Explosion-proof tank meter control system

Abstract

The present application belongs to the technical field of tank metering, and relates to an anti-explosion tank metering instrument control system. The present application constructs a temperature distribution matrix by collecting tank temperature time sequence signals, extracts dominant modal components based on material thermal expansion characteristics; adopts dynamic time sequence alignment technology to couple liquid level signals and deformation modal, and calculates deformation interference strength value in combination with structural damping characteristics; generates liquid level compensation displacement instructions based on energy-displacement mapping relationship, and drives an intrinsic safety compensation motor to adjust the reference position of the liquid level sensor. The system effectively solves the problem of liquid level measurement error caused by thermal expansion deformation of the tank due to temperature change, realizes high-precision automatic compensation of liquid level measurement, significantly improves the accuracy and reliability of anti-explosion tank metering, and is particularly suitable for high-precision liquid level measurement requirements in flammable and explosive environments.

Description

Technical Field

[0001] This invention belongs to the field of storage tank metering technology and relates to a control system for explosion-proof storage tank metering instruments. Background Technology

[0002] In high-risk industrial sectors such as chemical and petroleum, storage tanks, as core equipment for media storage, directly impact production safety, economic efficiency, and environmental compliance through their accurate level measurement. Because many stored media are flammable and explosive, tank metering equipment must meet stringent explosion-proof requirements to ensure inherent safety and continuous, stable operation in the area.

[0003] Although existing explosion-proof tank metering instruments meet basic explosion-proof safety requirements in terms of structure and electrical system, they still face a long-standing technical problem: the dynamic deformation of the tank caused by non-uniform temperature changes due to environmental or process conditions will directly interfere with the liquid level measurement benchmark, thereby introducing measurement errors that are difficult to identify and correct in the explosion-proof area.

[0004] Existing liquid level measurement systems generally focus on safety aspects such as explosion-proof isolation and spark protection for sensors and circuits. For handling temperature effects, simplified static or single-point compensation strategies are commonly employed. However, this approach has significant drawbacks in real-world explosion-proof industrial scenarios: firstly, the explosion-proof enclosure or isolation device not only alters the local heat conduction path, but its thermal shielding effect also creates monitoring blind spots. This means that internal single-point temperature sensors cannot fully perceive the spatial distribution of the thermal field on the tank's outer wall, nor can they capture the true structural deformation characteristics, ultimately leading to a distorted assessment of the overall deformation state.

[0005] On the other hand, the isolation and protection structure required for explosion protection makes the transmission link between temperature signal and liquid level measurement signal longer and more complex. Static compensation cannot cope with the dynamic phase difference and coupling relationship between the two, and is prone to problems such as incorrect compensation timing or inaccurate compensation amount.

[0006] Although existing technical solutions attempt to optimize compensation by increasing intrinsically safe temperature monitoring points or improving signal sampling frequency, they fail to overcome the fundamental contradiction between the energy constraints of explosion-proof systems and the requirements for compensation accuracy. Furthermore, simple data post-processing methods perform poorly in the face of dynamic thermal fields, failing to identify phase differences in the thermal response of different areas of the tank, and thus still cannot fundamentally solve the aforementioned measurement error problems. Summary of the Invention

[0007] In view of this, in order to solve the problems mentioned in the background technology, an explosion-proof storage tank metering instrument control system is proposed.

[0008] The objective of this invention can be achieved through the following technical solution: an explosion-proof storage tank metering instrument control system, comprising: a thermal field construction module: acquiring the temperature time-series signal of the storage tank and constructing a temperature distribution matrix according to the spatial coordinate distribution of the sensors.

[0009] Modal extraction module: Based on the thermal expansion characteristics of the tank material, the dominant modal components are extracted from the temperature distribution matrix through principal component analysis.

[0010] Signal coupling module: Receives the liquid level timing signal from the liquid level sensor, aligns it with the dominant modal component in time, and calculates the deformation interference intensity value in combination with the structural damping characteristics.

[0011] The calibration execution module generates a liquid level compensation displacement command based on the deformation interference intensity value through the energy-displacement mapping relationship, drives the intrinsically safe compensation motor to adjust the reference position of the liquid level sensor, and outputs the calibrated liquid level measurement value.

[0012] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention constructs a temperature field by deploying a distributed intrinsically safe temperature sensor array and uses principal component analysis to extract the dominant modal components of thermally induced deformation. This method transforms the global and complex temperature distribution into a few key deformation modes for tracking, thereby solving the problem of distorted perception and inaccurate judgment of the dynamic deformation state of the tank, and realizing accurate identification and quantitative characterization of the source of structural thermal interference.

[0013] (2) This invention performs dynamic timing alignment and coupling analysis between the liquid level signal and each dominant modal component. This method fully considers the lag and phase difference in signal transmission under the influence of the explosion-proof enclosure, and achieves accurate matching of the liquid level measurement signal and the actual deformation interference signal on the time axis under different heat conduction paths and isolation structures, thereby solving the problems of incorrect compensation timing and inaccurate compensation amount caused by signal asynchrony.

[0014] (3) This invention combines structural damping characteristics to dynamically calculate the deformation interference intensity value and generates physical compensation commands based on the principle of energy balance. This method transforms abstract signal correlation into mechanical displacement actions that conform to physical laws and are proportional to the real-time interference intensity, thereby solving the defect of insufficient adaptability of simple static or single-point compensation models in dynamically changing thermal fields and realizing online real-time tracking and cancellation of dynamic, multimodal thermal deformation. 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 schematic diagram showing the connections of each module in the explosion-proof storage tank metering control system of the present invention.

[0017] Figure 2 This is a flowchart of the method for generating the dominant modal components in this invention.

[0018] Figure 3 This is a flowchart illustrating the specific method for timing alignment of the signal coupling module in this invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Please see Figure 1 As shown, the present invention provides a control system for an explosion-proof storage tank metering instrument, including: a thermal field construction module, a modal extraction module, a signal coupling module, and a calibration execution module. The connection relationship between the modules is as follows: the thermal field construction module and the modal extraction module are connected, the modal extraction module and the signal coupling module are connected, and the signal coupling module and the calibration execution module are connected.

[0021] Thermal field construction module: Collects the temperature time-series signal of the storage tank and constructs a temperature distribution matrix according to the spatial coordinate distribution of the sensors.

[0022] Considering that when explosion-proof storage tanks are operating in flammable and explosive hazardous locations, the heat conduction path of the tank body is easily affected by the explosion-proof isolation structure, and the temperature changes in the mechanical deformation sensitive area and the critical heat conduction path are directly related to the deformation state of the tank body, conventional single-point temperature acquisition cannot fully reflect the spatial distribution of the thermal field. Therefore, temperature signals are acquired and preprocessed through distributed acquisition.

[0023] In one specific embodiment, the method for acquiring the temperature timing signal is as follows: the original temperature timing signal is collected in real time by an intrinsically safe distributed temperature sensor array deployed in mechanical deformation sensitive areas of the storage tank, such as welds and support parts, as well as key heat conduction paths of the tank body, such as the junction of the sunlit side and the shaded area. The signal is transmitted to the processing unit via an intrinsically safe isolation circuit to ensure explosion-proof safety.

[0024] The original temperature timing signal is filtered by a low-pass filter circuit to remove electromagnetic interference noise. The sensor output signal is then calibrated at zero and full scale using a standard temperature calibration source to obtain the temperature timing signal after noise and system error elimination.

[0025] Subsequently, based on the known spatial coordinate distribution of all sensors on the surface of the tank, the temperature values ​​collected by each sensor are arranged according to their installation spatial coordinates to construct a three-dimensional temperature distribution matrix.

[0026] Modal extraction module: Based on the thermal expansion characteristics of the tank material, the dominant modal components are extracted from the temperature distribution matrix through principal component analysis.

[0027] Because the temperature data collected by the distributed temperature sensor array on the surface of the storage tank are highly correlated in both spatial and temporal dimensions, the temperature change trends of adjacent measuring points are similar, and the temperature field changes follow a specific spatial pattern due to the inherent physical characteristics of the tank structure, the temperature distribution matrix contains a lot of redundant information. If it is directly used for deformation analysis, it will increase the computational complexity, especially when computational resources are limited in an explosion-proof environment.

[0028] The thermal expansion characteristics of the tank material determine the nonlinear mapping relationship between temperature change and structural deformation. That is, the temperature gradient is transformed into local strain through the material's thermal expansion coefficient, and then superimposed under structural constraints to form an overall deformation mode.

[0029] Of these deformation modes, only a few low-order modes have a significant impact on the liquid level measurement benchmark, while high-order modes contribute little but are computationally expensive. Therefore, by converting the temperature distribution matrix into a thermal strain spatiotemporal matrix based on the coefficient of thermal expansion, and then using principal component analysis to extract eigenvectors with high energy contribution rates, the dominant modal components that play a decisive role in the deformation of the storage tank can be identified.

[0030] Please see Figure 2 As shown, in one specific embodiment, the method for generating the dominant modal component is as follows: based on the thermal expansion coefficient of the tank material, the temperature change at each spatial coordinate point in the temperature distribution matrix is ​​converted into the corresponding thermal strain value, thereby generating a thermal strain spatiotemporal matrix.

[0031] Principal component analysis is performed on the thermal strain spatiotemporal matrix to obtain eigenvectors and their corresponding eigenvalues. The cumulative contribution rate of the eigenvalues ​​is calculated, and the first K eigenvectors whose cumulative contribution rate exceeds a preset threshold for the first time are selected as the dominant mode components.

[0032] The specific implementation of principal component analysis includes: standardizing the thermal strain spatiotemporal matrix, that is, subtracting the mean of the thermal strain sequence at each spatial coordinate point and dividing by its standard deviation to obtain the standardized matrix, calculating the covariance matrix of the standardized matrix, solving its eigenvalues ​​and eigenvectors, and normalizing each eigenvector to make its magnitude 1.

[0033] Arrange the eigenvalues ​​in descending order and adjust the order of the corresponding eigenvectors to form an ordered sequence of eigenvalues ​​and a set of their corresponding ordered eigenvectors.

[0034] The variance contribution rate of each principal component is calculated based on the ordered eigenvalue sequence, where the variance contribution rate is the ratio of a single eigenvalue to the sum of all eigenvalues.

[0035] The variance contribution rate is accumulated in descending order of eigenvalues ​​to obtain the cumulative contribution rate sequence corresponding to the number of principal components.

[0036] Select the position index corresponding to the first cumulative contribution rate exceeding the preset threshold from the cumulative contribution rate sequence, and record this position index as the target principal component number.

[0037] Specifically, the preset threshold is obtained by selecting historical temperature field data, calculating the cumulative contribution rate sequence of its principal components, and plotting the change curve. This curve usually rises rapidly and then flattens out. The cumulative contribution rate value corresponding to the inflection point of the curve (i.e., the point of maximum curvature) is set as the preset threshold, with a typical value range of 85% to 95%.

[0038] The set of the top K ordered feature vectors of the target principal components is defined as the principal component feature vector subset, where K is a positive integer.

[0039] The standardized matrix is ​​multiplied by a subset of principal component eigenvectors, and each column of the resulting projection coefficient matrix corresponds to the time evolution sequence of a dominant mode component.

[0040] Signal coupling module: Receives the liquid level timing signal from the liquid level sensor, aligns it with the dominant modal component in time, and calculates the deformation interference intensity value in combination with the structural damping characteristics.

[0041] Because the explosion-proof isolation structure of the storage tank changes the heat conduction path, and the material thickness, heat capacity and external environmental conditions of different areas of the tank are different, the response process of temperature change propagation to structural deformation is non-uniform in time and space. Therefore, there may be a phase difference between the liquid level timing signal and the time dimension of the dominant mode component.

[0042] Direct coupling analysis can lead to a distortion of the correlation between deformation and liquid level changes due to time misalignment, making it impossible to accurately identify the dynamic interference of thermal deformation on liquid level measurement, thus resulting in inaccurate quantification of deformation interference.

[0043] Meanwhile, because the damping characteristics of the storage tank structure dynamically evolve with factors such as material aging or temperature changes, the energy of thermally induced deformation is partially dissipated during propagation. This manifests as a decrease in the amplitude of the deformation response and a further lag in phase. Thermal disturbances of different frequencies are damped to varying degrees, with high-frequency disturbances being significantly suppressed while low-frequency disturbances are relatively preserved. This nonlinear attenuation characteristic causes a deviation between deformation predictions based solely on the temperature field and the actual displacement. Therefore, it is necessary to calculate the disturbance intensity by combining time-series alignment with damping characteristics.

[0044] Please see Figure 3 As shown, in one specific embodiment, the specific method for timing alignment in the signal coupling module includes: acquiring the temperature change rate of the outer wall of the storage tank through a distributed temperature sensor array, and dynamically adjusting the length of the timing analysis window used for peak comparison according to the magnitude of the temperature change rate.

[0045] The specific method for dynamic adjustment is as follows: based on the temperature sampling sequence output by the distributed temperature sensor array within a continuous time window, the sign of temperature change between adjacent sampling points is calculated.

[0046] When N consecutive temperature change signs are all positive, it is determined that the rate of temperature change is increasing, and the baseline length of the time series analysis window is shortened according to the preset reduction factor.

[0047] Where N is an integer from 3 to 5, the preset reduction factor is a coefficient factor of 0.85 to 0.95. This coefficient factor decreases linearly with the increase of the rate of temperature change. The specific acquisition process is as follows: based on the sum of the absolute values ​​of the temperature differences of the current N temperature sampling points, the ratio is calculated with the reference temperature change recorded during the initial operation of the system. When the ratio is greater than 1, the reduction factor decreases proportionally. For every increase of 0.5 in the ratio, the reduction factor decreases by 0.02 until the lower limit of 0.85 is reached.

[0048] When N consecutive temperature change signs are all negative, it is determined that the rate of temperature change is decreasing, and the baseline length of the time series analysis window is increased by a preset extension factor.

[0049] The preset extension factor is a coefficient factor of 1.05~1.15. This coefficient factor increases linearly as the rate of temperature change decreases. The specific acquisition process is as follows: calculate the sum of the absolute values ​​of the temperature differences of the current N temperature sampling points, and calculate the ratio with the reference temperature change recorded during the initial operation of the system. When the ratio is less than 1, the extension factor increases proportionally. For every 0.3 decrease in the ratio, the extension factor increases by 0.02 until it reaches the upper limit of 1.15.

[0050] The reference temperature change is calculated by continuously collecting temperature data for 10 minutes under a stable ambient temperature and then calculating the average change as the value.

[0051] It should be noted that when the temperature change sign alternates within M consecutive sampling points, the baseline length of the time series analysis window remains unchanged, where M is an integer greater than N.

[0052] Within the adjusted time series analysis window, the peak position of the liquid level time series signal is compared with the peak position of each dominant mode component using time coordinates, and the time difference between the two is calculated as the time offset corresponding to that dominant mode component.

[0053] The specific method for obtaining the time offset is as follows: a peak detection algorithm based on the sliding cross-correlation function is used to search for the time point corresponding to the maximum correlation coefficient between the liquid level time series signal and each dominant modal component within a window, and this time point is defined as the peak position. In specific implementation, the sliding window step size is set to an integer multiple of the sampling period, and the cross-correlation calculation is accelerated using Fast Fourier Transform (FFT).

[0054] When multiple peaks exist within a single window, the most significant peak with an amplitude exceeding 30% of the signal peak value is selected for comparison, and a weighted average method is used to integrate the time offsets of multiple peaks.

[0055] The weighted average method works as follows: For significant peaks within the window whose amplitude exceeds 30% of the signal peak value, the ratio of their amplitude to the signal peak value is calculated as a weighting coefficient. The time offset corresponding to each peak is multiplied by its weighting coefficient, summed, and then divided by the sum of the weighting coefficients to obtain the weighted average time offset. When the number of valid peaks exceeds 5, cluster analysis is used to group similar peaks, and a representative peak from each group is selected for calculation to avoid outlier interference.

[0056] The liquid level timing signal is shifted along the time axis according to each time offset, so that the peak position of the liquid level timing signal is aligned with the peak position of the dominant mode component on the time coordinate. The shifting operation uses linear interpolation or spline interpolation methods to reconstruct the signal.

[0057] Furthermore, the method for generating the deformation interference intensity value is as follows: differential calculation is performed on the time-aligned liquid level time-series signal to obtain the liquid level change rate. The differential calculation employs a center-difference format and is combined with low-pass filtering.

[0058] The maximum deformation displacement value of each dominant modal component at the corresponding moment after time alignment is extracted from the thermal strain spatiotemporal matrix as the deformation response amplitude.

[0059] The specific method for obtaining the maximum deformation displacement value is as follows: First, a spherical region with a radius of 1 / 10 of the tank diameter and centered on the liquid level sensor installation point is determined. Within this region, a local maximum search is performed on the deformation displacement field of each dominant modal component. If multiple local maxima exist within the region, the displacement value corresponding to the maximum point closest to the liquid level sensor is taken. If there are no significant maxima within the region, the weighted average value of the deformation displacement in this region is used, with the weight determined by the distance from the liquid level sensor, and the closer the distance, the greater the weight.

[0060] The initial correlation value is obtained by multiplying the rate of liquid level change by the amplitude of each deformation response. This product operation quantifies the energy coupling strength between dynamic liquid level change and structural deformation.

[0061] Based on the structural damping ratio of the tank material, a numerical reduction operation is performed on the initial correlation value to obtain the corrected correlation value.

[0062] Specifically, the numerical reduction operation involves multiplying the initial correlation value by a damping attenuation coefficient between 0 and 1. This damping attenuation coefficient is positively correlated with the structural damping ratio. The larger the structural damping ratio, the smaller the corresponding damping attenuation coefficient, and the greater the reduction in the initial correlation value. The damping attenuation coefficient can be obtained through a lookup table, which pre-establishes a mapping relationship from material type and structural damping ratio to specific attenuation coefficients.

[0063] The contribution priority of each dominant mode component is determined based on the duration of overlap between the liquid level timing signal waveform and the waveforms of each dominant mode component above a predetermined amplitude threshold after timing alignment. The longer the overlap duration, the higher the contribution priority.

[0064] The amplitude threshold is set to 25% to 35% of the peak value of each signal. The specific method for determining the contribution priority of each dominant mode component is as follows: calculate the percentage of the overlap duration of each dominant mode component to the sum of the overlap durations of all dominant mode components, and use this percentage value as the contribution priority weight of that dominant mode component.

[0065] For each dominant mode component, its corrected correlation value is multiplied by the corresponding contribution priority weight to obtain the interference intensity sub-value of that dominant mode component. The contribution priority weight is normalized to ensure that the sum of the weights of all dominant mode components is 1.

[0066] The interference intensity sub-values ​​of all dominant modal components are summed to generate a deformation interference intensity value, which comprehensively reflects the degree of dynamic interference of the tank's thermal deformation on the liquid level measurement.

[0067] In engineering implementation, considering the energy limitations of the explosion-proof area, the above calculation process is performed in an intrinsically safe signal processing unit, using a low-power optimization algorithm.

[0068] The calibration execution module generates a liquid level compensation displacement command based on the deformation interference intensity value through the energy-displacement mapping relationship, drives the intrinsically safe compensation motor to adjust the reference position of the liquid level sensor, and outputs the calibrated liquid level measurement value.

[0069] Considering that the deformation interference intensity value directly reflects the degree of interference of thermal deformation on the liquid level measurement reference, it is necessary to convert it into an executable compensation action to eliminate or reduce the measurement error introduced by thermal deformation.

[0070] In one specific embodiment, the method for generating the liquid level compensation displacement command is as follows: based on the principle of energy balance, the deformation interference intensity value is converted into thermo-mechanical interference energy acting on the tank structure.

[0071] The transformation method is implemented using a linear scaling function, specifically as follows: ,in, This represents the deformation interference intensity value. For thermo-mechanical disturbance energy, scaling factor and offset The determination was made through calibration experiments. The calibration method was as follows: under known and controllable thermal load conditions, the sequence of deformation disturbance intensity values ​​calculated by the system was recorded, and the actual thermo-mechanical energy input to the structural region near the sensor installation position was measured and calculated simultaneously using a high-precision strain gauge and displacement sensor. Finally, the result was determined through linear regression fitting.

[0072] Establish a mapping relationship between the thermo-mechanical interference energy and the sensor displacement compensation required to offset the measurement deviation caused by the energy.

[0073] Subsequently, based on the thermo-mechanical disturbance energy converted from the deformation disturbance intensity value at the current moment, the liquid level compensation displacement command is obtained through the mapping relationship.

[0074] Furthermore, the mapping relationship construction method is as follows: based on the geometric structure of the storage tank, such as the generatrix of the cylindrical tank body, the circumferential weld, the support area, etc., and the results of the finite element simulation analysis of heat conduction, select M (M≥3) representative calibration points on the outer surface of the storage tank.

[0075] Simulated thermal loads of known magnitude are applied at each calibration point. After each specific load is applied and the thermal state stabilizes, a high-precision displacement measuring device is used to accurately measure the actual deformation generated at the reference position of the liquid level sensor. Through this process, multiple sets of corresponding data on applied energy and measured deformation are obtained.

[0076] Based on the simulated thermal load and the measured actual deformation, the least squares method is used to fit the curve of the correspondence between the simulated thermal load energy and the measured deformation of the liquid level sensor installation point. Then, the deformation is negative to obtain the corresponding displacement compensation amount, thus finally constructing the mapping relationship between the thermal-mechanical interference energy and the displacement compensation amount.

[0077] Furthermore, the generation of the liquid level compensation displacement command is achieved through a dedicated signal processing circuit, which includes: receiving the deformation interference intensity value and converting the deformation interference intensity value into a voltage signal characterizing the thermo-mechanical interference energy based on the energy balance principle.

[0078] The specific conversion method of the voltage signal is as follows: the deformation interference intensity signal is converted into a voltage signal by a differential amplifier, and the adjustable resistor network corresponding to the geometric parameters, thermal parameters and structural damping parameters of the storage tank is multiplied to output the thermo-mechanical interference energy voltage signal.

[0079] The system stores the mapping relationship between thermo-mechanical interference energy and liquid level sensor displacement compensation amount constructed using the above method. Based on the input voltage signal, the system calculates and outputs the corresponding target displacement compensation amount through table lookup or interpolation. This can be implemented using a digital signal processor or a dedicated lookup table circuit.

[0080] The target displacement compensation amount is converted into the motor drive pulse width. Specifically, a voltage-controlled oscillator and a counter are used to convert the voltage amplitude corresponding to the target displacement compensation amount into the number of pulses within a fixed period, and then convert it into the motor drive pulse width through a preset ratio.

[0081] A PWM control signal is generated based on the motor drive pulse width. After being optocoupled and isolated, the PWM signal drives the H-bridge power circuit to control the compensated motor to operate at the matched power. The H-bridge circuit has a current feedback protection mechanism to prevent motor overload.

[0082] The compensation motor is an explosion-proof stepper motor equipped with a power failure braking device to ensure that the current position is maintained in the event of a power failure and to output liquid level compensation displacement commands.

[0083] In practical engineering implementation, the dedicated signal processing circuit adopts an intrinsically safe design, and all power supplies are subject to intrinsically safe gate current and voltage limiting.

[0084] In one specific embodiment, the method for obtaining the corrected liquid level measurement value is as follows: drive the compensation motor to run according to the liquid level compensation displacement command, and physically change the installation reference position of the liquid level sensor through a precision ball screw transmission mechanism.

[0085] The displacement feedback signal of the transmission mechanism is acquired in real time, and the cumulative adjustment amount of the reference position is calculated. The original liquid level signal measured by the liquid level sensor at the adjusted reference position is acquired synchronously, and the original liquid level signal is algebraically superimposed with the cumulative adjustment amount of the reference position to calculate the corrected liquid level value.

[0086] Specifically, when the compensation motor adjusts upward, the cumulative adjustment amount of the reference position is positive, and the corrected liquid level value = original liquid level signal + cumulative adjustment amount of the reference position; when the compensation motor adjusts downward, the cumulative adjustment amount of the reference position is negative, and the corrected liquid level value = original liquid level signal + cumulative adjustment amount of the reference position.

[0087] The calibrated liquid level value is then subjected to explosion-proof isolation and signal formatting, and the final liquid level measurement value is output.

[0088] In summary, this invention acquires distributed temperature time-series signals on the surface of the storage tank through a thermal field construction module and constructs a temperature distribution matrix; the modal extraction module converts the temperature data into thermal strain values ​​based on the thermal expansion characteristics of the material, and extracts the dominant modal components characterizing structural deformation through principal component analysis.

[0089] The signal coupling module dynamically aligns the timing of the liquid level signal with the dominant modal component, adaptively adjusts the analysis window based on the rate of temperature change, and calculates the deformation interference intensity value considering the structural damping characteristics. The correction execution module, based on the energy balance principle, converts the interference intensity into thermo-mechanical interference energy, generates precise compensation commands through the energy-displacement mapping relationship, drives the intrinsically safe compensation motor to adjust the reference position of the liquid level sensor in real time, and finally outputs a high-precision corrected liquid level value with explosion-proof isolation.

[0090] While meeting inherent safety requirements, the entire system achieves accurate identification and real-time compensation for thermally induced dynamic deformation of storage tanks, improving the reliability and accuracy of liquid level measurement in flammable and explosive hazardous locations.

[0091] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0092] Those skilled in the art will recognize that the algorithmic steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0093] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0094] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0095] Finally, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A metering control system for explosion-proof storage tanks, characterized in that, include: Thermal field construction module: Collects the temperature time-series signal of the storage tank and constructs a temperature distribution matrix according to the spatial coordinate distribution of the sensors; the acquisition of the temperature time-series signal includes real-time acquisition of the raw temperature time-series signal through a distributed temperature sensor array deployed in the mechanical deformation sensitive area and the key path of heat conduction of the tank. Modal extraction module: Based on the thermal expansion characteristics of the storage tank material, the dominant modal components are extracted from the temperature distribution matrix through principal component analysis; Signal coupling module: Receives the liquid level timing signal from the liquid level sensor, aligns it with the dominant modal component in time, and calculates the deformation interference intensity value in combination with the structural damping characteristics; The specific methods for timing alignment in the signal coupling module include: The rate of temperature change on the outer wall of the storage tank is obtained by a distributed temperature sensor array; The length of the time-series analysis window used for peak comparison is dynamically adjusted according to the magnitude of the temperature change rate. Within the adjusted time series analysis window, the peak position of the liquid level time series signal is compared with the peak position of each dominant mode component using time coordinates, and the time difference between the two is calculated as the time offset corresponding to that mode component. The liquid level timing signal is shifted along the time axis according to each time offset, so that the peak position of the liquid level timing signal is aligned with the peak position of the dominant mode component on the time coordinate. The method for generating the deformation interference intensity value is as follows: Differential calculation is performed on the time-aligned liquid level time signal to obtain the liquid level change rate; The maximum deformation displacement value of each dominant modal component at the corresponding moment after time alignment is extracted from the thermal strain spatiotemporal matrix as the deformation response amplitude. The initial correlation value is obtained by multiplying the rate of change of liquid level by the amplitude of each deformation response; Based on the structural damping ratio of the tank material, a numerical reduction operation is performed on the initial correlation value to obtain the corrected correlation value; Based on the duration of overlap between the liquid level timing signal waveform and the waveforms of each dominant mode component above a predetermined amplitude threshold after timing alignment, the contribution priority of each dominant mode component is determined. The longer the overlap duration, the higher the contribution priority. For each dominant mode component, its corrected correlation value is multiplied by the corresponding contribution priority weight to obtain the interference intensity sub-value of that mode component; The interference intensity sub-values ​​of all dominant modal components are summed to generate the deformation interference intensity value; The calibration execution module generates a liquid level compensation displacement command based on the deformation interference intensity value through the energy-displacement mapping relationship, drives the intrinsically safe compensation motor to adjust the reference position of the liquid level sensor, and outputs the calibrated liquid level measurement value.

2. The explosion-proof storage tank metering instrument control system as described in claim 1, characterized in that, The method for obtaining the temperature time-series signal further includes: The distributed temperature sensor array uses intrinsically safe sensors and transmits signals to the thermal field construction module through an intrinsically safe isolation circuit; The original temperature time series signal is then subjected to noise filtering and temperature calibration preprocessing to obtain the temperature time series signal.

3. The explosion-proof storage tank metering instrument control system as described in claim 1, characterized in that, The method for generating the dominant modal components is as follows: Based on the thermal expansion coefficient of the tank material, the temperature change at each spatial coordinate point in the temperature distribution matrix is ​​converted into the corresponding thermal strain value, thus generating a thermal strain spatiotemporal matrix. Principal component analysis was performed on the thermal strain spatiotemporal matrix to obtain the eigenvectors and their corresponding eigenvalues; Calculate the cumulative contribution rate of the feature values, and select the K feature vectors whose cumulative contribution rate first exceeds the preset threshold as the dominant modal components, where K is a positive integer.

4. The explosion-proof storage tank metering instrument control system as described in claim 1, characterized in that, The specific method for dynamically adjusting the length of the time-series analysis window used for peak alignment includes: Based on the temperature sampling sequence output by the distributed temperature sensor array within a continuous time window, the sign of temperature change between adjacent sampling points is calculated. When N consecutive temperature change signs are all positive, it is determined that the rate of temperature change is increasing, and the baseline length of the time series analysis window is shortened by a preset reduction factor. When N consecutive temperature change signs are all negative, it is determined that the rate of temperature change is decreasing, and the baseline length of the time series analysis window is increased by a preset extension factor, where N is an integer.

5. The explosion-proof storage tank metering instrument control system as described in claim 1, characterized in that, The method for generating the liquid level compensation displacement command is as follows: Based on the principle of energy balance, the deformation interference intensity value is converted into thermo-mechanical interference energy acting on the tank structure, and a mapping relationship is established between the thermo-mechanical interference energy and the sensor displacement compensation amount required to offset the measurement deviation caused by the energy. Based on the thermo-mechanical disturbance energy converted from the deformation disturbance intensity value at the current moment, the liquid level compensation displacement command is obtained through the mapping relationship.

6. The explosion-proof storage tank metering instrument control system as described in claim 5, characterized in that, The method for constructing the mapping relationship is as follows: Multiple calibration points are selected on the surface of the storage tank, and a simulated thermal load of known magnitude is applied at each calibration point, while the actual deformation at the installation location of the liquid level sensor is measured. Based on the correspondence between simulated thermal load and measured actual deformation, a functional relationship between thermo-mechanical disturbance energy and actual deformation is established through curve fitting. By taking negative values ​​for the deformation variables in the aforementioned functional relationship, the mapping relationship between thermo-mechanical disturbance energy and displacement compensation amount is obtained.

7. The explosion-proof storage tank metering instrument control system as described in claim 6, characterized in that, The generation of the liquid level compensation displacement command is achieved through a dedicated signal processing circuit, which includes: The deformation interference intensity value is received and converted into a voltage signal characterizing the thermo-mechanical interference energy based on the energy balance principle. It stores the mapping relationship between thermo-mechanical interference energy and liquid level sensor displacement compensation amount. Based on the input voltage signal, it calculates the corresponding target displacement compensation amount by looking up a table or interpolation. Convert the target displacement compensation amount into the motor drive pulse width; A PWM control signal is generated based on the motor drive pulse width to drive the compensation motor to operate at the matched power and output liquid level compensation displacement command.

8. The explosion-proof storage tank metering instrument control system as described in claim 1, characterized in that, The method for obtaining the corrected liquid level measurement value is as follows: The compensation motor is driven to run according to the liquid level compensation displacement command, and the installation reference position of the liquid level sensor is physically changed through the transmission mechanism. The displacement feedback signal of the transmission mechanism is acquired in real time, and the cumulative adjustment of the reference position is calculated. The original liquid level signal measured by the liquid level sensor at the adjusted reference position is acquired synchronously; The original liquid level signal is algebraically superimposed with the cumulative adjustment amount of the reference position to calculate the corrected liquid level value. The calibrated liquid level value is then subjected to explosion-proof isolation and signal formatting, and the final liquid level measurement value is output.

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