Big data-based industrial gas cylinder leakage prevention intelligent early warning system and method

Abstract

The application discloses an industrial gas cylinder anti-leakage intelligent early warning system and method based on big data, relates to the technical field of industrial gas cylinder leakage early warning, and comprises the following steps: collecting industrial gas cylinder storage site image data and industrial gas cylinder storage site thermal imaging data; according to the industrial gas cylinder storage site image data and industrial gas cylinder model characteristic image data, analyzing and processing the industrial gas cylinder model and the position of the industrial gas cylinder in the image contained in the image monitoring data to generate industrial gas cylinder model position data; the industrial gas cylinder anti-leakage intelligent early warning system and method based on big data realizes the leakage monitoring of the industrial gas cylinder by adopting the mode of arranging binocular cameras and infrared imagers, is suitable for monitoring the industrial gas cylinders filled with gases (such as carbon dioxide, methane and the like) having obvious absorption characteristics in the infrared region and the industrial gas cylinders filled with high-pressure gases, eliminates the arrangement and maintenance of a large number of sensors, and makes the monitoring cost lower and more efficient.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of industrial gas cylinder leakage early warning, in particular to an industrial gas cylinder anti-leakage intelligent early warning system and method based on big data. BACKGROUND

[0002] The gas cylinder is a pressure-bearing equipment with explosive danger, and its contained medium generally has the properties of flammability, explosiveness, toxicity, strong corrosion, etc. The use environment is more complex and harsh than other pressure vessels due to its mobility, repeated filling, non-fixed operation and use of personnel, and change of use environment. Once the gas cylinder explodes or leaks, fire or poisoning often occurs, and even catastrophic accidents occur, causing serious property loss, personnel casualties and environmental pollution. Therefore, it is necessary to monitor the gas cylinder and discover the leakage accident of the gas cylinder in time. The prior art with publication number CN112862304A discloses a gas cylinder monitoring and management method, which comprises the following steps: obtaining a regional map of a monitoring area, marking a target gas cylinder and a gas channel associated with the target gas cylinder on the regional map; obtaining position information and switch state information of a stop valve arranged on the gas channel; obtaining sensor data detected by a sensor arranged on the target gas cylinder; the sensor data includes gas pressure information; a background server determines parameter information of the target gas cylinder according to the position information, the switch state information and the sensor data of the stop valve, and sends the parameter information to a mobile terminal for display. The gas cylinders placed in the gas cylinder room are monitored, recorded and analyzed to ensure the safety and stability of the gas cylinders in the gas cylinder room, improve the user experience, effectively monitor the gas cylinders, and reduce the safety hazards caused by gas leakage.

[0003] However, the implementation of the gas cylinder leakage monitoring requires a large number of sensors to support, and the large number of sensors increases the probability of sensor failure, i.e. the arrangement, debugging and maintenance of the sensors require high time and cost, making the actual use process more complex, and not suitable for small or low-cost gas cylinder storage or transfer sites, so there is an urgent need for a simple and efficient gas cylinder leakage monitoring method. SUMMARY

[0004] The purpose of the present application is to provide an industrial gas cylinder anti-leakage intelligent early warning system and method based on big data to solve the above-mentioned deficiencies in the prior art.

[0005] In order to achieve the above-mentioned purpose, the present application provides the following technical scheme: an industrial gas cylinder anti-leakage intelligent early warning method based on big data, comprising the following steps:

[0006] S1, collecting industrial gas cylinder storage site image data and industrial gas cylinder storage site thermal imaging data;

[0007] S2, according to the industrial gas cylinder storage site image data and industrial gas cylinder model characteristic image data, the analysis processing of the industrial gas cylinder model and the position in the image contained in the image monitoring data is carried out, and the industrial gas cylinder model position data is generated;

[0008] S3, according to the industrial gas cylinder storage site image data and binocular camera parameter data, the calculation processing of the position of each pixel in the real world in the industrial gas cylinder storage site image data is carried out, and the industrial gas cylinder storage site image real position data is generated;

[0009] S4, according to the industrial gas cylinder model position data and the industrial gas cylinder storage site image real position data, the search processing of the industrial gas cylinder storage site image real position data corresponding to the industrial gas cylinder model position data is carried out, and the industrial gas cylinder model real position data is generated;

[0010] S5, referring to the industrial gas cylinder storage site image data, the image registration processing of the industrial gas cylinder storage site thermal imaging data is carried out, and the industrial gas cylinder storage site registration thermal imaging data is generated;

[0011] S6, according to the industrial gas cylinder storage site registration thermal imaging data and industrial gas cylinder leakage thermal imaging data, the industrial gas cylinder leakage feature recognition analysis processing of the industrial gas cylinder storage site is carried out, the storage site industrial gas cylinder leakage feature return data is generated, and according to the storage site industrial gas cylinder leakage feature return data and industrial gas cylinder leakage feature early warning scheme data, the early warning scheme analysis processing of the industrial gas cylinder leakage is carried out, and the industrial gas cylinder leakage early warning scheme analysis data is generated;

[0012] S7, according to the storage site industrial gas cylinder leakage feature return data and the industrial gas cylinder model real position data, the search processing of the real position corresponding to the identified industrial gas cylinder leakage feature is carried out, and the storage site industrial gas cylinder leakage position data is generated;

[0013] S8, the industrial gas cylinder storage site image data, the industrial gas cylinder storage site registration thermal imaging data, the storage site industrial gas cylinder leakage feature return data, the storage site industrial gas cylinder leakage position data and the industrial gas cylinder leakage early warning scheme analysis data are collected and combined, the industrial gas cylinder leakage early warning data is generated, and the leakage early warning information reporting operation is carried out according to the industrial gas cylinder leakage early warning data.

[0014] Further, the S1 includes the following steps:

[0015] S11, the industrial gas cylinder storage site image data is collected by the binocular camera installed in the industrial gas cylinder storage site, and the industrial gas cylinder storage site image data set is generated , , represents the image data of the oth industrial cylinder storage site, represents the maximum number of image data of industrial cylinder storage sites;

[0016] S12, through the infrared imager installed in the industrial cylinder storage site, real-time collection of industrial cylinder storage site thermal imaging data, generating industrial cylinder storage site thermal imaging data set , , represents the same time of industrial cylinder storage site thermal imaging data.

[0017] Further, the S2 includes the following steps:

[0018] S21, collecting the images of various types of industrial cylinders, establishing the industrial cylinder type characteristic image data set , , represents the pth type of industrial cylinder type characteristic image data, represents the maximum number of industrial cylinder types;

[0019] S22, based on the two-stage detection algorithm trained by the industrial cylinder type characteristic image data set C, searching out the industrial cylinder storage site image data in which the position matched with the industrial cylinder type characteristic image data set C and the corresponding industrial cylinder type characteristic image data of the matched position , generating the industrial cylinder type position data set of the industrial cylinder storage site image data , , represents the wth industrial cylinder type position data in represents the maximum number of industrial cylinders in , Z is the pixel coordinate set of the industrial cylinder in , , represents the u pixel coordinate, represents the maximum number of pixel coordinates in Z, that is represents the type of the wth industrial cylinder in , the position is Z.

[0020] Further, the S3 includes the following steps:

[0021] ​​​S31, collect binocular camera parameter data E of the binocular camera, including (1) camera intrinsic parameters: obtain the focal length, principal point and distortion parameters of the camera. These parameters are obtained by camera calibration (such as using a checkerboard); (2) camera extrinsic parameters: determine the position and orientation (rotation matrix and translation vector) of the camera in three-dimensional space; (3) coordinate system conversion: convert the image pixel coordinates (2D) to the camera coordinate system (3D), and finally convert to the world coordinate system through the extrinsic parameters;

[0022] S32, based on the stereo vision technology and the binocular camera parameter data E, calculate the industrial gas cylinder storage site image data The position of each pixel coordinate in the real world generates the industrial gas cylinder storage site image data The industrial gas cylinder storage site image real position data set , , represents the real position data corresponding to the qth pixel point in represents the maximum number of pixel points in

[0023] Further, the S4 includes the following steps:

[0024] S41, search the industrial gas cylinder model position data set and the industrial gas cylinder storage site image real position data set based on the double-pointer method, search out the corresponding to the Z pixel coordinate in , generate the industrial gas cylinder model real position data set , represents the model real position data of the wth industrial gas cylinder in , is the real position data set , represents the corresponding .

[0025] Further, the S5 includes the following steps:

[0026] S51, refer to the industrial gas cylinder storage site image data perform image registration processing on the industrial gas cylinder storage site thermal imaging data , generate the industrial gas cylinder storage site registration thermal imaging data .

[0027] Further, the S6 includes the following steps:​​​​​

[0028] S61, collect the thermal imaging data of industrial gas cylinder leakage, and establish an industrial gas cylinder leakage thermal imaging data set G;

[0029] S62, feature extraction is performed on the industrial gas cylinder leakage thermal imaging data set G, for example, Canny, Sobel, Laplacian operator, etc. can be used to generate industrial gas cylinder leakage thermal imaging feature data , and then based on the DBSCAN clustering algorithm, the feature clustering is performed to generate an industrial gas cylinder leakage feature type thermal imaging data set , , represents the vthindustrial gas cylinder leakage feature type thermal imaging data, represents the maximum number of industrial gas cylinder leakage feature types;

[0030] S63, based on the industrial gas cylinder model position data set and the industrial gas cylinder storage site registration thermal imaging data , the thermal imaging of each industrial gas cylinder in the is divided to obtain the industrial gas cylinder thermal imaging data set I , represents the Wthindustrial gas cylinder thermal imaging data;

[0031] S64, in the industrial gas cylinder leakage feature type thermal imaging data set H search space, sequentially search for the matching in the industrial gas cylinder thermal imaging data set I , that is, search for the matching , generate the storage site industrial gas cylinder leakage feature return data set , including the following steps:

[0032] S641, initialize the algorithm parameters, the number of firefly populations N, and the maximum number of iterations T;

[0033] S642, initialize the firefly population position, that is, randomly generate N fireflies in the industrial gas cylinder leakage feature type thermal imaging data set H search space;

[0034] S643, calculate the fitness of the firefly, which is used to simulate the light intensity of the firefly. The better the fitness of the firefly, the greater the light intensity;

[0035] S644, the firefly with low fitness moves towards the firefly with high fitness, which is used to simulate the movement of the firefly towards the firefly with high light intensity. The firefly position updating formula is as follows: ,

[0036] in, represents the position of firefly i, represents the position of the firefly whose fitness is lower than that of firefly i, t is the current iteration number, is the attraction coefficient, is the attraction attenuation coefficient, r is a random vector, in, is the initial attraction coefficient, is the Euclidean distance between firefly i and firefly j;

[0037] S645, determine whether the maximum number of iterations T is reached, if not, return to step S643, if so, output the position of the firefly with the best fitness Generate a data set of industrial gas cylinder leakage characteristics returned at storage sites , express Corresponding ;

[0038] S65. Collect thermal imaging data of leakage characteristics of various industrial gas cylinders Corresponding industrial gas cylinder leakage feature warning scheme, generating industrial gas cylinder leakage feature warning scheme data set , Represents Corresponding industrial gas cylinder leakage characteristic early warning plan data;

[0039] S66. Based on the double pointer method, return the data set of industrial gas cylinder leakage characteristics at the storage site middle Matched industrial gas cylinder leakage feature warning scheme data set J Search and generate analysis data for industrial gas cylinder leakage warning solutions .

[0040] Furthermore, the step S7 includes the following steps:

[0041] S71, if express The leakage characteristics of industrial gas cylinders in the storage site where the leakage is identified are returned to the data set;

[0042] S72, based on the double pointer method, and the actual location data set of the industrial gas cylinder model Search, search out Zhongyu Matched , storage site industrial gas cylinder leakage location data .

[0043] Further, the S8 comprises the following steps:

[0044] S81, collecting industrial gas cylinder storage site image data , industrial gas cylinder storage site registration thermal imaging data , storage site industrial gas cylinder leak feature return data set , storage site industrial gas cylinder leak location data And the industrial gas cylinder leak warning scheme analysis data Collect, combine, and generate industrial gas cylinder leak warning data According to the industrial gas cylinder leak warning data K, carry out leak warning information reporting operation.

[0045] The industrial gas cylinder leak prevention intelligent early warning system based on big data comprises a binocular camera, an infrared imager, a processor, a memory, and an alarm module.

[0046] The binocular camera is used to collect industrial gas cylinder storage site image data in real time, and generate an industrial gas cylinder storage site image data set.

[0047] The infrared imager is used to collect industrial gas cylinder storage site thermal imaging data in real time, and generate an industrial gas cylinder storage site thermal imaging data set.

[0048] The memory is used to store a computer program.

[0049] The processor is used to execute the computer program, and realize the industrial gas cylinder leak prevention intelligent early warning method based on big data.

[0050] The alarm module is used to send leak warning information according to the industrial gas cylinder leak warning data.

[0051] 1. Compared with the prior art, the industrial gas cylinder leak prevention intelligent early warning system and method based on big data provided by the present application realize accurate positioning of the gas cylinder by collecting visual image information of the gas cylinder storage site, i.e. industrial gas cylinder storage site image data, through the binocular camera, detecting the gas cylinder in the visual image through a target detection algorithm, and calculating the position of each gas cylinder in the real site through stereo vision technology.

[0052] 2. Compared with the prior art, the industrial gas cylinder leak prevention intelligent early warning system and method based on big data provided by the present application collect thermal imaging data of the gas cylinder through the infrared imager, judge whether the gas cylinder leaks and the leak condition (i.e. leak feature) by identifying the thermal imaging features of the gas cylinder and its surroundings, so as to select a warning scheme for warning according to the leak condition, and make the content of the warning more detailed.

[0053] 3. Compared with the prior art, the industrial gas cylinder anti-leakage intelligent early warning system and method based on big data provided by the application can realize accurate positioning of the leakage position by image registration of thermal imaging and industrial gas cylinder storage site image data, aligning the image pixel coordinates of the thermal imaging and the industrial gas cylinder storage site image data, and finding the position of the corresponding position of the thermal imaging and the industrial gas cylinder storage site image data in the display site according to the position of the industrial gas cylinder leakage feature recognized in the thermal imaging data.

[0054] 4. Compared with the prior art, the industrial gas cylinder anti-leakage intelligent early warning system and method based on big data provided by the application can realize leakage monitoring of the industrial gas cylinder by adopting the mode of arranging binocular cameras and infrared imagers, which is suitable for monitoring the industrial gas cylinders filled with gases having significant absorption characteristics in the infrared region (such as carbon dioxide, methane, ammonia, carbon monoxide, etc.) and the industrial gas cylinders filled with high-pressure gases, and eliminates the arrangement and maintenance of a large number of sensors, so that the monitoring cost is lower and more efficient. BRIEF DESCRIPTION OF DRAWINGS

[0055] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments described in the present application, and other drawings can also be obtained by those skilled in the art based on these drawings.

[0056] Figure 1 The method step diagram provided for the embodiments of the present application;

[0057] Figure 2 The system structure block diagram provided for the embodiments of the present application. DETAILED DESCRIPTION

[0058] In order to make those skilled in the art better understand the technical solutions of the present application, the present application will be further described in detail below with reference to the drawings.

[0059] In the description of the present application, it should be understood that the example embodiments will be described more fully below with reference to the accompanying drawings, but the example embodiments can be embodied in different forms and should not be interpreted as being limited to the embodiments set forth herein. On the contrary, the purpose of providing these embodiments is to make the present disclosure thorough and complete, and to enable those skilled in the art to fully understand the scope of the present disclosure.

[0060] The embodiments of the present disclosure and the features in the embodiments can be combined with each other without conflict.

[0061] As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0062] The terms used herein are used only to describe specific embodiments and are not intended to limit the present disclosure. As used herein, the singular forms "a," "an," and "the" are also intended to include the plural forms, unless the context clearly indicates otherwise. It will also be understood that when the terms "comprising" and / or "made of" are used in this specification, the presence of the features, wholes, steps, operations, elements, and / or components is specified, but the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or groups thereof is not excluded.

[0063] The embodiments described herein may be described with reference to plan views and / or cross-sectional views, with the aid of idealized schematic diagrams of the present disclosure. Thus, the example illustrations may be modified based on manufacturing techniques and / or tolerances. Therefore, the embodiments are not limited to the embodiments shown in the accompanying drawings, but include modifications of the configurations formed based on the manufacturing process. Therefore, the regions illustrated in the accompanying drawings are schematic in nature, and the shapes of the regions shown in the drawings illustrate specific shapes of the regions of the elements, but are not intended to be limiting.

[0064] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art. It will also be understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant art and the present disclosure, and will not be interpreted as having an idealized or overly formal meaning unless expressly defined as such herein.

[0065] The intelligent early warning method for preventing leakage of industrial gas cylinders based on big data includes the following steps:

[0066] S1. Collecting image data and thermal imaging data of industrial gas cylinder storage sites, including the following steps:

[0067] S11. Use binocular cameras installed at industrial gas cylinder storage sites to collect image data of industrial gas cylinder storage sites in real time and generate an image data set of industrial gas cylinder storage sites. , , represents the oth industrial gas cylinder storage site image data, Indicates the maximum number of image data for industrial gas cylinder storage sites;

[0068] S12. Use the infrared imager installed at the industrial gas cylinder storage site to collect the thermal imaging data of the industrial gas cylinder storage site in real time and generate a thermal imaging data set of the industrial gas cylinder storage site , , Represents Thermal imaging data of industrial gas cylinder storage sites at the same time, that is, thermal imaging data of each industrial gas cylinder storage site Each corresponds to an image data of an industrial gas cylinder storage site .

[0069] S2. Analyzing and processing the industrial gas cylinder models and positions in the images contained in the image monitoring data based on the industrial gas cylinder storage site image data and the industrial gas cylinder model characteristic image data to generate industrial gas cylinder model position data, including the following steps:

[0070] S21. Collect images of various types of industrial gas cylinders and establish a dataset of characteristic images of industrial gas cylinder models , , Represents the characteristic image data of the p-th type of industrial gas cylinder model, Indicates the maximum number of industrial gas cylinder models and identifies the models of industrial gas cylinders so that the data for industrial gas cylinder leakage feature early warning schemes can be formulated based on the models of industrial gas cylinders, making the early warning schemes more specific and refined.

[0071] S22. Based on the two-stage detection algorithm trained with the industrial gas cylinder model feature image dataset C, search for the industrial gas cylinder storage site image data. The position that matches the industrial gas cylinder model feature image data set C and the industrial gas cylinder model feature image data corresponding to the matching position , generate industrial gas cylinder storage site image data Industrial gas cylinder model location data collection , , express The wth industrial gas cylinder model location data, express The maximum number of industrial gas cylinders in China, , Z is the industrial gas cylinder The pixel coordinates set in , , represents the u-th pixel coordinate, represents the maximum number of pixel coordinates in Z, i.e. express The model of the wth industrial gas cylinder is , position is Z.

[0072] S3. Calculating and processing the real-world position of each pixel in the industrial gas cylinder storage site image data based on the industrial gas cylinder storage site image data and the binocular camera parameter data to generate real-world position data of the industrial gas cylinder storage site image, including the following steps:

[0073] S31, collect binocular camera parameter data E of binocular camera, including (1) camera intrinsic parameter: obtain focal length, focal point and distortion parameter of camera. These parameters are obtained by camera calibration (such as using checkerboard); (2) camera extrinsic parameter: determine the position and orientation (rotation matrix and translation vector) of camera in three-dimensional space; (3) coordinate system conversion: convert image pixel coordinates (2D) to camera coordinate system (3D), and finally convert to world coordinate system through extrinsic parameter;

[0074] S32, based on stereo vision technology and binocular camera parameter data E, calculate industrial gas cylinder storage site image data Each pixel coordinate position in the real world generates industrial gas cylinder storage site image data Industrial gas cylinder storage site image real position data set , , Indicates the real position data corresponding to the qth pixel point in Indicates the real position data corresponding to the qth pixel point in The maximum number of pixel points in The calculation of stereo vision technology includes the following steps: (1) disparity calculation: calculate the disparity by matching corresponding points (such as SIFT, ORB feature points) between left and right images; (2) based on the baseline distance (i.e. the distance between two cameras, which can be obtained through camera extrinsic parameter) of binocular camera and the calculated disparity, calculate the depth; the calculation process can use OpenCV's StereoBM or StereoSGBM algorithm.

[0075] S4, according to industrial gas cylinder model position data and industrial gas cylinder storage site image real position data, search processing of industrial gas cylinder model position data corresponding to industrial gas cylinder storage site image real position data, generate industrial gas cylinder model real position data, including the following steps:

[0076] S41, search based on double pointer method for industrial gas cylinder model position data set And the industrial gas cylinder storage site image real position data set Search out The pixel coordinate Z in Corresponding to Generate industrial gas cylinder model real position data set , Indicates the model real position data of the wth industrial gas cylinder in , , Real position data set , Indicates the corresponding ​​The real position data is three-dimensional position coordinate data in the storage site.

[0077] S5, image registration processing of the industrial gas cylinder storage site thermal imaging data is performed with reference to the industrial gas cylinder storage site image data, to generate registered thermal imaging data of the industrial gas cylinder storage site, including the following steps:

[0078] S51, the industrial gas cylinder storage site thermal imaging data is registered with reference to the industrial gas cylinder storage site image data to generate registered thermal imaging data of the industrial gas cylinder storage site .

[0079] S6, according to the registered thermal imaging data of the industrial gas cylinder storage site and the industrial gas cylinder leakage thermal imaging data, the industrial gas cylinder leakage feature recognition analysis processing of the industrial gas cylinder storage site is performed, to generate the storage site industrial gas cylinder leakage feature return data, and according to the storage site industrial gas cylinder leakage feature return data and the industrial gas cylinder leakage feature early warning scheme data, the industrial gas cylinder leakage early warning scheme analysis processing is performed, to generate the industrial gas cylinder leakage early warning scheme analysis data, including the following steps:

[0080] S61, the thermal imaging data of the industrial gas cylinder leakage is collected, and a set of industrial gas cylinder leakage thermal imaging data G is established;

[0081] S62, feature extraction is performed on the set of industrial gas cylinder leakage thermal imaging data G, for example, Canny, Sobel, Laplacian operator, etc., to generate industrial gas cylinder leakage thermal imaging feature data , and then based on the DBSCAN clustering algorithm, the feature clustering is performed, to generate a set of industrial gas cylinder leakage feature type thermal imaging data , , represents the vth industrial gas cylinder leakage feature type thermal imaging data, represents the maximum number of industrial gas cylinder leakage feature types, and the DBSCAN clustering algorithm can directly classify H according to the features of each in the set of industrial gas cylinder leakage feature type thermal imaging data H, without needing to set the number of clusters (i.e. the number of categories) in advance, and according to whether the corresponding leakage situation of the thermal imaging data corresponding to each is consistent, to adjust the parameters of the DBSCAN clustering algorithm to adjust the clustering results, so that the features of each are obviously different and the corresponding leakage situation of the thermal imaging data corresponding to each is basically consistent, to ensure the accuracy of subsequent leakage feature recognition;

[0082] S63, based on the set of industrial gas cylinder model position data Registering thermal imaging data with industrial gas cylinder storage sites ,right The thermal image corresponding to each industrial gas cylinder is divided into Thermal imaging data collection of industrial gas cylinders , represents the thermal imaging data of the Wth industrial gas cylinder;

[0083] S64, sequentially searching for the same thermal imaging data set I in the search space of the thermal imaging data set H for the leakage characteristic type of the industrial gas cylinder. Matched , that is, search and arrive Matched , generate the return data set of industrial gas cylinder leakage characteristics at the storage site , including the following steps:

[0084] S641, initialize algorithm parameters, firefly population size N, maximum number of iterations T;

[0085] S642, initializing the position of the firefly population, that is, randomly generating N fireflies in the search space H of the thermal imaging data set of industrial gas cylinder leakage feature types;

[0086] S643. Calculate the firefly fitness to simulate the light intensity of the fireflies. The better the firefly fitness, the greater the light intensity.

[0087] S644: Fireflies with low fitness move closer to fireflies with high fitness, which is used to simulate fireflies moving closer to fireflies with high light intensity. The firefly position update formula is as follows: ,

[0088] in, represents the position of firefly i, represents the position of the firefly whose fitness is lower than that of firefly i, t is the current iteration number, is the attraction coefficient, is the attraction attenuation coefficient, r is a random vector, in, is the initial attraction coefficient, is the Euclidean distance between firefly i and firefly j;

[0089] S645, determine whether the maximum number of iterations T is reached, if not, return to step S643, if so, output the position of the firefly with the best fitness Generate a data set of industrial gas cylinder leakage characteristics returned at storage sites , express Corresponding ;

[0090] S65, collect each industrial gas cylinder leak characteristic type thermal imaging data The corresponding industrial gas cylinder leak characteristic early warning scheme, industrial gas cylinder leak characteristic early warning scheme data set is generated , indicates the corresponding industrial gas cylinder leak characteristic early warning scheme data;

[0091] S66, based on the double pointer method, the industrial gas cylinder leak characteristic return data set of the storage site is matched with the industrial gas cylinder leak characteristic early warning scheme data set J search, generate industrial gas cylinder leak early warning scheme analysis data .

[0092] S7, according to the storage site industrial gas cylinder leak characteristic return data and the industrial gas cylinder model real position data, the search processing of the real position corresponding to the identified industrial gas cylinder leak characteristic is carried out, and the storage site industrial gas cylinder leak position data is generated, including the following steps:

[0093] S71, if indicates The storage site industrial gas cylinder leak characteristic return data set is identified in the leak;

[0094] S72, based on the double pointer method, the storage site industrial gas cylinder leak position data set and industrial gas cylinder model real position data set search, search the storage site industrial gas cylinder leak position data set matched with . .

[0095] S8, collect, combine the industrial gas cylinder storage site image data, the industrial gas cylinder storage site registration thermal imaging data, the storage site industrial gas cylinder leak characteristic return data, the storage site industrial gas cylinder leak position data and the industrial gas cylinder leak early warning scheme analysis data, generate the industrial gas cylinder leak early warning data, according to the industrial gas cylinder leak early warning data, carry out the leak early warning information reporting operation, including the following steps:

[0096] S81, collect the industrial gas cylinder storage site image data , the industrial gas cylinder storage site registration thermal imaging data , the storage site industrial gas cylinder leak characteristic return data set , the storage site industrial gas cylinder leak position data and industrial gas cylinder leak early warning scheme analysis data​​​​ Collect, combine and generate industrial gas cylinder leakage early warning data According to the industrial gas cylinder leakage early warning data K, the leakage early warning information reporting operation is performed.

[0097] The application also provides an industrial gas cylinder leakage prevention intelligent early warning system based on big data, which is used for executing the industrial gas cylinder leakage prevention intelligent early warning method based on big data provided by the application, and comprises a binocular camera, an infrared imager, a processor, a memory and an alarm module.

[0098] The binocular camera is used for collecting industrial gas cylinder storage site image data in real time and generating an industrial gas cylinder storage site image data set.

[0099] The infrared imager is used for collecting industrial gas cylinder storage site thermal imaging data in real time and generating an industrial gas cylinder storage site thermal imaging data set.

[0100] The memory is used for storing a computer program.

[0101] The processor is used for executing the computer program and realizing the industrial gas cylinder leakage prevention intelligent early warning method based on big data.

[0102] The alarm module is used for sending leakage early warning information according to the industrial gas cylinder leakage early warning data.

[0103] The above only describes certain exemplary embodiments of the application by way of illustration, and it is self-evident that those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the application. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the application.

Claims

1. A big data-based industrial gas cylinder leak prevention intelligent early warning method, characterized in that: It comprises the following steps: S1, collecting industrial gas cylinder storage site image data and industrial gas cylinder storage site thermal imaging data; S2, analyzing and processing the industrial gas cylinder model and the position in the image monitoring data image according to the S1 collected data, generating industrial gas cylinder model position data; S3, according to the binocular camera parameter data, calculating and processing the position of each pixel in the industrial gas cylinder storage site image data in the real world, generating industrial gas cylinder storage site image real position data; S4, searching the industrial gas cylinder storage site image real position data corresponding to the industrial gas cylinder model position data, generating industrial gas cylinder model real position data; S5, referring to the industrial gas cylinder storage site image data, performing image registration processing on the industrial gas cylinder storage site thermal imaging data, generating industrial gas cylinder storage site registration thermal imaging data; S6, according to the industrial gas cylinder storage site registration thermal imaging data and the industrial gas cylinder leakage thermal imaging data, performing industrial gas cylinder leakage feature recognition analysis processing, generating storage site industrial gas cylinder leakage feature return data, combining with industrial gas cylinder leakage feature early warning scheme data, performing industrial gas cylinder leakage early warning scheme analysis processing, generating industrial gas cylinder leakage early warning scheme analysis data; S7, according to the storage site industrial gas cylinder leakage feature return data and the industrial gas cylinder model real position data, performing industrial gas cylinder leakage feature real position search processing, generating storage site industrial gas cylinder leakage position data; S8, constructing industrial gas cylinder leakage early warning data and performing leakage early warning information reporting operation.

2. The big data-based industrial gas cylinder anti-leakage intelligent early warning method according to claim 1, characterized in that: The S1 comprises the following steps: S11, binocular camera installed through the industrial gas cylinder storage site, real-time collection of industrial gas cylinder storage site image data, generation of industrial gas cylinder storage site image data set , , represents the oth industrial gas cylinder storage site image data, represents the maximum number of industrial gas cylinder storage site image data; S12, an infrared imager installed through an industrial gas cylinder storage site, collects industrial gas cylinder storage site thermal imaging data in real time to generate an industrial gas cylinder storage site thermal imaging data set , , represents the industrial gas cylinder storage site thermal imaging data at the same time .

3. The big data-based industrial gas cylinder anti-leakage intelligent early warning method according to claim 2, characterized in that: The S2 comprises the following steps: S21. Collect images of various types of industrial gas cylinders and establish a dataset of characteristic images of industrial gas cylinder models , , Represents the characteristic image data of the p-th type of industrial gas cylinder model, Indicates the maximum number of industrial gas cylinder models; S22, search the industrial gas cylinder storage site image data based on the two-stage detection algorithm trained by the industrial gas cylinder model feature image data set C The position matched with the industrial gas cylinder model feature image data corresponding to the matched position in the middle , generate the industrial gas cylinder model position data set of the industrial gas cylinder storage site image data , , Indicates The wth industrial gas cylinder model position data in the middle Indicates The maximum number of industrial gas cylinders in the middle , Z is the pixel coordinate set of the industrial gas cylinder in the middle , , Indicates the u pixel coordinate Indicates the maximum number of pixel coordinates in Z.​​ 4. The big data-based industrial gas cylinder anti-leakage intelligent early warning method according to claim 3, characterized in that: The S3 comprises the following steps: S31, collecting binocular camera parameter data E of the binocular camera; S32. Calculate the image data of the industrial gas cylinder storage site based on stereo vision technology and binocular camera parameter data E The position of each pixel coordinate in the real world is used to generate image data of the industrial gas cylinder storage site Real-world location data set of industrial gas cylinder storage site images , , express The actual position data corresponding to the q-th pixel point in , express The maximum number of pixels in the image.

5. The big data-based industrial gas cylinder anti-leakage intelligent early warning method according to claim 4, characterized in that: The S4 comprises the following steps: S41, searching the industrial gas cylinder model position data set based on the double-pointer method and the industrial gas cylinder storage site image real position data set ​​​​​​​​​​​​​​ 6. The big data-based industrial gas cylinder anti-leakage intelligent early warning method according to claim 5, characterized in that: The S5 comprises the following steps: S51, reference the industrial gas cylinder storage site image data to the industrial gas cylinder storage site thermal imaging data image registration processing is performed to generate industrial gas cylinder storage site registration thermal imaging data .

7. The big data-based industrial gas cylinder anti-leakage intelligent early warning method according to claim 6, characterized in that: The S6 comprises the following steps: S61, collecting industrial gas cylinder leakage thermal imaging data, establishing industrial gas cylinder leakage thermal imaging data set G; S62, feature extraction is performed on the industrial gas cylinder leakage thermal imaging data set G to generate industrial gas cylinder leakage thermal imaging feature data Then, based on the DBSCAN clustering algorithm, feature clustering is performed on the generated industrial gas cylinder leakage feature type thermal imaging data set , , represents the vth industrial gas cylinder leakage feature type thermal imaging data, represents the maximum number of industrial gas cylinder leakage feature types; S63, based on the industrial gas cylinder model position data set and industrial gas cylinder storage site registration thermal imaging data , the thermal imaging corresponding to each industrial gas cylinder in the is divided to obtain industrial gas cylinder thermal imaging data set , indicates the Wth industrial gas cylinder thermal imaging data; S64, search in the industrial gas cylinder leakage feature type thermal imaging data set H search space in turn with the industrial gas cylinder thermal imaging data set I matching , generate storage site industrial gas cylinder leakage feature return data set , comprising the following steps: S641, initializing algorithm parameters, firefly population number N, maximum iteration number T; S642, initializing firefly population position; S643, calculating firefly fitness; S644, the glowworm with low fitness moves towards the glowworm with high fitness, and the position updating formula of the glowworm is as follows: , wherein, represents the position of firefly i, represents the position of firefly with a fitness lower than that of firefly i, t is the current iteration number, is the attractiveness coefficient, is the attractiveness decay coefficient, r is a random vector, wherein, is the initial attractiveness coefficient, is the Euclidean distance between firefly i and firefly j; S645, judging whether the maximum iteration number T is reached, if not, returning to step S643, if yes, outputting the position corresponding to the best fitness of the firefly Generating a set of return data of a storage site industrial cylinder leakage feature , representing corresponding ; S65, collect each industrial gas cylinder leak characteristic type thermal imaging data The corresponding industrial gas cylinder leak characteristic early warning scheme generates an industrial gas cylinder leak characteristic early warning scheme data set , indicates the corresponding industrial gas cylinder leak characteristic early warning scheme data ​ S66, based on the double-pointer method, return data set of industrial gas cylinder leakage characteristics of storage site In Matched industrial gas cylinder leakage characteristic early warning scheme data set J Search and generate industrial gas cylinder leakage early warning scheme analysis data .

8. The big data-based industrial gas cylinder anti-leakage intelligent early warning method according to claim 7, characterized in that: The S7 comprises the following steps: S71、if representing The storage site industrial gas cylinder leakage feature return data set is identified in the middle of the leakage. S72, based on the double-pointer method, to and the industrial cylinder model actual position data set search, search out in the matching , storage site industrial cylinder leak location data . 9.The big data-based industrial gas cylinder anti-leakage intelligent early warning method according to claim 8, characterized in that: The S8 comprises the following steps: S81, collecting industrial gas cylinder storage site image data , industrial gas cylinder storage site registered thermal imaging data , storage site industrial gas cylinder leakage feature return data set , storage site industrial gas cylinder leakage location data , and the industrial gas cylinder leakage early warning scheme analysis data Collect, combine, and generate industrial gas cylinder leakage early warning data According to the industrial gas cylinder leakage early warning data K, carry out leakage early warning information reporting operation.

10. The big data-based intelligent anti-leakage early warning system for industrial gas cylinders is used for executing the big data-based intelligent anti-leakage early warning method for industrial gas cylinders according to any one of claims 1-9, characterized in that: It comprises a binocular camera, an infrared imager, a processor, a memory, and an alarm module; The binocular camera is used for real-time collection of industrial gas cylinder storage site image data, generating industrial gas cylinder storage site image data set; The infrared imager is used for real-time collection of industrial gas cylinder storage site thermal imaging data, generating industrial gas cylinder storage site thermal imaging data set; The memory is used for storing computer programs; The processor is used for executing computer programs to realize the industrial gas cylinder anti-leakage intelligent early warning method based on big data in any one of claims 1-9; The alarm module is used for sending leakage early warning information according to the industrial gas cylinder leakage early warning data.

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