Storage tank secondary sealing gas phase space intelligent monitoring and nitrogen generation protection system

Abstract

The invention discloses an intelligent monitoring and nitrogen generation protection system for a secondary sealing gas phase space of a storage tank. The system comprises a gas concentration monitoring module which forms a gas concentration signal through a plurality of multi-parameter gas detection units distributed in the circumferential direction of the secondary sealing gas phase space of the storage tank; the intelligent analysis module receives the gas concentration signal and outputs a risk level signal in combination with a trend prediction algorithm; the nitrogen generation control module receives the risk level signal, adaptively adjusts a control strategy according to the risk level and generates a nitrogen generation control signal, and the nitrogen generation control signal drives a nitrogen generation system and a nitrogen distribution pipe network to inject nitrogen into the high-risk area of the gas phase space in a partitioned nitrogen injection mode; and the cloud platform module receives the gas concentration signal and the risk level signal, and displays a concentration distribution cloud picture and a system state in real time through a visual interface. The intelligent monitoring and nitrogen generation protection system for the secondary sealing gas phase space of the storage tank can solve the problem that explosion risks exist in the secondary sealing gas phase space of a large external floating roof storage tank due to combustible gas accumulation.

Description

Technical Field

[0001] This invention relates to the field of industrial safety monitoring and protection technology, specifically to an intelligent monitoring and nitrogen generation protection system for the secondary sealing gas phase space of storage tanks. Background Technology

[0002] Large external floating roof tanks are key equipment for storing volatile liquid materials such as crude oil and refined oil products in the petroleum and chemical industries. To reduce material evaporation losses and improve safety, a primary seal and a secondary seal are installed between the floating roof and the tank wall, forming an annular secondary sealed gas phase space. However, due to the continuous evaporation of the stored materials, a high concentration of flammable oil and gas mixture with air easily accumulates in this space. This space is usually narrow with poor gas flow, easily forming areas of excessively high concentrations. Furthermore, it is affected by external wind speed, temperature changes, and tank operation (such as liquid level fluctuations), resulting in a highly uneven gas concentration distribution within the space, exhibiting significant spatiotemporal dynamic variations. Currently, traditional safety technologies in this field face several prominent bottlenecks. In terms of monitoring, the common practice is to install a limited number of flammable gas detectors on the tank top or in the annular space. This single-point or few-point monitoring method cannot capture the complex gas concentration distribution of the entire annular space, resulting in blind spots. The representativeness and real-time nature of the data are insufficient, making it difficult to accurately reflect the overall safety situation, let alone pinpoint specific risk points. In terms of protection, inerting protection technology is typically used, which involves injecting nitrogen into a sealed space to reduce oxygen concentration and thus suppress the formation of an explosive atmosphere. However, the control strategies of existing systems are relatively crude, often relying on simple timed start-stop or simple threshold control based on the concentration at a single measuring point, lacking intelligence. This control method has a lag in response and cannot accurately address dynamic changes in risk areas, often leading to excessive nitrogen injection to ensure safety, resulting in a significant waste of nitrogen resources and electrical energy, and poor operational economy. Furthermore, uneven nitrogen distribution can lead to insufficient protection in localized areas, leaving safety hazards. In addition, the components of existing systems are often relatively independent, lacking deep collaboration between monitoring, analysis, and control units, and data is not fully integrated and utilized, making it difficult to achieve predictive maintenance and intelligent decision-making for global optimization. Therefore, the industry urgently needs an integrated solution that can achieve panoramic monitoring, intelligent diagnosis, and precise protection to comprehensively improve the intrinsic safety level and operational efficiency of storage tanks. Summary of the Invention

[0003] In view of the shortcomings of the prior art, the purpose of this invention is to provide an intelligent monitoring and nitrogen generation protection system for the secondary sealing gas phase space of storage tanks, which solves the problem of explosion risk due to the accumulation of combustible gas in the secondary sealing gas phase space of large external floating roof storage tanks. By deploying distributed multi-parameter gas detection units circumferentially along the annular secondary sealing space of the storage tank, the system collects real-time data on the concentration, temperature, and pressure of combustible gas and oxygen, forming a gas concentration signal containing spatiotemporal distribution information. An intelligent analysis module receives this signal, uses a concentration field reconstruction algorithm to generate a visualized concentration distribution cloud map, and dynamically outputs a risk level signal through a risk assessment model and trend prediction algorithm. Based on this risk level signal, the nitrogen generation control module adaptively adjusts the control strategy, driving the nitrogen generation system and nitrogen distribution network to precisely inject nitrogen into identified high-risk areas in a zoned nitrogen injection manner, achieving efficient inerting protection. Simultaneously, a cloud platform module integrates all data, providing remote real-time monitoring, visualization, alarm, and equipment management functions, thus forming a closed-loop safety protection system from comprehensive perception and intelligent analysis to precise intervention.

[0004] This invention provides an intelligent monitoring and nitrogen generation protection system for the secondary sealing gas phase space of storage tanks, comprising: The gas concentration monitoring module collects combustible gas concentration, oxygen concentration, temperature and pressure data in real time through multiple multi-parameter gas detection units distributed around the secondary sealed gas phase space of the storage tank, forming a gas concentration signal containing spatiotemporal distribution information. The intelligent analysis module receives gas concentration signals, generates a two-dimensional distribution cloud map of combustible gas and oxygen concentrations in the gas phase space through a concentration field reconstruction algorithm, and uses a risk assessment model to dynamically analyze the concentration distribution, and outputs a risk level signal in combination with a trend prediction algorithm. The nitrogen generation control module receives risk level signals, adaptively adjusts the control strategy according to the risk level, generates nitrogen generation control signals, and drives the nitrogen generation system and nitrogen distribution pipeline network to inject nitrogen into high-risk areas of the gas phase space in a zoned nitrogen injection manner. The cloud platform module receives gas concentration signals and risk level signals, displays the concentration distribution cloud map and system status in real time through a visual interface, and generates alarm signals and maintenance reminder signals based on the risk level.

[0005] In one embodiment of the present invention, the gas concentration monitoring module further includes a sample gas pretreatment unit. The sample gas pretreatment unit continuously extracts sample gas from the gas phase space by pumping and performs multi-stage processing on the sample gas. The processing includes heating the sample gas to a specific temperature range to eliminate the effect of condensation, using a multi-stage filtration device to remove solid particulate matter and liquid impurities from the sample gas, further reducing the humidity of the sample gas by a condensation dehumidification device, and finally stably delivering the processed dry and clean sample gas to a multi-parameter gas detection unit for accurate measurement. At the same time, the measured sample gas is safely discharged back to the gas phase space of the storage tank through a return pipeline, thereby ensuring the accuracy and representativeness of the gas concentration signal.

[0006] In one embodiment of the present invention, the concentration field reconstruction algorithm in the intelligent analysis module specifically adopts a spatial interpolation calculation method. Based on the location information of multiple discrete detection units and their measured gas concentration data, the concentration estimate of each point in the entire annular gas phase space is calculated through mathematical modeling, thereby generating a two-dimensional color cloud map that can intuitively reflect the distribution of combustible gas and oxygen concentrations. The cloud map is dynamically updated and clearly identifies areas where the concentration exceeds the standard. The risk assessment model integrates the current concentration distribution, gas explosion limit parameters, and historical concentration change trends to dynamically divide safe areas, warning areas, and dangerous areas, and outputs corresponding risk level signals.

[0007] In one embodiment of the present invention, the intelligent analysis module further integrates a trend prediction function. This function continuously collects and stores historical gas concentration data to form a time series, uses predictive algorithms to analyze the concentration change pattern, predicts the gas concentration development trend at key locations within a specific future time period, and inputs the prediction result as a feedforward signal to the nitrogen generation control module in advance. This enables the system to initiate preventive nitrogen injection measures before the concentration reaches the alarm threshold, achieving an intelligent safety protection upgrade from passive response to active intervention.

[0008] In one embodiment of the present invention, the nitrogen generation control module adopts a zoned precision control strategy. Based on the risk level signal and the location of high-risk areas identified by the concentration distribution cloud map provided by the intelligent analysis module, it independently controls the opening of the control valve and the nitrogen flow rate on the nitrogen injection branch of the corresponding area in the nitrogen distribution pipeline network, so as to achieve targeted nitrogen injection into the high-risk area, while maintaining the minimum guaranteed flow rate in the low-risk area. This control method ensures efficient utilization of nitrogen resources and forms a uniform inert protective atmosphere in the entire annular space.

[0009] In one embodiment of the present invention, the nitrogen generation control module further adopts a closed-loop feedback control mechanism. This mechanism uses the real-time oxygen concentration or combustible gas concentration in the high-risk area as the process control variable, compares it with the preset safe concentration threshold, and dynamically adjusts the total output power and total nitrogen flow rate of the nitrogen generation system according to the deviation through a proportional-integral-derivative control algorithm, and synchronously coordinates the flow distribution of each zone's nitrogen injection branch, thereby ensuring that the gas concentration in the gas phase space is stably controlled within a safe range.

[0010] In one embodiment of the present invention, the cloud platform module further has remote control and equipment management functions. This function allows authorized users to remotely access the system via network connection. Not only can they view all monitoring data, alarm information and equipment operating status in real time, but they can also issue remote operation commands such as forced nitrogen injection, mode switching and parameter setting to the nitrogen generation control module. At the same time, the platform integrates equipment management functions, records the cumulative operating time and performance status of key equipment such as analyzers and sampling pumps, and generates equipment maintenance reminder signals based on preset conditions or intelligent algorithms.

[0011] In one embodiment of the present invention, the system further includes a micro-positive pressure maintenance unit for the explosion suppression membrane. This unit works in conjunction with the nitrogen generation control module to continuously inject an appropriate amount of nitrogen into the sealing device on which the explosion suppression membrane is installed, thereby creating a stable micro-positive pressure environment in the sealed space. This micro-positive pressure can cause the explosion suppression membrane to fit tightly against the tank wall, effectively eliminating the original gaps, and at the same time forming an airtight seal for any possible leaks in the primary seal. It is particularly suitable for tank conditions where the primary seal effect is poor due to tank deformation.

[0012] In one embodiment of the present invention, the multi-parameter gas detection unit in the gas concentration monitoring module uses a non-consumable optical detection principle to measure the concentration of combustible gas, specifically infrared absorption spectroscopy. This technology has a broad spectrum response to different hydrocarbon gases and has high detection accuracy and good stability. At the same time, it uses an electrochemical sensing principle to measure the oxygen concentration. The two sensors are integrated in the same explosion-proof housing and are used in conjunction with temperature and pressure sensors for data compensation, together forming a complete multi-parameter gas detection unit.

[0013] In one embodiment of the present invention, the system further includes an automatic calibration unit, which is integrated inside the gas concentration monitoring module. The unit is equipped with multiple standard gas cylinders containing zero-point standard gas, full-scale standard oxygen, and standard combustible gas. The system can start the automatic calibration program according to a preset cycle or manual command, and sequentially introduce each standard gas into the multi-parameter gas detection unit. By comparing the measured value with the standard value, the system automatically completes the zero-point calibration and range calibration of the sensor, and generates a calibration record which is transmitted to the cloud platform module, thereby ensuring the long-term accuracy and metrological validity of the gas concentration monitoring data.

[0014] The intelligent monitoring and nitrogen generation protection system for the secondary sealing gas phase space of storage tanks provided by this invention deploys distributed multi-parameter gas detection units along the circumference of the annular secondary sealing space of the storage tank to collect real-time data on the concentration, temperature, and pressure of combustible gases and oxygen, forming a gas concentration signal containing spatiotemporal distribution information. The intelligent analysis module receives this signal, uses a concentration field reconstruction algorithm to generate a visualized concentration distribution cloud map, and dynamically outputs a risk level signal through a risk assessment model and trend prediction algorithm. The nitrogen generation control module adaptively adjusts the control strategy based on this risk level signal, driving the nitrogen generation system and nitrogen distribution network to precisely inject nitrogen into the identified high-risk areas in a zoned nitrogen injection manner, achieving efficient inerting protection. At the same time, the cloud platform module integrates all data, providing remote real-time monitoring, visualization, alarm, and equipment management functions, thus forming a closed-loop safety protection system from comprehensive perception and intelligent analysis to precise intervention. Attached Figure Description

[0015] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a system architecture diagram of an intelligent monitoring and nitrogen generation protection system for the secondary sealing gas phase space of a storage tank. Detailed Implementation

[0017] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and features described therein can be combined with each other.

[0018] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0019] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the invention. However, it will be apparent to those skilled in the art that embodiments of the invention may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the invention.

[0020] Please see Figure 1 This invention discloses an intelligent monitoring and nitrogen generation protection system for the secondary sealed gas phase space of a storage tank, comprising: a gas concentration monitoring module, which collects combustible gas concentration, oxygen concentration, temperature, and pressure data in real time through multiple multi-parameter gas detection units distributed around the circumference of the secondary sealed gas phase space of the storage tank, forming a gas concentration signal containing spatiotemporal distribution information; an intelligent analysis module, which receives the gas concentration signal, generates a two-dimensional distribution cloud map of combustible gas and oxygen concentration in the gas phase space through a concentration field reconstruction algorithm, dynamically analyzes the concentration distribution using a risk assessment model, and outputs a risk level signal in conjunction with a trend prediction algorithm; a nitrogen generation control module, which receives the risk level signal, adaptively adjusts the control strategy according to the risk level, generates a nitrogen generation control signal, and drives the nitrogen generation system and nitrogen distribution pipeline network to inject nitrogen into high-risk areas of the gas phase space in a zoned nitrogen injection manner; and a cloud platform module, which receives the gas concentration signal and the risk level signal, displays the concentration distribution cloud map and system status in real time through a visual interface, and generates alarm signals and maintenance reminder signals based on the risk level.

[0021] Figure 1As shown, this invention provides an intelligent monitoring and nitrogen generation protection system for the secondary sealed gas phase space of large storage tanks, particularly external floating roof tanks. This system integrates advanced sensing technology, data analysis algorithms, and precise control strategies to construct a closed-loop safety protection system from perception, analysis, decision-making to execution, aiming to comprehensively improve the inherent safety level and economic efficiency of storage tank operation. The core of the system consists of four mutually cooperating modules: a gas concentration monitoring module responsible for data acquisition, an intelligent analysis module responsible for intelligent data parsing, a nitrogen generation control module responsible for executing safety interventions, and a cloud platform module responsible for human-computer interaction and remote management. The gas concentration monitoring module is the perception layer of the entire system and the foundation for obtaining first-hand data from the field. This module innovatively deploys multiple multi-parameter gas detection units in a distributed manner along the circumference of the secondary sealed annular gas phase space of the storage tank, thus forming a sensor network covering the entire monitoring area. This distributed layout strategy fundamentally overcomes the shortcomings of traditional single-point monitoring methods in terms of insufficient representativeness, and can effectively capture the uneven gas concentration distribution within the annular space caused by fluid dynamics, temperature gradients, and changes in the operating state of the storage tank. Each multi-parameter gas detection unit is a functionally integrated sensing node, typically integrating multiple high-precision sensors. These include a combustible gas sensor for detecting volatile organic compound concentrations, which may employ non-consumable infrared principles and boasts advantages such as long lifespan and high stability; an oxygen sensor for monitoring ambient oxygen content, usually based on electrochemical principles and exhibiting high selectivity for oxygen; and temperature and pressure sensors integrated to simultaneously collect meteorological parameters at the detection point. All this sensor data is synchronously collected and packaged into a comprehensive data packet. This packet not only contains the absolute value of the gas concentration but also, due to its clear spatial location information and timestamp, constitutes a gas concentration signal containing spatiotemporal distribution information. This signal is stably and reliably transmitted to the system's central hub—the intelligent analysis module—via intrinsically safe fieldbus networks or wireless IoT technology, providing a solid data foundation for subsequent in-depth analysis. The intelligent analysis module acts as the system's "brain," responsible for refining, processing, and interpreting massive amounts of raw monitoring data, transforming it into decision-making information with clear guiding significance. The core of this module lies in its internally running advanced algorithm system. Upon receiving a gas concentration signal containing spatiotemporal information from the gas concentration monitoring module, the first step is to initiate a concentration field reconstruction algorithm. Since the deployed detection units are discrete, and the state of the entire continuous annular space needs to be understood, the algorithm uses spatial interpolation calculations, such as the inverse distance weighting method or kriging, to estimate the concentration at any unmeasured point within the space based on the known concentration values ​​at discrete points.This process ultimately generates a visually intuitive two-dimensional distribution map of combustible gas and oxygen concentrations. This map clearly displays the concentration distribution throughout the secondary sealed space using different color gradients, intuitively identifying which areas have normal concentrations, which areas have high concentrations, and even potentially high-risk areas with localized accumulation. However, a distribution map alone is insufficient. The intelligent analysis module further utilizes a built-in risk assessment model to dynamically analyze this concentration distribution map. This model comprehensively considers multiple safety parameters, such as the lower explosive limit of the gas and the oxygen-supported combustion threshold, combined with real-time concentration distribution, dynamically dividing the entire space into safe zones, warning zones, and danger zones, and identifying the core area with the highest risk level. Furthermore, the module integrates a trend prediction algorithm. By performing time-series analysis on historical concentration data or applying machine learning models, it can predict the future trend of gas concentration changes in key areas over a period of time. Finally, the intelligent analysis module integrates the current concentration field status, risk area classification, and future trend prediction to output a comprehensive risk level signal. This signal is no longer a simple binary judgment of "exceeding the standard" or "normal", but an intelligent instruction that can quantify the degree of risk, indicate the location of the risk, and even warn of the development trend of the risk, providing precise guidance for subsequent protective actions.

[0022] Furthermore, the nitrogen generation control module, acting as the system's "executive arm," is responsible for translating the decision-making instructions issued by the intelligent analysis module into concrete physical actions. This module receives risk level signals from upstream sources, but its control logic is not a simple "on" or "off" operation; rather, it adaptively adjusts its control strategy based on the risk level. For example, when the risk level signal indicates a localized high risk, the control strategy focuses on precise targeting; while when it indicates an overall upward trend in concentration, the strategy may focus on preventative, comprehensive inerting. After generating the corresponding nitrogen generation control signal, this signal drives two main actuators: first, the nitrogen generation system, typically a pressure swing adsorption (PSA) nitrogen generator, controlling its start-up, shutdown, and adjusting its gas production power; and second, the complex nitrogen distribution network, which runs circumferentially along the storage tank and has multiple independent nitrogen injection branches and ports. The nitrogen generation control signal precisely controls the solenoid valves or regulating valves on these branches to achieve zoned nitrogen injection. Specifically, it prioritizes or increases nitrogen injection into the nitrogen inlets corresponding to high-risk areas identified by the intelligent analysis module, while maintaining a low flow rate or even shutting off the flow to lower-risk areas, thus achieving targeted dilution and inerting of high-risk areas. This zoned, precise injection method, compared to traditional uniform or overall nitrogen injection, can reduce the oxygen concentration in high-risk areas below the safe threshold faster and more effectively with less nitrogen consumption, greatly improving protection efficiency and economy. The cloud platform module serves as the window for system-user interaction and the hub for remote management. It simultaneously receives raw gas concentration signals from the gas concentration monitoring module and risk level signals from the intelligent analysis module, and performs deep fusion and processing. At the data processing level, it is responsible for data parsing, storing in the time-series database, and generating various historical data reports. At the visualization level, it is the main interface for displaying system status, clearly presenting key information such as the concentration distribution cloud map generated by the intelligent analysis module, real-time system operating status, equipment operating parameters, and alarm information to operators through a beautifully designed graphical interface. Based on real-time risk level analysis, this module generates alarm signals of different levels, promptly notifying relevant personnel through screen flashing, sound alerts, and even SMS or email push notifications. Simultaneously, it monitors the operational status of critical equipment within the system, generating maintenance reminders based on operating time or performance data analysis to prompt equipment maintenance or calibration, thereby achieving predictive maintenance. Furthermore, the cloud platform module typically supports remote access and control, allowing authorized users to view the tank's safety status from anywhere via the network and issue remote commands to the nitrogen control module when necessary, such as forcibly starting nitrogen injection or switching operating modes, greatly improving management convenience and response speed. In summary, these four modules are closely interconnected through data and control flows, forming a complete closed loop of perception-analysis-decision-execution.The gas concentration monitoring module is responsible for collecting "battlefield intelligence," the intelligent analysis module is responsible for "analyzing intelligence and formulating combat plans," the nitrogen production control module is responsible for "precisely executing strike missions," and the cloud platform module provides a "global command and monitoring center." Working together, they achieve the knowability, visibility, predictability, and controllability of the safety status of the secondary sealed gas phase space of the storage tank, representing a new direction for the development of storage tank safety protection technology towards intelligence, precision, and efficiency.

[0023] Specifically, in the implementation of the gas concentration monitoring module, to ensure the accuracy and long-term reliability of the collected gas concentration signals, especially considering the often harsh environment at the storage tank site where the sample gas may contain interfering substances such as oil mist, moisture, and dust, this module further integrates a fully functional sample gas pretreatment unit. This unit is a crucial pre-processing step to ensure the normal and accurate operation of the high-precision detector at the back end. It typically employs a pump-suction sampling method, using negative pressure generated by a corrosion-resistant, long-life sampling pump to actively and continuously extract sample gas from specific sampling points within the secondary sealed space of the storage tank. Before entering the analytical sensor, the sample gas must undergo a series of rigorous processing steps. First, the sample gas enters a heating stage, usually through a heat tracing pipe or heating chamber, to heat the sample gas and maintain it at a specific temperature range above its dew point. The core purpose of this measure is to prevent condensation from forming during the sample gas transmission due to temperature drop, as condensation can not only dissolve some of the analytes in the sample gas, leading to concentration measurement distortion, but may also damage the delicate sensor. Next, the heated sample gas passes through a multi-stage filtration system. These filters, typically with different pore sizes and materials, progressively remove solid particles, oily aerosols, and any liquid impurities carried in the sample gas, ensuring that the sample gas entering the analyzer is clean and preventing sensor contamination or flow path blockage. Then, the sample gas enters a condensation and dehumidification device, which rapidly lowers the temperature of the sample gas using semiconductor refrigeration or other cooling methods, causing the water vapor to condense into liquid water, which is then automatically drained, significantly reducing the humidity of the sample gas and resulting in a dry sample gas. This is because excessive humidity can adversely affect the measurement accuracy and lifespan of certain types of sensors (such as electrochemical oxygen sensors). After the above heating, filtration, and dehumidification processes, a representative sample gas with a suitable temperature and clean, dry condition is obtained. At this point, the pretreatment unit uses a pressure and flow stabilization device to smoothly deliver it at a constant and appropriate flow rate and pressure to the core multi-parameter gas detection unit for accurate concentration measurement. A crucial but often overlooked detail is that the sample gas, after measurement, is not arbitrarily released. Instead, it is safely returned to the gas phase space of the storage tank via a specially designed return pipeline. This design not only meets environmental protection requirements and prevents the leakage of hazardous gases but also does not affect the internal pressure balance of the storage tank. The entire sample gas pretreatment process is continuous and automated. Its superior performance ensures that the final gas concentration signal generated and transmitted has high accuracy and true representativeness, laying a solid foundation for the reliable judgment and precise control of the entire intelligent protection system.

[0024] In one embodiment of the present invention, the core technology within the intelligent analysis module is the deep application and synergy of a concentration field reconstruction algorithm and a risk assessment model. The primary task of the concentration field reconstruction algorithm is to transform discrete, point-like measurement data into continuous, planar, and intuitive spatial distribution information. Because multiple multi-parameter gas detection units are deployed circumferentially in the annular secondary sealed space, each unit can only provide the instantaneous concentration at its installation location, while the situation in other areas of the space that are not directly measured is unknown. The concentration field reconstruction algorithm is designed to solve this information gap problem; it is essentially a spatial interpolation calculation method. This algorithm is based on a fundamental principle of spatial correlation, namely that the attribute values ​​(such as gas concentration) of adjacent points in space are interconnected, and the closer the points are, the more likely their attribute values ​​are to be similar. The algorithm acquires the precise spatial coordinates of all detection units and their real-time gas concentration data. Then, through complex mathematical modeling, such as the inverse distance weighting method (which assumes the value of an unknown point is a weighted average of known points, with weights inversely proportional to distance—the closer to a known point, the greater its influence), or the more precise Kriging method (which considers not only distance but also uses a variogram to characterize the spatial structure of the data, thus providing the best linear unbiased estimate), the system can calculate estimated concentrations of combustible gases and oxygen at tens of thousands of virtual grid points within the annular gas phase space. These estimated data are then color-mapped, ultimately generating a dynamically updated, clearly defined two-dimensional color cloud map on the software interface. This cloud map allows operators to clearly see the "health status" of the entire annular space, particularly identifying which localized areas have exceeded concentration limits, forming potential "risk islands." However, a distribution map alone is insufficient to directly guide action; this necessitates the use of a risk assessment model. This model integrates multi-dimensional information, including the current concentration distribution cloud map, pre-set gas explosion limit parameters, oxygen combustion-supporting concentration thresholds, and historical concentration change patterns, to conduct dynamic and quantitative risk assessment. Based on preset logical rules, such as combining different combinations of oxygen and combustible gas concentrations, it dynamically divides the entire annular space into absolutely safe green zones, yellow warning zones requiring close monitoring, and red danger zones requiring immediate intervention. More importantly, it can automatically identify and locate the highest-risk core areas from the cloud map, providing clear targets for subsequent precise nitrogen production control. This close integration of concentration field reconstruction and risk assessment means the system no longer simply responds to alarms at a single point, but rather gains a global perspective on the spatial distribution and evolution of risks, achieving a qualitative leap in safety monitoring from a "short-sighted" to a "comprehensive overview."

[0025] like Figure 1As shown, the intelligent analysis module of this invention, in addition to its concentration field reconstruction and risk assessment capabilities, further integrates a forward-looking trend prediction function. This function marks a leap from static, current-state-based monitoring to dynamic, future-oriented early warning and intervention. Its core lies in the deep mining and learning of historical and real-time gas concentration data. The system continuously stores timestamped gas concentration signals from the gas concentration monitoring module, forming a complete historical data time series. The trend prediction function analyzes this time series by running specific predictive algorithms. These algorithms may include classic time series analysis methods, such as the autoregressive integral moving average model, which can identify trend, seasonal, and random components in the data; or they may employ more advanced machine learning models, such as long short-term memory networks, which are particularly adept at learning long-term dependencies from time series data. By learning the patterns of historical concentration changes, including their rates of increase or decrease, periodic fluctuation characteristics, and correlations with external environmental factors such as temperature and pressure, the algorithm can construct a dynamic model of concentration changes. Using this model, the system can extrapolate the gas concentration trends over a specific future time period, especially in key high-risk areas, generating a quantitative prediction. This prediction is encapsulated as a feedforward signal, distinct from feedback signals based on current measured values; it depicts a scenario "about to happen." This feedforward signal is transmitted to the nitrogen control module in advance, its strategic value lying in breaking the traditional passive "post-event response" mode. It enables the nitrogen control module to initiate or adjust nitrogen injection measures in advance, even before the measured concentration reaches the alarm threshold, based on the prediction that it is about to reach or exceed it. This preventative nitrogen injection is equivalent to building a pre-emptive defense, suppressing dangerous atmospheres before they truly form, greatly reducing the probability of risk escalation, and achieving an intelligent upgrade in safety protection from post-event remediation to pre-event prevention, significantly improving the system's foresight and reliability.

[0026] like Figure 1As shown, at the system execution level, the nitrogen generation control module adopts and implements a highly refined zoned precision control strategy. The core idea of ​​this strategy is "on-demand allocation and targeted treatment," aiming to utilize nitrogen resources with the highest efficiency and achieve optimal protection. The strategy's formulation directly relies on the output of the intelligent analysis module. The nitrogen generation control module not only receives general risk level signals, but more importantly, it can acquire or analyze the spatial location information of specific high-risk areas identified in the concentration distribution cloud map. Based on this information, the control strategy is no longer simply to open or close the entire nitrogen generation system, but rather to differentiate and independently regulate the nitrogen distribution network. The nitrogen distribution network is typically designed as multiple independent nitrogen injection branches corresponding to monitoring zones. Each branch serves a specific ring section and is equipped with precisely controllable valves, such as electric regulating valves or combinations of solenoid valves and flow meters. When the intelligent analysis module identifies one or more specific sections as high-risk areas, the control signal generated by the nitrogen generation control module instructs the control valves on the nitrogen injection branches corresponding to these high-risk areas to increase their opening, thereby increasing the nitrogen flow to that area for targeted dilution and inerting. Meanwhile, for other sections with lower risk levels or deemed safe, their corresponding nitrogen injection branches maintain a low basic guaranteed flow rate, or are temporarily shut down under certain optimization strategies to conserve nitrogen. This control method ensures that precious nitrogen resources are prioritized and concentrated for the most urgent needs, achieving "using the best resources where they are most needed." It effectively avoids the unreasonable phenomenon in traditional uniform nitrogen injection modes, where safe areas are excessively inertized while dangerous areas remain at risk due to insufficient allocation. It can quickly establish a uniform and reliable safe atmosphere throughout the entire annular sealed space, while significantly reducing the overall energy consumption and gas consumption of the nitrogen generation system, demonstrating a perfect balance between safety and economy. To ensure the continuous stability and precise controllability of the protective effect, the nitrogen generation control module further introduces and implements a closed-loop feedback control mechanism. This is a classic and efficient control method that enables the system to have self-correction and dynamic optimization capabilities. In this mechanism, the controlled "process variable" is set as the real-time oxygen concentration or combustible gas concentration in high-risk areas, and these data are continuously fed back from the gas concentration monitoring module. The system internally presets a safe concentration threshold as a "set value," such as an upper limit of oxygen concentration sufficient to suppress combustion. The core of the control mechanism lies in continuously comparing the measured value of this process variable with the setpoint to calculate the real-time "deviation". This deviation signal is then fed into a proportional-integral-derivative (PID) control algorithm for calculation. The proportional term is responsible for responding immediately to the current deviation; the larger the deviation, the stronger the control effect. The integral term is responsible for accumulating historical deviations to eliminate persistent steady-state errors. The derivative term makes proactive adjustments based on the trend of deviation changes to suppress system oscillations.After calculation, the algorithm dynamically outputs a control command. This command macroscopically adjusts the total output power and total nitrogen flow rate of the nitrogen generation system, and microscopically coordinates the flow distribution ratio between nitrogen injection branches in each zone. For example, when the measured oxygen concentration in a high-risk area is higher than the set value and continues to rise, the algorithm calculates that the total nitrogen flow rate needs to be increased and may instruct the valves in the high-risk area branches to open further. Conversely, when the concentration is effectively suppressed and lower than the set value, the total flow rate and branch flow rate will be appropriately reduced to save resources. This closed-loop feedback control constitutes a continuous and automated adjustment cycle, which can effectively overcome interference caused by factors such as fluctuations in intake gas concentration, changes in environmental conditions, or minor degradation of equipment performance, firmly stabilizing the concentration of key gases in the gas phase space within the preset safety range, providing robust and reliable protection.

[0027] Furthermore, as the core of system-user interaction and the hub of remote management, the cloud platform module's functions extend far beyond data display. It deeply integrates powerful remote control and equipment management capabilities, greatly expanding the system's operability and ease of maintenance. Regarding remote control, this module provides authorized users with a virtual control panel through a secure network connection. Users can access the cloud platform interface via computer or mobile terminal without being physically present at the tank farm. Here, users can not only view all monitoring data, alarm information, and the operating status of each system module in real time, but also bypass the local control level and directly issue advanced commands to the remote nitrogen generation control module. These commands include, but are not limited to, forcibly starting or stopping nitrogen injection, switching between different operating modes, and modifying key control parameter settings. This capability is crucial in responding to emergencies, conducting remote commissioning, or performing special operations, breaking geographical limitations and improving emergency response speed and management flexibility. In terms of equipment management, the cloud platform module plays the role of a meticulous "equipment steward." Through its underlying data interface, it continuously collects and records the operating status and parameters of key equipment within the system, such as the cumulative operating hours of the analyzer, the number of start-ups and shutdowns of the sampling pump, and the signal stability of each sensor. The platform's built-in algorithm assesses the health of the equipment based on this data. It can automatically generate equipment maintenance reminders based on preset conditions, such as reaching a set operating time, or based on performance trend analysis, such as detecting a slow decline in sensor sensitivity. This signal clearly indicates to maintenance personnel that specific equipment needs calibration, maintenance, or inspection. This data-driven predictive maintenance replaces traditional maintenance methods that rely on fixed cycles or reactive fault diagnosis. It enables more scientific planning of maintenance schedules, avoids operating equipment with defects, and eliminates potential faults before they occur, thereby ensuring the long-term stable and reliable operation of the entire monitoring and protection system, extending equipment lifespan, and reducing the risk of unexpected downtime.

[0028] The intelligent monitoring and nitrogen generation protection system for the secondary sealing gas phase space of the storage tank of this invention deploys distributed multi-parameter gas detection units along the circumference of the annular secondary sealing space of the storage tank to collect real-time data on the concentration, temperature, and pressure of combustible gases and oxygen, forming a gas concentration signal containing spatiotemporal distribution information. The intelligent analysis module receives this signal, uses a concentration field reconstruction algorithm to generate a visualized concentration distribution cloud map, and dynamically outputs a risk level signal through a risk assessment model and a trend prediction algorithm. The nitrogen generation control module adaptively adjusts the control strategy based on this risk level signal, drives the nitrogen generation system and nitrogen distribution network, and precisely injects nitrogen into the identified high-risk areas in a zoned nitrogen injection manner to achieve efficient inerting protection. At the same time, the cloud platform module integrates all data and provides remote real-time monitoring, visualization, alarm, and equipment management functions, thus forming a closed-loop safety protection system from comprehensive perception and intelligent analysis to precise intervention.

[0029] Therefore, the intelligent monitoring and nitrogen generation protection system for the secondary sealed gas phase space of the storage tank of the present invention can solve the problems of explosion risk due to the accumulation of combustible gas in the secondary sealed gas phase space of large external floating roof storage tanks, as well as the problems of incomplete monitoring, inaccurate control and large nitrogen consumption of existing monitoring and protection technologies.

[0030] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A smart monitoring and nitrogen generation protection system for the secondary sealing gas phase space of a storage tank, characterized in that, include: The gas concentration monitoring module collects combustible gas concentration, oxygen concentration, temperature and pressure data in real time through multiple multi-parameter gas detection units distributed around the secondary sealed gas phase space of the storage tank, forming a gas concentration signal containing spatiotemporal distribution information. The intelligent analysis module receives the gas concentration signal, generates a two-dimensional distribution cloud map of combustible gas and oxygen concentration in the gas phase space through a concentration field reconstruction algorithm, performs dynamic analysis of the concentration distribution using a risk assessment model, and outputs a risk level signal in combination with a trend prediction algorithm. A nitrogen generation control module receives the risk level signal, adaptively adjusts the control strategy according to the risk level, generates a nitrogen generation control signal, and drives the nitrogen generation system and nitrogen distribution pipeline to inject nitrogen into the high-risk area of ​​the gas phase space in a zoned nitrogen injection manner. The cloud platform module receives the gas concentration signal and the risk level signal, displays the concentration distribution cloud map and system status in real time through a visual interface, and generates alarm signals and maintenance reminder signals based on the risk level.

2. The intelligent monitoring and nitrogen generation protection system for the secondary sealing gas phase space of the storage tank according to claim 1, characterized in that, The gas concentration monitoring module further includes a sample gas pretreatment unit. This sample gas pretreatment unit continuously extracts sample gas from the gas phase space via a pump and performs multi-stage processing on the sample gas. The processing includes heating the sample gas to a specific temperature range to eliminate the effects of condensation, using a multi-stage filtration device to remove solid particles and liquid impurities from the sample gas, further reducing the humidity of the sample gas through a condensation dehumidification device, and finally stably delivering the processed dry and clean sample gas to a multi-parameter gas detection unit for accurate measurement. At the same time, the measured sample gas is safely discharged back to the gas phase space of the storage tank through a return pipeline, thereby ensuring the accuracy and representativeness of the gas concentration signal.

3. The intelligent monitoring and nitrogen generation protection system for the secondary sealing gas phase space of the storage tank according to claim 1, characterized in that, The concentration field reconstruction algorithm in the intelligent analysis module specifically adopts a spatial interpolation calculation method. Based on the location information of multiple discrete detection units and their measured gas concentration data, it calculates the concentration estimate of each point in the entire annular gas phase space through mathematical modeling, thereby generating a two-dimensional color cloud map that can intuitively reflect the distribution of combustible gas and oxygen concentrations. This cloud map is dynamically updated and clearly identifies areas where the concentration exceeds the standard. Meanwhile, the risk assessment model integrates the current concentration distribution, gas explosion limit parameters, and historical concentration change trends to dynamically divide safe areas, warning areas, and dangerous areas, and outputs corresponding risk level signals.

4. The intelligent monitoring and nitrogen generation protection system for the secondary sealing gas phase space of the storage tank according to claim 1, characterized in that, The intelligent analysis module further integrates trend prediction function. This function continuously collects and stores historical gas concentration data to form a time series, uses predictive algorithms to analyze the concentration change pattern, predicts the gas concentration development trend of key locations in a specific future time period, and inputs the prediction result as a feedforward signal to the nitrogen generation control module in advance. This enables the system to initiate preventive nitrogen injection measures before the concentration reaches the alarm threshold, realizing an intelligent safety protection upgrade from passive response to active intervention.

5. The intelligent monitoring and nitrogen generation protection system for the secondary sealing gas phase space of the storage tank according to claim 1, characterized in that, The nitrogen generation control module adopts a zoned precision control strategy. Based on the risk level signal and the location of high-risk areas identified by the concentration distribution cloud map provided by the intelligent analysis module, it independently controls the opening of the control valves and the nitrogen flow rate on the nitrogen injection branches in the corresponding areas of the nitrogen distribution network. This achieves targeted nitrogen injection into high-risk areas while maintaining the minimum guaranteed flow rate in low-risk areas. This control method ensures efficient utilization of nitrogen resources and forms a uniform inert protective atmosphere throughout the entire annular space.

6. The intelligent monitoring and nitrogen generation protection system for the secondary sealing gas phase space of the storage tank according to claim 1, characterized in that, The nitrogen generation control module further adopts a closed-loop feedback control mechanism. This mechanism uses the real-time oxygen concentration or combustible gas concentration in high-risk areas as process control variables, compares them with preset safe concentration thresholds, and dynamically adjusts the total output power and total nitrogen flow rate of the nitrogen generation system according to the deviation through a proportional-integral-derivative control algorithm. It also coordinates the flow distribution of nitrogen injection branches in each zone, thereby ensuring that the gas concentration in the gas phase space is stably controlled within a safe range.

7. The intelligent monitoring and nitrogen generation protection system for the secondary sealing gas phase space of the storage tank according to claim 1, characterized in that, The cloud platform module further features remote control and equipment management functions. This function allows authorized users to remotely access the system via network connection. Users can not only view all monitoring data, alarm information, and equipment operating status in real time, but also issue remote operation commands to the nitrogen generation control module, such as forced nitrogen injection, mode switching, and parameter setting. At the same time, the platform integrates equipment management functions, records the cumulative operating time and performance status of key equipment such as analyzers and sampling pumps, and generates equipment maintenance reminder signals based on preset conditions or intelligent algorithms.

8. The intelligent monitoring and nitrogen generation protection system for the secondary sealing gas phase space of the storage tank according to claim 1, characterized in that, The system further includes a micro-positive pressure maintenance unit for the explosion suppression membrane. This unit works in conjunction with the nitrogen generation control module. By continuously injecting an appropriate amount of nitrogen into the sealing device equipped with the explosion suppression membrane, a stable micro-positive pressure environment is formed in the sealed space. This micro-positive pressure can cause the explosion suppression membrane to fit tightly against the tank wall, effectively eliminating the original gaps. At the same time, it forms an airtight seal for any possible leaks in the primary seal. It is particularly suitable for tank conditions where the primary seal effect is poor due to tank deformation.

9. The intelligent monitoring and nitrogen generation protection system for the secondary sealing gas phase space of a storage tank according to claim 1, characterized in that, The multi-parameter gas detection unit in the gas concentration monitoring module uses a non-consumable optical detection principle to measure the concentration of combustible gases, specifically infrared absorption spectroscopy. This technology has a broad spectrum response to different hydrocarbon gases and has high detection accuracy and good stability. At the same time, it uses an electrochemical sensing principle to measure oxygen concentration. The two sensors are integrated in the same explosion-proof housing and are used in conjunction with temperature and pressure sensors for data compensation, together forming a complete multi-parameter gas detection unit.

10. The intelligent monitoring and nitrogen generation protection system for the secondary sealing gas phase space of a storage tank according to claim 1, characterized in that, The system further includes an automatic calibration unit, which is integrated into the gas concentration monitoring module. This unit is equipped with multiple standard gas cylinders containing zero-point standard gas, full-scale standard oxygen, and standard combustible gas. The system can start the automatic calibration program according to a preset cycle or manual command, sequentially introducing each standard gas into the multi-parameter gas detection unit. By comparing the measured value with the standard value, the system automatically completes the zero-point calibration and range calibration of the sensor and generates a calibration record, which is transmitted to the cloud platform module, thereby ensuring the long-term accuracy and metrological validity of the gas concentration monitoring data.

Images