Industrial gas cylinder anti-leakage intelligent early warning system and method based on big data

Abstract

The invention discloses an industrial gas cylinder anti-leakage intelligent early warning system and method based on big data, and relates to the technical field of industrial gas cylinder leakage early warning, and the method comprises the following steps: collecting image data of an industrial gas cylinder storage site and thermal imaging data of the industrial gas cylinder storage site; according to the industrial gas cylinder storage site image data and the industrial gas cylinder model feature image data, the industrial gas cylinder model included in the image monitoring data and the position of the industrial gas cylinder in the image are analyzed and processed, and industrial gas cylinder model position data are generated; according to the industrial gas cylinder anti-leakage intelligent early warning system and method based on big data, leakage monitoring of an industrial gas cylinder is realized by arranging a binocular camera and an infrared imager; the method is suitable for monitoring industrial gas cylinders filled with gas (such as carbon dioxide and methane) with remarkable absorption characteristics in an infrared region and industrial gas cylinders filled with high-pressure gas, arrangement and maintenance of a large number of sensors are omitted, and the monitoring cost is lower and higher efficiency is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial gas cylinder leakage warning technology, and in particular to an industrial gas cylinder leakage prevention intelligent warning system and method based on big data. Background Art

[0002] A gas cylinder is a pressure-bearing device with explosion hazard, and its containing medium is generally flammable, explosive, toxic, highly corrosive, etc. The use environment is more complex and harsh than other pressure vessels due to its characteristics of mobility, repeated filling, non-fixed operating personnel and changing use environment. Once a gas cylinder explodes or leaks, it often causes fire or poisoning, or even catastrophic accidents, resulting in serious property losses, casualties and environmental pollution. Therefore, it is necessary to monitor the gas cylinder and promptly detect the leakage accident of the gas cylinder. The prior art of publication number CN112862304A discloses a gas cylinder monitoring and management method, including: obtaining a regional map of the monitoring area, marking the target gas cylinder and the gas channel associated with the target gas cylinder on the regional map; obtaining the position information and switch status information of the stop valve set on the gas channel; obtaining the sensor data detected by the sensor set on the target gas cylinder; the sensor data includes air pressure information; the background server determines the parameter information of the target gas cylinder according to the position information, switch status information and sensor data of the stop valve, and sends the parameter information to the mobile terminal for display. Carry out relevant monitoring, recording and data analysis on the gas cylinders placed in the gas cylinder room to ensure that all types of gas cylinders in the gas cylinder room can safely and stably serve users and improve user experience. At the same time, the gas cylinders are effectively monitored to reduce safety hazards caused by gas leakage.

[0003] However, the realization of gas cylinder leakage monitoring requires the support of a large number of sensors. More sensors increase the probability of sensor failure. That is, the layout, debugging and maintenance of sensors require a high time and monetary cost, making the actual use process more complicated and not suitable for small or low-cost gas cylinder storage or transfer sites. Therefore, a simple and efficient gas cylinder leakage monitoring method is urgently needed. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent early warning system and method for preventing leakage of industrial gas cylinders based on big data, so as to solve the above-mentioned deficiencies in the prior art.

[0005] In order to achieve the above object, the present invention provides the following technical solution: an intelligent early warning method for preventing leakage of industrial gas cylinders based on big data, comprising the following steps: S1. Collect image data and thermal imaging data of industrial gas cylinder storage sites; S2. Analyze and process the industrial gas cylinder model and the position in the image contained in the image monitoring data according to the industrial gas cylinder storage site image data and the industrial gas cylinder model characteristic image data, and generate industrial gas cylinder model position data; S3, calculating and processing the position of each pixel in the industrial gas cylinder storage site image data in the real world according to the industrial gas cylinder storage site image data and the binocular camera parameter data, and generating the industrial gas cylinder storage site image real position data; S4, according to the industrial gas cylinder model location data and the industrial gas cylinder storage site image actual location data, search and process the industrial gas cylinder storage site image actual location data corresponding to the industrial gas cylinder model location data to generate the industrial gas cylinder model actual location data; S5. Performing image registration processing on the thermal imaging data of the industrial gas cylinder storage site with reference to the image data of the industrial gas cylinder storage site to generate registered thermal imaging data of the industrial gas cylinder storage site; S6. Performing industrial gas cylinder leakage feature recognition and analysis processing at the industrial gas cylinder storage site based on the registered thermal imaging data of the industrial gas cylinder storage site and the industrial gas cylinder leakage thermal imaging data, generating storage site industrial gas cylinder leakage feature return data, and performing industrial gas cylinder leakage warning solution analysis processing based on the storage site industrial gas cylinder leakage feature return data and the industrial gas cylinder leakage feature warning solution data, generating industrial gas cylinder leakage warning solution analysis data; S7, according to the returned data of the leakage characteristics of the industrial gas cylinders at the storage site and the actual location data of the industrial gas cylinder model, searching for the actual location corresponding to the identified leakage characteristics of the industrial gas cylinders, and generating the leakage location data of the industrial gas cylinders at the storage site; S8. Collect and 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 leakage feature return data, the storage site industrial gas cylinder leakage location data and the industrial gas cylinder leakage warning plan analysis data to generate industrial gas cylinder leakage warning data, and perform leakage warning information notification operations based on the industrial gas cylinder leakage warning data.

[0006] Furthermore, the S1 comprises the following steps: 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 image data sets of industrial gas cylinder storage sites , , represents the oth industrial gas cylinder storage site image data, Indicates the maximum number of image data of industrial gas cylinder storage sites; S12. Use the infrared imager installed at the industrial gas cylinder storage site to collect 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 , , Representation and Thermal imaging data of industrial gas cylinder storage sites at the same time.

[0007] Further, the S2 comprises the following steps: S21. Collect images of various types of industrial gas cylinders and establish a data set of industrial gas cylinder model feature images , , 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. 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 Maximum number of industrial gas cylinders in China, , Z is the industrial gas cylinder The pixel coordinates 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.

[0008] Further, the S3 comprises the following steps: S31, collecting the binocular camera parameter data E of the binocular camera, including (1) camera intrinsic parameters: obtaining the focal length, principal point and distortion parameters of the camera. These parameters are obtained through camera calibration (such as using a chessboard); (2) camera extrinsic parameters: determining the position and orientation of the camera in three-dimensional space (rotation matrix and translation vector); (3) coordinate system conversion: converting the image pixel coordinates (2D) into the camera coordinate system (3D), and finally converting to the world coordinate system through extrinsic parameters; S32. Calculate the image data of the industrial gas cylinder storage site based on stereo vision technology and binocular camera parameter data E The location of each pixel coordinate in the real world to generate image data of industrial gas cylinder storage sites Industrial gas cylinder storage site image real location data set , , express The actual position data corresponding to the qth pixel point in , express The maximum number of pixels in the image.

[0009] Further, the S4 comprises the following steps: S41, based on the double pointer method, the industrial gas cylinder model location data set and the actual location data set of the industrial gas cylinder storage site image Search and find the middle The pixel coordinate in Z Corresponding , generate the actual location data set of industrial gas cylinder models , express The model and actual location data of the wth industrial gas cylinder, , A collection of real-world location data , express Corresponding .

[0010] Further, the S5 comprises the following steps: S51, referring to the industrial gas cylinder storage site image data Thermal imaging data of the industrial gas cylinder storage site Perform image registration processing to generate registered thermal imaging data for industrial gas cylinder storage sites .

[0011] Further, the S6 comprises the following steps: S61, collecting thermal imaging data of industrial gas cylinder leakage, and establishing a thermal imaging data set G of industrial gas cylinder leakage; S62, extracting features from the industrial gas cylinder leakage thermal imaging data set G, for example, using Canny, Sobel, Laplacian operators, etc., to generate industrial gas cylinder leakage thermal imaging feature data Then, based on the DBSCAN clustering algorithm, Perform feature clustering to generate thermal imaging data sets of industrial gas cylinder leakage feature types , , Represents the thermal imaging data of the leakage characteristic type of the v-type industrial gas cylinder, Indicates the maximum number of industrial gas cylinder leakage feature types; S63, based on industrial gas cylinder model location data collection Registering thermal imaging data with industrial gas cylinder storage sites , for the 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; S64, sequentially searching for the same thermal imaging data set I in the search space of the thermal imaging data set H for the characteristic type of leakage of industrial gas cylinders Matched , that is, search and arrive Matched , generate the data set returned by the leakage characteristics of industrial gas cylinders in the storage site , including the following steps: S641, initializing algorithm parameters, firefly population number N, maximum number of iterations T; 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; S643, calculating the fitness of fireflies, which is used to simulate the light intensity of fireflies. The better the fitness of fireflies, the greater the light intensity. S644, fireflies with low fitness approach fireflies with high fitness, which is used to simulate fireflies approaching fireflies with high light intensity. The firefly position update formula is as follows: , 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; 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 the storage site , express Corresponding ; 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 , Representation and Corresponding industrial gas cylinder leakage feature warning plan data; S66. Based on the double pointer method, return the data set for the leakage characteristics of industrial gas cylinders in the storage site middle Matching industrial gas cylinder leakage feature warning scheme data set J Search and generate industrial gas cylinder leakage warning solution analysis data .

[0012] Further, the S7 comprises the following steps: 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; S72, based on the double pointer method, and the actual location data set of the industrial gas cylinder model Search and find Zhongyu Matched , data on the location of industrial gas cylinder leaks at storage sites .

[0013] Further, the S8 comprises the following steps: S81, image data of the industrial gas cylinder storage site , Industrial gas cylinder storage site registration thermal imaging data , Industrial gas cylinder leakage characteristics return data set at storage sites , Data on the location of industrial gas cylinder leaks at storage sites And the industrial gas cylinder leakage warning program analysis data Collect and combine to generate industrial gas cylinder leakage warning data , perform leakage warning information notification operations according to the industrial gas cylinder leakage warning data K.

[0014] An intelligent early warning system for preventing leakage of industrial gas cylinders based on big data, including binocular cameras, infrared imagers, processors, memory, and alarm modules; 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; The infrared imager is used to collect thermal imaging data of industrial gas cylinder storage sites in real time and generate a thermal imaging data set of industrial gas cylinder storage sites; The memory is used to store computer programs; The processor is used to execute a computer program to implement the intelligent early warning method for preventing leakage of industrial gas cylinders based on big data; The alarm module is used to send leakage warning information according to the industrial gas cylinder leakage warning data.

[0015] 1. Compared with the prior art, the big data-based intelligent early warning system and method for preventing leakage of industrial gas cylinders provided by the present invention collects visual image information of gas cylinder storage sites, namely, image data of industrial gas cylinder storage sites, through a binocular camera, detects gas cylinders in visual images through a target detection algorithm, and calculates the position of each gas cylinder in the actual site through stereo vision technology to achieve accurate positioning of the gas cylinders.

[0016] 2. Compared with the prior art, the intelligent early warning system and method for preventing leakage of industrial gas cylinders based on big data provided by the present invention collects thermal imaging data of gas cylinders through infrared imagers, and determines whether the gas cylinder is leaking and the leakage situation (i.e., leakage characteristics) by identifying the thermal imaging characteristics of the gas cylinder and its surroundings, so as to select an early warning plan according to the leakage situation and make the content of the early warning more detailed.

[0017] 3. Compared with the prior art, the big data-based intelligent early warning system and method for preventing leakage of industrial gas cylinders provided by the present invention performs image registration between thermal imaging and image data of industrial gas cylinder storage sites, so that the image pixel coordinates of thermal imaging and image data of industrial gas cylinder storage sites are aligned, so that the corresponding positions of thermal imaging and image data of industrial gas cylinder storage sites can be found in the display site according to the positions of leakage features of industrial gas cylinders identified in thermal imaging data, thereby realizing accurate positioning of the leakage position.

[0018] 4. Compared with the prior art, the big data-based intelligent early warning system and method for preventing leakage of industrial gas cylinders provided by the present invention realizes leakage monitoring of industrial gas cylinders by arranging binocular cameras and infrared imagers. It is suitable for monitoring industrial gas cylinders containing gases with significant absorption characteristics in the infrared region (such as carbon dioxide, methane, ammonia, carbon monoxide, etc.) and industrial gas cylinders containing high-pressure gases, eliminating the need for the arrangement and maintenance of a large number of sensors, making the monitoring cost lower and more efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0020] Figure 1 A method step diagram provided for an embodiment of the present invention; Figure 2 A system structure block diagram provided for an embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0022] In the description of the present invention, it is to be understood that the exemplary embodiments will be described more fully below with reference to the accompanying drawings, but the exemplary embodiments may be embodied in different forms and should not be construed 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.

[0023] In the absence of conflict, the various embodiments of the present disclosure and the various features therein may be combined with each other.

[0024] As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0025] The terms used herein are only used 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.

[0026] The embodiments described herein may be described with reference to plan views and / or cross-sectional views by means of idealized schematic diagrams of the present disclosure. Therefore, the example illustrations may be modified according to 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 have schematic properties, and the shapes of the regions shown in the figures illustrate the specific shapes of the regions of the elements, but are not intended to be limiting.

[0027] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those 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 explicitly defined as such herein.

[0028] The intelligent early warning method for preventing leakage of industrial gas cylinders based on big data includes the following steps: S1. Collecting image data and thermal imaging data of industrial gas cylinder storage sites, including the following steps: 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 image data sets of industrial gas cylinder storage sites , , represents the oth industrial gas cylinder storage site image data, Indicates the maximum number of image data of industrial gas cylinder storage sites; S12. Use the infrared imager installed at the industrial gas cylinder storage site to collect 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 , , Representation and 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 .

[0029] S2. Analyzing and processing the industrial gas cylinder model and the position in the image contained in the image monitoring data according to the industrial gas cylinder storage site image data and the industrial gas cylinder model feature image data, and generating the industrial gas cylinder model position data, including the following steps: S21. Collect images of various types of industrial gas cylinders and establish a data set of industrial gas cylinder model feature images , , Represents the characteristic image data of the p-th type of industrial gas cylinder model, Indicates the maximum number of industrial gas cylinder models, identifies the models of industrial gas cylinders, and subsequently refers to the models of industrial gas cylinders to formulate industrial gas cylinder leakage feature warning plan data, making the warning plan more specific and detailed; 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 Maximum number of industrial gas cylinders in China, , Z is the industrial gas cylinder The pixel coordinates 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.

[0030] S3, based on the industrial gas cylinder storage site image data and 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, and generating the industrial gas cylinder storage site image real position data, including the following steps: S31, collect the binocular camera parameter data E of the binocular camera, including (1) camera intrinsic parameters: obtain the focal length, focus and distortion parameters of the camera. These parameters are obtained through camera calibration (such as using a chessboard); (2) camera extrinsic parameters: determine the position and orientation of the camera in three-dimensional space (rotation matrix and translation vector); (3) coordinate system conversion: convert the image pixel coordinates (2D) into the camera coordinate system (3D), and finally convert to the world coordinate system through extrinsic parameters; S32. Calculate the image data of the industrial gas cylinder storage site based on stereo vision technology and binocular camera parameter data E The location of each pixel coordinate in the real world to generate image data of industrial gas cylinder storage sites Industrial gas cylinder storage site image real location data set , , express The actual position data corresponding to the qth pixel point in , express The maximum number of pixels in the image; the calculation of stereo vision technology generally includes the following steps: (1) disparity calculation: calculate the disparity by matching corresponding points in the left and right images (such as SIFT, ORB feature points); (2) calculate the depth based on the baseline distance of the binocular camera (that is, the distance between the two cameras, which can be obtained through the camera extrinsic parameters) and the calculated disparity; the calculation process can use OpenCV's StereoBM or StereoSGBM algorithm.

[0031] S4, according to the industrial gas cylinder model location data and the industrial gas cylinder storage site image actual location data, searching and processing the industrial gas cylinder storage site image actual location data corresponding to the industrial gas cylinder model location data, generating the industrial gas cylinder model actual location data, including the following steps: S41, Industrial gas cylinder model location data collection based on double pointer method and the actual location data set of the industrial gas cylinder storage site image Search and find middle The pixel coordinate in Z Corresponding , generate the actual location data set of industrial gas cylinder models , express The model and actual location data of the wth industrial gas cylinder, , A collection of real-world location data , express Corresponding , the actual position data is the three-dimensional position coordinate data in the storage site.

[0032] S5. Performing image registration processing on the thermal imaging data of the industrial gas cylinder storage site with reference to the image data of the industrial gas cylinder storage site to generate registered thermal imaging data of the industrial gas cylinder storage site, including the following steps: S51, Reference industrial gas cylinder storage site image data Thermal imaging data of industrial gas cylinder storage sites Perform image registration processing to generate registered thermal imaging data for industrial gas cylinder storage sites .

[0033] S6. Based on the registered thermal imaging data of the industrial gas cylinder storage site and the thermal imaging data of the industrial gas cylinder leakage, the industrial gas cylinder leakage feature recognition and analysis processing of the industrial gas cylinder storage site is performed to generate the industrial gas cylinder leakage feature return data of the storage site, and based on the industrial gas cylinder leakage feature return data of the storage site and the industrial gas cylinder leakage feature warning plan data, the early warning plan analysis and processing of the industrial gas cylinder leakage is performed to generate the industrial gas cylinder leakage early warning plan analysis data, including the following steps: S61, collecting thermal imaging data of industrial gas cylinder leakage, and establishing a thermal imaging data set G of industrial gas cylinder leakage; S62, extracting features from the industrial gas cylinder leakage thermal imaging data set G, for example, using Canny, Sobel, Laplacian operators, etc., to generate industrial gas cylinder leakage thermal imaging feature data , and then based on the DBSCAN clustering algorithm Perform feature clustering to generate thermal imaging data sets of industrial gas cylinder leakage feature types , , Represents the thermal imaging data of the leakage characteristic type of the v-type industrial gas cylinder, represents the maximum number of industrial gas cylinder leakage feature types. The DBSCAN clustering algorithm can be used to cluster the industrial gas cylinder leakage feature type thermal imaging data set H according to the The features of H are directly classified without setting the number of clusters (i.e. the number of categories) in advance, and The corresponding thermal imaging data of industrial gas cylinder leakage is consistent with the corresponding leakage situation, so as to adjust the parameters of DBSCAN clustering algorithm to adjust the clustering results, so that each The characteristics of the thermal imaging data of the corresponding industrial gas cylinder leakage are obviously different, and the leakage conditions corresponding to the thermal imaging data of the corresponding industrial gas cylinder leakage are basically consistent, which ensures the accuracy of subsequent leakage feature identification; S63, based on industrial gas cylinder model location data collection 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; S64, sequentially searching for the same thermal imaging data set I in the search space of the thermal imaging data set H for the characteristic type of leakage of industrial gas cylinders Matched , that is, search and arrive Matched , generate the data set returned by the leakage characteristics of industrial gas cylinders in the storage site , including the following steps: S641, initializing algorithm parameters, firefly population number N, maximum number of iterations T; 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; S643, calculating the fitness of fireflies, which is used to simulate the light intensity of fireflies. The better the fitness of fireflies, the greater the light intensity. S644, fireflies with low fitness approach fireflies with high fitness, which is used to simulate fireflies approaching fireflies with high light intensity. The firefly position update formula is as follows: , 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; 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 the storage site , express Corresponding ; 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 , Representation and Corresponding industrial gas cylinder leakage feature warning plan data; S66. Based on the double pointer method, return the data set for the leakage characteristics of industrial gas cylinders in the storage site middle Matching industrial gas cylinder leakage feature warning scheme data set J Search and generate industrial gas cylinder leakage warning solution analysis data .

[0034] S7, according to the returned data of the leakage characteristics of the industrial gas cylinders at the storage site and the actual location data of the industrial gas cylinder models, searching and processing the actual location corresponding to the identified leakage characteristics of the industrial gas cylinders to generate the leakage location data of the industrial gas cylinders at the storage site, including the following steps: 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; S72, based on the double pointer method, and industrial gas cylinder model actual location data collection Search and find Zhongyu Matched , data on the location of industrial gas cylinder leaks at storage sites .

[0035] S8. Collect and 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 leakage feature return data, the storage site industrial gas cylinder leakage location data and the industrial gas cylinder leakage warning plan analysis data to generate industrial gas cylinder leakage warning data, and perform leakage warning information notification operations based on the industrial gas cylinder leakage warning data, including the following steps: S81, image data of industrial gas cylinder storage site , Industrial gas cylinder storage site registration thermal imaging data , Industrial gas cylinder leakage characteristics return data set at storage sites , Data on the location of industrial gas cylinder leaks at storage sites and industrial gas cylinder leakage warning program analysis data Collect and combine to generate industrial gas cylinder leakage warning data , and perform leakage warning information notification operations based on the industrial gas cylinder leakage warning data K.

[0036] The present invention also provides an industrial gas cylinder anti-leakage intelligent early warning system based on big data, which is used to execute the industrial gas cylinder anti-leakage intelligent early warning method based on big data provided by the present invention, including a binocular camera, an infrared imager, a processor, a memory, and an alarm module; The binocular camera is used 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; The infrared imager is used to collect thermal imaging data of industrial gas cylinder storage sites in real time and generate a thermal imaging data set of industrial gas cylinder storage sites; The memory is used to store computer programs; The processor is used to execute a computer program to implement an intelligent early warning method for preventing leakage of industrial gas cylinders based on big data; The alarm module is used to send leakage warning information based on industrial gas cylinder leakage warning data.

[0037] The above description is only by way of illustration of certain exemplary embodiments of the present invention. It is undoubted that those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. 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 present invention.

Claims

1. An intelligent early warning method for preventing leakage of industrial gas cylinders based on big data, characterized by: The following steps are involved: S1. Collect image data and thermal imaging data of industrial gas cylinder storage sites; S2, analyzing and processing the industrial gas cylinder model and the position in the image of the image monitoring data according to the data collected in S1, and generating the industrial gas cylinder model position data; S3. Calculate and process the position of each pixel in the industrial gas cylinder storage site image data in the real world according to the binocular camera parameter data to generate the real position data of the industrial gas cylinder storage site image; S4, searching and processing the actual position data of the industrial gas cylinder storage site image corresponding to the industrial gas cylinder model position data to generate the actual position data of the industrial gas cylinder model; S5. Perform image registration processing on the thermal imaging data of the industrial gas cylinder storage site with reference to the image data of the industrial gas cylinder storage site to generate registered thermal imaging data of the industrial gas cylinder storage site; S6. Performing industrial gas cylinder leakage feature recognition and analysis based on the industrial gas cylinder storage site registration thermal imaging data and industrial gas cylinder leakage thermal imaging data, generating industrial gas cylinder leakage feature return data for the storage site, and performing industrial gas cylinder leakage warning solution analysis and processing in combination with industrial gas cylinder leakage feature warning solution data, generating industrial gas cylinder leakage warning solution analysis data; S7. Performing a search process for the actual location of industrial gas cylinder leakage characteristics based on the returned data of industrial gas cylinder leakage characteristics at the storage site and the actual location data of the industrial gas cylinder model, and generating the location data of industrial gas cylinder leakage at the storage site; S8. Construct industrial gas cylinder leakage warning data and carry out leakage warning information notification operations.

2. The intelligent early warning method for preventing leakage of industrial gas cylinders based on big data according to claim 1 is characterized by: The S1 comprises the following steps: 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 image data sets of industrial gas cylinder storage sites , , represents the oth industrial gas cylinder storage site image data, Indicates the maximum number of image data of industrial gas cylinder storage sites; S12. Use the infrared imager installed at the industrial gas cylinder storage site to collect 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 , , Representation and Thermal imaging data of industrial gas cylinder storage sites at the same time.

3. The intelligent early warning method for preventing leakage of industrial gas cylinders based on big data according to claim 2 is characterized by: The S2 comprises the following steps: S21. Collect images of various types of industrial gas cylinders and establish a data set of industrial gas cylinder model feature images , , 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. 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 Maximum number of industrial gas cylinders in China, , Z is the industrial gas cylinder The pixel coordinates in , , represents the u-th pixel coordinate, Represents the maximum number of pixel coordinates in Z.

4. The intelligent early warning method for preventing leakage of industrial gas cylinders based on big data according to claim 3 is characterized by: 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 location of each pixel coordinate in the real world to generate image data of industrial gas cylinder storage sites Industrial gas cylinder storage site image real location data set , , express The actual position data corresponding to the qth pixel point in , express The maximum number of pixels in the image.

5. The intelligent early warning method for preventing leakage of industrial gas cylinders based on big data according to claim 4 is characterized in that: The S4 comprises the following steps: S41, based on the double pointer method, the industrial gas cylinder model location data set and the actual location data set of the industrial gas cylinder storage site image Search and find the middle The pixel coordinate in Z Corresponding , generate the actual location data set of industrial gas cylinder models , express The model and actual location data of the wth industrial gas cylinder, , A collection of real-world location data , express Corresponding .

6. The intelligent early warning method for preventing leakage of industrial gas cylinders based on big data according to claim 5 is characterized by: The S5 comprises the following steps: S51, referring to the industrial gas cylinder storage site image data Thermal imaging data of the industrial gas cylinder storage site Perform image registration processing to generate registered thermal imaging data for industrial gas cylinder storage sites .

7. The intelligent early warning method for preventing leakage of industrial gas cylinders based on big data according to claim 6 is characterized by: The S6 comprises the following steps: S61, collecting thermal imaging data of industrial gas cylinder leakage, and establishing a thermal imaging data set G of industrial gas cylinder leakage; S62, extracting features from 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, Perform feature clustering to generate thermal imaging data sets of industrial gas cylinder leakage feature types , , Represents the thermal imaging data of the leakage characteristic type of the v-type industrial gas cylinder, Indicates the maximum number of industrial gas cylinder leakage feature types; S63, based on industrial gas cylinder model location data collection Registering thermal imaging data with industrial gas cylinder storage sites , for the 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; S64, sequentially searching for the same thermal imaging data set I in the search space of the thermal imaging data set H for the characteristic type of leakage of industrial gas cylinders Matched , generate the data set returned by the leakage characteristics of industrial gas cylinders in the storage site , including the following steps: S641, initializing algorithm parameters, firefly population number N, maximum number of iterations T; S642, initializing the position of the firefly population; S643, calculate the fitness of fireflies; S644, the firefly with low fitness moves closer to the firefly with high fitness. The firefly position update formula is as follows: , 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; 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 the storage site , express Corresponding ; 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 , Representation and Corresponding industrial gas cylinder leakage feature warning plan data; S66. Based on the double pointer method, return the data set for the leakage characteristics of industrial gas cylinders in the storage site middle Matching industrial gas cylinder leakage feature warning scheme data set J Search and generate industrial gas cylinder leakage warning solution analysis data .

8. The intelligent early warning method for preventing leakage of industrial gas cylinders based on big data according to claim 7 is characterized in that: The S7 comprises the following steps: 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; S72, based on the double pointer method, and the actual location data set of the industrial gas cylinder model Search and find Zhongyu Matched , data on the location of industrial gas cylinder leaks at storage sites .

9. The intelligent early warning method for preventing leakage of industrial gas cylinders based on big data according to claim 8 is characterized by: The S8 comprises the following steps: S81, image data of the industrial gas cylinder storage site , Industrial gas cylinder storage site registration thermal imaging data , Industrial gas cylinder leakage characteristics return data set at storage sites , Data on the location of industrial gas cylinder leaks at storage sites And the industrial gas cylinder leakage warning program analysis data Collect and combine to generate industrial gas cylinder leakage warning data , perform leakage warning information notification operations according to the industrial gas cylinder leakage warning data K.

10. An intelligent early warning system for preventing leakage of industrial gas cylinders based on big data, used to implement the intelligent early warning method for preventing leakage of industrial gas cylinders based on big data according to any one of claims 1 to 9, characterized in that: Including binocular camera, infrared imager, processor, memory, alarm module; 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; The infrared imager is used to collect thermal imaging data of industrial gas cylinder storage sites in real time and generate a thermal imaging data set of industrial gas cylinder storage sites; The memory is used to store computer programs; The processor is used to execute a computer program to implement the intelligent early warning method for preventing leakage of industrial gas cylinders based on big data as described in any one of claims 1 to 9; The alarm module is used to send leakage warning information according to the industrial gas cylinder leakage warning data.

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