CN116413318B - Toxic gas joint detection method and system based on well lid - Google Patents
Toxic gas joint detection method and system based on well lid Download PDFInfo
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- 239000002341 toxic gas Substances 0.000 title claims abstract description 392
- 238000001514 detection method Methods 0.000 title claims abstract description 308
- 238000005457 optimization Methods 0.000 claims abstract description 131
- 238000009826 distribution Methods 0.000 claims abstract description 119
- 239000007789 gas Substances 0.000 claims abstract description 117
- 238000000835 electrochemical detection Methods 0.000 claims abstract description 68
- 238000005868 electrolysis reaction Methods 0.000 claims abstract description 36
- 238000000034 method Methods 0.000 claims abstract description 33
- 238000013461 design Methods 0.000 claims abstract description 7
- 238000004519 manufacturing process Methods 0.000 claims description 181
- 238000004458 analytical method Methods 0.000 claims description 63
- 239000003792 electrolyte Substances 0.000 claims description 42
- 239000002245 particle Substances 0.000 claims description 39
- 238000007619 statistical method Methods 0.000 claims description 19
- 238000009423 ventilation Methods 0.000 claims description 19
- 238000012216 screening Methods 0.000 claims description 18
- 230000007613 environmental effect Effects 0.000 claims description 16
- 238000004088 simulation Methods 0.000 claims description 15
- 238000009792 diffusion process Methods 0.000 claims description 12
- 230000003068 static effect Effects 0.000 claims description 10
- 239000000126 substance Substances 0.000 claims description 6
- 238000005094 computer simulation Methods 0.000 claims description 5
- 238000003708 edge detection Methods 0.000 claims description 4
- 238000009825 accumulation Methods 0.000 claims description 3
- 231100000614 poison Toxicity 0.000 claims description 2
- 230000007096 poisonous effect Effects 0.000 claims description 2
- 238000012512 characterization method Methods 0.000 claims 1
- 230000000694 effects Effects 0.000 abstract description 20
- 238000004364 calculation method Methods 0.000 description 2
- 238000004868 gas analysis Methods 0.000 description 2
- 239000012528 membrane Substances 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000003054 catalyst Substances 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
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- 238000010276 construction Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 239000003344 environmental pollutant Substances 0.000 description 1
- 238000000855 fermentation Methods 0.000 description 1
- 230000004151 fermentation Effects 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
- G01N27/26—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating electrochemical variables; by using electrolysis or electrophoresis
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
- G01N27/26—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating electrochemical variables; by using electrolysis or electrophoresis
- G01N27/27—Association of two or more measuring systems or cells, each measuring a different parameter, where the measurement results may be either used independently, the systems or cells being physically associated, or combined to produce a value for a further parameter
Abstract
The invention discloses a method and a system for jointly detecting toxic gas based on a well lid, and relates to the field of underground gas detection, wherein the method comprises the following steps: the method comprises the steps of obtaining toxic gas types and toxic gas distribution areas, and carrying out optimal design on electrochemical detection parameters according to the toxic gas types and toxic gas distribution areas to generate an electrochemical detection control optimal result; controlling a gas information sensor to detect according to an electrochemical detection control optimization result, and receiving an electrolysis current parameter and an electrolysis potential parameter; and determining gas type information according to the electrolysis potential parameters, determining gas concentration information according to the electrolysis current parameters, and determining toxic gas detection results by combining the gas type information. The technical problems that in the prior art, the detection accuracy of toxic gas aiming at the well lid is low, and the detection effect of the toxic gas aiming at the well lid is poor are solved. The technical effect of improving the accuracy of detecting toxic gas in the well cover and the quality of detecting toxic gas in the well cover is achieved.
Description
Technical Field
The invention relates to the field of underground gas detection, in particular to a method and a system for detecting toxic gas in a combined way based on a well lid.
Background
With the development of the urban process, the laying area of underground pipelines is wider and wider. Well covers are one of the important maintenance nodes of downhole pipelines. Because the inside of the well lid is in a closed state for a long time, toxic gases caused by pollutant fermentation, pipeline leakage and the like in the well lid are continuously gathered, and huge hidden danger is brought to the safety of people. How to effectively detect the poisonous gas in the well cover is widely paid attention to by people.
In the prior art, the detection accuracy of toxic gas aiming at the well lid is low, and then the technical problem of poor toxic gas detection effect of the well lid is caused.
Disclosure of Invention
The application provides a method and a system for jointly detecting toxic gas based on a well lid. The technical problems that in the prior art, the detection accuracy of toxic gas aiming at the well lid is low, and the detection effect of the toxic gas aiming at the well lid is poor are solved. The method has the advantages that the electrochemical detection parameters are adapted and comprehensively optimally designed through the toxic gas types and the toxic gas distribution areas, an accurate electrochemical detection control optimization result is generated, the toxic gas of the well lid is intelligently and reliably detected according to the electrochemical detection control optimization result, the accuracy of the toxic gas detection of the well lid is improved, and the technical effect of the toxic gas detection quality of the well lid is improved.
In view of the problems, the application provides a manhole cover-based toxic gas combined detection method and a manhole cover-based toxic gas combined detection system.
In a first aspect, the application provides a manhole cover-based toxic gas combined detection method, wherein the method is applied to a manhole cover-based toxic gas combined detection system, and the method comprises the following steps: performing scene analysis on the intelligent well lid deployment area to generate toxic gas detection environmental characteristics; carrying out big data statistical analysis according to the toxic gas detection environmental characteristics to obtain toxic gas types and toxic gas distribution areas; obtaining electrochemical detection parameters; optimally designing the electrochemical detection parameters according to the toxic gas type and the toxic gas distribution area to generate an electrochemical detection control optimization result; controlling a gas information sensor to detect according to the electrochemical detection control optimization result, and receiving sensor detection data, wherein the sensor detection data comprises an electrolysis current parameter and an electrolysis potential parameter; determining gas type information according to the electrolysis potential parameters, and determining gas concentration information according to the electrolysis current parameters; and adding the gas type information and the gas concentration information into a toxic gas detection result.
In a second aspect, the application also provides a manhole cover-based toxic gas combined detection system, wherein the system comprises: the scene analysis module is used for performing scene analysis on the intelligent well lid deployment area to generate toxic gas detection environment characteristics; the big data statistical analysis module is used for carrying out big data statistical analysis according to the toxic gas detection environment characteristics to obtain toxic gas types and toxic gas distribution areas; the electrochemical detection parameter acquisition module is used for acquiring electrochemical detection parameters; the optimal design module is used for optimally designing the electrochemical detection parameters according to the toxic gas type and the toxic gas distribution area to generate an electrochemical detection control optimal result; the sensor detection module is used for controlling the gas information sensor to detect according to the electrochemical detection control optimization result and receiving sensor detection data, wherein the sensor detection data comprises an electrolysis current parameter and an electrolysis potential parameter; the gas information determining module is used for determining gas type information according to the electrolysis potential parameters and determining gas concentration information according to the electrolysis current parameters; and the detection result obtaining module is used for adding the gas type information and the gas concentration information into a toxic gas detection result.
One or more technical schemes provided by the application have at least the following technical effects or advantages:
generating toxic gas detection environmental characteristics by performing scene analysis on the intelligent well lid deployment area; carrying out big data statistical analysis on the toxic gas detection environmental characteristics to obtain toxic gas types and toxic gas distribution areas; optimizing the electrochemical detection parameters through toxic gas types and toxic gas distribution areas to generate an electrochemical detection control optimizing result; controlling a gas information sensor to detect according to an electrochemical detection control optimization result, and receiving sensor detection data; and determining the toxic gas detection result by analyzing the sensor detection data. The method has the advantages that the electrochemical detection parameters are adapted and comprehensively optimally designed through the toxic gas types and the toxic gas distribution areas, an accurate electrochemical detection control optimization result is generated, the toxic gas of the well lid is intelligently and reliably detected according to the electrochemical detection control optimization result, the accuracy of the toxic gas detection of the well lid is improved, and the technical effect of the toxic gas detection quality of the well lid is improved.
The foregoing description is only an overview of the present application, and is intended to be implemented in accordance with the teachings of the present application in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present application more readily apparent.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings of the embodiments of the present disclosure will be briefly described below. It is apparent that the figures in the following description relate only to some embodiments of the present disclosure and are not limiting of the present disclosure.
FIG. 1 is a schematic flow chart of a method for detecting toxic gases by combining based on a well lid;
FIG. 2 is a schematic flow chart of generating an electrochemical detection control optimization result in the manhole cover-based toxic gas combined detection method;
fig. 3 is a schematic structural diagram of a manhole cover-based toxic gas combined detection system.
Reference numerals illustrate: the system comprises a scene analysis module 11, a big data statistics analysis module 12, an electrochemical detection parameter acquisition module 13, an optimal design module 14, a sensor detection module 15, a gas information determination module 16 and a detection result acquisition module 17.
Detailed Description
The application provides a method and a system for jointly detecting toxic gas based on a well lid. The technical problems that in the prior art, the detection accuracy of toxic gas aiming at the well lid is low, and the detection effect of the toxic gas aiming at the well lid is poor are solved. The method has the advantages that the electrochemical detection parameters are adapted and comprehensively optimally designed through the toxic gas types and the toxic gas distribution areas, an accurate electrochemical detection control optimization result is generated, the toxic gas of the well lid is intelligently and reliably detected according to the electrochemical detection control optimization result, the accuracy of the toxic gas detection of the well lid is improved, and the technical effect of the toxic gas detection quality of the well lid is improved.
Example 1
Referring to fig. 1, the application provides a manhole cover-based toxic gas combined detection method, wherein the method is applied to a manhole cover-based toxic gas combined detection system, and the method specifically comprises the following steps:
step S100: performing scene analysis on the intelligent well lid deployment area to generate toxic gas detection environmental characteristics;
further, the step S100 of the present application further includes:
step S110: carrying out production element analysis on the intelligent well lid deployment area to obtain a toxic gas production element set, wherein the toxic gas production element set refers to a toxic gas output source type set;
step S120: carrying out production scale analysis on the intelligent well lid deployment area to obtain a toxic gas production scale set, wherein the toxic gas production scale set refers to a toxic gas output source scale set;
step S130: analyzing production time length of the intelligent well lid deployment area to obtain a toxic gas production time length set, wherein the toxic gas production time length set refers to a toxic gas production source operation time length set;
step S140: analyzing production positions of the intelligent well lid deployment area to obtain a toxic gas production position set, wherein the toxic gas production position set refers to a toxic gas production source position set;
Step S150: carrying out underground pipeline structure analysis on the intelligent well lid deployment area to obtain pipeline structure distribution information;
step S160: and adding the toxic gas production element set, the toxic gas production scale set, the toxic gas production duration set, the toxic gas production position set and the pipeline structure distribution information into the toxic gas detection environment characteristic.
Specifically, production element information of an intelligent well lid deployment area is collected, and a toxic gas production element set is obtained. Furthermore, based on the toxic gas production element set, the toxic gas production scale information, the toxic gas production duration information and the toxic gas production position information of the intelligent well lid deployment area are respectively acquired to obtain the toxic gas production scale set, the toxic gas production duration set and the toxic gas production position set. And then, acquiring underground pipeline structure information of an intelligent well lid deployment area, obtaining pipeline structure distribution information, and generating toxic gas detection environmental characteristics by combining a toxic gas production element set, a toxic gas production scale set, a toxic gas production duration set and a toxic gas production position set.
Wherein, include a plurality of intelligent well lids in the intelligent well lid deployment region. The intelligent well covers are in communication connection with the toxic gas combined detection system based on the well covers. The set of toxic gas production elements includes a set of toxic gas production source types. The toxic gas output source type set comprises a plurality of toxic gas output source type information corresponding to the intelligent well lid deployment area. For example, the plurality of toxic gas production source type information includes gas leakage, organic decay, livestock manure, food processing waste gas, waste water, and the like in the intelligent manhole cover deployment area. The toxic gas production scale set comprises a toxic gas production source scale set. The toxic gas producer scale set comprises a plurality of toxic gas unit production volumes corresponding to a plurality of toxic gas producer type information in the toxic gas producer type set. The plurality of toxic gas unit production amounts comprise a plurality of toxic gas production source type information corresponding to a plurality of toxic gas production amount parameter information in unit time. The toxic gas production time duration set comprises a toxic gas production source operation time duration set. The toxic gas output source operation duration set comprises a plurality of operation duration information corresponding to a plurality of toxic gas output source type information in the toxic gas output source type set. The toxic gas production location set includes a toxic gas production source location set. The toxic gas production source position set comprises a plurality of production position information corresponding to a plurality of toxic gas production source type information in the toxic gas production source type set. The pipeline structure distribution information comprises underground pipeline structure information and underground pipeline layout information in an intelligent well lid deployment area. The toxic gas detection environment characteristics comprise a toxic gas production element set, a toxic gas production scale set, a toxic gas production duration set, a toxic gas production position set and pipeline structure distribution information. The technical effects of determining comprehensive toxic gas detection environment characteristics by carrying out multidimensional scene analysis on the intelligent well lid deployment area and improving the accuracy of toxic gas analysis on the intelligent well lid deployment area are achieved.
Step S200: carrying out big data statistical analysis according to the toxic gas detection environmental characteristics to obtain toxic gas types and toxic gas distribution areas;
further, step S200 of the present application further includes:
step S210: carrying out big data statistical analysis according to the toxic gas production element set to obtain a toxic gas production type set;
step S220: carrying out big data statistical analysis according to the toxic gas production scale set and the toxic gas production duration set to obtain a toxic gas production volume set;
step S230: when any one of the toxic gas production volumes in the toxic gas production volume sets is greater than or equal to a production volume threshold, setting the corresponding toxic gas production type in the toxic gas production type set as the toxic gas type;
step S240: screening toxic gas production positions from the toxic gas production position set according to the toxic gas type;
specifically, toxic gas production type analysis is performed based on the toxic gas production element set, and a toxic gas production type set is obtained. The set of toxic gas production types includes a plurality of toxic gas production types. In the case of obtaining the toxic gas production type set, a plurality of historical toxic gas production element sets and a plurality of historical toxic gas production type sets are obtained by performing a historical data query based on the toxic gas production element sets. Analyzing the corresponding relation between the plurality of historical toxic gas production element sets and the plurality of historical toxic gas output type sets, and arranging the plurality of historical toxic gas production element sets and the plurality of historical toxic gas output type sets according to the corresponding relation to obtain a toxic gas output type analysis database. And inputting the toxic gas production element set into a toxic gas production type analysis database to obtain a toxic gas production type set.
Further, the multiple production amounts of the multiple toxic gas units in the toxic gas production scale set and the multiple operation duration information in the corresponding toxic gas production duration set are multiplied, so that the toxic gas production amount set is obtained. The toxic gas production set includes a plurality of toxic gas production. The plurality of toxic gas production amounts include a plurality of products between a plurality of toxic gas unit production amounts in the toxic gas production scale set and a plurality of operation time period information in the corresponding toxic gas production time period set. And then, judging whether the plurality of toxic gas production amounts in the toxic gas production amount set are larger than or equal to a production amount threshold value or not respectively, and setting the toxic gas production type corresponding to the toxic gas production amount as the toxic gas type if the toxic gas production amount is larger than or equal to the production amount threshold value. And matching the toxic gas production position set according to the toxic gas type to obtain the toxic gas production position. Wherein the output threshold comprises a predetermined toxic gas output threshold. The toxic gas types include a plurality of toxic gas production types corresponding to a plurality of toxic gas production amounts greater than or equal to a production amount threshold. The toxic gas production location includes a plurality of production location information corresponding to a plurality of toxic gas production types within the toxic gas type. The method achieves the technical effects of obtaining accurate toxic gas types by analyzing and screening toxic gas output types of toxic gas detection environmental characteristics, thereby improving the adaptation degree of toxic gas detection of the well lid.
Step S250: and carrying out gas diffusion analysis according to the toxic gas production position and the pipeline structure distribution information to generate the toxic gas distribution area.
Further, step S250 of the present application further includes:
step S251: marking the distribution information of the pipeline structure to obtain the identification information of the gas passable area and the identification information of the gas non-passable area;
step S252: acquiring a pipeline ventilation direction parameter and a pipeline ventilation wind speed parameter;
step S253: performing simulation modeling according to the gas passable region identification information and the gas non-passable region identification information to generate a pipeline gas passing static model;
step S254: designing the pipeline gas passing static model according to the pipeline ventilation direction parameter and the pipeline ventilation wind speed parameter to generate a pipeline gas passing dynamic model;
step S255: inputting the toxic gas production position and the toxic gas production amount into the pipeline gas passing dynamic model for diffusion simulation to obtain a toxic gas gathering area;
step S256: the toxic gas accumulation region is set as the toxic gas distribution region.
Specifically, the pipeline structure distribution information is traversed for marking, and the gas passable area identification information and the gas non-passable area identification information are obtained. And then, performing simulation modeling based on the gas passable region identification information and the gas non-passable region identification information to generate a pipeline gas passing static model. And carrying out dynamic simulation on the pipeline gas passing static model according to the pipeline ventilation direction parameters and the pipeline ventilation wind speed parameters to obtain a pipeline gas passing dynamic model. And then, based on the toxic gas production position and the toxic gas production amount, carrying out diffusion simulation on the pipeline gas passing dynamic model to obtain a toxic gas gathering area, and setting the toxic gas gathering area as a toxic gas distribution area. The pipeline gas passing dynamic model, the toxic gas production position and the toxic gas production amount can be input into a simulation analysis platform, and the simulation analysis platform carries out diffusion simulation on the pipeline gas passing dynamic model according to the toxic gas production position and the toxic gas production amount to generate a toxic gas gathering area. The simulation analysis platform can be a simulation verification platform such as MATLAB and RT-LAB in the prior art.
Wherein the gas passable region identification information includes a plurality of gas passable region distribution information within the duct structure distribution information. The gas non-passage area identification information includes a plurality of gas non-passage area distribution information within the piping structure distribution information. The pipeline ventilation direction parameters comprise a plurality of pipeline wind direction information in the intelligent manhole cover deployment area. The pipeline ventilation wind speed parameters comprise a plurality of pipeline wind speed information in the intelligent manhole cover deployment area. The pipeline gas passing static model comprises a three-dimensional simulation model corresponding to the gas passable area identification information and the gas non-passable area identification information. By way of example, the gas passable region identification information and the gas non-passable region identification information can be input into simulation modeling software such as Rhino, formZ and the like in the prior art, and simulation calculation is performed on the gas passable region identification information and the gas non-passable region identification information through the simulation modeling software, so that a pipeline gas passing static model is obtained. The pipeline gas passing dynamic model comprises three-dimensional simulation models corresponding to gas passable area identification information, gas non-passable area identification information, pipeline ventilation direction parameters and pipeline ventilation wind speed parameters. The toxic gas distribution area includes a toxic gas accumulation area. The technical effects of obtaining a reliable toxic gas distribution area through the diffusion simulation of the pipeline gas passing dynamic model through the toxic gas production position and the toxic gas production amount are achieved, and the accuracy of toxic gas detection of the well lid is improved.
Step S300: obtaining electrochemical detection parameters;
step S400: optimally designing the electrochemical detection parameters according to the toxic gas type and the toxic gas distribution area to generate an electrochemical detection control optimization result;
further, as shown in fig. 2, step S400 of the present application further includes:
step S410: the electrochemical detection parameters comprise electrolyte type parameters, sensor detection position parameters and detection condition parameters, wherein the detection condition parameters refer to physical conditions and chemical conditions during detection;
step S420: optimizing the electrolyte type parameter and the detection condition parameter according to the toxic gas type to obtain an electrolyte type optimization result and a detection condition parameter optimization result;
further, step S420 of the present application further includes:
step S421: setting a first optimization constraint condition according to the detection duration information;
step S422: setting a second optimization constraint condition according to the detection precision information;
step S423: setting a third optimization constraint condition according to the detection cost information;
step S424: traversing the first optimization constraint condition, the second optimization constraint condition and the third optimization constraint condition to construct an optimization fitness function:
Wherein Fit (x i ,y i ) Characterizing fitness, T (x i ,y i ) A detection duration function characterizing the optimization results of the i-th group, C (x i ,y i ) A detection cost function characterizing the i-th set of optimization results, D (x i ,y i ) The detection precision function characterizing the i-th set of optimization results, minFit (x i ,y i ) Characterizing fitness minima in the optimized total particles, maxFit (x i ,y i ) Maximum fitness, x, of the total particles optimized i Electrolyte type parameter, y, characterizing the i-th set of optimization results i Characterizing the detection condition parameters of the i-th group of optimization results, wherein alpha, beta and gamma characterize the weight indexes of the respective dimensions and are larger than or equal to 0;
step S425: collecting historical detection records according to the electrolyte type parameters and the detection condition parameters, and constructing a preset number of particles to be optimized according to the historical detection records, wherein any one particle to be optimized represents historical selection of a group of electrolyte type parameters and detection condition parameters;
step S426: and traversing the particles to be optimized according to the optimization fitness function to screen, and obtaining the electrolyte type optimization result and the detection condition parameter optimization result.
Specifically, the electrochemical detection parameters include an electrolyte type parameter, a sensor detection position parameter, and a detection condition parameter. Detecting the condition parameter includes detecting a physical condition parameter and detecting a chemical condition parameter. The detection of the physical condition parameters includes detection instruments, detection equipment and the like during detection. The detection of the chemical condition parameters comprises temperature, illumination, pressure, catalyst and the like during detection. Furthermore, the detection duration information, the detection precision information and the detection cost information are respectively set as a first optimization constraint condition, a second optimization constraint condition and a third optimization constraint condition, and an optimization fitness function is constructed based on the first optimization constraint condition, the second optimization constraint condition and the third optimization constraint condition.
Further, historical detection information acquisition is carried out based on electrolyte type parameters and detection condition parameters, and a historical detection record is obtained. The history detection record includes a plurality of sets of history detection data. Each set of historical detection data comprises historical electrolyte type parameters, historical detection condition parameters, historical detection duration information, historical detection precision information and historical detection cost information. And then, based on the preset quantity, randomly selecting a plurality of groups of history detection data in the history detection records to obtain a plurality of particles to be optimized. Each particle to be optimized comprises a random set of historical detection data in a historical detection record. And the number of the particles to be optimized satisfies the preset number. And then, respectively taking a plurality of particles to be optimized as input information, and inputting an optimizing fitness function to obtain a plurality of particle fitness. And outputting electrolyte type parameters and detection condition parameters in the particles to be optimized corresponding to the maximum particle fitness as electrolyte type optimization results and detection condition parameter optimization results.
The preset number comprises a preset determined threshold value of the number of the particles to be optimized. In optimizing the fitness function, fit (x i ,y i ) For the particle fitness, T (x i ,y i ) For the input function of the detection duration of the particles to be optimized, C (x i ,y i ) For the input detection cost function of the particle to be optimized, D (x i ,y i ) As an input detection precision function of the particles to be optimized, minFit (x i ,y i ) For the minimum particle fitness corresponding to the input plurality of particles to be optimized, maxFit (x i ,y i ) For the maximum particle fitness, x, corresponding to the input plurality of particles to be optimized i For the electrolyte type parameter, y, in the input particles to be optimized i And alpha, beta and gamma are weight indexes of respective dimensions which are preset and determined for the input detection condition parameters in the particles to be optimized, and the alpha, the beta and the gamma are all larger than or equal to 0. And the electrolyte type optimization result comprises electrolyte type parameters in the particles to be optimized corresponding to the maximum particle fitness. And the detection condition parameter optimization result comprises detection condition parameters in the particles to be optimized corresponding to the maximum particle fitness. The technical effects of optimizing and analyzing electrolyte type parameters and detection condition parameters through optimizing fitness functions, obtaining reliable electrolyte type optimizing results and detection condition parameter optimizing results and improving the accuracy of toxic gas detection of the well lid are achieved.
Step S430: optimizing the sensor detection position parameters according to the toxic gas distribution area to obtain a sensor detection position optimization result;
further, step S430 of the present application further includes:
step S431: acquiring area parameters according to the toxic gas distribution area, and matching the quantity information of detection points;
step S432: setting a detection point distribution position constraint area according to the toxic gas distribution area;
step S433: non-repeated random arrangement is carried out for M times according to the detection point quantity information and the detection point distribution position constraint area, and M groups of sensor detection position adjustment results are generated;
specifically, area identification is performed based on a toxic gas distribution area, an area parameter of the area is obtained, and the number information of detection points is matched according to the area parameter of the area. The toxic gas distribution area is set as a detection point distribution position constraint area. And then, carrying out random arrangement of M times of non-repeated sensor detection positions based on the detection point quantity information and the detection point distribution position constraint area, and generating M groups of sensor detection position adjustment results. Wherein the regional area parameter comprises the area information of the toxic gas distribution region. The detection point quantity information comprises the quantity of detection points of the sensor corresponding to the toxic gas distribution area. The larger the area parameter, the greater the number of corresponding sensor detection points. For example, the manhole cover detection expert can calibrate the number of detection points of the sensor on the area parameter of the area, and the information of the number of detection points is determined. Each set of sensor detection position adjustment results comprises a plurality of sensor detection point position parameters in a detection point distribution position constraint area. And the quantity corresponding to the position parameters of the detection points of the plurality of sensors in the detection position adjustment result of each group of sensors meets the quantity information of the detection points. The position parameters of the detection points of the plurality of sensors between the detection position adjustment results of the M groups of sensors are different from each other. The value of M may be adaptively set. Preferably, 2/3 of the detection point number information is set to M. The technical effects of determining the detection position adjustment results of the M groups of sensors by carrying out non-repeated random arrangement on the quantity information of the detection points and the constraint areas of the distribution positions of the detection points are achieved, and carrying out distribution uniformity analysis and screening tamping bases on the detection position adjustment results of the M groups of sensors in the follow-up process.
Step S434: and traversing the detection position adjustment results of the M groups of sensors to perform distribution uniformity analysis, and performing maximum value screening on the analysis results to obtain the detection position optimization results of the sensors.
Further, step S434 of the present application further includes:
step S4341: obtaining a distribution uniformity scoring function:
wherein G represents the distribution uniformity score of the detection position adjustment result of any group of sensors, and d k And d m Respectively representing the distance between any two points in the detection position adjustment result of any group of sensors, A 1 Characterizing the area in the circle of the first connection edge detection point, A 2 Representing the total area of the distribution position constraint area of the detection points;
step S4342: and traversing the detection position adjustment results of the M groups of sensors according to the distribution uniformity scoring function to perform distribution uniformity analysis, and performing maximum value screening on the analysis results to obtain the detection position optimization results of the sensors.
Step S440: and adding the electrolyte type optimization result, the detection condition parameter optimization result and the sensor detection position optimization result into the electrochemical detection control optimization result.
Specifically, the detection position adjustment results of the M groups of sensors are respectively used as input information, a distribution uniformity scoring function is input, and distribution uniformity analysis is performed on the detection position adjustment results of the M groups of sensors through the distribution uniformity scoring function, so that analysis results are obtained. The analysis result comprises M distribution uniformity scores corresponding to the detection position adjustment results of the M groups of sensors. In the distribution uniformity scoring function, G is the distribution uniformity score corresponding to any group of output sensor detection position adjustment results, d k And d m For the distance between the position parameters of any two sensor detection points in the input arbitrary set of sensor detection position adjustment results, A 1 For input first connecting the faces in the edge detection ringProduct A 2 The total area of the area is constrained for the input detection point distribution position, i.e. A 2 Is an input area parameter of the region. Further, maximum value screening is carried out on M distribution uniformity scores in the analysis result to obtain a maximum distribution uniformity score, the maximum distribution uniformity score is matched with M groups of sensor detection position adjustment results to obtain a sensor detection position optimization result, and an electrochemical detection control optimization result is generated by combining the electrolyte type optimization result and the detection condition parameter optimization result. The sensor detection position optimization result comprises a group of sensor detection position adjustment results corresponding to the maximum distribution uniformity score. The electrochemical detection control optimization result comprises an electrolyte type optimization result, a detection condition parameter optimization result and a sensor detection position optimization result. The technical effects of analyzing and screening the distribution uniformity of the detection position adjustment results of the M groups of sensors through the distribution uniformity scoring function and obtaining the sensor detection position optimization results with higher distribution uniformity are achieved, so that the reliability of toxic gas detection of the well lid is improved.
Step S500: controlling a gas information sensor to detect according to the electrochemical detection control optimization result, and receiving sensor detection data, wherein the sensor detection data comprises an electrolysis current parameter and an electrolysis potential parameter;
step S600: determining gas type information according to the electrolysis potential parameters, and determining gas concentration information according to the electrolysis current parameters;
step S700: and adding the gas type information and the gas concentration information into a toxic gas detection result.
Specifically, the gas information sensor is controlled to detect the intelligent well lid deployment area in real time according to the electrochemical detection control optimization result, and sensor detection data are obtained. The sensor detection data includes an electrolysis current parameter and an electrolysis potential parameter. Further, gas type information is determined according to the electrolysis potential parameter, gas concentration information is determined according to the electrolysis current parameter, and the gas type information and the gas concentration information are added to the toxic gas detection result. The toxic gas detection result comprises gas type information and gas concentration information. The gas information sensor may be a potentiostatic electrolytic sensor in the prior art. The fixed potential electrolytic method sensor has high sensitivity to the detection of toxic gases, and the fixed potential electrolytic method sensor has good selectivity to the gases because of different electrolytic potentials of different gases, and can detect various toxic gases. The potentiometric electrolytic sensor comprises a filter sheet, a semipermeable membrane, electrolyte and electrodes. The toxic gas diffuses into the semipermeable membrane and is dissolved in the electrolyte, and contacts with the electrode to generate chemical reaction on the surface of the electrode to form charged substances such as ions, electrons and the like. The charged species generates an electric current from which the concentration of the toxic gas can be quantitatively calculated. By way of example, the gas type information can be determined by comparing the electrolysis potential parameter with a range of gas electrolysis potentials known in the prior art. And inputting the electrolysis current parameters into an electrolysis current-gas concentration calculation formula known in the prior art to obtain gas concentration information. The technical effects of obtaining accurate toxic gas detection results and improving the toxic gas detection quality of the well lid by calculating and analyzing the sensor detection data are achieved.
In summary, the manhole cover-based toxic gas combined detection method provided by the application has the following technical effects:
1. generating toxic gas detection environmental characteristics by performing scene analysis on the intelligent well lid deployment area; carrying out big data statistical analysis on the toxic gas detection environmental characteristics to obtain toxic gas types and toxic gas distribution areas; optimizing the electrochemical detection parameters through toxic gas types and toxic gas distribution areas to generate an electrochemical detection control optimizing result; controlling a gas information sensor to detect according to an electrochemical detection control optimization result, and receiving sensor detection data; and determining the toxic gas detection result by analyzing the sensor detection data. The method has the advantages that the electrochemical detection parameters are adapted and comprehensively optimally designed through the toxic gas types and the toxic gas distribution areas, an accurate electrochemical detection control optimization result is generated, the toxic gas of the well lid is intelligently and reliably detected according to the electrochemical detection control optimization result, the accuracy of the toxic gas detection of the well lid is improved, and the technical effect of the toxic gas detection quality of the well lid is improved.
2. Through carrying out multidimensional scene analysis to the intelligent well lid deployment area, comprehensive toxic gas detection environment characteristics are determined, so that the accuracy of toxic gas analysis to the intelligent well lid deployment area is improved.
3. And carrying out optimization analysis on the electrolyte type parameter and the detection condition parameter by optimizing the fitness function to obtain a reliable electrolyte type optimization result and a reliable detection condition parameter optimization result, thereby improving the accuracy of detecting the toxic gas in the well lid.
4. And analyzing and screening the distribution uniformity of the detection position adjustment results of the M groups of sensors by using a distribution uniformity scoring function to obtain a sensor detection position optimization result with higher distribution uniformity, thereby improving the reliability of toxic gas detection of the well lid.
Example two
Based on the same inventive concept as the method for detecting toxic gas based on the manhole cover in the foregoing embodiment, the invention also provides a toxic gas combined detection system based on the manhole cover, referring to fig. 3, the system comprises:
the scene analysis module 11 is used for performing scene analysis on the intelligent well lid deployment area to generate toxic gas detection environment characteristics;
The big data statistical analysis module 12 is used for carrying out big data statistical analysis according to the toxic gas detection environment characteristics to obtain toxic gas types and toxic gas distribution areas;
the electrochemical detection parameter acquisition module 13 is used for acquiring electrochemical detection parameters;
the optimal design module 14 is configured to optimally design the electrochemical detection parameters according to the toxic gas type and the toxic gas distribution area, and generate an electrochemical detection control optimization result;
the sensor detection module 15 is used for controlling a gas information sensor to detect according to the electrochemical detection control optimization result and receiving sensor detection data, wherein the sensor detection data comprises an electrolysis current parameter and an electrolysis potential parameter;
a gas information determining module 16, wherein the gas information determining module 16 is configured to determine gas type information according to the electrolysis potential parameter, and determine gas concentration information according to the electrolysis current parameter;
a detection result obtaining module 17, wherein the detection result obtaining module 17 is used for adding the gas type information and the gas concentration information into a toxic gas detection result.
Further, the system further comprises:
the production element analysis module is used for carrying out production element analysis on the intelligent well lid deployment area to obtain a toxic gas production element set, wherein the toxic gas production element set refers to a toxic gas output source type set;
the production scale analysis module is used for carrying out production scale analysis on the intelligent well lid deployment area to obtain a toxic gas production scale set, wherein the toxic gas production scale set refers to a toxic gas output source scale set;
the production time length analysis module is used for carrying out production time length analysis on the intelligent well lid deployment area to obtain a toxic gas production time length set, wherein the toxic gas production time length set refers to a toxic gas output source operation time length set;
the production position analysis module is used for carrying out production position analysis on the intelligent well lid deployment area to obtain a toxic gas production position set, wherein the toxic gas production position set refers to a toxic gas output source position set;
The underground pipeline structure analysis module is used for carrying out underground pipeline structure analysis on the intelligent well lid deployment area to acquire pipeline structure distribution information;
the first execution module is used for adding the toxic gas production factor set, the toxic gas production scale set, the toxic gas production duration set, the toxic gas production position set and the pipeline structure distribution information into the toxic gas detection environment characteristics.
Further, the system further comprises:
the toxic gas output type determining module is used for carrying out big data statistical analysis according to the toxic gas production element set to obtain a toxic gas output type set;
the toxic gas generation amount determining module is used for carrying out big data statistical analysis according to the toxic gas production scale set and the toxic gas production duration set to obtain a toxic gas generation amount set;
a toxic gas type determining module, configured to set, when any one of the toxic gas production amounts in the toxic gas production amount set is greater than or equal to a production amount threshold, a corresponding toxic gas production type in the toxic gas production type set as the toxic gas type;
The position screening module is used for screening toxic gas production positions from the toxic gas production position set according to the toxic gas type;
and the gas diffusion analysis module is used for carrying out gas diffusion analysis according to the toxic gas production position and the pipeline structure distribution information to generate the toxic gas distribution area.
Further, the system further comprises:
the pipeline marking module is used for marking the pipeline structure distribution information and acquiring gas passable area identification information and gas non-passable area identification information;
the pipeline ventilation parameter acquisition module is used for acquiring pipeline ventilation direction parameters and pipeline ventilation wind speed parameters;
the simulation module is used for performing simulation modeling according to the gas passable area identification information and the gas non-passable area identification information to generate a pipeline gas passing static model;
the passage dynamic design module is used for designing the pipeline gas passage static model according to the pipeline ventilation direction parameter and the pipeline ventilation wind speed parameter to generate a pipeline gas passage dynamic model;
The diffusion simulation module is used for inputting the toxic gas production position and the toxic gas production amount into the pipeline gas passing dynamic model to perform diffusion simulation, so as to obtain a toxic gas gathering area;
and the second execution module is used for setting the toxic gas gathering area as the toxic gas distribution area.
Further, the system further comprises:
the parameter composition module is used for the electrochemical detection parameters including electrolyte type parameters, sensor detection position parameters and detection condition parameters, wherein the detection condition parameters refer to physical conditions and chemical conditions during detection;
the third execution module is used for optimizing the electrolyte type parameter and the detection condition parameter according to the toxic gas type to obtain an electrolyte type optimization result and a detection condition parameter optimization result;
the fourth execution module is used for optimizing the sensor detection position parameters according to the toxic gas distribution area and obtaining a sensor detection position optimization result;
and the fifth execution module is used for adding the electrolyte type optimization result, the detection condition parameter optimization result and the sensor detection position optimization result into the electrochemical detection control optimization result.
Further, the system further comprises:
the first optimization constraint condition determining module is used for setting a first optimization constraint condition according to the detection duration information;
the second optimization constraint condition determining module is used for setting a second optimization constraint condition according to the detection precision information;
the third optimization constraint condition determining module is used for setting a third optimization constraint condition according to the detection cost information;
the optimization fitness function construction module is used for traversing the first optimization constraint condition, the second optimization constraint condition and the third optimization constraint condition to construct an optimization fitness function:
wherein Fit (x i ,y i ) Characterizing fitness, T (x i ,y i ) A detection duration function characterizing the optimization results of the i-th group, C (x i ,y i ) A detection cost function characterizing the i-th set of optimization results, D (x i ,y i ) The detection precision function characterizing the i-th set of optimization results, minFit (x i ,y i ) Characterizing fitness minima in the optimized total particles, maxFit (x i ,y i ) Maximum fitness, x, of the total particles optimized i Electrolyte type parameter, y, characterizing the i-th set of optimization results i Characterizing the detection condition parameters of the i-th group of optimization results, wherein alpha, beta and gamma characterize the weight indexes of the respective dimensions and are larger than or equal to 0;
the particle to be optimized determining module is used for acquiring historical detection records according to the electrolyte type parameters and the detection condition parameters and constructing a preset number of particles to be optimized according to the historical detection records, wherein any one particle to be optimized characterizes historical selection of a group of electrolyte type parameters and detection condition parameters;
and the particle screening module is used for traversing the particles to be optimized according to the optimization fitness function to screen, and obtaining the electrolyte type optimization result and the detection condition parameter optimization result.
Further, the system further comprises:
the matching module is used for acquiring area parameters according to the toxic gas distribution area and matching the quantity information of detection points;
the constraint setting module is used for setting a constraint area of a distribution position of the detection point according to the toxic gas distribution area;
The random arrangement module is used for carrying out non-repeated random arrangement for M times according to the detection point quantity information and the detection point distribution position constraint area, and generating M groups of sensor detection position adjustment results;
and the maximum value screening module is used for traversing the detection position adjustment results of the M groups of sensors to perform distribution uniformity analysis and performing maximum value screening on the analysis results to obtain the detection position optimization results of the sensors.
Further, the system further comprises:
the scoring function determining module is used for obtaining a distribution uniformity scoring function:
wherein G represents the distribution uniformity score of the detection position adjustment result of any group of sensors, and d k And d m Respectively representing the distance between any two points in the detection position adjustment result of any group of sensors, A 1 Characterizing the area in the circle of the first connection edge detection point, A 2 Characterizing detection point distribution position constraintsThe total area of the areas;
and the sixth execution module is used for traversing the detection position adjustment results of the M groups of sensors according to the distribution uniformity scoring function to perform distribution uniformity analysis, and performing maximum value screening on the analysis results to obtain the detection position optimization results of the sensors.
The manhole cover-based toxic gas combined detection system provided by the embodiment of the application can execute the manhole cover-based toxic gas combined detection method provided by any embodiment of the application, and has the corresponding functional modules and beneficial effects of the execution method.
All the included modules are only divided according to the functional logic, but are not limited to the above-mentioned division, so long as the corresponding functions can be realized; in addition, the specific names of the functional modules are only for distinguishing from each other, and are not used for limiting the protection scope of the present application.
The application provides a manhole cover-based toxic gas combined detection method, wherein the method is applied to a manhole cover-based toxic gas combined detection system, and the method comprises the following steps: generating toxic gas detection environmental characteristics by performing scene analysis on the intelligent well lid deployment area; carrying out big data statistical analysis on the toxic gas detection environmental characteristics to obtain toxic gas types and toxic gas distribution areas; optimizing the electrochemical detection parameters through toxic gas types and toxic gas distribution areas to generate an electrochemical detection control optimizing result; controlling a gas information sensor to detect according to an electrochemical detection control optimization result, and receiving sensor detection data; and determining the toxic gas detection result by analyzing the sensor detection data. The technical problems that in the prior art, the detection accuracy of toxic gas aiming at the well lid is low, and the detection effect of the toxic gas aiming at the well lid is poor are solved. The method has the advantages that the electrochemical detection parameters are adapted and comprehensively optimally designed through the toxic gas types and the toxic gas distribution areas, an accurate electrochemical detection control optimization result is generated, the toxic gas of the well lid is intelligently and reliably detected according to the electrochemical detection control optimization result, the accuracy of the toxic gas detection of the well lid is improved, and the technical effect of the toxic gas detection quality of the well lid is improved.
Note that the above is only a preferred embodiment of the present invention and the technical principle applied. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, while the invention has been described in connection with the above embodiments, the invention is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the invention, which is set forth in the following claims.
Claims (9)
1. The utility model provides a poisonous gas joint detection method based on well lid which characterized in that is applied to intelligent well lid, includes:
performing scene analysis on the intelligent well lid deployment area to generate toxic gas detection environmental characteristics;
carrying out big data statistical analysis according to the toxic gas detection environmental characteristics to obtain toxic gas types and toxic gas distribution areas;
obtaining electrochemical detection parameters;
optimally designing the electrochemical detection parameters according to the toxic gas type and the toxic gas distribution area to generate an electrochemical detection control optimization result;
Controlling a gas information sensor to detect according to the electrochemical detection control optimization result, and receiving sensor detection data, wherein the sensor detection data comprises an electrolysis current parameter and an electrolysis potential parameter;
determining gas type information according to the electrolysis potential parameters, and determining gas concentration information according to the electrolysis current parameters;
and adding the gas type information and the gas concentration information into a toxic gas detection result.
2. The method of claim 1, wherein performing a scene analysis on the smart manhole cover deployment area to generate a toxic gas detection environmental feature comprises:
carrying out production element analysis on the intelligent well lid deployment area to obtain a toxic gas production element set, wherein the toxic gas production element set refers to a toxic gas output source type set;
carrying out production scale analysis on the intelligent well lid deployment area to obtain a toxic gas production scale set, wherein the toxic gas production scale set refers to a toxic gas output source scale set;
analyzing production time length of the intelligent well lid deployment area to obtain a toxic gas production time length set, wherein the toxic gas production time length set refers to a toxic gas production source operation time length set;
Analyzing production positions of the intelligent well lid deployment area to obtain a toxic gas production position set, wherein the toxic gas production position set refers to a toxic gas production source position set;
carrying out underground pipeline structure analysis on the intelligent well lid deployment area to obtain pipeline structure distribution information;
and adding the toxic gas production element set, the toxic gas production scale set, the toxic gas production duration set, the toxic gas production position set and the pipeline structure distribution information into the toxic gas detection environment characteristic.
3. The method of claim 2, wherein performing a big data statistical analysis based on the toxic gas detection environmental characteristics to obtain a toxic gas type and a toxic gas distribution area, comprises:
carrying out big data statistical analysis according to the toxic gas production element set to obtain a toxic gas production type set;
carrying out big data statistical analysis according to the toxic gas production scale set and the toxic gas production duration set to obtain a toxic gas production volume set;
when any one of the toxic gas production volumes in the toxic gas production volume sets is greater than or equal to a production volume threshold, setting the corresponding toxic gas production type in the toxic gas production type set as the toxic gas type;
Screening toxic gas production positions from the toxic gas production position set according to the toxic gas type;
and carrying out gas diffusion analysis according to the toxic gas production position and the pipeline structure distribution information to generate the toxic gas distribution area.
4. The method of claim 3, wherein performing a gas diffusion analysis based on the toxic gas production location and the piping structure distribution information to generate the toxic gas distribution region comprises:
marking the distribution information of the pipeline structure to obtain the identification information of the gas passable area and the identification information of the gas non-passable area;
acquiring a pipeline ventilation direction parameter and a pipeline ventilation wind speed parameter;
performing simulation modeling according to the gas passable region identification information and the gas non-passable region identification information to generate a pipeline gas passing static model;
designing the pipeline gas passing static model according to the pipeline ventilation direction parameter and the pipeline ventilation wind speed parameter to generate a pipeline gas passing dynamic model;
inputting the toxic gas production position and the toxic gas production amount into the pipeline gas passing dynamic model for diffusion simulation to obtain a toxic gas gathering area;
The toxic gas accumulation region is set as the toxic gas distribution region.
5. The method of claim 1, wherein optimizing the electrochemical detection parameters according to the toxic gas type and the toxic gas distribution area to generate an electrochemical detection control optimization result comprises:
the electrochemical detection parameters comprise electrolyte type parameters, sensor detection position parameters and detection condition parameters, wherein the detection condition parameters refer to physical conditions and chemical conditions during detection;
optimizing the electrolyte type parameter and the detection condition parameter according to the toxic gas type to obtain an electrolyte type optimization result and a detection condition parameter optimization result;
optimizing the sensor detection position parameters according to the toxic gas distribution area to obtain a sensor detection position optimization result;
and adding the electrolyte type optimization result, the detection condition parameter optimization result and the sensor detection position optimization result into the electrochemical detection control optimization result.
6. The method of claim 5, wherein optimizing the electrolyte type parameter and the detection condition parameter according to the toxic gas type to obtain an electrolyte type optimization result and a detection condition parameter optimization result comprises:
Setting a first optimization constraint condition according to the detection duration information;
setting a second optimization constraint condition according to the detection precision information;
setting a third optimization constraint condition according to the detection cost information;
traversing the first optimization constraint condition, the second optimization constraint condition and the third optimization constraint condition to construct an optimization fitness function:
wherein Fit (x i ,y i ) Characterizing fitness, T (x i ,y i ) A detection duration function characterizing the optimization results of the i-th group, C (x i ,y i ) Characterization of group i optimization resultsIs a function of the detection cost of D (x i ,y i ) The detection precision function characterizing the i-th set of optimization results, minFit (x i ,y i ) Characterizing fitness minima in the optimized total particles, maxFit (x i ,y i ) Maximum fitness, x, of the total particles optimized i Electrolyte type parameter, y, characterizing the i-th set of optimization results i Characterizing the detection condition parameters of the i-th group of optimization results, wherein alpha, beta and gamma characterize the weight indexes of the respective dimensions and are larger than or equal to 0;
collecting historical detection records according to the electrolyte type parameters and the detection condition parameters, and constructing a preset number of particles to be optimized according to the historical detection records, wherein any one particle to be optimized represents historical selection of a group of electrolyte type parameters and detection condition parameters;
And traversing the particles to be optimized according to the optimization fitness function to screen, and obtaining the electrolyte type optimization result and the detection condition parameter optimization result.
7. The method of claim 5, wherein optimizing the sensor detection location parameter based on the toxic gas distribution area to obtain a sensor detection location optimization result comprises:
acquiring area parameters according to the toxic gas distribution area, and matching the quantity information of detection points;
setting a detection point distribution position constraint area according to the toxic gas distribution area;
non-repeated random arrangement is carried out for M times according to the detection point quantity information and the detection point distribution position constraint area, and M groups of sensor detection position adjustment results are generated;
and traversing the detection position adjustment results of the M groups of sensors to perform distribution uniformity analysis, and performing maximum value screening on the analysis results to obtain the detection position optimization results of the sensors.
8. The method of claim 7, wherein traversing the M sets of sensor detection position adjustment results for distribution uniformity analysis and maximum screening of analysis results, obtaining the sensor detection position optimization results, comprises:
Obtaining a distribution uniformity scoring function:
wherein G represents the distribution uniformity score of the detection position adjustment result of any group of sensors, and d k And d m Respectively representing the distance between any two points in the detection position adjustment result of any group of sensors, A 1 Characterizing the area in the circle of the first connection edge detection point, A 2 Representing the total area of the distribution position constraint area of the detection points;
and traversing the detection position adjustment results of the M groups of sensors according to the distribution uniformity scoring function to perform distribution uniformity analysis, and performing maximum value screening on the analysis results to obtain the detection position optimization results of the sensors.
9. A manhole cover based toxic gas joint detection system for performing the method of any one of claims 1 to 8, the system comprising:
the scene analysis module is used for performing scene analysis on the intelligent well lid deployment area to generate toxic gas detection environment characteristics;
the big data statistical analysis module is used for carrying out big data statistical analysis according to the toxic gas detection environment characteristics to obtain toxic gas types and toxic gas distribution areas;
The electrochemical detection parameter acquisition module is used for acquiring electrochemical detection parameters;
the optimal design module is used for optimally designing the electrochemical detection parameters according to the toxic gas type and the toxic gas distribution area to generate an electrochemical detection control optimal result;
the sensor detection module is used for controlling the gas information sensor to detect according to the electrochemical detection control optimization result and receiving sensor detection data, wherein the sensor detection data comprises an electrolysis current parameter and an electrolysis potential parameter;
the gas information determining module is used for determining gas type information according to the electrolysis potential parameters and determining gas concentration information according to the electrolysis current parameters;
and the detection result obtaining module is used for adding the gas type information and the gas concentration information into a toxic gas detection result.
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