Leak-proof system for oil storage tank of product oil skid-mounted station

Abstract

The invention provides a product oil skid-mounted station oil storage tank leakage prevention system, which relates to the technical field of oil storage tank leakage prevention and comprises a distributed negative pressure wave sensing network, a central signal processing unit and a human-computer interaction interface. The sensing network is composed of a plurality of sensors arranged on the outer wall of the storage tank and key nodes of a pipeline, the central processing unit collects background signals to establish a steady-state pressure base line, and abnormal conditions conforming to negative pressure wave characteristics are recognized by dynamically comparing real-time signals; calculating the spatial position of the leakage point by adopting a time difference of arrival algorithm based on the time difference of the signals arriving at different sensors; and multi-stage alarm is carried out according to the ratio of the signal amplitude to the baseline noise. Millisecond-level response and accurate positioning of tiny leakage are achieved, an emergency cut-off system can be linked, and the problems of hysteresis and positioning fuzziness of traditional liquid level monitoring are effectively solved.

Description

Technical Field

[0001] This invention relates to the field of oil storage tank leak prevention technology, and in particular to an oil skid-mounted station oil storage tank leak prevention system. Background Technology

[0002] In the field of refined oil storage and transportation, skid-mounted refueling units have become an important component of modern energy infrastructure due to their compact structure, flexible deployment, and short construction period. As the core unit of a skid-mounted station, the leak-proof performance of the storage tank directly affects the safety of personnel, property, and the stability of the ecological environment. In the event of a leak, not only could it trigger catastrophic consequences such as fires or explosions, but it could also cause oil to seep into the soil and groundwater systems, resulting in irreparable environmental pollution.

[0003] Currently, the industry generally adopts a monitoring mechanism based on liquid level changes as a means of preventing leaks. This mechanism mainly includes two levels: First, liquid level monitoring of the storage tank itself, which involves installing a liquid level sensor inside the tank to continuously track abnormal drops in liquid level in order to determine if a leak is occurring; Second, liquid level monitoring of the anti-leakage tank, which involves placing the storage tank in a sealed tank in accordance with safety regulations and installing a fixed-point liquid level alarm at the bottom of the tank, which triggers an alarm when leaked oil accumulates to a preset height.

[0004] However, in terms of monitoring timeliness, this type of monitoring solution requires the level sensor to wait for the volume of leaked oil or the liquid level to accumulate to a threshold before it can respond. This causes the system to be completely ineffective in detecting initial minor leaks, slow-spreading leaks, or leaks hidden at the bottom of the tank wall. This lag allows leaks to continue to develop undetected, significantly compressing the risk response window and making it extremely easy for small leaks to escalate into major safety accidents. Regarding leak location capabilities, when the leak prevention tank alarm is triggered, the system can only confirm the presence of a leak within the tank, but cannot identify the specific leaking tank. Even if the target tank is located, operators still need to manually inspect dozens of potential risk points, such as tank welds, valve interfaces, flange connections, and pipeline nodes. This process is not only time-consuming but also significantly increases the risk of operator exposure in emergency situations, while also expanding the scope of pollution spread, posing a significant challenge to accident control. Summary of the Invention

[0005] The purpose of this invention is to provide a leak-proof system for oil storage tanks in skid-mounted refined oil stations, thereby solving the above-mentioned problems.

[0006] To achieve the above-mentioned objectives, the technical solution adopted by this invention is as follows: A distributed negative pressure wave sensing network consists of multiple high-precision negative pressure wave sensors. The sensors are physically fixed on the outer wall surface of the storage tank and on key nodes of the pipelines connected to it. Key nodes include the tank head, cylinder welds, inlet and outlet valves and flange connections, and the layout density is determined according to the leakage risk level; A human-machine interface is used to display the steady-state pressure baseline, real-time sensor signal waveforms, alarm information, and spatial location of the leak point; A central signal processing unit is connected in communication with a distributed negative pressure wave sensor network; The central signal processing unit is configured to perform the following operations: Collect background signals from each sensor under leak-free conditions to establish a system steady-state pressure baseline; The real-time sensor signal is dynamically compared with the steady-state pressure baseline; When an abnormal signal matching the characteristics of a negative pressure wave is identified, the precise time difference between the arrival of the abnormal signal at different sensors in the network is recorded. Based on the time difference and the preset spatial coordinates of each sensor, the spatial location of the leak point is calculated; The output includes alarm information containing the spatial location of the leak point. Furthermore, this application proposes that the leakage risk level of critical nodes be calculated using the following formula:

[0007] in, For material factors, The structural stress coefficient, This refers to the operating pressure coefficient. It is classified as a risk level.

[0008] Furthermore, this application also proposes that the negative pressure wave sensor be fixed to the outer wall of the storage tank and the pipeline by means of a magnetic base or threaded fastener in physical contact. Furthermore, this application also proposes a communication connection between the central signal processing unit and the negative pressure wave sensor.

[0009] Furthermore, this application also proposes that the central signal processing unit, when calculating the spatial location of the leak point, adopts a positioning algorithm based on the time difference of arrival, and calculates it using the following formula:

[0010] in, and For any two sensors, The time difference of receiving the signal. The distance difference to the leak point This represents the propagation speed of the negative pressure wave within the tank material. Furthermore, this application also proposes that the human-computer interaction interface be connected to the central signal processing unit. Furthermore, this application proposes that the central signal processing unit performs frequency statistics on leakage events, generates a risk escalation report for the area, and synchronizes the data using the following formula:

[0011] Among them, For the preset threshold, For the same region within the time window, This represents the number of leak alarms.

[0012] Furthermore, this application also proposes that the central signal processing unit is linked with the emergency shut-off system of the skid-mounted station. After confirming a leakage event, the central signal processing unit sends a signal to the emergency shut-off system to automatically close the corresponding inlet and outlet oil valves. 8. Furthermore, this application also proposes that the central signal processing unit calculates the system steady-state pressure baseline using the following formula:

[0013] in, The average value of the background signal. Standard deviation, Configurable confidence coefficient. Furthermore, this application also proposes that the system is equipped with multiple alarm thresholds, and the central signal processing unit adjusts the alarm thresholds based on the amplitude of the negative pressure wave signal. Compared with baseline noise amplitude The ratio is used to determine the result, and when it satisfies...

[0014] Timely triggering of warnings; When satisfied

[0015] When an emergency alarm is triggered, among which .

[0016] The beneficial effects of this invention are as follows: by directly capturing the stress wave signal generated by the pressure transient at the moment of leakage through a distributed negative pressure wave sensing network, without waiting for the oil to accumulate to a specific level, it can make a millisecond-level response to initial minor leaks, slow leaks and hidden leaks at the bottom of the tank, fundamentally solving the safety hazards caused by the inherent delay of the monitoring mechanism in the existing technology, and winning valuable time for emergency response. By recording the precise time difference of the negative pressure wave signal arriving at different sensors in the network, and calculating the spatial coordinates of the leak point based on a preset positioning algorithm, this mechanism can directly locate the leak source to specific microscopic areas such as tank welds, flanges, or valve interfaces. This changes the outdated situation where traditional methods can only confirm the presence of a leak but cannot pinpoint its location, requiring operators to conduct large-scale manual inspections at risk. It significantly shortens inspection time and reduces personnel exposure risk and the probability of secondary accidents. Attached Figure Description

[0017] Figure 1 This is a diagram illustrating the leak-proof system architecture of an oil storage tank at a skid-mounted refined oil station according to the present invention. Figure 2 This invention provides a flowchart of a leakage detection process for an oil storage tank leak prevention system at a skid-mounted refined oil station. Figure 3 This is a timing diagram for leak location of a skid-mounted oil storage tank leak prevention system of the present invention. Detailed Implementation

[0018] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0019] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance. This application proposes a leak-proof system for oil storage tanks in a skid-mounted refined oil station, comprising: A distributed negative pressure wave sensing network consists of multiple high-precision negative pressure wave sensors. The sensors are physically fixed on the outer wall surface of the storage tank and on key nodes of the pipelines connected to it. Key nodes include the tank head, cylinder welds, inlet and outlet valves and flange connections, and the layout density is determined according to the leakage risk level; A human-machine interface is used to display the steady-state pressure baseline, real-time sensor signal waveforms, alarm information, and spatial location of the leak point; A central signal processing unit is connected in communication with a distributed negative pressure wave sensor network; The central signal processing unit is configured to perform the following operations: Collect background signals from each sensor under leak-free conditions to establish a system steady-state pressure baseline; The real-time sensor signal is dynamically compared with the steady-state pressure baseline; When an abnormal signal matching the characteristics of a negative pressure wave is identified, the precise time difference between the arrival of the abnormal signal at different sensors in the network is recorded. Based on the time difference and the preset spatial coordinates of each sensor, the spatial location of the leak point is calculated; The output includes alarm information containing the spatial location of the leak point.

[0020] This embodiment relates to a leak prevention system for oil storage tanks in a skid-mounted refined oil station. The distributed negative pressure wave sensor network refers to a monitoring system composed of multiple high-precision negative pressure wave sensors. These sensors are physically fixed to the outer wall surface of the storage tank and key nodes of the connected pipelines. Key nodes include the tank's end caps, cylinder welds, inlet and outlet valves, and flange connections. The deployment density can be determined based on the leakage risk level. Specifically, this can be achieved through quantitative analysis using on-site safety assessment reports or historical leakage event databases. The main purpose is to achieve targeted monitoring coverage of high-risk areas. Furthermore, the human-machine interface is configured to display the steady-state pressure baseline, real-time sensor signal waveforms, alarm information, and the spatial location of the leak point. The central signal processing unit is communicatively connected to the distributed negative pressure wave sensor network and is configured to collect background signals from each sensor under leak-free conditions to establish a steady-state pressure baseline for the system. This baseline can be achieved through statistical processing of the background signals, such as calculating the long-term average value and dynamic fluctuation range. This is primarily to provide a reference benchmark for real-time signal comparison. After dynamically comparing the real-time sensor signals with the steady-state pressure baseline, when an abnormal signal matching the characteristics of a negative pressure wave is identified, the precise time difference between the arrival of this abnormal signal at different sensors in the network is recorded. Based on the time difference and the preset spatial coordinates of each sensor, the spatial location of the leak point is calculated. As a preferred implementation, a polygonal localization algorithm can be used to achieve this through geometric cross-calculation, primarily to achieve precise spatial localization of the leak source. Alarm information including the spatial location of the leak point is output. Thus, this application directly captures the weak vibration signal generated in the early stage of the leak through a distributed negative pressure wave sensor network, avoiding the response delay caused by the monitoring mechanism that relies on the cumulative change of oil level in the prior art. It also uses the time difference positioning principle of multi-sensor network to output the coordinates of the leak point, eliminating the operation process of manually checking multiple potential risk points in the traditional method.

[0021] The distributed negative pressure wave sensing network consists of multiple high-precision negative pressure wave sensors. These sensors are physically fixed to the outer surface of the storage tank and key nodes of the connected pipelines. Key nodes include the tank head, cylinder welds, inlet and outlet valves, and flange connections. The deployment density is determined based on the leakage risk level to ensure denser monitoring coverage in high-risk areas. A central signal processing unit communicates with this sensing network and is configured to collect background signals from each sensor under leak-free conditions. Based on these background signals, a steady-state pressure baseline is established, which reflects normal process fluctuations through a dynamic reference range. Furthermore, real-time sensor signals are dynamically compared with the steady-state pressure baseline. When an abnormal signal matching the characteristics of a negative pressure wave is detected, the precise time difference between the arrival of this abnormal signal at different sensors in the network is recorded. Based on this time difference and the preset spatial coordinates of each sensor, the spatial location of the leak point is calculated. The steady-state pressure baseline, real-time sensor signal waveforms, alarm information, and the spatial location of the leak point are displayed through a human-machine interface, providing operators with intuitive decision-making support. Specifically, the propagation characteristics of negative pressure waves in the tank material are utilized in the positioning process. The multi-sensor network directly outputs the precise coordinates of the leak point through the triangulation principle, avoiding the lag monitoring mechanism that relies on the accumulated oil level.

[0022] Thus, the system enables early identification of leaks, avoiding the monitoring lag caused by waiting for oil to accumulate to a certain level threshold, as is common in existing technologies. Simultaneously, the precise leak location mechanism eliminates the cumbersome process of manually checking multiple risk points, significantly improving emergency response efficiency. Specifically, by establishing a steady-state pressure baseline to distinguish between normal fluctuations and actual leak signals, the system can trigger an early warning at the leak's initial stage. Furthermore, the spatial location calculation based on time difference directly provides the leak source coordinates, effectively solving the technical bottlenecks of leak monitoring lag and location ambiguity.

[0023] In some of the embodiments described above in this application, a risk level for leakage at key nodes is proposed to guide the density of sensor deployment. However, in its implementation, the assessment of risk level lacks objective quantitative standards and relies on subjective experience judgment, which leads to the sensor deployment density failing to accurately match the actual risk distribution. High-risk areas, such as welds or flange connections, may have insufficient monitoring coverage, while low-risk areas may be over-deployed, resulting in a waste of resources. At the same time, it exacerbates the ambiguity of leak point location, making it impossible to capture initial leakage signals in a timely manner, thus affecting early warning and accurate location capabilities.

[0024] In response, this application further proposes that the leakage risk level of critical nodes be calculated using the following formula:

[0025] in, For material factors, The structural stress coefficient, This refers to the operating pressure coefficient. It is classified as a risk level.

[0026] In practical applications, material factor This refers to parameters reflecting the physicochemical properties of storage tank materials. These can be achieved using corrosion resistance indicators or fatigue strength data, with the aim of objectively assessing the contribution of material aging or damage to leakage risk; structural stress coefficient. This refers to a parameter characterizing the weak points in the tank structure. It can be achieved using the stress concentration factor at welds or flange connections, with the aim of accurately identifying high-stress areas; operating pressure coefficient. It refers to the parameter that quantifies the impact of the system's working pressure. It can be achieved by using the ratio of real-time operating pressure to rated pressure, with the aim of making the risk level match the actual working conditions.

[0027] Specifically, the solution in this application generates a unified and quantifiable risk index by multiplying the material factor, structural stress coefficient, and operating pressure coefficient. This index directly drives the adjustment of the deployment strategy of the distributed negative pressure wave sensor network. The central signal processing unit dynamically allocates the sensor deployment density based on the risk level calculation results, so that high-risk areas can obtain denser monitoring coverage, thereby efficiently capturing negative pressure wave signals and narrowing the location range when a leak occurs, while avoiding resource redundancy in low-risk areas.

[0028] As a specific implementation method, the solution of this application is implemented as follows: In a certain refined oil skid-mounted station oil storage tank system, for the weld area of ​​the cylinder, due to the structural stress coefficient... High risk level The calculated value increases significantly, therefore multiple negative pressure wave sensors are deployed at this node; while for low-risk areas such as straight pipe sections, the risk level... If the calculated value is low, the number of sensors will be reduced accordingly to optimize the allocation of monitoring resources.

[0029] The above technical solutions enable an objective quantitative assessment of leakage risk levels, allowing the sensor deployment density to accurately match the actual risk distribution. This avoids the problems of insufficient monitoring coverage in high-risk areas and excessive deployment in low-risk areas, thereby improving early warning capabilities and location accuracy for leaks.

[0030] Specifically, in some of the embodiments described above in this application, a physical contact fixing method for negative pressure wave sensors is proposed to achieve early detection and accurate location of oil tank leaks. However, in this process, insufficient stability of sensor installation may lead to signal acquisition distortion. Specifically, in the dynamic operating environment of skid-mounted stations, if the fixing method is not clear, the sensor is prone to displacement or loosening, causing negative pressure wave signal attenuation and increased time difference measurement error, which in turn affects the accuracy of the spatial location calculation of the leak point, and may even cause false alarms or missed alarms, thus repeating the defects of lag and fuzzy positioning in the prior art of leak monitoring.

[0031] In this regard, this application further proposes that the negative pressure wave sensor be fixed to the outer wall of the storage tank and pipeline by means of a magnetic base or threaded fastener in physical contact.

[0032] Among them, the magnetic base refers to the fixing device that enables the rapid installation of the sensor by using the principle of magnetic adsorption. It can be implemented using permanent magnet materials or electromagnetic structures, and its purpose is to adapt to non-destructive installation on the surface of metal tanks. The threaded fastener refers to the component that provides a stable fixation through mechanical thread connection. It can be implemented using bolts, screws or stud structures, and its purpose is to ensure long-term stability in non-magnetic materials or high-vibration areas. The physical contact method refers to the installation method in which the sensor is in direct contact with the surface of the tank without gaps. It can be implemented using planar fitting or curved surface adaptation design, and its purpose is to eliminate the interference of air layer on the propagation of pressure waves.

[0033] Specifically, the solution of this application uses a magnetic base or threaded fasteners to physically fix the negative pressure wave sensor to the outer wall of the storage tank and key parts of the pipeline, ensuring that the sensor remains stable under equipment vibration or temperature fluctuations. When the storage tank leaks, the generated negative pressure wave propagates to the sensor through the tank material. Due to the reliable fixing method, the sensor can accurately capture pressure fluctuations and record the arrival time, providing accurate time difference data to the central signal processing unit, thereby achieving precise location of the leak point. At the same time, the physical contact method eliminates the interference of the air layer on the propagation of the pressure wave, enabling the sensor to truly respond to the dynamic changes of the negative pressure wave in the tank material, supporting the system's sensitive detection of minor leak events.

[0034] As a preferred embodiment, the solution of this application is implemented as follows: In the metal cylinder area of ​​the outer wall of the storage tank, the negative pressure sensor is fixed with a magnetic base made of neodymium iron boron permanent magnet to ensure that the sensor is in close contact with the surface of the tank; for non-magnetic material areas such as flange connections, stainless steel screws are used to fasten the sensor to the pipeline surface with threaded fasteners to maintain the positional accuracy of the sensor during long-term operation.

[0035] Through the above-mentioned solution, this application effectively prevents the sensor from shifting or loosening in the dynamic operating environment of the skid-mounted station, reduces the attenuation of the negative pressure wave signal and the time difference measurement error, improves the accuracy of the spatial location calculation of the leak point, and avoids false alarms or missed alarms caused by signal distortion, thereby ensuring the reliable identification capability of the leak prevention system for early minor leak events.

[0036] Specifically, in some of the embodiments described above in this application, a central signal processing unit is proposed to communicate with a distributed negative pressure wave sensing network to collect sensor signals. However, in the process of its implementation, the insufficiency of the stability and real-time performance of the communication connection may lead to signal transmission interruption or delay, making it impossible for the system to obtain negative pressure wave abnormal signals in a timely manner, thereby affecting the accurate location of the leak point and the early warning capability, and failing to effectively overcome the detection lag caused by signal transmission problems in the prior art.

[0037] In this regard, this application further proposes a communication connection between the central signal processing unit and the negative pressure wave sensor.

[0038] In practical applications, the communication connection refers to the data transmission channel established between the central signal processing unit and the negative pressure wave sensor. It can be implemented using wired or wireless communication methods. Its purpose is to ensure that the real-time pressure signal collected by the sensor can be transmitted to the processing unit in a timely and complete manner, avoiding signal loss due to transmission interruption or delay, thereby providing a reliable basis for subsequent dynamic comparison and time difference recording.

[0039] Specifically, the solution in this application achieves real-time transmission and processing of sensor signals through a direct communication connection between the central signal processing unit and the negative pressure wave sensor. When the negative pressure wave sensor detects a pressure signal on the outer wall of the storage tank or a key node in the pipeline, the signal is immediately transmitted to the central signal processing unit via this communication connection. The processing unit dynamically compares the real-time signal based on a steady-state pressure baseline. Once an abnormal signal matching the characteristics of a negative pressure wave is identified, the time difference between the arrival of the signal at different sensors in the network is accurately recorded. Since the calculation of the spatial location of the leak point is highly dependent on the accuracy of the time difference, this direct communication connection eliminates interference from intermediate links, effectively preventing signal jitter or loss, thereby ensuring the stability of the positioning algorithm and supporting the timely output of alarm information containing the spatial location of the leak point through the human-machine interface.

[0040] As a preferred embodiment, the solution of this application is implemented as follows: the central signal processing unit adopts a microcontroller based on the ARM Cortex-M7 core, and the negative pressure wave sensor establishes a communication connection with the processing unit through an industrial-grade CAN bus to ensure the reliability and real-time performance of signal transmission in the complex electromagnetic environment of the finished oil skid-mounted station.

[0041] Through the above solution, the system can continuously and stably acquire real-time sensor signals, avoiding signal transmission interruptions or delays caused by communication problems, thereby significantly improving the accuracy of leak point location and the timeliness of early warning response, and effectively overcoming the detection lag caused by signal transmission problems in the existing technology.

[0042] In some of the embodiments described above in this application, a central signal processing unit is proposed to calculate the spatial location of the leak point based on the time difference. However, in its implementation, there is a lack of accurate positioning algorithms, resulting in insufficient positioning accuracy and an inability to quickly and accurately determine the specific location of the leak point. This prolongs the leak investigation time and increases the risk of secondary accidents and the scope of environmental pollution.

[0043] To address this, this application further proposes that the central signal processing unit employ a location algorithm based on time difference of arrival when calculating the spatial location of the leak point, using the following formula:

[0044] in, and For any two sensors, The time difference of receiving the signal. The distance difference to the leak point This represents the propagation speed of the negative pressure wave within the tank material.

[0045] Specifically, the time-of-arrival (TOA) based positioning algorithm refers to a mathematical method for spatial positioning using the time difference of signal propagation. It can be implemented using generalization techniques such as hyperbolic positioning or polygonal positioning. The purpose is to transform the abstract time difference into quantifiable spatial distance information, providing a basis for calculating the location of the leak point. Here, v is the propagation speed of the negative pressure wave in the tank material, which can be understood as the physical speed of signal propagation in a specific metal material. It can be obtained through material property experimental calibration or theoretical model derivation. The purpose is to eliminate the influence of tank material differences on signal propagation speed and ensure that the positioning result matches the actual physical environment. In practical applications, i and j are the settings of any two sensors, allowing the system to flexibly select sensor combinations in the distributed sensor network for calculation. This can be achieved using redundant sensor configuration or dynamic sensor pairing mechanism. The purpose is to enhance the adaptability and fault tolerance of the positioning process and avoid the interruption of positioning function due to the failure of a single sensor.

[0046] Specifically, the solution in this application accurately acquires the timestamps of the negative pressure wave signals arriving at different sensors through a central signal processing unit, and calculates the time difference based on a high-precision time synchronization mechanism. Then apply the formula The time difference is converted into the distance difference between the leak point and each sensor. Combined with the preset spatial coordinate information of each sensor, multiple sets of hyperbola intersections are formed using the geometric positioning principle. Finally, the precise spatial location of the leak point is calculated, thereby realizing the real-time positioning function based on the physical characteristics of signal propagation.

[0047] As a specific embodiment, the solution of this application is implemented as follows: The central signal processing unit can be a high-performance embedded processor. The processor receives signal data transmitted by the distributed negative pressure wave sensor network in real time. When an abnormal signal that matches the characteristics of a negative pressure wave is detected, it immediately records the precise timestamp of the signal arriving at each sensor. Then, based on the pre-calibrated propagation velocity parameters of the tank material, it calculates the time difference and the corresponding distance difference between any two sensors, and outputs the location information of the leak point to the human-machine interface through the coordinate calculation module.

[0048] Through the above technical solution, this application achieves rapid and accurate location of the leak point, significantly shortens the leak investigation time, and effectively reduces the risk of secondary accidents and the scope of environmental pollution.

[0049] Specifically, in the system design, the human-machine interface is configured to display the steady-state pressure baseline, real-time sensor signal waveforms, alarm information, and the spatial location of the leak point. However, in this process, there is a lack of a clear physical or data connection mechanism between the interface and the central signal processing unit. This results in the inability to transmit the key information generated by the central unit to the operating interface in real time, causing display delays or interruptions. As a result, operators cannot obtain leak alarms and accurate location data in a timely manner and are forced to rely on manual investigation or experience-based judgment. This further amplifies the lag and ambiguity of leak monitoring, delays emergency response, and increases safety risks and potential environmental pollution hazards.

[0050] In this regard, this application further proposes the connection between the human-computer interaction interface and the central signal processing unit.

[0051] The connection refers to the data communication link, which can be implemented using wired communication interfaces such as RS-485 or Ethernet, or wireless communication methods such as Wi-Fi or Bluetooth. Its purpose is to ensure that the processed data generated by the central signal processing unit can be transmitted to the human-machine interface in real time and reliably, avoiding the phenomenon of information silos.

[0052] Specifically, after completing background signal acquisition, steady-state pressure baseline establishment, real-time signal dynamic comparison, and leakage point spatial location calculation, the central signal processing unit generates a comprehensive data stream containing the steady-state pressure baseline, real-time sensor signal waveforms, alarm information, and leakage point spatial location. Through connection with the human-machine interface, this data can be transmitted to the interface in real time, enabling operators to observe system status changes and precise leakage locations immediately. This forms a closed-loop process from signal processing to human-machine interaction, effectively alleviating the information gap problem in leakage event response.

[0053] As a preferred embodiment, the solution of this application is implemented as follows: The central signal processing unit establishes a communication connection with the industrial control computer of the human-machine interface through the Ethernet interface, and transmits the spatial location data of the leakage point to the interface for dynamic display in real time.

[0054] By employing the above-mentioned solution, this application avoids the problem of blank display caused by communication failure, enabling operators to accurately locate the leak source without having to check each risk point such as tank, valve, or flange one by one. This significantly shortens the emergency response time and reduces safety risks and potential environmental pollution hazards.

[0055] In the practical application of the oil leakage prevention system for skid-mounted oil storage tanks, the central signal processing unit is configured to detect and locate leakage points in real time. However, in its implementation, the system lacks statistical analysis of the frequency of leakage events, cannot automatically identify high-risk areas and generate risk escalation reports, resulting in the risk of repeated leakage being ignored and operators finding it difficult to take preventive maintenance measures in a timely manner.

[0056] In response, this application further proposes that the central signal processing unit perform frequency statistics on leakage events and generate a risk escalation report for the area, synchronized using the following formula:

[0057] Among them, For the preset threshold, For the same region within the time window, This represents the number of leak alarms.

[0058] Leakage event frequency statistics refer to the periodic quantitative analysis of the number of leakage alarms in the same area. This can be achieved using a time-window-based counter or database log recording method, with the aim of transforming isolated leakage events into quantifiable cumulative risk indicators. Risk escalation reports can be understood as automatically generated early warning outputs when statistical results reach preset conditions. They can be in the form of structured electronic documents or real-time push messages, with the aim of providing standardized risk alerts. (Formula) Specifically, this refers to the logical conditions for determining whether the frequency of leakage triggers a risk escalation, among which... As a configurable threshold parameter, its purpose is to adapt to risk tolerance settings under different security levels.

[0059] Specifically, the central signal processing unit continuously monitors and records the same area within a time window during system operation. Number of internal leakage alarms ;when Reaching or exceeding a preset threshold When the risk escalation report generation process is triggered automatically, the process integrates regional identification, statistical period and alarm frequency data to form a structured report and push it to the human-computer interaction interface, thereby transforming the repetitive characteristics of leakage in the time dimension into an actionable risk warning signal, ensuring that the identification of high-risk areas is not affected by the delay of human intervention.

[0060] As a specific implementation method, the solution of this application is implemented as follows: the central signal processing unit can be specifically an ARM Cortex-M7 series microcontroller, with a time window... Configured for a 24-hour cycle, The system is set to a 5-time alarm threshold. When a storage tank area triggers 5 leak alarms within 24 hours, the system automatically generates a risk escalation report containing the area coordinates and statistical details, and displays it in real time as a highlighted warning box through the human-machine interface.

[0061] Through the above solution, this application can automatically quantify the cumulative frequency of leakage events, promptly identify high-risk areas of repeated leakage, avoid the tedious process of operators relying on manual alarm summarization, enable preventive maintenance measures to be proactively implemented before the risk escalates, and effectively reduce the probability of secondary accidents caused by repeated leakage.

[0062] In some of the embodiments described above in this application, a central signal processing unit is proposed for real-time monitoring of oil tank leaks and precise location of leak points. However, in its implementation, the system can only output alarm information for manual intervention by operators, which means that the oil source cannot be cut off immediately after the leak is confirmed. The response delay may cause the initial seepage to evolve into a large-scale leak, exacerbating the risk of environmental pollution and secondary accidents.

[0063] In response, this application further proposes the linkage between the central signal processing unit and the emergency shut-off system of the skid-mounted station. After confirming a leakage event, the central signal processing unit sends a signal to the emergency shut-off system to automatically close the corresponding inlet and outlet oil valves.

[0064] In practical applications, the linkage between the central signal processing unit and the skid-mounted station's emergency shut-off system refers to establishing a direct communication channel between the detection system and the actuators. This can be achieved using industrial Ethernet communication protocols or fieldbus interfaces, aiming to eliminate manual operation and ensure that leak monitoring data can drive safety equipment actions in real time. After confirming a leak event, the central signal processing unit performs risk verification based on steady-state pressure baseline comparison and leak point spatial location calculation mechanisms. This can be achieved based on the amplitude threshold determination of negative pressure wave characteristic signals or time difference positioning results, aiming to filter false alarm interference and maintain system stability. Sending signals to the emergency shut-off system refers to generating control commands containing leak point association logic, which can be achieved using digital output signals or structured data messages, aiming to accurately match the pipeline nodes corresponding to the leak source. Automatically closing the corresponding inlet and outlet valves refers to implementing directional shut-off operations based on the spatial location of the leak point, which can be achieved using electric actuators or pneumatic drive devices, aiming to block specific oil flow paths and curb the spread of leaks.

[0065] Specifically, the solution in this application establishes a direct linkage mechanism between the central signal processing unit and the emergency shut-off system of the skid-mounted station. Once the steady-state pressure baseline confirms a leak, the central signal processing unit generates a directional control command based on the calculated spatial location information of the leak point. This command is transmitted to the emergency shut-off system via a pre-set communication link, triggering the actuators of specific inlet and outlet valves associated with the leak point, thereby achieving rapid oil source cut-off without manual intervention. This process relies on precise leak location data provided by a distributed negative pressure wave sensor network, ensuring that only the pipeline node valves corresponding to the leak source are closed. This effectively blocks the leak path while preventing operational interruptions in non-leakage areas, forming a complete closed-loop control process from leak detection and precise location to emergency response.

[0066] As a specific implementation method, the solution of this application is implemented as follows: The central signal processing unit adopts an industrial-grade programmable logic controller, and its communication interface is connected to the control module of the emergency shut-off system via an RS-485 bus; when the system identifies an abnormal signal that conforms to the characteristics of a negative pressure wave and completes the spatial location calculation of the leak point, the central signal processing unit sends a control signal containing the valve address code to the emergency shut-off system; after receiving the signal, the emergency shut-off system drives the electric ball valve actuator associated with the leak point to operate, thereby realizing the automatic closure of the corresponding inlet and outlet oil valves.

[0067] Through the above technical solution, this application can immediately cut off the oil supply path of the leak source after confirming the leak event, avoid the initial leakage from expanding into a large-scale leak due to response delay, significantly reduce the risk of environmental pollution and the possibility of secondary accidents, and at the same time ensure the normal operation of non-leakage areas through the targeted shutdown mechanism.

[0068] Specifically, in some of the embodiments described above in this application, a system steady-state pressure baseline is proposed to distinguish between normal signals and leakage anomalies. However, in the implementation process, random fluctuations and noise interference of the background signal make it difficult for the baseline with a fixed or simple threshold setting to accurately capture the natural range of signal changes. This results in the system being insensitive to minor leaks and causing false alarms, or overreacting to normal fluctuations and triggering false alarms, which seriously affects the reliability and timeliness of leak detection.

[0069] In this regard, this application further proposes that the central signal processing unit calculates the system steady-state pressure baseline using the following formula:

[0070] in, The average value of the background signal. Standard deviation, Configurable confidence coefficient.

[0071] Average value of background signal This refers to the central tendency quantification of a signal under leak-free conditions. It can be calculated using an arithmetic mean or a weighted average, aiming to accurately reflect typical pressure levels and avoid the influence of signal drift; standard deviation. This can be understood as a measure of signal dispersion, which can be achieved using methods such as sample standard deviation or population standard deviation. The aim is to capture the actual fluctuation amplitude of background noise to dynamically adjust the baseline range; configurable confidence coefficients are also available. It refers to the parameter used to control the sensitivity of the baseline range. It can be set by the operator through the human-machine interface or automatically adjusted based on preset rules. The purpose is to flexibly adjust the detection sensitivity according to the field conditions.

[0072] Specifically, the solution in this application acquires the background signals of each sensor under leak-free conditions through a central signal processing unit and calculates their average value. and standard deviation And combined with configurable confidence coefficients Generate dynamic baseline range This baseline range can be automatically adjusted according to the statistical characteristics of the background signal. In real-time monitoring, the sensor signal is compared with the baseline, and when the signal exceeds the baseline range, it is identified as an anomaly, triggering the leak detection process. This dynamic baseline construction method based on statistical distribution ensures a close match between the baseline and the actual background state, effectively distinguishing between normal fluctuations and negative pressure wave anomalies caused by leaks.

[0073] As a specific implementation method, the solution of this application is implemented as follows: The central signal processing unit can be specifically implemented as an embedded microcontroller system based on an ARM Cortex-M7 core, which is equipped with non-volatile memory for storing background signal data. When establishing a steady-state pressure baseline, the processing unit executes a statistical analysis algorithm to calculate the average value. and standard deviation And provide confidence coefficients through a human-computer interaction interface. The configuration options allow operators to select an appropriate sensitivity level based on the ambient noise level.

[0074] Through the above technical solutions, the system can dynamically adapt to random fluctuations in background signals, significantly reduce the false alarm rate caused by noise interference, and improve the ability to detect minor initial leaks, thereby enhancing the reliability and timeliness of leak detection.

[0075] Specifically, in some of the embodiments described above in this application, a leakage alarm mechanism for the central signal processing unit is proposed. However, in its implementation, relying solely on a single alarm threshold cannot effectively distinguish the severity of leakage, causing minor leakage to be ignored due to insufficient signal amplitude, thus missing the opportunity for early intervention. At the same time, environmental noise interference can easily trigger false alarms, affecting system reliability and operational response efficiency.

[0076] In response, this application further proposes a system with multiple alarm threshold levels, wherein the central signal processing unit sets alarm thresholds based on the amplitude of the negative pressure wave signal. Compared with baseline noise amplitude The ratio is used to determine the result, and when it satisfies...

[0077] Timely triggering of warnings; When satisfied

[0078] When an emergency alarm is triggered, among which . Among them, multi-level alarm thresholds refer to the system setting multiple alarm level thresholds, which can be implemented using two or more discrete thresholds, such as early warning thresholds and emergency alarm thresholds. The purpose of this is to provide a tiered response based on the severity of the leak, avoiding the failure to address minor leaks or overreactions caused by noise interference under a single threshold. The central signal processing unit determines the alarm level based on the amplitude of the negative pressure wave signal. Compared with baseline noise amplitude The ratio is used for judgment, which can be understood as using the ratio to normalize the signal strength. This can be achieved by calculating the ratio in real time and comparing it with a preset threshold. The purpose of this is to dynamically adapt to changes in environmental noise, suppressing false alarms from small interferences when the noise is high, and capturing weak leakage signals when the noise is low; when the condition is met... When an alert is triggered, As a lower threshold, it can be set slightly above the normal noise level. Its purpose is to allow the system to issue an alert in the early stages of a leak, providing operators with a buffer time to investigate. When the threshold is met... When an emergency alarm is triggered, As a higher threshold, it can be set at a position significantly higher than the noise level. Its purpose is to ensure that emergency measures are quickly activated when the leakage is large, so as to prevent the accident from escalating. The conditions and constraints make A value greater than 1 ensures that the signal must significantly exceed the background noise to be considered a valid anomaly. Greater than The system strictly distinguishes between the threshold levels of early warning and emergency alarms, and its purpose is to enhance the system's ability to classify and identify the degree of leakage. Specifically, the solution in this application combines a multi-level alarm threshold with a signal ratio judgment mechanism. The central signal processing unit calculates the ratio of the negative pressure wave signal amplitude to the baseline noise amplitude in real time. When this ratio exceeds a lower threshold... A warning is triggered when the ratio exceeds a higher threshold, indicating a possible minor leak; The emergency alarm being triggered indicates a relatively serious leak. The system ensures that early warning precedes emergency alarm, forming a logical sequence. The ratio judgment mechanism uses the baseline noise amplitude to dynamically reflect the normal fluctuation range of the system, so that the judgment benchmark matches the real-time operating conditions. Thus, when the environmental noise changes, it can suppress false alarms caused by small interferences and capture weak leakage signals, achieving reliable early warning and accurate response.

[0079] As a specific implementation method, the solution of this application is implemented as follows: The central signal processing unit can be specifically implemented as a signal processing system based on an embedded microcontroller, whose software module periodically acquires negative pressure wave sensor signals and calculates the amplitude. Compared with baseline noise amplitude The ratio, and compare that ratio with a preset value. and Compare them. When the ratio exceeds... After a short period of time, the system displays a warning message on the human-computer interaction interface; when the ratio exceeds... Upon activation, an emergency alarm will be triggered immediately, and the emergency shutdown system will be activated. Among these, and The value can be configured according to the on-site noise characteristics. Set to a value slightly higher than 1 to catch early leaks. Set to greater than The value is used in response to a serious leak. Through the above solution, this application can effectively distinguish the severity of leakage, issue early warnings in the early stages of minor leakage, avoid being ignored due to insufficient signal amplitude, reduce false alarms caused by environmental noise interference, and improve the reliability and operational response efficiency of the system.

[0080] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A leak-proof system for oil storage tanks in a skid-mounted refined oil station, characterized in that, include: A distributed negative pressure wave sensing network consists of multiple high-precision negative pressure wave sensors, which are physically fixed on the outer wall surface of the storage tank and on key nodes of the pipelines connected to it. The key nodes include the tank head, cylinder welds, inlet and outlet valves and flange connections, and the layout density is determined according to the leakage risk level. A human-computer interaction interface is provided to display the steady-state pressure baseline, real-time sensor signal waveforms, alarm information, and the spatial location of the leak point; A central signal processing unit is communicatively connected to the distributed negative pressure wave sensor network; The central signal processing unit is configured to perform the following operations: Collect background signals from each sensor under leak-free conditions to establish a system steady-state pressure baseline; The real-time sensor signal is dynamically compared with the steady-state pressure baseline; When an abnormal signal matching the characteristics of a negative pressure wave is identified, the precise time difference between the arrival of the abnormal signal at different sensors in the network is recorded. Based on the time difference and the preset spatial coordinates of each sensor, the spatial location of the leak point is calculated. The output includes alarm information containing the spatial location of the leak point.

2. The oil leakage prevention system for skid-mounted oil storage tanks in a refined oil product station according to claim 1, characterized in that, The leakage risk level of the critical node is calculated using the following formula: ； in, For material factors, The structural stress coefficient, This refers to the operating pressure coefficient. Risk level.

3. The oil leakage prevention system for skid-mounted refined oil storage tanks according to claim 1, characterized in that, The negative pressure wave sensor is physically fixed to the outer wall of the storage tank and the pipeline by means of a magnetic base or threaded fastener.

4. The oil leakage prevention system for skid-mounted oil storage tanks in a refined oil product station according to claim 1, characterized in that, The central signal processing unit is communicatively connected to the negative pressure wave sensor.

5. The oil leakage prevention system for skid-mounted oil storage tanks in a refined oil product station according to claim 1, characterized in that, When calculating the spatial location of the leak point, the central signal processing unit uses a positioning algorithm based on the time difference of arrival, and calculates it using the following formula: ； in, and For any two sensors, The time difference of receiving the signal. The distance difference to the leak point This represents the propagation speed of the negative pressure wave within the tank material.

6. The oil leakage prevention system for skid-mounted oil storage tanks in a refined oil product station according to claim 1, characterized in that, The human-computer interaction interface is connected to the central signal processing unit.

7. The oil leakage prevention system for skid-mounted refined oil storage tanks according to claim 1, characterized in that, The central signal processing unit performs frequency statistics on leakage events and generates a risk escalation report for the area, which is synchronized using the following formula: ； Among them, For the preset threshold, For the same region within the time window, This represents the number of leak alarms.

8. The oil leakage prevention system for skid-mounted oil storage tanks in a refined oil product station according to claim 1, characterized in that, The central signal processing unit is linked to the emergency shut-off system of the skid-mounted station. After confirming a leakage event, the central signal processing unit sends a signal to the emergency shut-off system to automatically close the corresponding inlet and outlet oil valves.

9. A leak-proof system for oil storage tanks in a skid-mounted refined oil station according to claim 1, characterized in that, The central signal processing unit calculates the system steady-state pressure baseline using the following formula: ； in, The average value of the background signal. Standard deviation, Configurable confidence coefficient.

10. A leak-proof system for oil storage tanks in a skid-mounted refined oil station according to claim 1, characterized in that, The system is equipped with multiple alarm threshold levels, and the central signal processing unit determines the alarm threshold based on the amplitude of the negative pressure wave signal. Compared with baseline noise amplitude The ratio is used to determine the result, and when it satisfies... ； Timely triggering of warnings; When satisfied ； When an emergency alarm is triggered, among which .

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