Chemical storage tank corrosion safety detection device and method

Abstract

The invention belongs to the technical field of chemical safety detection, and discloses a chemical storage tank corrosion safety detection device and method.The method comprises the steps that a route planning module plans routes of a side face detection mechanism and an end face detection assembly; the transverse driving mechanism drives the side face detection mechanism to move, and a detection unit on the side face detection mechanism detects the circumferential side face of the storage tank. The transverse moving assembly drives the end face detection assembly and the detection unit to detect the two end faces of the storage tank. The ultrasonic detection module, the infrared detection module and the image analysis module identify abnormal conditions of the storage tank; the comprehensive evaluation module comprehensively evaluates the corrosion safety of the storage tank and predicts potential risks. According to the invention, the circumferential side surface and the two end surfaces of the storage tank are rapidly and comprehensively detected, and corrosion safety detection is carried out on the storage tank by multiple means through ultrasonic detection, infrared detection and image analysis; and the detection results of the plurality of detection modules are fused with environmental data, the corrosion safety of the storage tank is comprehensively evaluated, and potential risks are predicted.

Description

Technical Field

[0001] The present application relates to the technical field of chemical safety detection, and more specifically, to a chemical storage tank corrosion safety detection device and method. Background Art

[0002] Storage tanks are widely used as static equipment for storing media in the petroleum and chemical industries. However, during use, storage tanks are more susceptible to electrochemical corrosion, and the degree of corrosion is more serious than that of the tank wall. Sometimes, corrosion perforation may occur, resulting in oil leakage. The tank bottom is not easy to inspect and repair, and is prone to corrosion. When welding the bottom plate, the anti-corrosion coating near the weld is often burned, which increases the severity of corrosion.

[0003] The document with the prior art publication number CN220730120U provides a corrosion detection device for chemical safety storage tanks, including a base, a track is installed on the top of the base, the track is rollingly connected to the track wheel, the track wheel is installed on the side of the mounting seat, a first motor is provided on the other side of the mounting seat, the output shaft of the first motor is connected to the track wheel, a first mounting frame is installed on the top of the mounting seat, the first mounting frame is fixedly connected to the detection device fixing seat, an electric cylinder is installed on the detection device fixing seat, a bearing seat is installed at the bottom of the piston rod of the electric cylinder, the bearing seat is rotatably connected to the multifunctional detection device, a second motor is installed on the side of the bearing seat, the output shaft of the second motor is connected to the multifunctional detection device, the device has the functions of automatic cleaning of the storage tank surface, automatic coupling agent spraying and automatic ultrasonic detection, which greatly facilitates the corrosion detection work of the chemical storage tank.

[0004] Although the above-mentioned prior art solutions can achieve relevant beneficial effects through the structure of the prior art, they still have the following defects: 1. Low detection efficiency. 2. Through a single detection method, the tank corrosion detection is not accurate enough, and it is impossible to comprehensively and accurately evaluate the corrosion of the tank.

[0005] In view of this, we propose a chemical storage tank corrosion safety detection device and method. Summary of the invention

[0006] 1. Technical problems to be solved

[0007] The purpose of this application is to provide a corrosion safety detection device and method for chemical storage tanks, which solves the technical problems raised in the above-mentioned background technology, realizes all-round detection of the circumferential side and two end faces of the storage tank, and performs corrosion safety detection on the storage tank by various means such as ultrasonic detection, infrared detection and image analysis; the comprehensive evaluation module integrates the detection results of multiple detection modules with environmental data, comprehensively evaluates the corrosion safety of the storage tank and predicts the technical effect of potential risks.

[0008] 2. Technical solution

[0009] The technical solution of the present application provides a chemical tank corrosion safety detection device, including: a base, a side detection bracket, a support assembly, a lateral drive mechanism, a side detection mechanism, a lifting drive mechanism, a lateral movement assembly, an end face detection assembly, a detection unit and a monitoring mechanism.

[0010] Pillars are fixedly arranged at the four corners above the base, and a top plate is fixedly arranged above the four pillars; a transverse driving mechanism is fixedly arranged on the top plate, and a side detection bracket is movably arranged on the transverse driving mechanism; the transverse driving mechanism and the side detection bracket are transmission-connected; the transverse driving mechanism can move the side detection bracket.

[0011] The side detection bracket is rotatably provided with a side detection mechanism, which is transmission-connected to the side detection bracket. The side detection mechanism can rotate on the side detection bracket. A detection unit is fixedly provided on the side detection mechanism.

[0012] A plurality of supporting components are fixedly arranged on the base, and chemical storage tanks can be supported by the supporting components; a lifting drive mechanism is arranged on the base, a lateral movement component is slidably arranged on the lifting drive mechanism, an end face detection component is slidably arranged on the lateral movement component, and a detection unit is fixedly arranged on the end face detection component.

[0013] A monitoring mechanism is fixed on the base, which detects and evaluates the process of corrosion safety detection of chemical storage tanks to detect abnormal conditions and potential risks in time.

[0014] Through the above technical scheme, the chemical storage tanks that need to be tested for corrosion safety are placed on the support assembly, the side detection mechanism is driven to move by the lateral driving mechanism, and the circumferential side of the storage tank is detected by the detection unit on the side detection mechanism; the transverse movement assembly is driven up and down by the lifting driving mechanism, and the transverse movement assembly drives the end face detection assembly and the detection unit to detect the two end faces of the storage tank.

[0015] As an optional solution of the present invention, the monitoring mechanism includes:

[0016] Data collection module: collects material and size data of chemical storage tanks; collects data of storage media in chemical storage tanks.

[0017] Environmental data acquisition module: real-time collection of environmental data, including temperature and humidity data.

[0018] Route planning module: According to the material size of the chemical storage tank and the detection range of the detection unit, the travel route of the side detection mechanism and the end face detection component is reasonably planned.

[0019] Ultrasonic detection module: perform ultrasonic detection on storage tanks; analyze and identify ultrasonic data to detect abnormal situations in a timely manner.

[0020] Infrared detection module: perform infrared detection on storage tanks; analyze and identify infrared data to detect abnormal situations in a timely manner.

[0021] Image acquisition module: includes a high-definition camera and LED lights to collect high-definition images of the storage tank.

[0022] Image analysis module: Analyze and identify the collected images to promptly identify abnormal conditions on the tank surface.

[0023] Comprehensive assessment module: Integrates the detection results of the infrared detection module, ultrasonic detection module and image analysis module with environmental data (temperature, humidity) to conduct a comprehensive assessment of the corrosion safety of the storage tank and predict potential risks.

[0024] Alarm module: includes an alarm, which will sound an alarm in time when abnormal conditions or potential risks are detected.

[0025] Control center: connected to the data collection module, environmental data collection module, ultrasonic detection module, infrared detection module, image acquisition module, route planning module, image analysis module, comprehensive evaluation module and alarm module network.

[0026] As an optional solution of the present invention, the comprehensive evaluation module integrates the detection results of the infrared detection module, the ultrasonic detection module and the image analysis module with the environmental data to comprehensively evaluate the corrosion safety of the storage tank and predict potential risks.

[0027] The following steps are involved:

[0028] 1. Data collection and organization: Obtain test data from the infrared detection module, including information such as temperature distribution, hot spot size, shape and temperature change, as well as identified possible abnormalities (such as corrosion, leakage, etc.) and their location and severity assessment. Obtain test data from the ultrasonic detection module, covering the analysis results of ultrasonic data, such as the location, size and characteristic parameters of defects such as wall thinning, holes and internal cracks. Obtain test data from the image analysis module, including information such as the location, type and severity of identified abnormalities on the surface of the tank (such as cracks and deformation). Collect ambient temperature and humidity data. Organize the test results and environmental data of each module to ensure the accuracy and consistency of the data. Format the data so that it has a unified format and structure.

[0029] 2. Data fusion: Extract features from the detection results and environmental data of each module. Based on correlation analysis and domain knowledge, select features that have a significant impact on the safety assessment of tank corrosion, remove redundant or irrelevant features to reduce data dimensions and improve analysis efficiency and accuracy. Select the feature layer fusion method for data fusion: fuse the features extracted from each module, and splice the temperature features of infrared detection, the defect features of ultrasonic detection, and the surface features of image analysis to form a feature vector that fully reflects the state of the tank.

[0030] 3. Standardization of fused data: Standardize the fused data and unify the numerical ranges of different features to the same scale to avoid excessive impact of some features on the evaluation results due to excessively large or small values.

[0031] 4. Comprehensive evaluation: Based on the relevant standards and experience of tank corrosion safety, a comprehensive evaluation index system is established. The evaluation indicators include corrosion degree, defect type and severity, environmental influencing factors, etc. Select the support vector machine regression model, input the fused and standardized data into the constructed evaluation model, and calculate the comprehensive evaluation results of tank corrosion safety. Determine the current corrosion safety status of the tank based on the evaluation results.

[0032] 5. Potential risk prediction: Select the artificial neural network prediction model to predict future development trends. The artificial neural network prediction model has strong nonlinear mapping and learning capabilities, can handle complex nonlinear relationships, and predict future potential risks by learning and training a large amount of historical data. Input the current detection data and environmental data into the trained prediction model to predict the corrosion safety status and potential risks of the storage tank in the future. According to the prediction results, analyze the types and extent of potential risks that may occur, such as predicting whether new corrosion areas will appear and whether existing defects will expand.

[0033] 6. Result output: The comprehensive assessment results and potential risk prediction results are sorted out and presented in an intuitive and easy-to-understand manner. The assessment results are presented in the form of charts, such as radar charts, bar charts, etc., to intuitively display the scores of each assessment indicator and the comprehensive assessment level; the prediction results are presented in the form of curves to predict the changing trend of the corrosion safety status of the tank in the future. A detailed comprehensive assessment report is generated, which includes the test time, test location, tank number, results of each test module, environmental data, comprehensive assessment results, potential risk prediction results, and corresponding suggestions and measures.

[0034] The present invention provides a chemical storage tank corrosion safety detection method, comprising the following steps:

[0035] S1. Place the chemical storage tank on the support assembly; the data collection module collects the material and size data of the chemical storage tank; and collects the data of the storage medium in the chemical storage tank.

[0036] S2. The route planning module of the monitoring mechanism reasonably plans the travel routes of the side detection mechanism and the end face detection component according to the material size of the chemical storage tank and the detection range of the detection unit.

[0037] S3. The lateral detection mechanism is driven to move by the lateral driving mechanism, and the circumferential side of the storage tank is detected by the detection unit on the lateral detection mechanism; the environmental data acquisition module collects environmental data in real time, including temperature and humidity data.

[0038] S31. When the lateral driving mechanism drives the side detection bracket and the side detection mechanism to move to one of the support assembly positions, the hydraulic cylinder of the support assembly drives the arc-shaped support plate to descend, making room for the side detection bracket to move, and other support assemblies support the storage tank.

[0039] S32. When the lateral driving mechanism drives the side detection bracket and the side detection mechanism to pass through the support assembly position, the hydraulic cylinder of the support assembly drives the arc-shaped support plate to rise to support the storage tank.

[0040] S4. The lifting drive mechanism drives the transverse movement assembly to move up and down, and the transverse movement assembly drives the end surface detection assembly and the detection unit to detect the two end surfaces of the storage tank.

[0041] S5. The ultrasonic detection module performs ultrasonic detection on the storage tank; analyzes and identifies the ultrasonic data to promptly detect abnormal conditions (including thinning of the wall thickness, holes and internal cracks, etc.).

[0042] S6. The infrared detection module performs infrared detection on the storage tank; analyzes and identifies the infrared data to detect abnormal conditions (corrosion, leakage, etc.) in a timely manner.

[0043] S7. The image acquisition module acquires high-definition images of the storage tank; the image analysis module analyzes and identifies the acquired images, and promptly identifies abnormal conditions (cracks and deformations, etc.) on the surface of the storage tank.

[0044] S8. The comprehensive assessment module integrates the detection results of the infrared detection module, ultrasonic detection module and image analysis module with environmental data (temperature, humidity) to conduct a comprehensive assessment of the corrosion safety of the storage tank and predict potential risks.

[0045] S9. When an abnormal situation or potential risk is detected, the alarm module will issue an alarm in time.

[0046] 3. Beneficial effects

[0047] One or more technical solutions provided in the technical solution of this application have at least the following technical effects or advantages.

[0048] 1. The present invention can perform all-round detection on the circumferential side and two end faces of the storage tank, and can fully obtain relevant information on the side of the storage tank.

[0049] 2. Ensure the smooth progress of the detection process: The hydraulic cylinder of the support assembly drives the arc-shaped support plate to descend and rise, making room for the side detection bracket and the side detection mechanism to move or support the storage tank. This design can ensure that during the detection process, it will not affect the normal movement of the side detection mechanism, and can ensure the stability of the storage tank, avoiding imbalance or damage to the storage tank due to the detection process, and ensuring the safety and smooth progress of the detection work.

[0050] 3. Conduct corrosion safety inspections on storage tanks using various methods including ultrasonic testing, infrared testing and image analysis.

[0051] 4. The comprehensive assessment module integrates the test results of multiple detection modules with environmental data to conduct a comprehensive assessment of the corrosion safety of the tank and predict potential risks. This comprehensive analysis method can make full use of the advantages of each detection module, and the information obtained from different angles complement each other to improve the accuracy and reliability of the assessment. By predicting potential risks, corresponding maintenance and management strategies can be formulated in advance to prevent accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 This is an overall schematic diagram of a chemical storage tank corrosion safety detection device disclosed in a preferred embodiment of the present application.

[0053] Figure 2 This is a bottom schematic diagram of a chemical storage tank corrosion safety detection device disclosed in a preferred embodiment of the present application.

[0054] Figure 3 This is a schematic diagram of the structure of a detection unit of a chemical tank corrosion safety detection device disclosed in a preferred embodiment of the present application.

[0055] 1. Base; 2. Side detection bracket; 3. Support assembly; 4. Lateral drive mechanism; 5. Side detection mechanism; 6. Lifting drive mechanism; 7. Transverse movement assembly; 8. End face detection assembly; 9. Detection unit; 11. Pillar; 12. Top plate; 21. Sliding seat; 22. Electric push rod A; 23. Ring bracket; 31. Hydraulic cylinder; 32. Arc support plate; 41. Motor A; 42. Screw rod A; 43. Slide rod A; 51. Arc surface slider; 52. Electric push rod B; 53. Motor B; 54. Gear; 61. Motor C; 62. Screw rod B; 63. Slide rod B; 71. Lifting frame; 72. Slide rod C; 73. Bidirectional screw rod; 74. Motor D; 81. Sliding plate; 82. Electric telescopic rod; 91. Positioning plate; 92. Infrared detector; 93. Ultrasonic detection probe; 94. Laser rangefinder; 95. High-definition camera. DETAILED DESCRIPTION

[0056] The present application is further described in detail below in conjunction with the accompanying drawings.

[0057] Reference Figure 1 , Figure 2 and Figure 3 The embodiment of the present application provides a chemical tank corrosion safety detection device, including: a base 1, a side detection bracket 2, a support assembly 3, a lateral drive mechanism 4, a side detection mechanism 5, a lifting drive mechanism 6, a lateral movement assembly 7, an end face detection assembly 8, a detection unit 9 and a monitoring mechanism.

[0058] Support columns 11 are fixedly arranged at the four corners above the base 1 , and a top plate 12 is fixedly arranged above the four support columns 11 .

[0059] A transverse driving mechanism 4 is fixedly provided on the top plate 12 , and a side detection bracket 2 is movably provided on the transverse driving mechanism 4 ; the transverse driving mechanism 4 and the side detection bracket 2 are transmission-connected; and the transverse driving mechanism 4 can move the side detection bracket 2 .

[0060] A side detection mechanism 5 is rotatably provided on the side detection bracket 2, and the side detection mechanism 5 is transmission-connected with the side detection bracket 2. The side detection mechanism 5 can rotate on the side detection bracket 2. A detection unit 9 is fixedly provided on the side detection mechanism 5.

[0061] A plurality of support components 3 are fixedly arranged on the base 1 , and the chemical storage tanks can be supported by the support components 3 .

[0062] The base 1 is provided with a lifting drive mechanism 6, on which a lateral movement component 7 is slidably provided, on which an end face detection component 8 is slidably provided, and on which a detection unit 9 is fixedly provided.

[0063] A monitoring mechanism is fixedly arranged on the base 1, and the monitoring mechanism detects and evaluates the process of corrosion safety detection of chemical storage tanks, and promptly discovers abnormal conditions and potential risks.

[0064] In this technical solution, a chemical storage tank that needs to be inspected for corrosion safety is placed on a support assembly 3, and the side detection mechanism 5 is driven to move by a transverse driving mechanism 4. The circumferential side of the storage tank is inspected by a detection unit 9 on the side detection mechanism 5. The transverse movement assembly 7 is driven up and down by a lifting driving mechanism 6, and the transverse movement assembly 7 drives the end face detection assembly 8 and the detection unit 9 to inspect the two end faces of the storage tank.

[0065] Furthermore, the transverse driving mechanism 4 includes a motor A41, a screw rod A42 and a slide rod A43;

[0066] A motor A41 is fixedly arranged on the top plate 12; a screw rod A42 and a slide rod A43 are rotatably arranged on the top plate 12, and the output end of the motor A41 is coaxially fixedly connected with the screw rod A42.

[0067] The screw rod A42 is threadably connected to the side detection bracket 2 , and the slide rod A43 is slidably connected to the side detection bracket 2 .

[0068] In this technical solution, the starting motor A41 drives the screw rod A42 to rotate, and the screw rod A42 drives the side detection bracket 2 to move and adjust the position.

[0069] Further, the side detection bracket 2 includes a sliding seat 21, an electric push rod A22 and a ring bracket 23;

[0070] An electric push rod A22 is fixedly arranged on the sliding seat 21, and an annular bracket 23 is fixedly arranged on the movable rod of the electric push rod A22.

[0071] The sliding seat 21 is connected with the screw rod A42 by threaded fit; the sliding seat 21 is connected with the slide rod A43 by sliding fit. The annular bracket 23 is connected with the side detection mechanism 5 by transmission.

[0072] In this technical solution, when the motor A41 drives the screw rod A42 to rotate, the screw rod A42 drives the sliding seat 21 to move, thereby driving the electric push rod A22 and the annular bracket 23 to move and adjust the position.

[0073] Further, the support assembly 3 includes a hydraulic cylinder 31 and an arc-shaped support plate 32;

[0074] A plurality of hydraulic cylinders 31 are fixedly arranged on the base 1, and an arc-shaped support plate 32 is fixedly arranged on the movable rod of the hydraulic cylinder 31; a rubber pad is fixedly arranged on the inner side of the arc-shaped support plate 32. A pressure sensor is fixedly arranged on the inner side of the arc-shaped support plate 32. A micro electric push rod can be fixedly arranged on the inner side of the upper end of the arc-shaped support plate 32 as needed, and a rubber pad is arranged at the end of the movable rod of the micro electric push rod to fix the chemical storage tank.

[0075] In this technical solution, the storage tank can be supported by the arc-shaped support plate 32, and the arc-shaped support plate 32 can be moved and adjusted in height by the hydraulic cylinder 31. When one of the support components 3 stops supporting the storage tank, the remaining support components 3 can provide good support for the storage tank, ensuring that the detection process proceeds smoothly.

[0076] Furthermore, the side detection mechanism 5 includes a curved slider 51, an electric push rod B52, a motor B53 and a gear 54;

[0077] A closed slide groove is provided inside the annular bracket 23; a curved slider 51 is slidably arranged in the slide groove of the annular bracket 23; an electric push rod B52 is fixedly arranged on the curved slider 51; a detection unit 9 is fixedly arranged on the movable rod of the electric push rod B52. A groove is provided on the curved slider 51, a motor B53 is fixedly arranged in the groove, and a gear 54 is coaxially fixedly arranged at the output end of the motor B53; a plurality of tooth grooves are provided at the slide groove of the annular bracket 23, and the gear 54 is meshed and transmission-connected with the tooth grooves of the annular bracket 23.

[0078] In this technical solution, the starting motor B53 drives the gear 54 to rotate. Due to the tooth-groove meshing transmission connection between the gear 54 and the annular bracket 23, the gear 54 makes a circular motion and revolves around the annular bracket 23; thereby driving the detection unit 9 on the electric push rod B52 to rotate and detect the side of the tank.

[0079] Furthermore, the lifting drive mechanism 6 includes a motor C61, a screw rod B62 and a slide rod B63;

[0080] The motor C61 is fixedly arranged on the base 1; the screw rod B62 and the slide rod B63 are rotatably arranged between the base 1 and the top plate 12; the output end of the motor C61 is coaxially fixedly connected with the screw rod B62. The screw rod B62 is threadedly connected with the lateral movement component 7, and the slide rod B63 is slidably connected with the lateral movement component 7.

[0081] In this technical solution, the starting motor C61 drives the screw rod B62 to rotate, and the screw rod B62 drives the transverse movement assembly 7 to move up and down.

[0082] Furthermore, the transverse movement assembly 7 includes a lifting frame 71, a slide rod C72, a bidirectional screw rod 73 and a motor D74.

[0083] The lifting frame 71 is threadedly connected to the screw rod B62, and the lifting frame 71 is slidably connected to the slide rod B63; the lifting frame 71 is fixedly provided with a motor D74; the lifting frame 71 is rotatably provided with a slide rod C72 and a bidirectional screw rod 73; the output end of the motor D74 is coaxially fixedly connected to the bidirectional screw rod 73. The bidirectional screw rod 73 is threadedly connected to the end face detection component 8; the slide rod C72 is slidably connected to the end face detection component 8.

[0084] In this technical solution, the starting motor D74 drives the bidirectional screw 73 to rotate, and the bidirectional screw 73 drives the two end face detection components 8 to move synchronously in opposite directions to adjust the positions.

[0085] Furthermore, the end face detection assembly 8 includes a sliding plate 81 and an electric telescopic rod 82 .

[0086] The sliding plate 81 is threadedly connected to the bidirectional screw rod 73; the sliding plate 81 is slidably connected to the sliding rod C72.

[0087] An electric telescopic rod 82 is fixedly arranged on the sliding plate 81, and a detection unit 9 is fixedly arranged on the electric telescopic rod 82. The two end surface detection components 8 are symmetrically arranged.

[0088] In this technical solution, when the motor D74 drives the bidirectional screw 73 to rotate, the bidirectional screw 73 drives the two sliding plates 81 to move synchronously in opposite directions to adjust their positions, and the detection unit 9 on the electric telescopic rod 82 detects the two end faces of the storage tank.

[0089] Furthermore, the detection unit 9 includes a positioning plate 91 , an infrared detector 92 , an ultrasonic detection probe 93 , a laser rangefinder 94 and a high-definition camera 95 .

[0090] A positioning plate 91 is fixedly arranged on the movable rod of the electric telescopic rod 82 ; an infrared detector 92 , an ultrasonic detection probe 93 , a laser rangefinder 94 and a high-definition camera 95 are fixedly arranged on the positioning plate 91 .

[0091] A coupling agent applicator is fixedly disposed on the positioning plate 91 . This is a prior art and is only borrowed by the present invention and will not be described in detail herein.

[0092] The infrared detector 92 is an important detection device that works based on the principle of thermal radiation of objects. It adopts advanced infrared thermal imaging technology, equipped with highly sensitive infrared detectors and professional image processing algorithms. The instrument can quickly and accurately capture the temperature distribution on the surface of chemical storage tanks, and judge whether there is corrosion, defects or other abnormalities on the surface of the tank by analyzing the temperature differences in different parts. For example, when corrosion occurs on the surface of the tank, the thermal conductivity of the corroded area will change, causing its temperature to be different from that of the normal area. In the thermal imaging image generated by the infrared detector 92, obvious temperature abnormal areas will appear, and these abnormalities can be observed intuitively, and then the location and degree of corrosion can be preliminarily judged.

[0093] The ultrasonic detection probe 93 is a key device that uses the characteristics of ultrasonic waves propagating in different media to detect the internal structural conditions of chemical storage tanks. It is made of high-performance piezoelectric ceramic materials and can generate and receive high-frequency ultrasonic signals. During the detection process, the ultrasonic detection probe 93 emits ultrasonic waves to the tank wall. When the ultrasonic waves encounter defects inside the tank (such as cracks, holes, corrosion thinning areas, etc.), reflection, refraction and scattering phenomena will occur. The reflected ultrasonic signal is received by the probe and converted into an electrical signal. After the signal processing and analysis system, the location, size and shape of the defect can be accurately determined. The ultrasonic detection probe 93 has a variety of operating frequencies to choose from. According to the material, thickness and detection requirements of the tank, the operating frequency can be flexibly adjusted to achieve the best detection effect.

[0094] The laser rangefinder 94 in the detection unit 9 is mainly used to accurately measure the distance between the detection device and the surface of the tank.

[0095] Furthermore, monitoring agencies include:

[0096] Data collection module: collects material and size data of chemical storage tanks (including parameters such as the diameter, height, wall thickness, etc. of the tank body); collects data on the storage medium in chemical storage tanks (including the chemical composition, concentration, pH, corrosiveness, etc. of the medium).

[0097] Environmental data acquisition module: real-time collection of environmental data, including temperature and humidity data.

[0098] Route planning module: According to the material size of the chemical storage tank and the detection range of the detection unit 9, the travel routes of the side detection mechanism 5 and the end face detection component 8 are reasonably planned; through the cooperation of the lateral drive mechanism 4, the side detection mechanism 5, the lifting drive mechanism 6, the lateral movement component 7, the end face detection component 8 and the detection unit 9, a comprehensive detection of the storage tank is achieved; the occurrence of blind spots in detection or repeated detection is avoided, and the detection efficiency and accuracy are improved.

[0099] Ultrasonic testing module: Perform ultrasonic testing on storage tanks; analyze and identify ultrasonic data to detect abnormal conditions in a timely manner (including thinning of wall thickness, holes and internal cracks, etc.).

[0100] Infrared detection module: perform infrared detection on storage tanks; analyze and identify infrared data to detect abnormal conditions (corrosion, leakage, etc.) in a timely manner.

[0101] Image acquisition module: including high-definition camera and LED light to collect high-definition images of the storage tank;

[0102] Image analysis module: Analyze and identify the collected images, and promptly identify abnormal conditions on the tank surface (cracks and deformations, etc.).

[0103] Comprehensive assessment module: Integrates the detection results of the infrared detection module, ultrasonic detection module and image analysis module with environmental data (temperature, humidity) to conduct a comprehensive assessment of the corrosion safety of the storage tank and predict potential risks.

[0104] Alarm module: includes an alarm, which will sound an alarm in time when abnormal conditions or potential risks are detected.

[0105] Control center: connected to the data collection module, environmental data acquisition module, ultrasonic detection module, infrared detection module, image acquisition module, route planning module, image analysis module, comprehensive evaluation module and alarm module. Through the coordinated control of each module, the control center ensures the efficient operation of the entire monitoring mechanism. According to the actual detection needs, the working parameters and operation mode of each module can be flexibly adjusted to achieve comprehensive and accurate control of the corrosion safety detection of chemical storage tanks. During the detection process, the control center can monitor the working status of each module in real time, discover and solve possible problems in a timely manner, and ensure the stable operation of the entire detection system.

[0106] Furthermore, the route planning module rationally plans the travel routes of the side detection mechanism 5 and the end face detection component 8 according to the material size of the chemical storage tank and the detection range of the detection unit 9; through the cooperation of the lateral drive mechanism 4, the side detection mechanism 5, the lifting drive mechanism 6, the lateral displacement component 7, the end face detection component 8 and the detection unit 9, a comprehensive detection of the storage tank is achieved; the occurrence of blind spots or repeated detection is avoided, and the detection efficiency and accuracy are improved. Through the cooperation of the lateral drive mechanism 4, the side detection mechanism 5 and the detection unit 9, a comprehensive surrounding detection of the circumferential side of the storage tank is achieved. Through the cooperation of the lifting drive mechanism 6, the lateral displacement component 7, the end face detection component 8 and the detection unit 9, a comprehensive detection of the end faces at both ends of the storage tank is achieved. The following steps are included:

[0107] 1. Information collection: The data collection module transmits the material and size data (such as tank diameter, height, wall thickness, etc.) of the chemical storage tank to the route planning module. The route planning module obtains the detection range parameters of the detection unit 9, including the effective detection distance, angle and other information of the infrared detector 92, ultrasonic detection probe 93, laser rangefinder 94 and high-definition camera 95.

[0108] 2. Plan the surrounding inspection route for the circumferential side of the tank.

[0109] 2.1. Determine the starting position: Based on the shape and size of the storage tank and the detection range of the detection unit 9, the route planning module determines the starting detection position of the side detection mechanism 5. Generally, a fixed point on the circumferential side of the storage tank is selected as the starting point to ensure that the detection can completely cover the circumference.

[0110] 2.2. Route planning: The route planning module calculates the number of steps and spacing that the side detection mechanism 5 needs to move under the drive of the lateral drive mechanism 4 according to the circumference of the storage tank and the lateral detection range of the detection unit 9. The route planning module sends instructions to the lateral drive mechanism 4 to control it to drive the side detection mechanism 5 to move laterally according to the predetermined spacing and direction.

[0111] 2.3. Planning the rotation angle: In order to ensure that the detection unit 9 can fully detect the circumferential side, the route planning module determines the angle and speed of rotation of the side detection mechanism 5 at each lateral position according to the detection angle range of the detection unit 9, ensuring that the entire circumferential side can be detected.

[0112] 3. Plan the comprehensive inspection route for both ends of the tank.

[0113] 3.1. Determine the starting position of the end face: According to the height of the tank and the detection range of the detection unit 9, the route planning module determines the starting detection position of the end face detection component 8 on the end face of the tank. Usually, a corner of the end face is selected as the starting point.

[0114] 3.2. Planning the lifting route: The route planning module calculates the number of steps and spacing that the lifting drive mechanism 6 needs to drive the lateral movement component 7 and the end surface detection component 8 to lift and lower according to the height of the storage tank and the vertical detection range of the detection unit 9.

[0115] 3.3. Planning the lateral movement route: At each lifting position, the route planning module calculates the number of steps and spacing that the lateral movement component 7 needs to drive the end face detection component 8 to move horizontally based on the diameter of the tank end face and the lateral detection range of the detection unit 9.

[0116] 4. Real-time monitoring and correction: During the inspection process, the route planning module monitors the inspection progress and coverage in real time through the data fed back by each inspection device and the distance information provided by the laser rangefinder 94. If a blind spot or an area where repeated inspection may occur is found, the route planning module will promptly adjust the subsequent inspection route and parameters to ensure that the entire tank surface can be accurately and comprehensively inspected.

[0117] In this technical solution, by utilizing the coordinated cooperation of the lateral drive mechanism 4, the side detection mechanism 5, the lifting drive mechanism 6, the transverse movement assembly 7, the end face detection assembly 8 and the detection unit 9, a comprehensive detection of chemical storage tanks can be achieved, effectively avoiding detection blind spots and repeated detections, and improving detection efficiency and accuracy.

[0118] Furthermore, the ultrasonic detection module performs ultrasonic detection on the storage tank; analyzes and identifies the ultrasonic data to promptly detect abnormal conditions (including thinning of the wall thickness, holes and internal cracks, etc.); including the following steps:

[0119] 1. Data preprocessing: Import the collected ultrasonic data into the analysis software and preprocess the data, including noise removal, filtering and other operations to improve the data quality. Normalize the data to make the data at different detection points comparable.

[0120] 2. Feature extraction: According to the principle of ultrasonic testing and the characteristics of defects, relevant feature parameters are extracted from the preprocessed data, such as echo amplitude, echo time, waveform characteristics, etc. A feature parameter database is established to classify and store the feature parameters of different types of defects for subsequent comparison and identification. Waveform analysis is performed according to the following formula. R j (τ)=Σ k Σ l (c j,k c j,l )*(1 / T)f T 0[ψ j,k (t)*ψ j,l (t+τ)dt]. j,k (t) = 2 0.5 *ψ(2 j tk).

[0121] Where X(t) represents the original ultrasonic signal, which is a function of time t. This signal contains information related to tank defects and is collected by ultrasonic testing equipment in actual testing. J is the maximum scale of decomposition. In multi-scale analysis, the signal is decomposed into different scales for observation, and the maximum level of decomposition is determined. It is a positive integer set according to actual needs and signal characteristics. j represents the scale parameter, and its value range is from 1 to J. k and l are discrete translation parameters. In wavelet decomposition, for each scale j, the signal is translated on the time axis by different k and l values ​​to cover the entire signal interval, which are integers. c j,k s is the wavelet coefficient. It indicates that at scale j and position k, the signal X(t) is related to the wavelet function ψ j,k The similarity of (t) reflects the energy distribution of the signal at this scale and position, and is a value calculated by the wavelet decomposition algorithm. ψ(t) is a wavelet function. It is a function with specific properties, usually with compact support (zero outside a finite interval) and oscillation characteristics, and is the basic function for wavelet decomposition. Different wavelet functions have different shapes and characteristics and are suitable for different types of signal analysis. j,k (t) is the wavelet basis function obtained by scaling and translating the basic wavelet function ψ(t). j (τ) is the autocorrelation function at scale j, which is a function of time delay τ. By calculating this function, we can obtain the similarity information of the signal at different time delays at scale j, thereby extracting the waveform features related to the scale. τ is the time delay parameter.

[0122] 3. Build a defect recognition model: According to the detection requirements and data characteristics, select appropriate defect recognition algorithms, such as threshold-based methods, pattern recognition methods, machine learning algorithms, etc. Use machine learning algorithms, such as artificial neural networks, support vector machines, etc., to build a defect recognition model through learning and training a large amount of known defect data.

[0123] 4. Defect identification and classification: The extracted feature parameters are input into the selected defect identification algorithm for defect identification and classification. Based on the identification results, the defect type is determined, such as wall thinning, holes or internal cracks, and the location and size of the defect are determined.

[0124] 5. Report generation: Once an abnormality is found, a detailed abnormality report will be generated immediately. The report content includes information such as detection time, detection location, defect type, location, size, etc.

[0125] Furthermore, the infrared detection module performs infrared detection on the storage tank; analyzes and identifies the infrared data to promptly detect abnormal conditions (corrosion, leakage, etc.); including the following steps:

[0126] 1. Data preprocessing: Import the collected infrared data into professional data analysis software. Preprocess the data, including removing noise, enhancing image contrast, etc., to improve the quality and readability of the data. Correct and register the infrared image to ensure that the images at different detection points can be accurately aligned to facilitate subsequent analysis and comparison.

[0127] 2. Feature extraction: Extract characteristic parameters related to abnormal conditions from the preprocessed infrared data, such as temperature distribution, temperature gradient, hot spot size, etc.

[0128] In the case of corrosion, the infrared radiation characteristics of the corroded part usually change due to the change of the surface state, which is manifested as abnormal temperature. By analyzing the temperature distribution and temperature gradient, the area where corrosion may exist can be determined. The corrosion area analysis is performed according to the following formula:

[0129] γ(x,y)=|T(x,y)-T - | / (σ T )+|▽T(x,y)-▽T - | / (σ ▽T ).

[0130] [▽T(x,y)] 2 =[DT(x,y) / Dx] 2 +[DT(x,y) / Dy] 2 ; In the formula, γ(x,y) is the corrosion characteristic index, which is a value that comprehensively considers the temperature and temperature gradient related information at the point (x,y), and is used to evaluate the possibility of corrosion in the area where the point is located. The larger the value, the higher the possibility of corrosion in the area. T(x,y) represents the temperature value at the position with coordinates (x,y) in the infrared image. This temperature value is the actual measurement value obtained by the infrared detection equipment. T - Represents the average temperature of the entire infrared image area. It is obtained by summing the temperature values ​​of all pixels in the image and dividing it by the total number of pixels (MxN), reflecting the overall temperature level of the area covered by the image. M and N are the number of pixels in the horizontal direction (x-axis) and the vertical direction (y-axis) of the infrared image, respectively, which are used to determine the size of the image and are used as denominators for normalization calculations when calculating parameters such as the average temperature and temperature standard deviation. σ T is the standard deviation of the temperature value, which is used to measure the degree of dispersion of the temperature distribution in the entire image area. The larger the standard deviation, the more dispersed and uneven the temperature distribution; the smaller the standard deviation, the relatively concentrated and uniform the temperature distribution. It is calculated based on the difference between the temperature value of each pixel and the average temperature, reflecting the temperature fluctuation. ▽T(x,y) is the temperature gradient at point (x,y). The temperature gradient reflects the trend and speed of temperature change at this point. ▽T- It is the average value of the temperature gradient of the entire image area. It is obtained by summing the temperature gradient amplitudes of all pixels in the image and dividing it by the total number of pixels (MxN), representing the overall level of the temperature gradient of the entire image area. ▽T is the standard deviation of the temperature gradient, which is used to measure the discreteness of the temperature gradient distribution in the entire image area. D represents the partial derivative.

[0131] In the case of leakage, the leaked material will have a temperature difference with the surrounding environment, forming a hot spot. By detecting the size, shape and temperature change of the hot spot, it is possible to determine whether there is a leak and the severity of the leak. Leakage analysis is performed according to the following formula: δ = S*Ω*ΔT / Δt.

[0132] Ω=P2 / (4πA); S=Σ M-1 x＝0 Σ N-1 y＝0 [B(x,y)*a(x,y)].

[0133] a(x,y)=1+β*|▽T(x,y)| / [▽T - ]; where δ is the leakage assessment index, which comprehensively considers factors such as hot spot size, shape complexity, temperature difference, and temperature change time, and is used to assess whether there is a leak and the severity of the leak. S is the hot spot size. B(x,y) is a binary image obtained by an image segmentation algorithm (such as threshold segmentation), and (x,y) represents the coordinates of the pixel in the image. a(x,y) is the hot spot influence factor, which reflects the degree of influence of the hot spot at the point (x,y) on the surrounding temperature field, and is related to the temperature gradient of the point and the average value of the temperature gradient amplitude of the entire image area. β is the weight coefficient, which is used to adjust the contribution of the temperature gradient to the hot spot influence factor. It is a parameter that is set and adjusted according to the actual detection situation. Ω is the hot spot shape complexity factor, which reflects the degree to which the hot spot shape deviates from a regular shape (such as a circle), and is calculated by the perimeter and area of ​​the hot spot. P is the perimeter of the hot spot, which is used to calculate the hot spot shape complexity factor. A is the area of ​​the hot spot, which is used to calculate the hot spot shape complexity factor. ΔT is the temperature difference between the hot spot and the surrounding environment, which is an important parameter for measuring leakage. Δt is the temperature change time within the detection time interval and is used to calculate the leakage assessment index.

[0134] 3. Build an anomaly recognition model: Select a suitable anomaly recognition algorithm based on the detection requirements and data characteristics. Commonly used algorithms include threshold method, cluster analysis, neural network, etc.

[0135] Threshold method: Set appropriate temperature thresholds and characteristic parameter thresholds. When the detection data exceeds the threshold, it is judged as an abnormal situation. For example, when the temperature of a certain detection point exceeds the normal operating temperature range to a certain extent, it is considered that there may be a problem at this point.

[0136] Cluster analysis: Cluster infrared data and group similar data points into one category. By analyzing the clustering results, clusters that are different from normal ones are found, thus identifying abnormal areas.

[0137] Neural network: A neural network model is established by learning and training a large amount of infrared data with known abnormalities. The data to be detected is input into the model, and the model identifies and classifies abnormalities based on the learned features.

[0138] 4. Abnormality judgment and classification: Input the extracted feature parameters into the selected abnormality recognition algorithm for abnormality judgment and classification. According to the recognition results, the type of abnormality, such as corrosion, leakage, etc., is judged, and the location and severity of the abnormality is determined.

[0139] 5. Abnormal report generation: Once an abnormal situation is found, a detailed abnormal report will be generated immediately. The report content includes information such as detection time, detection location, tank number, abnormal type, abnormal location, severity, related data and images.

[0140] Furthermore, the image analysis module analyzes and identifies the collected images, and promptly identifies abnormal conditions (cracks and deformations, etc.) on the surface of the storage tank; the following steps are included:

[0141] 1. Image preprocessing: Preprocess the collected images, including grayscale, filtering, denoising and image enhancement.

[0142] 2. Feature extraction: Extract features from the preprocessed image, including color, texture, and shape; improve the Canny edge detection algorithm for edge extraction; use the gray-level co-occurrence matrix (GLCM) to extract texture features. Use contour detection algorithms (such as the findContours function in OpenCV) to extract the shape contours of objects in the image, and then calculate the contour's area, perimeter, major axis length, minor axis length, and other geometric features.

[0143] 3. Anomaly recognition: Based on the extracted features, select the support vector machine (SVM) classification algorithm to establish an anomaly recognition model. The extracted features are used as training samples, and the features of normal images and abnormal images are marked as different categories. Then use these training samples to train the SVM model, and separate samples of different categories by finding the optimal classification hyperplane. The image features in the standard database are divided into training sets and test sets. The training set is used to train the recognition model, and the parameters of the model are adjusted so that the model can accurately classify the training set. The trained model is evaluated using the test set, and the model's accuracy, recall rate, F1 value and other indicators are calculated to evaluate the model's performance. The features of the image to be detected after preprocessing and feature extraction are input into the trained recognition model. The model classifies the image according to the learned pattern, and determines whether there are abnormal conditions such as cracks and deformations in the image, as well as the type and severity of the abnormality.

[0144] 4. Result output: If an abnormality is identified, the abnormal part is marked on the original image, such as using boxes or lines of different colors to mark the location and shape of the crack, and using text to describe the type and degree of deformation, etc. A detailed test report is generated, including the test time, test location, tank number, image acquisition information, type, location, severity of the abnormality, confidence level of the recognition result, etc.

[0145] Furthermore, the comprehensive assessment module integrates the detection results of the infrared detection module, the ultrasonic detection module and the image analysis module with the environmental data (temperature, humidity) to conduct a comprehensive assessment of the corrosion safety of the storage tank and predict potential risks.

[0146] The following steps are involved:

[0147] 1. Data collection and organization: Obtain test data from the infrared detection module, including information such as temperature distribution, hot spot size, shape and temperature change, as well as identified possible abnormalities (such as corrosion, leakage, etc.) and their location and severity assessment. Obtain test data from the ultrasonic detection module, covering the analysis results of ultrasonic data, such as the location, size and characteristic parameters of defects such as wall thinning, holes and internal cracks. Obtain test data from the image analysis module, including information such as the location, type and severity of identified abnormalities on the surface of the tank (such as cracks and deformation). Collect ambient temperature and humidity data. Organize the test results and environmental data of each module to ensure the accuracy and consistency of the data. Format the data so that it has a unified format and structure.

[0148] 2. Data fusion: Extract features from the test results and environmental data of each module. For infrared detection data, extract temperature gradients, geometric features of hot spots, etc.; for ultrasonic detection data, extract size features of defects, reflection wave features, etc.; for image analysis data, extract edge features, texture features, etc.; for environmental data, extract features such as the rate of change of temperature and humidity. Based on correlation analysis and domain knowledge, select features that have an important impact on the safety assessment of tank corrosion, remove redundant or irrelevant features, reduce data dimensions, and improve analysis efficiency and accuracy.

[0149] Select the feature layer fusion method for data fusion: fuse the features extracted by each module, and splice the temperature features of infrared detection, the defect features of ultrasonic detection and the surface features of image analysis to form a feature vector that comprehensively reflects the status of the tank.

[0150] 3. Standardization of fused data: Standardize the fused data and unify the numerical ranges of different features to the same scale to avoid excessive impact of some features on the evaluation results due to excessively large or small values. Commonly used standardization methods include minimum-maximum standardization and Z-score standardization.

[0151] 4. Comprehensive evaluation: Establish a comprehensive evaluation index system based on the relevant standards and experience of tank corrosion safety. The evaluation indicators include corrosion degree, defect type and severity, environmental influencing factors, etc. Select the support vector machine regression model, input the fused and standardized data into the constructed evaluation model, and calculate the comprehensive evaluation results of tank corrosion safety. Determine the current corrosion safety status of the tank based on the evaluation results. Perform a comprehensive evaluation according to the following formula:

[0152] S=Σ(w Ij *I j +w Uk *U k +w Pl *P l +w Eq *E q ), where I is the feature vector of the infrared detection module; I is a vector containing m elements, representing a series of features extracted from the infrared detection module. j (j=1,2,...,m) is the jth feature in the vector, and U is the ultrasonic detection module feature vector; it is a vector containing n elements, which comes from the feature set of the ultrasonic detection module. U k (k=1,2,...,n) is the kth feature in the vector. P is the image analysis module feature vector, which is a vector containing p elements and is the feature vector extracted from the image analysis module. l(l=1,2,...,p) is the lth feature in the vector. E is the environmental data feature vector, including temperature and humidity features; w I is a vector with the same dimension as the infrared detection module feature vector m, containing m weight values. Ij (j=1,2,...,m) is the corresponding I j The weight of the feature. U It is a vector with the same dimension as the ultrasonic detection module feature vector U, containing n weight values. Uk (k=1,2,...,n) is the corresponding U k The weight of the feature. Pl It is a vector with the same dimension as the feature vector P of the image analysis module, containing p weight values. Pl It corresponds to P l The weight of the feature. E It is a vector with the same dimension as the environmental data feature vector E, containing two weight values, w E =[w E1 ,w E2 ]. E1 The weight corresponding to the ambient temperature, w E2 The weights corresponding to the ambient humidity. These two weights respectively indicate the importance of temperature and humidity in the comprehensive evaluation.

[0153] 5. Potential risk prediction: Select the artificial neural network prediction model to predict future development trends. The artificial neural network prediction model has strong nonlinear mapping and learning capabilities, can handle complex nonlinear relationships, and predict future potential risks by learning and training a large amount of historical data. Input the current detection data and environmental data into the trained prediction model to predict the corrosion safety status and potential risks of the storage tank in the future. According to the prediction results, analyze the types and extent of potential risks that may occur, such as predicting whether new corrosion areas will appear and whether existing defects will expand.

[0154] 6. Result output: The comprehensive assessment results and potential risk prediction results are sorted out and presented in an intuitive and easy-to-understand manner. For example, the assessment results are presented in the form of charts, such as radar charts, bar charts, etc., to intuitively display the scores of each assessment indicator and the comprehensive assessment level; the prediction results are presented in the form of curves to predict the changing trend of the corrosion safety status of the tank in the future. A detailed comprehensive assessment report is generated, which includes the test time, test location, tank number, results of each test module, environmental data, comprehensive assessment results, potential risk prediction results, and corresponding suggestions and measures.

[0155] The present invention provides a method for detecting corrosion safety of chemical storage tanks, comprising the following steps:

[0156] S1. Place the chemical storage tank on the support assembly 3; the data collection module collects the material and size data of the chemical storage tank; and collects the data of the storage medium in the chemical storage tank.

[0157] S2. The route planning module of the monitoring mechanism reasonably plans the travel routes of the side detection mechanism 5 and the end face detection assembly 8 according to the material size of the chemical storage tank and the detection range of the detection unit 9.

[0158] S3. The lateral detection mechanism 5 is driven to move by the lateral driving mechanism 4, and the circumferential side of the storage tank is detected by the detection unit 9 on the lateral detection mechanism 5; the environmental data acquisition module collects environmental data in real time, including temperature and humidity data.

[0159] S31. When the lateral driving mechanism 4 drives the side detection bracket 2 and the side detection mechanism 5 to move to the position of one of the support components 3, the hydraulic cylinder 31 of this support component 3 drives the arc-shaped support plate 32 to descend, making room for the side detection bracket 2 to move, and the other support components 3 support the storage tank.

[0160] S32. When the lateral driving mechanism 4 drives the side detection bracket 2 and the side detection mechanism 5 to pass the position of the support assembly 3, the hydraulic cylinder 31 of the support assembly 3 drives the arc-shaped support plate 32 to rise to support the storage tank.

[0161] S4. The lifting drive mechanism 6 drives the lateral movement assembly 7 to move up and down, and the lateral movement assembly 7 drives the end surface detection assembly 8 and the detection unit 9 to detect the two end surfaces of the storage tank.

[0162] S5. The ultrasonic detection module performs ultrasonic detection on the storage tank; analyzes and identifies the ultrasonic data to promptly detect abnormal conditions (including thinning of the wall thickness, holes and internal cracks, etc.).

[0163] S6. The infrared detection module performs infrared detection on the storage tank; analyzes and identifies the infrared data to detect abnormal conditions (corrosion, leakage, etc.) in a timely manner.

[0164] S7. The image acquisition module acquires high-definition images of the storage tank; the image analysis module analyzes and identifies the acquired images, and promptly identifies abnormal conditions (cracks and deformations, etc.) on the surface of the storage tank.

[0165] S8. The comprehensive assessment module integrates the detection results of the infrared detection module, ultrasonic detection module and image analysis module with environmental data (temperature, humidity) to conduct a comprehensive assessment of the corrosion safety of the storage tank and predict potential risks.

[0166] S9. When an abnormal situation or potential risk is detected, the alarm module will issue an alarm in time.

[0167] The working principle of the corrosion safety detection device for chemical storage tanks of the present invention is as follows: placing the chemical storage tank on the support assembly 3; the data collection module collects the material and size data of the chemical storage tank; collects the data of the storage medium in the chemical storage tank; the route planning module of the monitoring mechanism reasonably plans the travel route of the side detection mechanism 5 and the end face detection assembly 8 according to the material size of the chemical storage tank and the detection range of the detection unit 9; the side detection mechanism 5 is driven to move by the lateral driving mechanism 4, and the circumferential side of the storage tank is detected by the detection unit 9 on the side detection mechanism 5; the environmental data collection module collects environmental data in real time, including temperature and humidity data; the lateral movement assembly 7 is driven to move up and down by the lifting driving mechanism 6, and the lateral movement assembly 7 drives the end face detection assembly 8 and the detection unit 9 to detect the two end faces of the storage tank. The ultrasonic detection module performs ultrasonic detection on the storage tank; analyzes and identifies the ultrasonic data to detect abnormalities in time; the infrared detection module performs infrared detection on the storage tank; analyzes and identifies the infrared data to detect abnormalities in time; the image acquisition module collects high-definition images of the storage tank; the image analysis module analyzes and identifies the collected images to identify abnormalities on the surface of the storage tank in time; the comprehensive evaluation module integrates the detection results of the infrared detection module, ultrasonic detection module and image analysis module with environmental data (temperature, humidity), conducts a comprehensive evaluation of the corrosion safety of the storage tank, and predicts potential risks. When abnormal conditions or potential risks are detected, the alarm module will issue an alarm in time.

[0168] The present invention rationally plans the travel routes of the side detection mechanism and the end face detection assembly according to the material size of the chemical storage tank and the detection range of the detection unit through the route planning module. This can ensure that the detection mechanism can fully cover all parts of the storage tank, avoid missing important areas, optimize the travel route, reduce unnecessary movement, improve detection efficiency, and save detection time and cost. The lateral drive mechanism drives the side detection mechanism to move, and the circumferential side of the storage tank is detected, so that the relevant information of the side of the storage tank can be fully obtained. The detection process can be guaranteed to proceed smoothly. The hydraulic cylinder of the support assembly drives the arc support plate to descend and rise, and makes room for movement or supports the storage tank for the side detection bracket and the side detection mechanism. This design can ensure that during the detection process, the normal movement of the side detection mechanism is not affected, and the stability of the storage tank can be guaranteed, so as to avoid imbalance or damage of the storage tank due to the detection process, and ensure the safety and smooth progress of the detection work. The comprehensive evaluation module integrates the detection results of multiple detection modules with environmental data, comprehensively evaluates the corrosion safety of the storage tank and predicts potential risks. This comprehensive analysis method can make full use of the advantages of each detection module, and the information obtained from different angles can complement each other to improve the accuracy and reliability of the assessment. At the same time, by predicting potential risks, corresponding maintenance and management strategies can be formulated in advance to prevent accidents and reduce operating costs.

[0169] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A chemical storage tank corrosion safety detection method, characterized in that: The following steps are involved: S1. Place the chemical storage tank on the support assembly; The data collection module collects material and size data of chemical storage tanks; Collect data on the medium stored in chemical tanks; S2. The route planning module of the monitoring mechanism reasonably plans the travel routes of the side detection mechanism and the end face detection component according to the material size of the chemical storage tank and the detection range of the detection unit; S3, the lateral driving mechanism drives the side detection mechanism to move, and the detection unit on the side detection mechanism detects the circumferential side of the storage tank; the environmental data acquisition module collects environmental data in real time; S4, the lifting drive mechanism drives the transverse moving assembly to move up and down, and the transverse moving assembly drives the end surface detection assembly and the detection unit to detect the two end surfaces of the storage tank; S5, the ultrasonic detection module performs ultrasonic detection on the storage tank; analyzes and identifies the ultrasonic data to detect abnormal conditions in a timely manner; S6. The infrared detection module performs infrared detection on the storage tank; analyzes and identifies the infrared data to detect abnormal conditions in a timely manner; S7, the image analysis module analyzes and identifies the collected images, and promptly identifies abnormal conditions on the surface of the storage tank; S8, the comprehensive assessment module integrates the detection results of the infrared detection module, ultrasonic detection module and image analysis module with environmental data to conduct a comprehensive assessment of the corrosion safety of the storage tank and predict potential risks; S9. When an abnormal situation or potential risk is detected, the alarm module will issue an alarm in time.

2. The method for detecting corrosion safety of chemical storage tanks according to claim 1, characterized in that: Step S3 comprises the following steps: S31. When the lateral driving mechanism drives the side detection bracket and the side detection mechanism to move to one of the support assembly positions, the hydraulic cylinder of the support assembly drives the arc-shaped support plate to descend, making room for the side detection bracket to move, and other support assemblies support the storage tank; S32. When the lateral driving mechanism drives the side detection bracket and the side detection mechanism to pass through the support assembly position, the hydraulic cylinder of the support assembly drives the arc-shaped support plate to rise to support the storage tank.

3. The method for detecting corrosion safety of chemical storage tanks according to claim 1, characterized in that: Step S2 includes the following steps: S21, collecting information: the data collection module collects the material size data of the chemical storage tank; obtains the detection range parameters of the detection unit; S22. Planning of the surrounding inspection route for the circumference of the tank: S22.

1. Determine the starting position: Determine the starting detection position of the side detection mechanism according to the shape and size of the storage tank; S22.2, route planning: according to the circumference of the storage tank and the lateral detection range of the detection unit, calculate the number of steps and spacing that the side detection mechanism needs to move under the drive of the lateral drive mechanism; S22.

3. Plan the rotation angle: determine the angle and speed at which the side detection mechanism needs to rotate at each lateral position according to the detection angle range of the detection unit; S23. Comprehensive inspection route planning for both ends of the tank: S23.

1. Determine the starting position of the end face: determine the starting detection position of the end face detection component on the end face of the tank according to the height of the tank and the detection range of the detection unit; S23.

2. Plan the lifting route: According to the height of the storage tank and the vertical detection range of the detection unit, calculate the number of steps and spacing that the lifting drive mechanism needs to drive the lateral movement component and the end surface detection component to rise and fall; S23.

3. Plan the lateral movement route: At each lifting position, calculate the number of lateral movement steps and spacing that the lateral movement component needs to drive the end face detection component according to the end face diameter of the tank and the lateral detection range of the detection unit; S24. Real-time monitoring and correction: Real-time monitoring of detection progress and coverage; timely adjustment of detection routes and parameters to ensure that the entire tank surface can be accurately and comprehensively detected.

4. The chemical storage tank corrosion safety detection method according to claim 1 is characterized in that: Step S5 includes the following steps: S51, data preprocessing: importing the ultrasonic data into the analysis software and preprocessing the data; S52, feature extraction: extract relevant feature parameters from the preprocessed data according to the principle of ultrasonic testing and the characteristics of defects; establish a feature parameter database; S53, build defect recognition model: select a threshold-based defect recognition algorithm, adopt a support vector machine machine learning algorithm, learn and train a large amount of known defect data, and build a defect recognition model; S54, defect identification and classification: input the extracted feature parameters into the selected defect identification algorithm to perform defect identification and classification, and determine the type of defect, and the location and size of the defect according to the identification result; S55. Report generation: Once an abnormal situation is found, a detailed abnormal situation report is generated immediately.

5. The chemical storage tank corrosion safety detection method according to claim 1 is characterized in that: Step S6 includes the following steps: S61, data preprocessing: preprocessing the collected infrared data; S62, feature extraction: extracting feature parameters related to abnormal conditions from the pre-processed infrared data, including temperature distribution, temperature gradient and hot spot size; S63, construct an abnormality recognition model: select an abnormality recognition algorithm of the threshold method; set a suitable temperature threshold and characteristic parameter threshold, and when the detection data exceeds the threshold, it is judged as an abnormal situation; S64, abnormality judgment and classification: input the extracted feature parameters into the abnormality recognition algorithm to perform abnormality judgment and classification; based on the recognition results, judge the type of abnormal situation, and determine the location and severity of the abnormality; S65. Exception report generation: Once an abnormal situation is found, a detailed exception report is generated immediately.

6. The chemical storage tank corrosion safety detection method according to claim 1 is characterized in that: Step S8 includes the following steps: S81, data collection and arrangement: obtain the detection data of the infrared detection module, the ultrasonic detection module and the image analysis module; collect the ambient temperature and humidity data; format the data; S82, data fusion: extract features from the detection results and environmental data of each module; fuse the features extracted from each module, and splice the temperature features of infrared detection, the defect features of ultrasonic detection, and the surface features of image analysis to form a feature vector that fully reflects the state of the storage tank; S83, fusion data standardization: standardize the fused data; S84. Comprehensive evaluation: Establish a comprehensive evaluation index system, select a support vector machine regression model, input the fused and standardized data into the constructed evaluation model, and calculate the comprehensive evaluation results of the corrosion safety of the storage tank; determine the current corrosion safety status of the storage tank based on the evaluation results; S85. Potential risk prediction: Select artificial neural network prediction model to predict future development trends; S86. Result output: Organize the comprehensive assessment results and potential risk prediction results and present them in an intuitive and easy-to-understand manner.

7. The chemical storage tank corrosion safety detection method according to claim 1 is characterized by: The lateral driving mechanism includes a motor A, a screw rod A and a slide rod A; the motor A is fixedly arranged on the top plate; the screw rod A and the slide rod A are rotatably arranged on the top plate, and the output end of the motor A is coaxially fixedly connected with the screw rod A; the screw rod A is threadedly connected with the side detection bracket, and the slide rod A is slidably connected with the side detection bracket; The side detection bracket includes a sliding seat, an electric push rod A and an annular bracket; the sliding seat is fixedly provided with the electric push rod A, and the movable rod of the electric push rod A is fixedly provided with the annular bracket; the sliding seat is threadedly connected with the screw rod A; the sliding seat is slidably connected with the sliding rod A; The side detection mechanism includes a curved slider, an electric push rod B, a motor B and a gear; a closed slide groove is provided on the inner side of the annular bracket; the curved slider is slidably arranged in the slide groove of the annular bracket; the electric push rod B is fixedly arranged on the curved slider; and a detection unit is fixedly arranged on the movable rod of the electric push rod B; The detection unit includes a positioning plate, an infrared detector, an ultrasonic detection probe, a laser rangefinder and a high-definition camera; the positioning plate is fixedly arranged on the movable rod of the electric telescopic rod; the infrared detector, the ultrasonic detection probe, the laser rangefinder and the high-definition camera are fixedly arranged on the positioning plate; A motor B is fixedly arranged on the arc surface slider, and a gear is coaxially fixedly arranged on the output end of the motor B; a plurality of tooth grooves are arranged at the slide groove of the annular bracket, and the gear is meshed and transmission-connected with the tooth grooves of the annular bracket.

8. The chemical storage tank corrosion safety detection method according to claim 1 is characterized by: The lifting drive mechanism includes a motor C, a screw rod B and a slide rod B; the motor C is fixedly arranged on the base; the screw rod B and the slide rod B are rotatably arranged between the base and the top plate; the output end of the motor C is coaxially fixedly connected with the screw rod B; the screw rod B is threadedly connected with the lateral movement component, and the slide rod B is slidably connected with the lateral movement component; The traverse assembly includes a lifting frame, a slide rod C, a bidirectional screw rod and a motor D; the lifting frame is connected to the screw rod B by threaded fit, and the lifting frame is connected to the slide rod B by sliding fit; the motor D is fixedly arranged on the lifting frame; the slide rod C and the bidirectional screw rod are rotatably arranged on the lifting frame; the output end of the motor D is coaxially fixedly connected to the bidirectional screw rod; the bidirectional screw rod is connected to the end face detection assembly by threaded fit; The supporting assembly includes a hydraulic cylinder and an arc-shaped support plate; a plurality of hydraulic cylinders are fixedly arranged on the base, and an arc-shaped support plate is fixedly arranged on the movable rod of the hydraulic cylinder; a rubber pad is fixedly arranged on the inner side of the arc-shaped support plate; The end face detection component comprises a sliding plate and an electric telescopic rod; the sliding plate is threadedly connected with a bidirectional lead screw; the electric telescopic rod is fixedly arranged on the sliding plate, and a detection unit is fixedly arranged on the electric telescopic rod.

9. The chemical storage tank corrosion safety detection method according to claim 1 is characterized by: Monitoring agencies include: Data collection module: collects material and size data of chemical storage tanks; collects data of storage media in chemical storage tanks; Environmental data collection module: real-time collection of environmental data, including temperature and humidity data; Route planning module: rationally plan the travel routes of the side detection mechanism and end face detection components according to the material size of the chemical storage tank and the detection range of the detection unit; Ultrasonic detection module: perform ultrasonic detection on storage tanks; analyze and identify ultrasonic data to detect abnormal conditions in a timely manner; Infrared detection module: perform infrared detection on storage tanks; analyze and identify infrared data to detect abnormal situations in a timely manner; Image acquisition module: including high-definition camera and LED light to collect high-definition images of the storage tank; Image analysis module: analyzes and identifies the collected images and identifies abnormal conditions on the surface of the tank; Comprehensive assessment module: Integrates the detection results of the infrared detection module, ultrasonic detection module and image analysis module with environmental data to conduct a comprehensive assessment of the corrosion safety of the storage tank and predict potential risks; Alarm module: including an alarm, which sounds an alarm when an abnormal situation or potential risk is detected; Control center: connected to the data collection module, environmental data collection module, ultrasonic detection module, infrared detection module, image acquisition module, route planning module, image analysis module, comprehensive evaluation module and alarm module network.

10. A chemical tank corrosion safety detection device, comprising: Base, side detection bracket, support assembly, lateral drive mechanism, side detection mechanism, lifting drive mechanism, lateral movement assembly, end face detection assembly, detection unit and monitoring mechanism; characterized in that: Support pillars are fixedly arranged at the four corners above the base, and a top plate is fixedly arranged above the four support pillars; a lateral driving mechanism is fixedly arranged on the top plate, and a side detection bracket is movably arranged on the lateral driving mechanism; the lateral driving mechanism and the side detection bracket are transmission-connected; A side detection mechanism is rotatably provided on the side detection bracket, and the side detection mechanism is transmission-connected to the side detection bracket; a detection unit is fixedly provided on the side detection mechanism; A plurality of supporting components are fixedly arranged on the base, and the chemical storage tank can be supported by the supporting components; a lifting drive mechanism is arranged on the base, a lateral movement component is slidably arranged on the lifting drive mechanism, an end face detection component is slidably arranged on the lateral movement component, and a detection unit is fixedly arranged on the end face detection component; A monitoring mechanism is fixed on the base, which detects and evaluates the process of corrosion safety detection of chemical storage tanks to detect abnormal conditions and potential risks in time.

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