External floating roof storage tank liquid limiting optical fiber sensing detection system

Abstract

The invention relates to the technical field of liquid level detection, in particular to an external floating roof storage tank liquid limiting optical fiber sensing detection system which comprises an optical fiber sensing detection module used for detecting light refraction and absorption characteristics of liquid to sense liquid level changes and obtain liquid level change optical signals; the photoelectric conversion module is used for receiving the liquid level change optical signal and converting the liquid level change optical signal into electric signal intensity data; the dynamic threshold value adjusting module is used for acquiring the temperature data of the storage tank in real time, and calculating a reference electric signal intensity threshold value at the current temperature through a preset temperature drift compensation algorithm in combination with the electric signal intensity data; the multi-parameter fusion analysis module is used for acquiring the pressure data in the storage tank in real time, and calculating the liquid level state confidence coefficient through a preset fuzzy logic calculation model in combination with the reference electric signal intensity threshold value and the electric signal intensity data at the current temperature; and the detection result obtaining module is used for comparing the liquid level state confidence coefficient with a preset limiting safety threshold value to obtain a current liquid level detection result.

Description

Technical Field

[0001] This invention relates to the technical field of liquid level detection, and more particularly to a fiber optic sensing detection system for liquid level control in an external floating roof tank. Background Technology

[0002] External floating roof tanks are core equipment in the petrochemical industry for storing bulk liquid media such as crude oil and refined oil. Their liquid level safety limit detection is directly related to production safety and environmental risk control. Currently, liquid level detection in external floating roof tanks mainly uses traditional technologies such as float-type, radar-type, and ultrasonic-type. However, research has found that existing detection technologies generally suffer from false alarms at high liquid levels, leading to frequent triggering of interlock shutdowns, which not only reduces production efficiency but may also cause safety hazards. Summary of the Invention

[0003] This invention provides a fiber optic sensing detection system for liquid limit in external floating roof tanks, which can improve detection accuracy, reduce false alarms, and increase production efficiency, effectively solving the problems in the background art.

[0004] To achieve the above objectives, in a first aspect, the present invention provides a fiber optic sensing and detection system for liquid limiting in an external floating roof tank, comprising: The fiber optic sensing module is used to detect the refraction and absorption characteristics of light by the liquid to sense changes in liquid level and obtain the optical signal of the liquid level change. The photoelectric conversion module is used to receive the optical signal of liquid level change and convert the optical signal of liquid level change into electrical signal intensity data; The dynamic threshold adjustment module acquires the tank temperature data in real time, and calculates the reference electrical signal strength threshold at the current temperature by combining it with the electrical signal strength data and using a preset temperature drift compensation algorithm. The multi-parameter fusion analysis module acquires the internal pressure data of the storage tank in real time, and calculates the confidence level of the liquid level status by combining the reference electrical signal strength threshold at the current temperature and the electrical signal strength data through a preset fuzzy logic calculation model. The detection result acquisition module compares the liquid level status confidence level with the preset limit safety threshold to obtain the current liquid level detection result.

[0005] In conjunction with the first aspect, in one possible design, the liquid level change optical signal is transmitted via optical fiber.

[0006] In conjunction with the first aspect, in one possible design, the photoelectric conversion module further includes an automatic gain adjustment module for amplifying the converted electrical signal.

[0007] In conjunction with the first aspect, in one possible design, the photoelectric conversion module further includes a noise suppression algorithm and a filtering mechanism for denoising and filtering the amplified electrical signal.

[0008] In conjunction with the first aspect, in one possible design, the formula for calculating the reference electrical signal strength threshold at the current temperature using a preset temperature drift compensation algorithm is as follows: Wherein, the T c T represents the threshold value after compensation. b The threshold value at the reference temperature is represented by α, which represents the temperature drift coefficient. The T value is... a The T represents the actual temperature. r Indicates the reference temperature.

[0009] In conjunction with the first aspect, in one possible design, the multi-parameter fusion analysis module also includes an intrinsically safe pressure sensor for real-time acquisition of internal pressure data of the storage tank.

[0010] In conjunction with the first aspect, in one possible design, the confidence level of the liquid level state is calculated using a pre-defined fuzzy logic calculation model, including: The preset fuzzy logic calculation model fuzzifies the input parameters; The fuzzy logic calculation model has a built-in fuzzy rule library, which includes liquid level state judgment logic corresponding to different combinations of signal states and pressure conditions. The fuzzy parameters of the input are inferred and calculated based on the fuzzy rule base to obtain the fuzzy result of the liquid level state; The fuzzy results of the liquid level status are defuzzified and converted into liquid level status confidence values.

[0011] In conjunction with the first aspect, in one possible design, the factors influencing the setting of the preset limit safety threshold include the characteristics of the storage tank itself, the properties of the storage medium, the operating conditions and operational requirements, and the accuracy of the detection system.

[0012] In conjunction with the first aspect, in one possible design, the preset limit safety threshold includes two levels: a warning threshold and an over-limit threshold.

[0013] In conjunction with the first aspect, in one possible design, the detection result acquisition module also includes a continuous judgment mechanism, which generates the corresponding detection result and performs subsequent operations only when the confidence level of the liquid level reaches or exceeds the corresponding threshold multiple times consecutively.

[0014] The technical solution of this invention can achieve the following technical effects: By incorporating temperature data through a dynamic threshold adjustment module and combining it with a temperature drift compensation algorithm, signal deviations caused by temperature fluctuations can be corrected in real time, ensuring accurate liquid level measurement under different ambient temperatures and responding to environmental changes in real time to guarantee the accuracy of the liquid level signal. The introduction of a multi-parameter fusion analysis module, combining pressure data from inside the tank with the intensity of a reference electrical signal at real-time temperature, enhances the accuracy of liquid level status judgment, further eliminating errors that may arise from relying on a single signal and improving detection accuracy. A pre-set fuzzy logic calculation model is used to calculate the confidence level of the liquid level status, effectively handling ambiguity between different data and avoiding false alarms that may occur when relying solely on simple threshold judgments in traditional methods. The fuzzy logic model, by comprehensively considering multiple aspects of information such as temperature, pressure, and liquid level signals, can automatically adjust the system according to different situations. The system adjusts the judgment criteria to more accurately determine the liquid level status and reduce the false alarm rate. By acquiring changes in temperature, pressure, and liquid level signals in real time, the system dynamically adjusts the signal thresholds at each stage and calculates the liquid level reliability through comprehensive analysis. This ensures that the system can immediately adjust and provide accurate liquid level information when the tank status changes, avoiding the risks caused by information lag or misjudgment in traditional systems, and improving the reliability and safety of detection. Through multi-level analysis of temperature, pressure, and liquid level signals, this system significantly reduces the probability of false alarms at high liquid levels, avoiding frequent interlock shutdowns caused by false alarms, thereby improving the stability and safety of the production process. In summary, this system not only improves the accuracy and reduces false alarms in liquid level detection but also dynamically adapts to changes in different environmental factors, greatly improving safety and production efficiency. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in 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 schematic diagram of the structure of the present invention. Detailed Implementation

[0017] This application will now be described with reference to the accompanying drawings.

[0018] like Figure 1 As shown, the external floating roof tank liquid limit fiber optic sensing detection system of the present invention specifically includes the following modules: The fiber optic sensing module is used to detect the refraction and absorption characteristics of light by the liquid to sense changes in liquid level and obtain the optical signal of the liquid level change. The photoelectric conversion module is used to receive the optical signal of liquid level change and convert the optical signal of liquid level change into electrical signal intensity data; The dynamic threshold adjustment module acquires the tank temperature data in real time, and calculates the reference electrical signal strength threshold at the current temperature by combining it with the electrical signal strength data and using a preset temperature drift compensation algorithm. The multi-parameter fusion analysis module acquires the internal pressure data of the storage tank in real time, and calculates the confidence level of the liquid level status by combining the reference electrical signal strength threshold at the current temperature and the electrical signal strength data through a preset fuzzy logic calculation model. The detection result acquisition module compares the liquid level status confidence level with the preset limit safety threshold to obtain the current liquid level detection result.

[0019] In this embodiment, temperature data is introduced through a dynamic threshold adjustment module and combined with a temperature drift compensation algorithm to correct signal deviations caused by temperature fluctuations in real time, ensuring accurate liquid level measurement under different ambient temperatures and responding to environmental changes in real time to ensure the accuracy of the liquid level signal. By introducing a multi-parameter fusion analysis module, combining pressure data inside the tank with the intensity of a reference electrical signal at real-time temperature, the accuracy of liquid level status judgment is enhanced, further eliminating errors that may arise from relying on a single signal and improving detection accuracy. A preset fuzzy logic calculation model is used to calculate the confidence level of the liquid level status, effectively handling ambiguity between different data and avoiding false alarms that may occur if the traditional method relies solely on simple threshold judgments. The fuzzy logic model, by comprehensively considering multiple aspects of information such as temperature, pressure, and liquid level signal, can adjust the liquid level signal according to different conditions. The system automatically adjusts its judgment criteria to more accurately determine the liquid level status and reduce false alarm rates. By acquiring real-time changes in temperature, pressure, and liquid level signals, the system dynamically adjusts signal thresholds at each stage and calculates liquid level reliability through comprehensive analysis. This ensures that the system can immediately adjust and provide accurate liquid level information when the tank status changes, avoiding the risks caused by information lag or misjudgment in traditional systems, thus improving the reliability and safety of detection. Furthermore, by integrating multi-level analysis of temperature, pressure, and liquid level signals, this system significantly reduces the probability of false alarms at high liquid levels, avoiding frequent interlock shutdowns caused by false alarms, thereby improving the stability and safety of the production process. In summary, this system not only improves accuracy and reduces false alarms in liquid level detection but also dynamically adapts to changes in different environmental factors, greatly enhancing safety and production efficiency.

[0020] In some embodiments of the present invention, the fiber optic sensing module is used to detect the refraction and absorption characteristics of light by the liquid to sense changes in liquid level and obtain a light signal of liquid level change. It includes at least one fiber optic sensor, which adopts a dual fiber optic probe structure; it uses a solderless quick-install bracket, the fiber optic sensor is fixed to the edge of the floating roof of the storage tank, the probe is vertically downward aligned with the liquid level detection area, and the bracket is equipped with a fine-tuning mechanism; The probe uses a side-by-side arrangement of transmitting and receiving optical fibers. The transmitting fiber directs the light beam emitted by the light source into the liquid in the storage tank, while the receiving fiber receives the light signal after it has been refracted and absorbed by the liquid. The probe tip is designed with a conical structure, which creates a gradually changing refraction angle in the liquid, enhancing the sensitivity to changes in liquid level. When the liquid level rises, the propagation path of the beam in the liquid becomes shorter, the refraction angle increases, and the light intensity received by the receiving fiber weakens. When the liquid level falls, the light intensity increases. A dual-wavelength light source is used to eliminate the influence of medium color and turbidity on the detection results by comparing the differences in light intensity attenuation at different wavelengths. The entire transmission from the light source to the receiver uses fiber optics to avoid the conduction of electrical signals within the explosion-proof area, completely eliminating the risk of lightning strikes and electrostatic sparks.

[0021] In this embodiment, the transmitting and receiving optical fibers are arranged side by side, which improves the propagation effect of the light beam in the liquid. The conical probe causes the light beam to form a gradually changing refraction angle in the liquid, thereby enhancing the sensitivity to changes in liquid level. When the liquid level rises, the light beam propagation path becomes shorter and the refraction angle increases, thus reducing the light intensity received by the receiving optical fiber. Conversely, when the liquid level falls, the light intensity increases, ensuring that liquid level fluctuations can be detected quickly and accurately. The use of dual-wavelength light sources effectively eliminates the interference of factors such as liquid color and turbidity on the detection results by comparing the differences in light intensity attenuation at different wavelengths. Even if the color or transparency of the liquid changes, The system can still measure the liquid level stably and accurately, greatly improving its reliability under various operating conditions. This fiber optic sensing module uses fiber optics to transmit signals throughout the process, completely avoiding the conduction of electrical signals within the storage tank. The fiber optic itself is non-energized, thus effectively eliminating the risk of lightning strikes and electrostatic sparks, ensuring the safety of the storage tank and the surrounding environment, and improving system safety. The use of a solderless quick-install bracket simplifies the installation process of the fiber optic sensor, and the fine-tuning mechanism on the bracket allows for easy adjustment of the probe position, ensuring that the probe is always accurately aligned with the liquid level detection area. This simplifies the installation and maintenance process, guaranteeing detection accuracy and stability.

[0022] In some embodiments of the present invention, a photoelectric conversion module is used to receive liquid level change optical signals and convert the liquid level change optical signals into electrical signal intensity data; The optical signal of liquid level change is transmitted to the photoelectric conversion module through optical fiber and enters the optical signal receiving end; the optical signal receiving end uses a PIN photodiode with wide wavelength response as the main photoelectric conversion element, combined with an optical window with filtering function to filter out background light interference in the environment. After the light signal received by the photodiode is converted into a current signal, the intensity of the current signal represents the change in liquid level. However, since the change in liquid level is small and may be affected by environmental factors such as external temperature, humidity, and liquid properties, the original current signal is relatively weak and may contain noise. Therefore, an automatic gain adjustment module is added to amplify the signal to ensure that the signal has sufficient intensity in subsequent processing. The automatic gain adjustment module adopts automatic gain control technology, which adjusts the amplifier gain in real time by monitoring the signal strength to adapt to changes in liquid level and environmental fluctuations; specifically, it analyzes the amplitude of the current signal in real time through a digital signal processor and adjusts the amplifier gain according to the preset target signal range. Noise suppression algorithms and filtering mechanisms are introduced. The noise suppression algorithm removes noise introduced by external factors such as ambient light and temperature fluctuations, ensuring that the received electrical signal is more stable and reliable. In addition, a high-frequency noise filtering device is added to the signal path to further improve the system's anti-interference capability. After gain adjustment and noise filtering, the electrical signal is converted into a digital signal by an analog-to-digital converter and transmitted to the downstream dynamic threshold adjustment module for processing.

[0023] In this embodiment, by using a PIN photodiode with a wide wavelength response and a filtered optical window, interference from ambient background light is effectively filtered out, ensuring that the received optical signal is more accurate and reliable. The automatic gain adjustment module adjusts the signal gain in real time through automatic gain control technology, effectively amplifying the weak current signal and ensuring sufficient signal strength in subsequent processing. The automatic gain adjustment module can monitor the signal strength in real time and automatically adjust the amplifier gain according to changes in liquid level and fluctuations in the external environment, ensuring that the system can work stably under different environmental conditions. By introducing noise suppression algorithms, digital filters, and high-frequency noise filtering devices, noise introduced by external factors can be effectively removed, further improving the clarity and stability of the signal. The electrical signal after gain adjustment and noise filtering is converted into a digital signal by an analog-to-digital converter and transmitted to the downstream dynamic threshold adjustment module for processing, ensuring that the final output signal is more accurate and stable.

[0024] In some embodiments of the present invention, for the dynamic threshold adjustment module, the tank temperature data is acquired in real time, and the reference electrical signal strength threshold at the current temperature is calculated by combining the electrical signal strength data with the preset temperature drift compensation algorithm. Obtain tank temperature data, including: Install a small temperature sensor on the fiber optic sensor probe to directly measure the temperature near the sensor. Place a corrosion-resistant temperature sensor in the liquid inside the storage tank to measure the actual liquid temperature; Install a temperature sensor inside the photoelectric signal conversion device to measure the operating temperature of the device. The temperature signal inside the tank is transmitted to the control room via optical fiber, while the temperature inside the equipment is transmitted wirelessly, avoiding the hassle of wiring. Take the average temperature of the three points to obtain a comprehensive temperature; When one sensor malfunctions, the system automatically uses the temperatures of the other two to calculate the value; the temperature data is updated every second; and it is directly transmitted to the dynamic threshold adjustment module to calculate the standard value at the current temperature. The formula for calculating the reference electrical signal strength threshold at the current temperature using a preset temperature drift compensation algorithm is as follows: Wherein, the T c T represents the threshold value after compensation. b The threshold value at the reference temperature is represented by α, which represents the temperature drift coefficient. The T value is... a The T represents the actual temperature. r Indicates the reference temperature.

[0025] In this embodiment, by installing multiple temperature sensors, comprehensive and real-time temperature data from different locations inside and outside the storage tank can be acquired, ensuring that the temperature compensation algorithm can dynamically adjust the liquid level detection threshold according to actual temperature changes. By setting multiple temperature sensors and calculating the average temperature, the system can automatically switch to data from other sensors for calculation when one sensor fails. This ensures that even if some sensors fail, accurate temperature data can still be provided continuously and stably, avoiding system paralysis or data distortion caused by temperature sensor failure. By using wireless transmission of internal temperature data, complex wiring work is avoided, effectively reducing wiring trouble and maintenance costs. Adjusting the electrical signal threshold based on temperature changes ensures that liquid level signals can be accurately detected under different temperature environments. When the actual temperature differs from the reference temperature, the system adjusts the threshold of electrical signal strength through compensation calculation, reducing liquid level misjudgments caused by temperature fluctuations, thereby improving the accuracy of liquid level detection and avoiding false alarms at high liquid levels. Real-time updates of temperature data and automatic adjustment of dynamic thresholds make the entire liquid level monitoring system more stable and reliable, maintaining efficient and accurate operation at all times.

[0026] In some embodiments of the present invention, for the multi-parameter fusion analysis module, the internal pressure data of the storage tank is acquired in real time, and the liquid level status confidence is calculated by combining the reference electrical signal strength threshold at the current temperature and the electrical signal strength data through a preset fuzzy logic calculation model. Real-time acquisition of internal pressure data of the storage tank is achieved by installing an intrinsically safe pressure sensor on the top of the storage tank. This sensor adopts an explosion-proof design, which can adapt to the explosion-proof environment of the storage tank area. It directly contacts the gas inside the tank to sense pressure changes. The pressure data is transmitted to the multi-parameter fusion analysis module through a dedicated signal line. The transmitted raw pressure data is preprocessed by continuously collecting multiple pressure data and taking the average value to eliminate the interference caused by instantaneous fluctuations and obtain a stable actual pressure value. Meanwhile, the reference electrical signal strength threshold at the current temperature is obtained from the dynamic threshold adjustment module, and real-time electrical signal strength data is obtained from the photoelectric conversion module. These three types of data are used as input parameters for the fuzzy logic calculation model. The preset fuzzy logic calculation model first fuzzifies the input parameters; for electrical signal strength data, the difference between it and the reference electrical signal strength threshold is divided into different fuzzy levels: significantly lower, slightly lower, close to, slightly higher, and significantly higher, with each level corresponding to a different signal state; for pressure data, according to the pressure range when the storage tank is operating normally, it is divided into fuzzy levels: too low, slightly low, normal, slightly high, and too high, reflecting different pressure conditions. A fuzzy rule base is established, which includes liquid level status judgment logic corresponding to different combinations of signal states and pressure conditions. When the electrical signal strength is slightly higher than the benchmark threshold and the pressure is normal, the corresponding liquid level status has a medium confidence level; when the electrical signal strength is significantly higher than the benchmark threshold and the pressure is high, the corresponding liquid level status has a very high confidence level. The fuzzy parameters of the input are inferred and calculated based on the fuzzy rule base to obtain the fuzzy result of the liquid level state; By defuzzing, the fuzzy results are converted into specific liquid level confidence values. The higher the value, the higher the confidence that the current liquid level has reached or exceeded the limit.

[0027] In this embodiment, combining pressure data and electrical signal strength data from inside the storage tank provides a more comprehensive reflection of the tank's liquid level status, thereby improving the accuracy and reliability of liquid level monitoring. By employing an intrinsically safe explosion-proof pressure sensor, reliable operation in explosion-proof environments is ensured, guaranteeing equipment safety, especially in hazardous applications. Preprocessing the pressure data by continuously collecting multiple data points and averaging them effectively eliminates interference from instantaneous fluctuations, making the pressure data more stable and improving the accuracy of liquid level assessment. Furthermore, fuzzification processing is applied to both the electrical signal strength and pressure data. By inferring liquid level status through a fuzzy rule base, the system can flexibly handle different signal combinations under various operating conditions, avoiding the rigid rule limitations of traditional judgment methods and improving the system's intelligence and responsiveness. Through defuzzification, the fuzzy results are converted into specific liquid level status confidence values, making the judgment of liquid level status more quantitative and enabling corresponding control measures to be taken based on the confidence values, thereby enhancing the system's real-time performance and decision support capabilities. This step, combined with the fusion analysis of multiple data sources, greatly improves the system's responsiveness and accuracy to changes in tank liquid level, thereby reducing safety hazards caused by misjudgments of liquid level.

[0028] In some embodiments of the present invention, for the detection result acquisition module, the liquid level status confidence level is compared with a preset limit safety threshold to obtain the current liquid level detection result; The factors influencing the setting of the preset limit safety threshold include: The inherent characteristics of the storage tank: The design parameters of the storage tank directly determine the basic range of the threshold. This includes the difference between the tank's maximum design liquid level and the actual liquid level it can hold. If there are protruding components such as pipelines or instruments on the top of the tank, their space must be included in the safety margin, and the threshold should be appropriately lowered. It also includes the type of floating roof structure. Double-deck floating roofs are more stable than single-deck ones, and liquid level fluctuations have less impact on the floating roof, so the threshold can be set closer to the maximum design liquid level. Single-deck floating roofs are more susceptible to medium fluctuations and require a larger safety margin, so the threshold needs to be appropriately lowered. In addition, the service life of the storage tank also affects the threshold. The tank walls of older storage tanks may have slight deformation, which can easily lead to deviations in liquid level measurement. The safety margin of the threshold needs to be increased to avoid the actual liquid level exceeding the limit due to deformation. Storage medium properties: The characteristics of the medium affect the stability of the liquid level detection signal, and thus the threshold setting. These include the viscosity and wall adhesion of the medium. High-viscosity media tend to adhere to the fiber optic probe, causing abnormal attenuation of the optical signal and resulting in a higher confidence level. If the conventional threshold setting is still used, it is easy to trigger false alarms. In this case, the threshold needs to be increased to filter out false signals. The volatility and density of the medium also play a role. Volatile media can form a large amount of oil-gas mixture in the tank, which may slightly affect the refractive properties of light, causing slight fluctuations in the electrical signal intensity. The threshold interval needs to be widened to avoid fluctuations triggering false alarms. The purity and impurity content of the medium also play a role. Media containing a large amount of suspended matter will absorb more optical signal, which may cause the confidence level to be lower than the actual liquid level. The threshold needs to be lowered to prevent missed alarms. Operating conditions and operational requirements: The actual operating scenarios and procedures of the storage tank determine that the threshold needs to have a certain degree of flexibility. This includes the feeding and discharging speeds. If the storage tank is often used for rapid feeding, the liquid level rises quickly, and the interlocking system requires a certain response time from alarm to pump shutdown, so the threshold needs to be set lower to allow sufficient emergency time. If the feeding is slow and the liquid level changes gradually, the threshold can be appropriately increased. It also includes the response capability of the interlocking system. If the interlocking pump shutdown and valve closing system of the storage tank reacts quickly, the threshold can be close to the design maximum liquid level. If the response speed is slow, the threshold needs to be significantly reduced to avoid tank overflow due to response delay. Detection system accuracy: The accuracy level of the detection system determines the error buffer space that needs to be reserved for the threshold. This includes the detection error of the fiber optic sensing module. If the liquid level detection error of the system is small, the threshold can be set more accurately. If the error is large, the safety margin of the threshold needs to be increased to avoid the actual liquid level exceeding the limit due to error. It also includes the compensation effect of the dynamic threshold adjustment module. If the temperature drift compensation algorithm can control the influence of temperature on the electrical signal, the threshold does not need to consider temperature interference too much. If the compensation effect is limited, the threshold interval needs to be increased to prevent false alarms caused by temperature fluctuations. The preset limit safety threshold is divided into two levels: warning threshold and over-limit threshold. The warning threshold is used to indicate that the liquid level is approaching the safety limit, and the over-limit threshold is used to determine that the liquid level has exceeded the safety limit. The system receives liquid level confidence data in real time from the multi-parameter fusion analysis module, with the receiving frequency matching the calculation and update frequency of the multi-parameter fusion analysis module, to ensure that the latest liquid level judgment criteria can be obtained in a timely manner. The system compares the real-time received liquid level confidence level with the warning threshold. If the liquid level confidence level is lower than the warning threshold, the current liquid level is determined to be in a safe state, and a liquid level safety detection result is generated. If the liquid level confidence level reaches or exceeds the warning threshold but is lower than the over-limit threshold, the current liquid level is determined to be in a warning state, and a liquid level warning detection result is generated, while triggering the system's warning prompt function. If the liquid level confidence level reaches or exceeds the over-limit threshold, the current liquid level is determined to be in an over-limit state, and a liquid level over-limit detection result is generated. In this case, in addition to issuing a strong alarm signal in the control room, the over-limit signal will also be transmitted to the interlock control system of the storage tank, triggering emergency measures such as interlock shutdown and closing the tank root valve to prevent liquid overflow from causing a safety accident. During the comparison process, in order to avoid false alarms caused by instantaneous fluctuations in the confidence level of the liquid level, a continuous judgment mechanism is set up. That is, only when the confidence level of the liquid level reaches or exceeds the corresponding threshold multiple times consecutively will the corresponding detection result be officially generated and subsequent operations be executed. At the same time, each liquid level detection result is automatically stored in the system's database.

[0029] In this embodiment, by comprehensively considering multiple factors such as the characteristics of the storage tank itself, the properties of the stored medium, operating conditions and operational requirements, and the accuracy of the detection system, a reasonable preset limit safety threshold is set. This effectively reduces false alarms or missed alarms caused by environmental factors and system errors, improving the accuracy of liquid level detection results. The threshold is dynamically adjusted according to different usage scenarios and medium characteristics of the storage tank, making the threshold setting more flexible. This not only improves the adaptability of liquid level monitoring but also optimizes the safety and efficiency of detection under different conditions. By monitoring the liquid level status in real time and comparing it with the set warning threshold and over-limit threshold, a warning signal is promptly issued when the liquid level approaches a dangerous level, and an interlocking system is quickly triggered to take emergency measures when the liquid level exceeds the limit, preventing liquid overflow or other safety accidents. By setting a continuous judgment mechanism, a detection result is generated and subsequent operations are executed only when the confidence level of the liquid level status reaches or exceeds the corresponding threshold multiple times consecutively. This avoids false alarms or missed alarms caused by instantaneous fluctuations in the liquid level status, improving the stability and accuracy of the system. This step, through the comprehensive consideration of multiple factors and intelligent judgment mechanisms, improves the accuracy, safety, and reliability of liquid level monitoring and the system.

[0030] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A fiber optic sensing and detection system for liquid limiting in an external floating roof tank, characterized in that, The application relates to a liquid level detection system, which comprises the following modules: a fiber sensing detection module for detecting the refraction and absorption characteristics of liquid to light to perceive liquid level changes and obtain liquid level change optical signals; a photoelectric conversion module for receiving the liquid level change optical signals and converting the liquid level change optical signals into electrical signal intensity data; a dynamic threshold adjustment module for obtaining tank temperature data in real time, combining the electrical signal intensity data, and calculating a reference electrical signal intensity threshold value at the current temperature through a preset temperature drift compensation algorithm; a multi-parameter fusion analysis module for obtaining tank internal pressure data in real time, combining the reference electrical signal intensity threshold value at the current temperature and the electrical signal intensity data, and calculating a liquid level state confidence through a preset fuzzy logic calculation model; a detection result acquisition module for comparing the liquid level state confidence with a preset limit safety threshold value to obtain a current liquid level detection result.

2. The liquid limiting optical fiber sensing detection system for external floating roof tank according to claim 1, characterized in that, The liquid level change optical signals are transmitted through optical fibers.

3. The liquid limiting optical fiber sensing detection system for external floating roof tank according to claim 1, characterized in that, The photoelectric conversion module further comprises a gain automatic adjustment module for amplifying the converted electrical signals.

4. The liquid limiting optical fiber sensing detection system for external floating roof tank according to claim 3, characterized in that, The photoelectric conversion module further comprises a noise suppression algorithm and a filtering mechanism for denoising and filtering the amplified electrical signals.

5. The liquid limiting optical fiber sensing detection system for external floating roof tank of claim 1, wherein, The formula for calculating the reference electrical signal intensity threshold value at the current temperature through the preset temperature drift compensation algorithm is as follows: Wherein, T c represents the compensated threshold value, T b represents the threshold value at the reference temperature, a represents the temperature drift coefficient, T a represents the actual temperature, and T r represents the reference temperature.

6. The liquid limiting optical fiber sensing detection system for external floating roof tank of claim 1, wherein, The multi-parameter fusion analysis module further comprises an intrinsically safe pressure sensor for collecting tank internal pressure data in real time.

7. The liquid limiting optical fiber sensing detection system for external floating roof tank of claim 1, wherein, The liquid level state confidence is calculated through the preset fuzzy logic calculation model, which comprises the following steps: The preset fuzzy logic calculation model performs fuzzy processing on input parameters; The fuzzy logic calculation model has a built-in fuzzy rule base, and the fuzzy rule base comprises liquid level state judgment logic corresponding to different signal states and pressure working condition combinations; The fuzzy rule base is used to infer and calculate the fuzzy parameters to obtain a fuzzy result of the liquid level state; The fuzzy result of the liquid level state is de-fuzzied to convert the fuzzy result into a liquid level state confidence value.

8. The liquid limiting optical fiber sensing detection system for external floating roof tank of claim 1, wherein, The setting factors of the preset limit safety threshold value include tank characteristics, storage medium properties, operation conditions, operation requirements and detection system accuracy.

9. The liquid limiting optical fiber sensing detection system for external floating roof tank according to claim 8, characterized in that, The preset limit safety threshold value comprises two levels of early warning threshold values and overrun threshold values.

10. The liquid limiting optical fiber sensing detection system for external floating roof tank of claim 1, wherein, The detection result acquisition module further comprises a continuous judgment mechanism, which generates corresponding detection results and performs subsequent operations only when the liquid level state confidence continuously reaches or exceeds the corresponding threshold value for multiple times.

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