historical data. The actual lifespan of the gas sensor is equal to the time from the start of use of the corresponding gas sensor to its replacement by a new gas sensor. S22. Obtain the environmental information corresponding to Ai, denoted as Ci; S23. Obtain the value of the operating state interference affecting the i-th gas sensor in the test area at the current time, denoted as Gi. Gi=(Li+Cdi) (1+Cgi) and Ccgi , Where Cgi represents the value corresponding to the midpoint of the field intensity variation interval in Ci affected by surrounding interference sources, Ccgi represents the length of the field intensity variation interval in Ci affected by surrounding interference sources, and Cdi represents the accumulation velocity of dust in the air in Ci. The method for constructing extended correlation chains corresponding to each effective monitoring point within the test area in S3 includes the following steps: S31. Obtain the relationship between historical monitoring data of gas sensors that are adjacent to each other in the test area. The obtained relationship is the relationship between gas detection deviation rate and deviation value affected by interference in operation status. Different gas sensors whose distance between gas sensor positions is less than the preset distance in the database are identified as adjacent gas sensors. Let AI be the number of any gas sensor adjacent to the location of the i-th gas sensor, and let PQ be the gas detection deviation rate between Ai and AI at any time point T in the historical data. （Ai，AI） The deviation value of the interference effect of the running status between Ai and AI at time T in the historical data is denoted as PG. （Ai，AI） The PG （Ai，AI） It equals the difference between the operating state interference impact value corresponding to Ai and the operating state interference impact value corresponding to AI at time T in the historical data; it is assumed that the specifications and models of all gas sensors in the test area are the same. ， Where j1 represents the number of gas types monitored by the gas sensors corresponding to Ai and AI; β j Let β represent the deviation conversion coefficient of the j-th gas monitored by the gas sensor, and β j Retrieved by querying a pre-defined form in the database; DAI j DAI represents the monitoring result for the j-th gas within the monitoring results corresponding to time point T in historical data; j This represents the monitoring result for the j-th gas within the monitoring results corresponding to AI at time point T in the historical data. Construct a correlation data pair between Ai and AI at time point T, corresponding to the monitoring data, denoted as (PG). （Ai，AI） PQ （Ai，AI） ); A Cartesian coordinate system is constructed with o as the origin, the deviation value of the interference effect of the operating state as the x-axis and the gas detection deviation rate as the y-axis. In the Cartesian coordinate system, the coordinate points corresponding to each of the obtained correlation data are marked. The coordinate points in the Cartesian coordinate system are linearly fitted according to the linear regression equation formula. The function corresponding to the fitting result is used as the relationship function between Ai and AI in the test area. The average distance between each marker point in the Cartesian coordinate system and the fitted function is recorded as the average deviation fluctuation value of the relationship between Ai and AI in the test area; S32. Taking any effective gas monitoring point as the starting node, obtain any gas sensor adjacent to the gas sensor position corresponding to the starting node and the extended relationship analysis pair formed by the starting node, and obtain different extended relationship analysis pairs. Each extended relationship analysis pair contains a gas sensor adjacent to the starting node position. Each extended relationship analysis pair contains two elements: the first element is a node in the known extended association chain, and the second element is the gas sensor to be analyzed. S33. Determine whether the second element in each extended relation analysis pair is the node extended by the first element in the extended association chain to which the first element belongs; Get the relationship function between the historical monitoring data of the gas sensors corresponding to the first and second elements, denoted as F(x); get the average deviation fluctuation value of the relationship between the gas sensors corresponding to the first and second elements, denoted as R; Let Zq be the gas detection deviation rate corresponding to the most recently acquired monitoring data of the gas sensors corresponding to the first and second elements respectively, and let Zg be the deviation value of the operating state interference effect corresponding to the most recently acquired monitoring data of the gas sensors corresponding to the first and second elements respectively. The function value obtained by substituting Zg into x in F(x) is denoted as F(Zg). When Zq belongs to [F(Zg)-R, F(Zg)+R], it is determined that in the corresponding extended relation analysis pair, the second element is the node extended by the first element on the extended relation chain to which the first element belongs, and the second element is added to the extended relation chain to which the first element belongs. When Zq does not belong to [F(Zg)-R, F(Zg)+R], it is determined that in the corresponding extended relation analysis pair, the second element is not the node of the first element's extended association chain on which the first element belongs; S34. When the second element in the extended relation analysis pair is a node of the extended association chain to which the first element belongs, obtain all gas sensors that are adjacent to the position of the second element in the corresponding extended relation analysis pair, and take the second element in the corresponding extended relation analysis pair as a node to construct different extended relation analysis pairs respectively, and jump to S33. S35. When the second element in the extended relation analysis pair is not a node of the extended association chain to which the first element belongs, stop constructing the extended relation analysis pair with the second element in the corresponding extended relation analysis pair as a node. S36. After the analysis of the extended relationship between all nodes in the corresponding extended association chain and the gas sensors adjacent to their positions is completed, the corresponding extended association chain is output.

2. The environmental gas monitoring method based on sensor networks according to claim 1, characterized in that: In step S1, the number of the i-th gas sensor in the area to be measured is denoted as Ai; the position of the gas sensor corresponding to Ai is denoted as Bi. The environmental information includes the range of field intensity variation due to interference from surrounding sources and the accumulation rate of dust in the air. The accumulation rate of dust in the air is equal to the average accumulation thickness of dust in the air within a preset radius around the location of the corresponding gas sensor per unit time. The field intensity of interference from surrounding sources in the environmental information varies at different times.

3. The environmental gas monitoring method based on sensor networks according to claim 1, characterized in that: In step S3, when screening effective monitoring points for environmental gases within the test area, the operating state interference impact value corresponding to each gas sensor is obtained. This value is then compared with a state interference threshold, which is a preset constant in the database. The locations of all gas sensors within the test area whose corresponding operating state interference values ​​are less than or equal to the state interference threshold are considered as effective monitoring points for ambient gases within the test area.

4. The environmental gas monitoring method based on sensor networks according to claim 1, characterized in that: In step S4, when determining the operating status of the sensor network in the area to be tested, if the number of elements in the obtained union is less than the total number of gas sensors in the area to be tested, then the operating status of the sensor network monitoring the ambient gas in the area to be tested is determined to be abnormal; if the number of elements in the obtained union is equal to the total number of gas sensors in the area to be tested, then the operating status of the sensor network monitoring the ambient gas in the area to be tested is determined to be normal. The inspection and investigation task includes the inspection and investigation objects in the sensor network that monitors ambient gases, and the inspection and investigation objects are the gas sensors in the area to be measured; When the inspection and investigation objects are obtained in the inspection and investigation task of the sensor network for monitoring ambient gases in S4, the inspection and investigation objects are the gas sensors corresponding to the missing nodes and abnormal endpoints of the chain, respectively. The gas sensors corresponding to the missing nodes in the chain are all gas sensors in the area to be tested that are not included in the union of the sets of nodes corresponding to each of the obtained extended association chains. The gas sensors corresponding to the abnormal endpoints of the chain are the gas sensors corresponding to all nodes in the extended association chain whose interference investigation association ratio is less than a preset value and which are not effective monitoring points; the interference investigation association ratio is equal to the quotient of the number of gas sensors that are adjacent to the corresponding node and belong to the extended association chain node of the corresponding node divided by the total number of gas sensors that are adjacent to the corresponding node.

5. An environmental gas monitoring system based on a sensor network, wherein the system is implemented using the environmental gas monitoring method based on a sensor network according to any one of claims 1-4, characterized in that, The system includes the following modules: The sensor data acquisition module acquires the locations of all gas sensors in the area to be measured, assigns numbers to the gas sensors, binds the assigned numbers to the corresponding gas sensor locations, and acquires environmental information within a preset radius around each sensor location. The operation interference analysis module analyzes the impact value of the operation status interference on each gas sensor in the test area at the current time based on the historical monitoring data of each gas sensor in the test area and the environmental information corresponding to each gas sensor. An extended correlation chain construction module is used to screen effective monitoring points of environmental gas in the area to be tested based on the interference impact value of the operating status corresponding to each gas sensor; and to construct an extended correlation chain corresponding to each effective monitoring point in the area to be tested by combining the relationship between the historical monitoring data of adjacent gas sensors at any position in the area to be tested. The inspection and investigation task supervision module obtains the union of the node sets corresponding to each extended association chain obtained in the extended association chain construction module. Based on the comparison result of the number of elements in the obtained union with the total number of gas sensors in the area to be tested, it determines the operating status of the sensor network in the area to be tested. If the operating status is abnormal, it generates an inspection and investigation task for the sensor network monitoring the ambient gas and feeds it back to the administrator.

6. An environmental gas monitoring system based on a sensor network according to claim 5, characterized in that: The extended association chain construction module includes an effective monitoring point screening unit and an association chain construction unit. The effective monitoring point screening unit screens effective monitoring points of environmental gas in the area to be tested based on the obtained interference impact value of the operating status of each gas sensor. The association chain construction unit combines the relationship between historical monitoring data of adjacent gas sensors at any location within the test area to construct an extended association chain corresponding to each effective monitoring point within the test area.

7. An environmental gas monitoring system based on a sensor network according to claim 6, characterized in that: The inspection and investigation task supervision module includes a relational chain union element analysis unit and an inspection and investigation task generation and feedback unit. The association chain union element analysis unit obtains the union of the node sets corresponding to each extended association chain obtained in the extended association chain construction module; The inspection and troubleshooting task generation and feedback unit determines the operating status of the sensor network in the area under test based on the comparison result of the obtained and aggregated element count with the total number of gas sensors in the area under test. If the operating status is abnormal, it generates an inspection and troubleshooting task for the sensor network monitoring the ambient gas and feeds it back to the administrator.

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