Monitoring method for grounding body resistance of storage tank

Abstract

The invention provides a monitoring method of grounding body resistance of a storage tank. The monitoring method comprises the following steps: detecting a current signal I on a loop of a grounding body resistor in real time; de-noising processing is carried out on the current signal I; the actual resistance value R0 of the grounding body resistor is calculated based on the voltage E and the current signal I1, and the detected resistance change value delta R is equal to R0-R; r is an initial value of the grounding body resistance, and delta R is a label of a data set of the LSSVM prediction model; respectively collecting parameters corresponding to the environmental information of each grounding down lead to construct an environmental information database of each grounding down lead; building an LSSVM (least square support vector machine) model; dividing parameters corresponding to the environment information into a training set, a verification set and a test set according to a preset proportion; inputting the training set into the LSSVM model for iterative training, inputting the verification set into the LSSVM model after iterative training for optimization after iterative training is completed, and storing the final optimized model; inputting the test set into the final optimized model to obtain a predicted value of the change value delta R of the grounding body resistance; the real-time monitoring of the change of the grounding body resistance is jointly ensured through the real-time monitoring value of the grounding body resistance and the predicted value of the change value delta R of the grounding body resistance. According to the monitoring method for the grounding body resistance of the storage tank, the calculated real-time monitoring value of the grounding body resistance is more accurate, real-time on-line monitoring of the grounding body resistance of the storage tank can be achieved, the existing period of a grounding fault is effectively shortened, and more professional technical guidance is provided for lightning protection of the storage tank.

Description

Technical Field

[0001] The invention relates to the technical field of storage tank safety monitoring, and in particular to a storage tank grounding body resistance monitoring method. Background Art

[0002] For large crude oil storage tanks, lightning protection grounding is crucial. The grounding body plays an important role in the normal operation of the storage tank. By connecting the tank grounding down conductor to the grounding body, the storage tank can operate normally and stably, while ensuring the safety of equipment and operators. The outer shell of the storage tank is connected to the grounding body through the grounding down conductor, so that when lightning strikes, the current can be conducted to the earth through the grounding down conductor and the grounding body, preventing accidents caused by lightning strikes on the storage tank.

[0003] At present, the commonly used method for measuring the resistance of the tank grounding body is the clamp method, which uses a non-destructive method to apply a constant voltage to the grounding lead of a large tank, and then detect the current in the loop, and finally calculate the grounding resistance. However, time has shown that this method has defects such as obvious detection current noise and inaccurate resistance value calculation.

[0004] Therefore, we urgently need to develop a new tank grounding resistance monitoring method to solve the defects of the above-mentioned tank grounding resistance measurement method in the prior art. Summary of the invention

[0005] In order to overcome the shortcomings of the above-mentioned prior art, the present invention provides an online monitoring method for the grounding resistance of a storage tank, which can realize real-time online monitoring of the grounding resistance of the storage tank, effectively shorten the period of the grounding fault, and provide more professional technical guidance for the lightning protection of the storage tank.

[0006] Therefore, the purpose of the present invention is to provide a method for monitoring the grounding resistance of a storage tank.

[0007] In order to achieve the above-mentioned purpose, the technical solution of the present invention provides a method for monitoring the grounding body resistance of a storage tank. A constant voltage provider is provided on the loop of the grounding body resistance, and the constant voltage provider is used to generate a constant voltage E on the loop of the grounding body resistance, and the grounding body resistance is connected to a plurality of grounding down conductors. The monitoring method comprises: using a measuring unit to detect the current signal I on the loop of the grounding body resistance in real time; using a current signal denoising unit to denoise the current signal I to obtain a denoised current signal I1;

[0008] Based on the voltage E and the current signal I1, the actual resistance value R0 of the grounding body resistance is calculated, and the detected resistance change value ΔR=R0-R; R is the initial value of the grounding body resistance, and ΔR is the label of the data set of the LSSVM prediction model; through the environmental information acquisition unit, the parameters corresponding to the environmental information of each grounding down lead are respectively collected to construct the environmental information database of each grounding down lead; through the grounding body fault diagnosis and prediction module, the LSSVM model is built; the parameters corresponding to the environmental information are divided into a training set, a verification set and a test set according to a preset ratio; the training set is input into the LSSVM model for iterative training, and after the iterative training is completed, the verification set is input into the LSSVM model after iterative training for optimization, and the final optimized model is saved; the test set is input into the final optimized model to obtain the predicted value of the change value ΔR of the grounding body resistance; through the real-time monitoring value of the grounding body resistance and the predicted value of the change value ΔR of the grounding body resistance, the real-time monitoring of the change of the grounding body resistance is jointly ensured.

[0009] Preferably, the constant voltage provider is an excitation coil; the measuring unit includes a current detector and a grounding wire fixture; the current detector is an induction coil, which is used to detect the current signal I on the loop of the grounding body resistance in real time; and the excitation coil and the induction coil are fixed to the grounding wire through a grounding wire fixture.

[0010] Preferably, the current signal I is denoised based on a wavelet transform algorithm and a Kalman filter algorithm.

[0011] Preferably, the environmental information includes one of the following or a combination thereof: soil moisture content, soil resistivity, soil porosity, and soil sulfate and chloride ion content.

[0012] Beneficial effects of the present invention:

[0013] The present invention provides a method for monitoring the grounding resistance of a storage tank. The current signal I on the grounding resistance loop is detected in real time by a measuring unit. Since there is often noise in the signal detected by the measuring unit, the current signal I detected in real time cannot accurately reflect the real current of the grounding resistance loop, thereby affecting the calculation of the grounding resistance value. Therefore, the detected current signal I is denoised by a current signal denoising unit to obtain the denoised current signal I1. Further, based on the voltage E and the current signal I1, the actual resistance value R0 of the grounding resistance is calculated, and the detected resistance change value ΔR=R0-R; R is the initial value of the grounding resistance, and ΔR is the label of the data set of the LSSVM prediction model; specifically, based on Kirchhoff's current law, through the principle of magnetic field induction, an electric field is generated by a timing pulse, and the actual resistance value R0 of the grounding resistance is calculated by the detected current signal I: R0=E / I1, and the actual resistance value R0 of the grounding body is theoretically calculated by the grid method. Furthermore, the environmental information acquisition unit is used to collect parameters corresponding to the environmental information of each grounding down conductor to construct an environmental information database of each grounding down conductor, and then the grounding body fault diagnosis prediction module is used to build an LSSVM model, and then the parameters corresponding to the environmental information are divided into a training set, a validation set and a test set according to a preset ratio, and then the training set is input into the LSSVM model for iterative training. After the iterative training is completed, the validation set is input into the iteratively trained LSSVM model for optimization, and the final optimized model is saved. Then, the test set is input into the final optimized model to obtain the predicted value of the change value ΔR of the grounding body resistance, and the real-time monitoring value of the grounding body resistance and the predicted value of the change value ΔR of the grounding body resistance are used to ensure the real-time monitoring of the change of the grounding body resistance. Since R0 is the actual measured value of the resistance, the change value ΔR of the grounding body resistance is the label of the data set of the LSSVM prediction model. R0 is the actual resistance value detected, and ΔR is the predicted resistance change value, because theoretically R=R0-ΔR, where R is the initial value of the grounding body resistance. Therefore, the monitoring method of the ground body resistance of the storage tank of the present invention can not only detect the ground body resistance value, but also use the trained model to predict the ground body resistance, thereby realizing double insurance and further improving the accuracy of ground body resistance monitoring. At the same time, the monitoring method of the ground body resistance of the storage tank of the present invention takes into account that the parameters corresponding to the environmental information of each grounding down conductor may affect the resistance value change of the ground body resistance, so that the real-time monitoring value of the ground body resistance of the storage tank calculated by the monitoring method of the ground body resistance of the storage tank of the present invention is more accurate, and the real-time online monitoring of the ground body resistance of the storage tank can be realized, which effectively shortens the period of existence of the ground fault and provides more professional technical guidance for the lightning protection of the storage tank.

[0014] Additional aspects and advantages of the invention will become apparent from the following description, or may be learned by practice of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A schematic flow chart showing a method for monitoring ground body resistance of a storage tank according to an embodiment of the present invention;

[0016] Figure 2 A workflow diagram of an LSSVM model constructed by a ground fault diagnosis and prediction module according to an embodiment of the present invention is shown;

[0017] Figure 3 A schematic diagram showing the positional relationship between the excitation coil, the induction coil and the grounding wire of the storage tank according to an embodiment of the present invention is shown;

[0018] Figure 4 A schematic diagram showing a grounding body resistance loop and the current direction of the loop according to an embodiment of the present invention;

[0019] Figure 5 A schematic flow chart of performing denoising processing on a current signal I on a loop of ground body resistance monitored in real time according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0020] In order to more clearly understand the above-mentioned objects, features and advantages of the present invention, Figures 1 to 5 As shown, the present invention is further described in detail below in conjunction with the accompanying drawings and specific implementations. It should be noted that, in the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other.

[0021] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0022] Figure 1 A schematic flow chart of a method for monitoring the grounding resistance of a storage tank according to an embodiment of the present invention is shown. A constant voltage provider is provided on the grounding resistance loop, and the constant voltage provider is used to generate a constant voltage E on the grounding resistance loop, and the grounding resistance is connected to a plurality of grounding down conductors, and the constant voltage provider is an excitation coil; the measuring unit includes a current detector and a grounding wire fixture; Figure 1 As shown, the monitoring method includes:

[0023] Step 1: Install an excitation coil and a current detector (i.e., a current detection module) on the tank grounding wire; Figure 3As shown, the grounding flat steel is the grounding down conductor, which connects the tank body of the storage tank to the grounding grid; the current detector is an induction coil, which is used to detect the current signal I on the loop of the grounding body resistance in real time; and the excitation coil and the induction coil are fixed to the grounding wire through a grounding wire fixture;

[0024] Step 2: Using a measuring unit, real-time detection of a current signal I on the loop of the grounding body resistance;

[0025] Step 3: De-noising the detected current signal I by a current signal de-noising unit to obtain a de-noised current signal I1;

[0026] Step 4: Based on the voltage E and the current signal I1, the actual resistance value R0 of the ground body resistance is calculated; then the detected resistance change value ΔR=R0-R; R is the initial value of the ground body resistance, and ΔR is the label of the data set of the LSSVM prediction model;

[0027] Step 5: Collect parameters corresponding to the environmental information near each grounding down conductor through the environmental information collection unit to build an environmental information database for each grounding down conductor;

[0028] Step 6: Build the LSSVM model through the ground fault diagnosis and prediction module;

[0029] Step 7: Divide the parameters corresponding to the environmental information into a training set, a validation set, and a test set according to a preset ratio;

[0030] Step 8: Input the training set into the LSSVM model for iterative training. After the iterative training is completed, input the validation set into the LSSVM model after iterative training for optimization, and save the final optimized model;

[0031] Step 9: predicting the change value of the ground body resistance; specifically, inputting the test set into the finally optimized model to obtain the predicted value of the change value ΔR of the ground body resistance;

[0032] Step 10: Real-time monitoring of the change in grounding resistance is ensured by monitoring the real-time value of grounding resistance and predicting the change in grounding resistance ΔR.

[0033] In this embodiment, the monitoring method of the grounding body resistance of the storage tank of the present invention belongs to a real-time online detection method. Specifically, the monitoring method of the grounding body resistance of the storage tank provided by the present invention detects the current signal I on the loop of the grounding body resistance in real time through the measuring unit. Since there is often noise in the signal detected by the measuring unit, the current signal I detected in real time cannot accurately reflect the real current of the grounding body resistance loop, thereby affecting the calculation of the grounding body resistance value. Therefore, the detected current signal I is denoised by the current signal denoising unit to obtain the denoised current signal I1. Further, based on the voltage E and the current signal I1, the actual resistance value R0 of the grounding body resistance is calculated, and the detected resistance change value ΔR=R0-R; R is the initial value of the grounding body resistance, and ΔR is the label of the data set of the LSSVM prediction model; specifically, based on Kirchhoff's current law, through the principle of magnetic field induction, the electric field is generated by a timing pulse, and the actual resistance value R0 of the grounding body resistance is calculated by the detected current signal I: R0=E / I1, and the actual resistance value R0 of the grounding body is calculated by the grid method theory. Furthermore, the environmental information acquisition unit is used to collect parameters corresponding to the environmental information of each grounding down conductor to construct an environmental information database of each grounding down conductor, and then the grounding body fault diagnosis prediction module is used to build an LSSVM model, and then the parameters corresponding to the environmental information are divided into a training set, a validation set and a test set according to a preset ratio, and then the training set is input into the LSSVM model for iterative training. After the iterative training is completed, the validation set is input into the iteratively trained LSSVM model for optimization, and the final optimized model is saved. Then, the test set is input into the final optimized model to obtain the predicted value of the change value ΔR of the grounding body resistance, and the real-time monitoring value of the grounding body resistance and the predicted value of the change value ΔR of the grounding body resistance are used to ensure the real-time monitoring of the change of the grounding body resistance. Since R0 is the actual measured value of the resistance, the change value ΔR of the grounding body resistance is the label of the data set of the LSSVM prediction model. R0 is the actual resistance value detected, and ΔR is the predicted resistance change value, because theoretically R=R0-ΔR, where R is the initial value of the grounding body resistance. Therefore, the monitoring method of the ground body resistance of the storage tank of the present invention can not only detect the ground body resistance value, but also use the trained model to predict the ground body resistance, thereby realizing double insurance and further improving the accuracy of ground body resistance monitoring. At the same time, the monitoring method of the ground body resistance of the storage tank of the present invention takes into account that the parameters corresponding to the environmental information of each grounding down conductor may affect the resistance value change of the ground body resistance, so that the real-time monitoring value of the ground body resistance of the storage tank calculated by the monitoring method of the ground body resistance of the storage tank of the present invention is more accurate, and the real-time online monitoring of the ground body resistance of the storage tank can be realized, which effectively shortens the period of existence of the ground fault and provides more professional technical guidance for the lightning protection of the storage tank.In a specific embodiment, if the grounding body resistance is R3, the loop of the grounding body resistance R3 and the direction of the current in the loop are as follows. Figure 4 As shown, the grounding body resistor is connected to 5 grounding leads.

[0034] Furthermore, the specific process of building the LSSVM model for the grounding fault diagnosis and prediction module is described in detail. The bee colony genetic algorithm and the least squares support vector machine supervised learning algorithm (LSSVM) are integrated to construct the grounding fault diagnosis and prediction module. The function expression of the LSSVM model is:

[0035]

[0036] In formula (1), a i is represented by the Lagrange multiplier; b is represented by the bias term; j is represented by; K(x, x i ) is represented as kernel function; x is represented as sample; x i is represented as the value of the sample;

[0037] The parameters corresponding to the collected environmental information of each grounding down conductor are normalized:

[0038]

[0039] In formula (2), N represents the amount of data;

[0040] Specifically, the workflow of the LSSVM model built by the ground fault diagnosis and prediction module is as follows: Figure 2 As shown in the figure: the parameters (i.e., data samples) corresponding to the environmental information collected for each grounding down conductor are normalized; the LSSVM model is pre-trained on the training set (i.e., an LSSVM prediction model is established on the training set); the parameters of the LSSVM model are optimized; it is determined whether the number of iterations has been reached; when the judgment result is yes, the optimal parameters are output and the corresponding model is established for prediction.

[0041] In one embodiment of the present invention, the current signal I is denoised based on a wavelet transform algorithm and a Kalman filter algorithm.

[0042] In this embodiment, a current signal denoising unit is constructed by integrating a wavelet transform algorithm and a Kalman filter algorithm. Specifically: 1. Based on the wavelet transform algorithm, the current signal I is filtered to remove electromagnetic interference. The process of filtering out electromagnetic interference can be expressed as:

[0043]

[0044] In formula (4), a represents the scale, which is a parameter representing the frequency; b represents the parameter representing the time or spatial position; t represents the time; R represents a real number; ψ represents the wavelet basis function;

[0045] 2. Calculate the dynamic noise and observation noise based on the Kalman filter algorithm to filter out the Gaussian white noise in the current signal I. The process of filtering out the Gaussian white noise in the current signal I can be expressed as:

[0046] The Kalman filter time update equation is as follows:

[0047]

[0048] The Kalman filter state update equation is as follows:

[0049]

[0050] In formula (5), and Respectively represent the posterior state estimate at time k-1 and time k, which is one of the results of filtering, that is, the updated result, also called the optimal estimate (the estimated state, according to theory, we cannot know the exact result of the state at each moment, so it is called an estimate); represents the prior state estimate at time k, which is the intermediate calculation result of filtering, that is, the result at time k predicted based on the optimal estimate at the previous time (time k-1), which is the result of the prediction equation; P k-1 and P k Respectively represent the posterior estimated covariance (i.e., covariance, indicating the uncertainty of the state) at time k-1 and time k, which is one of the results of filtering; represents the prior estimated covariance at time k, which is the intermediate calculation result of filtering; H is the conversion matrix from state variables to measurements (observations), which represents the relationship connecting the state and observations. It is a linear relationship in Kalman filtering. It is responsible for converting the m-dimensional measurement value to the n-dimensional one to conform to the mathematical form of the state variable, which is one of the prerequisites for filtering; z k The measured value (observation value) is the input of the filter; K k represents the filter gain matrix, which is the intermediate calculation result of the filter, the Kalman gain, or the Kalman coefficient; A represents the state transfer matrix; Q represents the process excitation noise covariance (the covariance of the system process); R represents the measurement noise covariance; B represents the matrix that converts the input into the state; Represents the residual between the actual observation and the predicted observation, and together with the Kalman gain, corrects the prior (prediction) to obtain the posterior. In this embodiment, the specific process of denoising the current signal I based on the wavelet transform algorithm and the Kalman filter algorithm is introduced below. Figure 5As shown, filtering begins, firstly, the detection data is brought into the wavelet transform; the decomposition layer number is set to 1, the reconstructed signal is obtained, and the signal-to-noise ratio is calculated; the detection data is subjected to n-layer wavelet decomposition and reconstruction; the signal-to-noise ratio SNR(n) is calculated respectively; it is determined whether the signal-to-noise ratio SNR(n) is less than or equal to the signal-to-noise ratio SNR(n-1); when the judgment result is yes, the optimal decomposition layer number is determined, and the detection data is reconstructed; the reconstructed data is substituted into the adaptive Kalman filter algorithm to determine the dynamic noise and the observation noise; the detection data is subjected to secondary filtering to obtain the final data. That is, the denoising process of the current signal I in this implementation is based on the signal-to-noise ratio and other indicators to obtain the optimal decomposition layer number, and then filter out the noise in the signal. In one embodiment of the present invention, the environmental information includes one of the following or a combination thereof: soil moisture content, soil resistivity, soil porosity, soil sulfate and chloride ion content.

[0051] In this embodiment, we collect environmental information near each grounding down conductor, that is, the environmental information includes one or a combination of the following: soil moisture content, soil resistivity, soil porosity, soil sulfate and chloride ion content, so as to construct an environmental information database of each grounding down conductor. The information of the environmental information database in the specific embodiment is shown in the following table:

[0052]

[0053] We selected these factors for the following reasons:

[0054] The influence of soil moisture content on soil corrosion is specifically reflected in the following aspects: First of all, the influence of moisture content is the conductivity of soil. When the moisture content in the soil is low and the salt content in the soil is also low, the resistance of the soil will be relatively large; conversely, the soil resistance will present a smaller value. At the same time, the moisture content will also affect the oxygen content of the soil. Studies have found that when the soil moisture content gradually increases from a low level, the corrosion rate of metals in the soil will also increase accordingly. When the soil moisture content increases to a critical value, the metal corrosion rate will no longer continue to increase, but will gradually decrease with the increase of moisture content.

[0055] Furthermore, the effect of soil resistivity on metal corrosion is more complex, and there is no direct correspondence between the two. Combined with soil environmental analysis, in most cases, for metals in a moderately alkaline soil environment, the corrosion rate will increase with the increase of resistivity.

[0056] Furthermore, soil porosity is used to characterize the state of gas circulation in the soil. There are gaps between soil particles, and the air contained in them is also an important component of the soil. In addition to nitrogen and oxygen, the air components in the soil also include other gases such as water vapor. Among these gas components, oxygen is an important substance involved in the redox reaction during the electrochemical corrosion of the soil. Therefore, the aeration of the soil directly affects the oxygen content in the soil, which in turn affects the corrosion of metals in the soil. At the same time, the relationship between aeration and soil corrosion is also relatively complex, and there is no simple correspondence between the two.

[0057] Furthermore, the salt in the soil will participate in the process of electrochemical corrosion, and the salt content will also have an important impact on the resistivity of the soil. Therefore, the salt content is an important factor affecting metal corrosion in the soil. The soil usually contains many types of salts, among which cationic salts have a very weak effect on metal corrosion in the soil, while the content of SO42- (i.e. soil sulfate) and Cl- (i.e. chloride ion) and other anions have a more significant effect on metal corrosion.

[0058] In one embodiment of the present invention, the actual resistance value of the grounding body resistor R0=R1||R2||R3||...|R n (The resistors are connected in parallel). If n is larger (the more grounding points there are), the R0 value is closer to 0. From an engineering perspective, R0 can be regarded as the grounding resistance value of the entire grounding system.

[0059] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for monitoring the grounding resistance of a storage tank, wherein a constant voltage provider is provided on the loop of the grounding resistance, the constant voltage provider is used to generate a constant voltage E on the loop of the grounding resistance, and the grounding resistance is connected to a plurality of grounding down conductors, characterized in that: The monitoring method comprises: The current signal I on the grounding body resistance loop is detected in real time by a measuring unit; The current signal I is subjected to denoising processing by a current signal denoising unit to obtain a denoised current signal I1; Based on the voltage E and the current signal I1, the actual resistance value R0 of the ground body resistance is calculated, and the detected resistance change value ΔR=R0-R; R is the initial value of the ground body resistance, and ΔR is the label of the data set of the LSSVM prediction model; The environmental information collection unit collects parameters corresponding to the environmental information of each grounding down conductor to construct an environmental information database of each grounding down conductor; Through the ground fault diagnosis and prediction module, the LSSVM model is built; Dividing the parameters corresponding to the environmental information into a training set, a validation set, and a test set according to a preset ratio; The training set is input into the LSSVM model for iterative training. After the iterative training is completed, the validation set is input into the LSSVM model after iterative training for optimization, and the final optimized model is saved; Inputting the test set into the finally optimized model to obtain a predicted value of the change value ΔR of the ground body resistance; The real-time monitoring of the change of the grounding body resistance is ensured by the real-time monitoring value of the grounding body resistance and the predicted value of the change value ΔR of the grounding body resistance.

2. The method for monitoring the grounding resistance of a storage tank according to claim 1, characterized in that: The constant voltage provider is an excitation coil; the measuring unit includes a current detector and a grounding wire fixture; the current detector is an induction coil, which is used to detect the current signal I on the loop of the grounding body resistance in real time; and the excitation coil and the induction coil are fixed to the grounding wire through a grounding wire fixture.

3. The method for monitoring the grounding resistance of a storage tank according to claim 1, characterized in that: Based on the wavelet transform algorithm and the Kalman filter algorithm, the current signal I is denoised.

4. The method for monitoring the grounding resistance of a storage tank according to claim 1, characterized in that: The environmental information includes one of the following or a combination thereof: soil moisture content, soil resistivity, soil porosity, and soil sulfate and chloride ion content.

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