Automatic oil depot safety inspection method based on digital twinning

Abstract

The invention discloses an oil depot safety automatic inspection method based on digital twinning, and the method comprises the steps: building a digital twinning model of a target oil depot, configuring model information, and exporting twinning scene application; the twinborn model obtains an inspection route, an automatic inspection view angle of the twinborn model enters a first area in the inspection route area queue, and all facility equipment sets in the area are obtained; entering the first facility equipment from an automatic inspection view angle, and obtaining all sensing equipment bound under the equipment; equipment self-inspection instructions are sent to the sensing equipment in sequence, and equipment self-inspection results are displayed on models corresponding to the twin models in a panel mode; for an abnormal index or sensor, marking the model with a remarkable color so as to distinguish the abnormal index or sensor; during operation and maintenance management operation of the oil depot, the problems of high labor input cost and high operation and maintenance cost of the oil depot can be solved, and the situation that numerical values are possibly inaccurate due to the fact that the working environment of precision equipment is changed is avoided.

Description

Technical Field

[0001] The present invention relates to the field of Internet of Things inspection technology, and in particular to an automatic safety inspection method for oil depots based on digital twins. Background Art

[0002] In the current operation and maintenance management of most oil depots, a large amount of manpower is required to maintain key equipment, and personnel inspections are required to be arranged regularly and quantitatively every day. Since oil depots generally occupy a large area and have a large number of inspection equipment, it is necessary to further increase manpower to complete the designated workload. It is also necessary to consider the storage of important national resources and flammable and explosive factors, so morning and evening shifts or eight-hour three-shift shifts will be arranged. Human resources need to be doubled to achieve the goal, which results in a huge proportion of human resources and a large amount of manpower time is spent on maintenance and inspection, making the overall efficiency of oil depot operation and maintenance management low.

[0003] When staff conduct equipment inspections, since most of the key equipment in the oil depot is high-precision and large in size, and considering the low quality of personnel or lack of necessary professional skills, the inspection may be incomplete or wrong, so that the accuracy and efficiency of the inspection are difficult to guarantee. During the inspection, it is impossible to ensure that every detail is checked in place, which is prone to omissions and errors. It is more likely that some important inspection points will be overlooked, resulting in equipment failure or problems that cannot be discovered and handled in a timely manner.

[0004] Oil depots are high-risk environments with disaster risks such as fire, poisoning, and flammable and explosive materials. The safety of inspection personnel is difficult to guarantee. When conducting inspections, being closer to the source of danger will further reduce the safety factor, and the environment may make inspections impossible. Therefore, based on the risks of the oil depot itself and environmental factors, the danger of manual inspections of oil depot equipment will increase.

[0005] In summary, the following problems may occur when oil depots conduct equipment inspections: ① Manual inspections of equipment in designated areas require a lot of manpower, resources and time, which is inefficient and costly; ② In addition, manual inspections are prone to omissions and errors, and cannot guarantee that every detail is checked in place. Due to limited human resources, inspectors may overlook some important inspection points, resulting in equipment failures or problems that cannot be discovered and handled in a timely manner; ③ In dangerous environments, such as high pressure, high temperature, flammable and explosive environments, the safety of inspectors is difficult to guarantee and is greatly affected by the weather. Especially in severe weather conditions, manual inspections appear to be extremely weak.

[0006] In the current operation and maintenance management of oil depots, environmental safety is often the top priority. Any carelessness will cause irreparable disasters and consequences. In order to prevent such dangerous situations, safety sensor devices are usually installed on key equipment and flammable and explosive equipment. By collecting sensor data from this device, it is detected whether the operating environment is safe. Equipment inspection uses a human handheld terminal to check the target sensor devices one by one and record the inspection results. This method will have several key problems described above. Summary of the invention

[0007] The technical problem to be solved by the present invention is to solve the problems existing in the above-mentioned inspections, reduce human resources and inspection time, solve the problems that equipment failures cannot be identified in time, and the high risk, etc. In order to solve the above-mentioned problems, a safe automatic inspection method for oil depots based on digital twins is provided.

[0008] The object of the present invention is achieved in the following manner: A digital twin-based oil depot safety automatic inspection method, the method comprising: S1: Establish a digital twin model of the target oil depot, configure model information and export twin scenario applications; S2: Integrate the exported twin scene into the platform to display the panoramic page, obtain model information and bind it with the connected sensor devices in a one-to-many manner, realize the multi-sensor data information query of the device model, and complete the sensor device information statistics of the digital twin scene; S3: The twin model obtains the inspection route, which is composed of two levels of lists: area and facility and equipment collection in the area. The order of the inspection areas can be set on the platform. S4: The automatic inspection perspective of the twin model enters the first area in the inspection route area queue and obtains the set of all facilities and equipment in the area; S5: The automatic inspection perspective enters the first facility equipment and obtains all sensor devices bound to the equipment; S6: Send device self-check instructions to the sensor devices in turn, and display the results of the device self-check in the form of a panel on the model corresponding to the twin model; for abnormal indicators or sensors, mark them with obvious colors on the model to distinguish them; S7: Pop the current facility equipment out of the queue and continue S5 until all the facilities and equipment in the area are inspected; S8: Pop the current area out of the area queue and continue with S4 until all areas are inspected; S9: The inspection is completed and the inspection results of each area in the current round are obtained.

[0009] The S1 specifically includes: making the overall scene of the oil depot and key equipment models according to the design drawings of the target oil depot and key equipment and other relevant materials, using the scene data separation mode of the digital twin tool, relying on local integration, building the scene through models, components, and environmental conditions, laying out the scene based on the tool's drag-and-drop mode, configuring the model information and exporting the twin scene application.

[0010] The self-check of the sensor device includes two parts. The first part is to judge the online status of the sensor device. If the sensor device is not online, the offline result is directly returned. The second part is to collect data for each indicator of the sensor device if the sensor device is online. The data collection reads and escapes the sensor value through the Modbus protocol. The data collected from each indicator is tested through its corresponding threshold range. If the threshold setting is violated, an alarm is issued and the information details are returned.

[0011] Beneficial effects of the present invention: The present invention uses an automatic inspection method based on array twins during the operation and maintenance management of the oil depot, which can solve the problem of high manpower input cost and high operation and maintenance cost of the oil depot, and avoid the situation where the numerical value may be inaccurate due to the change of the working environment of the precision equipment. It further ensures the life safety of the personnel and ensures that the oil depot can be operated and maintained safely and stably. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a schematic diagram of the inspection process of the present invention. DETAILED DESCRIPTION

[0013] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0014] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same technical meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0015] like Figure 1 As shown, a method for automatic safety inspection of oil depots based on digital twins, the method comprising: S1: Establish a digital twin model of the target oil depot, configure model information and export twin scenario applications; S2: Integrate the exported twin scene into the platform to display the panoramic page, obtain model information and bind it with the connected sensor devices in a one-to-many manner, realize the multi-sensor data information query of the device model, and complete the sensor device information statistics of the digital twin scene; S3: The twin model obtains the inspection route, which is composed of two levels of lists: area and facility and equipment collection in the area. The order of the inspection areas can be set on the platform. S4: The automatic inspection perspective of the twin model enters the first area in the inspection route area queue and obtains the set of all facilities and equipment in the area; S5: The automatic inspection perspective enters the first facility equipment and obtains all sensor devices bound to the equipment; S6: Send device self-check instructions to the sensor devices in turn, and display the results of the device self-check in the form of a panel on the model corresponding to the twin model; for abnormal indicators or sensors, mark them with obvious colors on the model to distinguish them; S7: Pop the current facility equipment out of the queue and continue S5 until all the facilities and equipment in the area are inspected; S8: Pop the current area out of the area queue and continue with S4 until all areas are inspected; S9: The inspection is completed and the inspection results of each area in the current round are obtained.

[0016] The S1 specifically includes: making the overall scene of the oil depot and key equipment models according to the design drawings of the target oil depot and key equipment and other relevant materials, using the scene data separation mode of the digital twin tool, relying on local integration, building the scene through models, components, environment and other conditions, laying out the scene based on the tool's drag-and-drop mode, configuring the model information and exporting the twin scene application.

[0017] The self-check of the sensor device includes two parts. The first part is to judge the online status of the sensor device. If the sensor device is not online, the offline result is directly returned. The second part is to collect data for each indicator of the sensor device if the sensor device is online. The data collection reads and escapes the sensor value through the Modbus protocol. The data collected from each indicator is tested through its corresponding threshold range. If the threshold setting is violated, an alarm is issued and the information details are returned.

[0018] The digital twin in the present invention is a kind of technology that uses physical models, sensors, operation history and other data to complete mapping in virtual space by integrating multi-disciplinary, multi-physical quantity, multi-scale and multi-probability simulation processes, thereby reflecting the full life cycle of the corresponding physical equipment. Digital twin technology obtains data of physical entities through sensors and Internet of Things technology, and integrates it into the model to form a virtual environment, which helps to grasp the state and operation of the physical system, and realizes comprehensive perception, monitoring and intelligent control of physical entities through mapping and simulation in virtual space.

[0019] Sensor data collection is achieved through equipment information configuration, operation and maintenance relationship binding, and communication protocol access. The operating status and data information of all sensor devices are collected in real time and stored in the database. Multi-source data fusion analysis is performed based on real-time data, and auxiliary decision analysis is performed based on historical data to achieve fault alarms and risk warnings for inspection equipment in the safety management of oil depot operation and maintenance.

[0020] By integrating inspection equipment in the operation and maintenance management of the oil depot, inspection routes for all equipment can be customized and intelligently arranged with high flexibility. They can be arranged by plane dragging and applied to the digital twin panorama, and the inspection routes can be automatically updated dynamically.

[0021] The present invention comprehensively considers the typical shortcomings in the operation and maintenance management of the above-mentioned oil depots, and uses an automatic inspection method based on array twins to solve the problems of high manpower investment costs and high operation and maintenance costs of oil depots, solves the problem that precision inspection equipment may cause inaccuracies, and solves the danger of personnel working in high-risk environments. It plays a role in reducing costs and increasing efficiency for the oil depot as a whole, improves the probability of fault handling during equipment operation, further ensures the safety of personnel lives, and ensures that the oil depot can be operated and maintained safely and stably.

[0022] Based on digital twin technology, automatic inspection can be visualized and dynamic, and the progress and results of inspection can be presented to users more intuitively.

[0023] The above is only a preferred embodiment of the present invention. It should be pointed out that for those skilled in the art, several changes and improvements can be made without departing from the overall concept of the present invention, which should also be regarded as the scope of protection of the present invention.

Claims

1. A digital twin-based oil depot safety automatic inspection method, characterized by: The method comprises: S1: Establish a digital twin model of the target oil depot, configure model information and export twin scenario applications; S2: Integrate the exported twin scene into the platform to display the panoramic page, obtain model information and bind it with the connected sensor devices in a one-to-many manner, realize the multi-sensor data information query of the device model, and complete the sensor device information statistics of the digital twin scene; S3: The twin model obtains the inspection route, which is composed of two levels of lists: area and facility equipment collection in the area. The order of the inspection areas can be set on the platform. S4: The automatic inspection perspective of the twin model enters the first area in the inspection route area queue and obtains the set of all facilities and equipment in the area; S5: The automatic inspection perspective enters the first facility equipment and obtains all sensor devices bound to the equipment; S6: Send device self-check instructions to the sensor devices in turn, and display the results of the device self-check in the form of a panel on the model corresponding to the twin model; for abnormal indicators or sensors, mark them with obvious colors on the model to distinguish them; S7: Pop the current facility equipment out of the queue and continue S5 until all the facilities and equipment in the area are inspected; S8: Pop the current area out of the area queue and continue with S4 until all areas are inspected; S9: The inspection is completed and the inspection results of each area in the current round are obtained.

2. The digital twin-based oil depot safety automatic inspection method according to claim 1 is characterized by: The S1 specifically includes: making the overall scene of the oil depot and key equipment models according to the design drawings of the target oil depot and key equipment and other relevant materials, using the scene data separation mode of the digital twin tool, relying on local integration, building the scene through models, components, and environmental conditions, laying out the scene based on the tool's drag-and-drop mode, configuring the model information and exporting the twin scene application.

3. The oil depot safety automatic inspection method based on digital twin according to claim 1 is characterized in that: The self-check of the sensor device includes two parts. The first part is to judge the online status of the sensor device. If the sensor device is not online, the offline result is directly returned. The second part is to collect data for each indicator of the sensor device if the sensor device is online. The data collection reads and escapes the sensor value through the Modbus protocol. The data collected from each indicator is tested through its corresponding threshold range. If the threshold setting is violated, an alarm is issued and the information details are returned.

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