CN114777698A - Oil storage tank corrosion detection method and system - Google Patents
Oil storage tank corrosion detection method and system Download PDFInfo
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- CN114777698A CN114777698A CN202210705581.3A CN202210705581A CN114777698A CN 114777698 A CN114777698 A CN 114777698A CN 202210705581 A CN202210705581 A CN 202210705581A CN 114777698 A CN114777698 A CN 114777698A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B17/00—Measuring arrangements characterised by the use of infrasonic, sonic or ultrasonic vibrations
- G01B17/02—Measuring arrangements characterised by the use of infrasonic, sonic or ultrasonic vibrations for measuring thickness
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
Abstract
The invention relates to the technical field of data processing, in particular to a method and a system for detecting corrosion of an oil storage tank, wherein the method comprises the following steps: acquiring the thickness of each area at the bottom of the oil storage tank; quantifying all thicknesses into a plurality of thickness grades, constructing a first thickness matrix, and obtaining a first corrosion degree; constructing a second thickness matrix in each calculation direction to obtain a second corrosion degree; further acquiring the comprehensive corrosion degree of the tank bottom; performing thickness detection once every preset time period to obtain corresponding thickness distribution, calculating the difference between the thickness distributions of two adjacent thickness detections, and calculating the corrosion rate according to a plurality of differences; and acquiring a risk index according to the comprehensive corrosion degree, the difference and the corrosion rate so as to evaluate the corrosion leakage risk of the oil storage tank. The embodiment of the invention can realize the nondestructive detection of the thickness of the bottom of the in-service oil storage tank, and can perform accurate risk assessment on the corrosion condition of the bottom of the oil storage tank, thereby avoiding potential safety hazards.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a method and a system for detecting corrosion of an oil storage tank.
Background
The oil storage tank is widely applied to the fields of petroleum, chemical industry, national defense, transportation and the like, and is special production and storage equipment with high risk. The oil storage tank bears flammable and explosive raw materials, which brings great challenges to the safe use of the oil tank, and in addition, most of the oil tank use sites are severe, and a series of problems such as corrosion leakage and the like of the oil tank cannot be avoided. The bottom of the oil storage tank is extremely easy to damage and difficult to detect, if leakage or damage occurs, a great safety accident can be caused, and the life and property safety of people is threatened, so that the detection of the corrosion defect of the steel plate at the bottom of the oil storage tank is the key for judging whether the oil storage tank has safety problems.
At present, the nondestructive detection of the bottom of the oil storage tank is mainly carried out by using a penetration detection method, a magnetic particle detection method and other penetration detection methods which cannot detect internal defects, the magnetic particle detection method is not suitable for the detection of the bottom of the oil storage tank in service, and can only detect ferromagnetic material workpieces and cannot be suitable for the detection of the bottom of the oil storage tank made of all materials.
Disclosure of Invention
In order to solve the above technical problems, the present invention aims to provide a method and a system for detecting corrosion of an oil storage tank, wherein the adopted technical scheme is as follows:
in a first aspect, an embodiment of the present invention provides a method for detecting corrosion of an oil storage tank, the method including the steps of:
dividing the tank bottom of the oil storage tank into areas, and detecting the thickness of the central point of each area based on ultrasonic waves to obtain the thickness of each area;
quantifying all thicknesses into a plurality of thickness grades, and constructing a first thickness matrix by taking the thickness grades as a vertical coordinate and taking the number of mutually adjacent areas as a horizontal coordinate; calculating a large-area low-thickness factor of the first thickness matrix as a first corrosion degree;
for each calculation direction, constructing a second thickness matrix by taking the thickness grade as a vertical coordinate and taking the run length as a horizontal coordinate; calculating the long-run low-thickness factor of each second thickness matrix, and taking the maximum long-run low-thickness factor as a second corrosion degree; taking the product of the first corrosion degree and the second corrosion degree as the comprehensive corrosion degree of the tank bottom;
performing thickness detection once every preset time period, fitting the thickness grades of all the regions by using a Gaussian mixture model during each thickness detection to obtain corresponding thickness distribution, calculating the difference between the thickness distributions of two adjacent thickness detections, and calculating the corrosion rate according to a plurality of differences;
and acquiring a risk index according to the comprehensive corrosion degree, the difference and the corrosion rate so as to evaluate the corrosion leakage risk of the oil storage tank.
Preferably, the thickness detection of the center point of each region based on the ultrasonic wave further includes the following steps:
denoising an echo signal of ultrasonic detection, extracting a peak point of the denoised ultrasonic echo signal, and calculating the thickness of each region by combining the thickness of the ultrasonic wave.
Preferably, the method for calculating the thickness of each region includes:
and acquiring the thickness of each region according to the wave speed of the ultrasonic waves and the time corresponding to the peak point.
Preferably, all thicknesses are quantified as a plurality of thickness classes, including:
the factory-leaving thickness of the bottom of the oil storage tank is uniformly divided into a plurality of grades, and the detected thickness of each area is quantized according to the corresponding grade to obtain the thickness grade of each area after quantization.
Preferably, the calculation method of the large-area low thickness factor comprises the following steps:
and processing each element according to the number of rows and columns of each element in the first thickness matrix, summing all the processed elements to obtain a first element sum, summing all the elements in the first thickness matrix to obtain a second element sum, and taking the normalization result of the ratio of the first element sum to the second element sum as the large-area low-thickness factor.
Preferably, the calculation method of the long-run low-thickness factor comprises the following steps:
and for the second thickness matrix in each calculation direction, processing each element according to the row number and the column number of each element in the second thickness matrix, summing all the processed elements to obtain a third element sum, summing all the elements in the second thickness matrix to obtain a fourth element sum, and taking the normalization result of the ratio of the third element sum to the fourth element sum as the long-run low-thickness factor.
Preferably, the method for obtaining the thickness distribution comprises the following steps:
and taking the proportion of the number of the regions corresponding to each thickness grade in all the regions as the probability of the thickness grade, and fitting all the thickness grades and the corresponding probabilities by using a Gaussian mixture model to obtain a fitting result as the thickness distribution.
Preferably, the calculating the difference between the thickness distribution of two adjacent thickness tests comprises
And calculating the relative entropy between the thickness distributions of two adjacent thickness detections, and symmetrically deforming the relative entropy to obtain the difference between the two thickness distributions.
Preferably, the method for acquiring the risk indicator includes:
and acquiring the comprehensive corrosion degree of the last thickness detection corresponding to the corrosion rate and the difference between the last two thickness detections, and acquiring the risk index by combining the corrosion rate.
In a second aspect, another embodiment of the present invention provides a corrosion detection system for a storage tank, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the corrosion detection method for a storage tank when executing the computer program.
The embodiment of the invention at least has the following beneficial effects:
the thickness detection is carried out on the bottom of the oil storage tank in different areas, then the thickness of each area is analyzed, the comprehensive corrosion degree is obtained, the difference between the thickness detection in different time is obtained through fitting thickness distribution, the corrosion rate is further obtained, and the corrosion risk of the bottom of the oil storage tank is evaluated based on the comprehensive corrosion degree, the difference and the corrosion rate. The invention can scan the bottom of the in-service oil storage tank one by one, realize the nondestructive detection of the thickness of the bottom of the in-service oil storage tank, carry out accurate risk assessment on the corrosion condition of the bottom of the oil storage tank and avoid potential safety hazards.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions and advantages of the prior art, the drawings used in the embodiments or the description of the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart illustrating steps of a method for detecting corrosion of an oil storage tank according to an embodiment of the present invention.
Detailed Description
To further illustrate the technical means and effects of the present invention adopted to achieve the predetermined objects, the following detailed description will be given of a corrosion detection method and system for an oil storage tank according to the present invention, and the detailed implementation, structure, features and effects thereof with reference to the accompanying drawings and preferred embodiments. In the following description, the different references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The following describes a specific scheme of the method and system for detecting corrosion of an oil storage tank provided by the present invention in detail with reference to the accompanying drawings.
Referring to fig. 1, a flow chart illustrating steps of a method for detecting corrosion of an oil storage tank according to an embodiment of the present invention is shown, the method including the steps of:
and S001, performing area division on the tank bottom of the oil storage tank, and performing thickness detection on the central point of each area based on ultrasonic waves to obtain the thickness of each area.
The method comprises the following specific steps:
1. and performing area division on the bottom of the oil storage tank, and performing thickness detection on the central point of each area based on ultrasonic waves.
The method comprises the following steps of dividing the bottom of an oil storage tank into a plurality of regions with the same size according to actual conditions, and detecting the thickness of the central point of each region by a common ultrasonic-based detection method: pulse reflection method, diffraction time difference method, resonance method, transmission method, and the like.
The ultrasonic wave diffraction time difference method is suitable for detecting defects and welding seams in a detected workpiece, the ultrasonic wave penetration method needs to respectively place ultrasonic emission probes and ultrasonic receiving probes on the front surface and the back surface of the detected workpiece, and the detection scene of the invention is tank bottom detection of an in-service storage tank, and the probes cannot be placed on the tank bottom.
The ultrasonic thickness measurement based on the resonance method has very high measurement precision, but is very harsh to the detection scene, the upper surface and the lower surface of the detected workpiece are required to be parallel, smooth and tidy, otherwise, the thickness of the detected workpiece is difficult to measure.
For the detection of the storage tank in service, a large amount of oil sludge is stored in the tank, and if the cleaning is not clean, the detection result has larger error. Based on the analysis, the thickness measurement of the tank bottom by the pulse reflection method is reasonable.
As an example, an embodiment of the present invention employs an Olympus piezoelectric ultrasound probe with a center frequency of 10M to transmit and receive pulsed signals, the probe being 9mm in diameter. And a Tektronix MDO 4054C type digital oscilloscope is used for signal display and acquisition, and the acquisition frequency is 2.5 GHz. The probe is coupled with the tank bottom by adding a coupling agent, so that ultrasonic waves can enter a detected area.
2. Denoising an echo signal of ultrasonic detection, extracting a peak point of the denoised ultrasonic echo signal, and calculating the thickness of each region by combining the thickness of the ultrasonic wave.
In the actual detection of ultrasonic scanning of the steel plate at the bottom of the oil storage tank, noise pollution often exists in the acquired information. Due to the existence of the position where the oil sludge is not thoroughly cleaned, the intensity of echo signals is weak, noise pollution may annihilate the echo signals with small signal intensity, certain errors and even defect misjudgment are inevitably brought to the detection result of the storage tank under the condition, and in order to improve the accuracy of the detection result of the storage tank, the echo signals of ultrasonic detection need to be denoised.
As an example, the embodiment of the present invention employs a wavelet analysis method to perform ultrasonic signal denoising, extracts an envelope and a peak point in a denoised ultrasonic echo signal by using hilbert transform, and performs signal feature extraction by extracting the envelope, so that the peak point can be found more accurately, quickly, and intuitively.
And acquiring the thickness of each region according to the wave speed of the ultrasonic waves and the time corresponding to the peak point.
The pulse reflection type thickness measuring principle is that the thickness of a workpiece is obtained by measuring the time of once-round propagation of ultrasonic waves between the upper bottom surface and the lower bottom surface of the workpiece, and the calculation formula is as follows:
wherein
The thickness of the bottom of the tank in the detected area;
is the speed of the ultrasonic waves in the tank bottom;
the ultrasonic wave at the peak point has a round trip time once inside the can bottom.
Step S002, quantizing all thicknesses into a plurality of thickness grades, taking the thickness grades as a vertical coordinate, taking the number of mutually adjacent areas as a horizontal coordinate, and constructing a first thickness matrix; the first degree of erosion is calculated by calculating a large area low thickness factor of the first thickness matrix.
The method comprises the following specific steps:
1. all thicknesses were quantified as a number of thickness classes.
The delivery thickness of the bottom of the oil storage tank is evenly divided into
And quantizing the detected thickness of each region according to the corresponding grade to obtain the thickness grade of each region after quantization.
As an example of this, it is possible to provide,in the embodiment of the invention, the factory thickness of the bottom of the oil storage tank is uniformly divided into 16 grades, namely
。
2. A first thickness matrix is constructed.
Constructing a first thickness matrix by using the thickness grade as a vertical coordinate and the number of mutually adjacent areas as a horizontal coordinate
Value of each element in the matrix
The number of the combined regions is j, which corresponds to the thickness rank i and is adjacent to each other. The number of matrix lines is the total thickness
The number of columns is the maximum number of adjacent regions
。
For example, if the number of the mutually adjacent combined regions having a thickness level of 1 is 3, the value of the element in the third column of the first row of the matrix is 5; the number of combined regions of 4 adjacent to each other with a thickness level of 2 is 6, and the element value of the fourth column of the second row of the matrix is 6.
3. A large-area low-thickness factor of the first thickness matrix is calculated as a first degree of erosion.
And processing each element according to the number of rows and columns of each element in the first thickness matrix, summing all the processed elements to form a first element sum, summing all the elements in the first thickness matrix to form a second element sum, and taking the normalized result of the ratio of the first element sum to the second element sum as a large-area low-thickness factor.
The corrosion can lead to the thickness attenuation of tank bottom, if the area of the thinner region of tank bottom is bigger, the degree of corrosion of tank bottom just is darker, therefore calculate the low thickness factor in big region:
wherein, the first and the second end of the pipe are connected with each other,
a large area low thickness factor, i.e., a first degree of erosion, representing a first thickness matrix.
Each element is multiplied by the square of the column number, divided by the square of the row number, and summed to obtain the first element sum
Summing all elements of the first thickness matrix to obtain a second element sum
Since the number of columns is the maximum number of areas adjacent to each other, the normalization of the ratio of the first element sum to the second element sum is achieved by multiplying the ratio by the inverse of the square of the number of columns of the first thickness matrix.
The large-area low-thickness factor is used to measure the size area of the low-thickness area, and the larger the value, the larger the area of the low-thickness area, i.e. the more severe the corrosion of the bottom of the oil tank.
Step S003, regarding each calculation direction, constructing a second thickness matrix by taking the thickness grade as a vertical coordinate and the run length as a horizontal coordinate; calculating the long-run low-thickness factor of each second thickness matrix, and taking the maximum long-run low-thickness factor as a second corrosion degree; and taking the product of the first corrosion degree and the second corrosion degree as the comprehensive corrosion degree of the tank bottom.
The method comprises the following specific steps:
1. a second thickness matrix is constructed in each calculation direction.
Thickness grade is used as ordinate, run length is used as abscissa, and in each calculation direction
In the above, corresponding second thickness matrix is constructed
In the embodiment of the present invention, the first and second substrates,
take 0 degrees, 45 degrees, 90 degrees and 135 degrees.
Taking the 0 degree direction as an example, the run length corresponding to each thickness level in this direction, i.e. the longest continuous area number of each thickness level in the 0 degree direction, is obtained. Value of each element in the matrix
The number of runlengths n corresponding to a thickness level m. Number of rows of matrix as total thickness grade
The number of columns being the maximum run length
。
For example, if the number of 4 regions having a run length of the order of thickness 1 is 3, the element value of the fourth column of the first row of the matrix is 3. The number of 7 regions of a run length of thickness level 3 is 2 and the element value of the third row and the seventh column of the matrix is 2.
2. A long-run low thickness factor is calculated for each second thickness matrix.
And for the second thickness matrix in each calculation direction, processing each element according to the number of rows and columns of each element in the second thickness matrix, summing all the processed elements to form a third element sum, summing all the elements in the second thickness matrix to form a fourth element sum, and taking the normalization result of the ratio of the third element sum to the fourth element sum as a long-run low-thickness factor.
The corrosion will cause the thickness of the bottom of the oil storage tank to become thin, the thinner the bottom of the oil storage tank is, the longer the length of the area is, the deeper the corrosion degree of the bottom of the oil storage tank is, thus calculating the long-run low-thickness factor:
wherein the content of the first and second substances,
is shown in the calculation direction
Long run low thickness factor.
Each element is multiplied by the square of the column number, divided by the square of the row number, and summed to obtain a third element sum
Summing all elements of the second thickness matrix to obtain a fourth element sum
Since the number of columns is the maximum run length
The normalization of the ratio of the third element sum to the fourth element sum is thus achieved by multiplying the ratio by the inverse of the square of the number of columns of the second thickness matrix.
The long run low thickness factor is used to measure the length of the low thickness zone, and a larger value indicates a greater length of the low thickness zone, indicating a greater degree of corrosion at the bottom of the storage tank.
3. Selecting the largest long-run low-thickness factor as the second corrosion degree
And taking the product of the first corrosion degree and the second corrosion degree as the comprehensive corrosion degree of the tank bottom.
Evaluating the comprehensive corrosion degree of the bottom of the oil storage tank:
wherein, the first and the second end of the pipe are connected with each other,
indicating the general degree of corrosion.
The greater the value of the combined corrosion degree Z, the more severe the corrosion degree of the bottom of the oil storage tank.
And S004, performing thickness detection once every other preset time period, fitting the thickness grades of all the areas by using a Gaussian mixture model during each thickness detection to obtain corresponding thickness distribution, calculating the difference between the thickness distributions of two adjacent thickness detections, and calculating the corrosion rate according to a plurality of differences.
The method comprises the following specific steps:
1. and performing Gaussian mixture model fitting on the result of each thickness detection to obtain corresponding thickness distribution.
And taking the proportion of the number of the regions corresponding to each thickness grade in all the regions as the probability of the thickness grade, and fitting all the thickness grades and the corresponding probabilities by using a Gaussian mixture model to obtain a fitting result as thickness distribution.
The Gaussian mixture model refers to a linear combination of a plurality of Gaussian distribution functions, theoretically, the Gaussian mixture model can fit any type of distribution and is usually used for solving the problem that data under the same set contain a plurality of different distributions.
Taking the proportion of the number of the regions corresponding to each thickness grade in all the regions as the probability p of the thickness grade, and assuming that the thickness grade is a random variable X, the mixed gaussian model can be represented by the following formula:
wherein, the first and the second end of the pipe are connected with each other,
the number of components of the mixed Gaussian model, namely the number of contained sub-Gaussian models;
representing the kth component
The weight of (a) is calculated,
；
for the k-th component in the mixture model,
indicating the expectation of the k-th component,
representing the variance of the kth component.
In the embodiment of the invention, the number K of the sub-Gaussian models is 5, and then the parameters of the Gaussian mixture model are solved by using an EM (effective electromagnetic) algorithm
Until the parameters converge or the log-likelihood function converges.
Substituting the parameters obtained by solving into the Gaussian mixture model
In (3), a thickness-level Gaussian mixture model is obtained as the thickness distribution.
2. And calculating the difference between the thickness distribution of two adjacent thickness detections.
And performing thickness detection once every preset time period, calculating the relative entropy between the thickness distributions of two adjacent thickness detections, and performing symmetric deformation on the relative entropy to obtain the difference between the two thickness distributions.
The K-L divergence, also called relative entropy, is a method for describing the difference between two probability distributions, and the embodiment of the invention describes the difference between two thickness detections by using the relative entropy between the thickness distributions of two adjacent thickness detections:
wherein the content of the first and second substances,
represents the K-L divergence between the two thickness distributions, i.e., the relative entropy;
the thickness distribution obtained by one thickness detection is shown,
representing the thickness distribution obtained by another thickness detection;
representing a total thickness rating of 16.
Since the K-L divergence does not satisfy symmetry, i.e.
Since the calculation result is affected by the sequential change, symmetric deformation is performed, and JS divergence is used to represent the difference:
wherein the content of the first and second substances,
showing the thickness distribution
And thickness distribution
JS divergence, i.e. variability, between;
indicating the thickness distribution
And thickness distribution
The K-L divergence between the two,
indicating the thickness distribution
And thickness distribution
The K-L divergence between.
The bottom corrosion of the tank can cause the bottom thickness value of the oil storage tank to change, so that the Gaussian mixture model measured in the previous and subsequent two times can change, the thickness distribution detected in the adjacent two times can also generate difference, and the difference is larger, which shows that the thickness value change is larger, and the bottom corrosion rate of the oil storage tank is larger.
As another example, to solve the problem of K-L divergence asymmetry, the difference can also be used
And
represents:
wherein the content of the first and second substances,
indicating the difference.
3. The corrosion rate is calculated from the plurality of differences.
In the embodiment of the invention, four thickness measurements are averagely carried out on the bottom of the oil storage tank within one month, namely the preset time period is one week, the thickness measurements are carried out every other week to obtain four thickness distributions, one difference exists between the thickness distributions obtained by every two adjacent thickness measurements to obtain three differences, and the difference between the first thickness measurement and the second thickness measurement is recorded as
The difference between the second and third thickness measurements is recorded as
The difference between the third and fourth thickness measurements is recorded as
And acquiring the corrosion rate according to the difference:
wherein, B represents the corrosion rate of the alloy,
is a very small number but not 0.
Adding at the denominator
In order to avoid the case where the denominator is 0, as an example, in the embodiment of the present invention
。
And S005, acquiring a risk index according to the comprehensive corrosion degree, the difference and the corrosion rate so as to evaluate the corrosion leakage risk of the oil storage tank.
The method comprises the following specific steps:
1. obtaining the comprehensive corrosion degree of the last thickness detection corresponding to the corrosion rate
Difference between last two thickness measurements
And acquiring a risk index by combining the corrosion rate B.
In the embodiment of the invention, the comprehensive corrosion degree obtained by the fourth thickness detection, the difference between the third thickness measurement and the fourth thickness measurement and the corrosion rate obtained after the fourth thickness detection are obtained, so as to obtain the risk index:
wherein H represents a risk indicator;
which is indicative of a first coefficient of the first coefficient,
and the second coefficient is used for adjusting the numerical range to enable the numerical range of the addend of the two parts to be close.
As an example, in an embodiment of the present invention,
，
。
2. and evaluating the corrosion leakage risk of the oil storage tank according to the risk index.
The risk indicator H is segmented by setting a plurality of leakage thresholds, each segment representing a different risk level.
As an example, embodiments of the present invention set leakage thresholds of 0.1, 0.4, and 0.7 when
When, is no risk, when
When, it is a mild risk, 0.
When, for general risk, when
Time, is a serious risk.
In summary, the embodiment of the invention divides the tank bottom of the oil storage tank into regions, and performs thickness detection on the central point of each region based on ultrasonic waves to obtain the thickness of each region; quantifying all thicknesses into a plurality of thickness grades, and constructing a first thickness matrix by taking the thickness grades as a vertical coordinate and taking the number of mutually adjacent areas as a horizontal coordinate; calculating a large-area low-thickness factor of the first thickness matrix as a first corrosion degree; for each calculation direction, constructing a second thickness matrix by taking the thickness grade as a vertical coordinate and the run length as a horizontal coordinate; calculating the long-run low-thickness factor of each second thickness matrix, and taking the maximum long-run low-thickness factor as a second corrosion degree; taking the product of the first corrosion degree and the second corrosion degree as the comprehensive corrosion degree of the tank bottom; performing thickness detection once every preset time period, fitting the thickness grades of all the areas by using a Gaussian mixture model during each thickness detection to obtain corresponding thickness distribution, calculating the difference between the thickness distributions of two adjacent thickness detections, and calculating the corrosion rate according to a plurality of differences; and acquiring a risk index according to the comprehensive corrosion degree, the difference and the corrosion rate so as to evaluate the corrosion leakage risk of the oil storage tank. The embodiment of the invention can realize the nondestructive detection of the thickness of the bottom of the in-service oil storage tank, and can perform accurate risk assessment on the corrosion condition of the bottom of the oil storage tank, thereby avoiding potential safety hazards.
The embodiment of the invention also provides a corrosion detection system for an oil storage tank, which comprises a memory, a processor and a computer program which is stored in the memory and can run on the processor, wherein the processor realizes the steps when executing the computer program. Since a method of detecting corrosion of an oil storage tank is described in detail above, it will not be described again.
It should be noted that: the sequence of the above embodiments of the present invention is only for description, and does not represent the advantages or disadvantages of the embodiments. And that specific embodiments have been described above. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The above-mentioned embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications or substitutions do not cause the essential features of the corresponding technical solutions to depart from the scope of the technical solutions of the embodiments of the present application, and are intended to be included within the scope of the present application.
Claims (10)
1. A corrosion detection method for an oil storage tank is characterized by comprising the following steps:
dividing the tank bottom of the oil storage tank into areas, and detecting the thickness of the central point of each area based on ultrasonic waves to obtain the thickness of each area;
quantifying all thicknesses into a plurality of thickness grades, and constructing a first thickness matrix by taking the thickness grades as a vertical coordinate and taking the number of mutually adjacent areas as a horizontal coordinate; calculating a large-area low-thickness factor of the first thickness matrix as a first corrosion degree;
for each calculation direction, constructing a second thickness matrix by taking the thickness grade as a vertical coordinate and taking the run length as a horizontal coordinate; calculating the long-run low-thickness factor of each second thickness matrix, and taking the maximum long-run low-thickness factor as a second corrosion degree; taking the product of the first corrosion degree and the second corrosion degree as the comprehensive corrosion degree of the tank bottom;
performing thickness detection once every preset time period, fitting the thickness grades of all the regions by using a Gaussian mixture model during each thickness detection to obtain corresponding thickness distribution, calculating the difference between the thickness distributions of two adjacent thickness detections, and calculating the corrosion rate according to a plurality of differences;
and acquiring a risk index according to the comprehensive corrosion degree, the difference and the corrosion rate so as to evaluate the corrosion leakage risk of the oil storage tank.
2. The method for detecting corrosion of an oil storage tank as claimed in claim 1, wherein said detecting the thickness of the center point of each region based on ultrasonic waves further comprises the steps of:
denoising an echo signal of ultrasonic detection, extracting a peak point of the denoised ultrasonic echo signal, and calculating the thickness of each region by combining the thickness of the ultrasonic wave.
3. The method for detecting corrosion of an oil storage tank as claimed in claim 2, wherein the thickness of each region is calculated by:
and acquiring the thickness of each region according to the wave speed of the ultrasonic waves and the time corresponding to the peak point.
4. The method of claim 1, wherein quantifying all thicknesses to a plurality of thickness levels comprises:
the factory-leaving thickness of the bottom of the oil storage tank is uniformly divided into a plurality of grades, and the detected thickness of each area is quantized according to the corresponding grade to obtain the thickness grade of each area after quantization.
5. The method of claim 1, wherein the large area low thickness factor is calculated by:
and processing each element according to the number of rows and columns of each element in the first thickness matrix, summing all the processed elements to obtain a first element sum, summing all the elements in the first thickness matrix to obtain a second element sum, and taking the normalization result of the ratio of the first element sum to the second element sum as the large-area low-thickness factor.
6. The method for detecting corrosion of an oil storage tank as claimed in claim 1, wherein the calculation method of the long-run low-thickness factor is as follows:
and for the second thickness matrix in each calculation direction, processing each element according to the number of rows and columns of each element in the second thickness matrix, summing all the processed elements to form a third element sum, summing all the elements in the second thickness matrix to form a fourth element sum, and taking the normalization result of the ratio of the third element sum to the fourth element sum as the long-run low-thickness factor.
7. The method for detecting corrosion of an oil storage tank according to claim 1, wherein the thickness distribution is obtained by:
and taking the proportion of the number of the regions corresponding to each thickness grade in all the regions as the probability of the thickness grade, and fitting all the thickness grades and the corresponding probabilities by using a Gaussian mixture model to obtain a fitting result as the thickness distribution.
8. The method of claim 1, wherein calculating the difference between the thickness distribution of two adjacent thickness measurements comprises
And calculating the relative entropy between the thickness distributions of two adjacent thickness detections, and symmetrically deforming the relative entropy to obtain the difference between the two thickness distributions.
9. The method for detecting corrosion of an oil storage tank according to claim 1, wherein the risk indicator is obtained by:
and acquiring the comprehensive corrosion degree of the last thickness detection corresponding to the corrosion rate and the difference between the last two thickness detections, and acquiring the risk index by combining the corrosion rate.
10. A corrosion detection system for an oil storage tank, comprising a memory, a processor and a computer program stored in said memory and executable on said processor, wherein said processor when executing said computer program performs the steps of the method according to any one of claims 1 to 9.
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