Crude oil storage and transportation safety state dynamic monitoring method for pressure pipeline

Abstract

The invention discloses a pressure pipeline-oriented crude oil storage and transportation safety state dynamic monitoring method, and belongs to the field of pressure pipeline engineering safety monitoring, and the method comprises the steps: obtaining multi-modal sensing data collected by a plurality of sensor nodes; performing signal space-time fusion processing on the multi-modal sensing data to generate environment interference compensation parameters; constructing a dynamic compensation model based on the environmental interference compensation parameters, and outputting a pipeline body damage feature vector and a medium state feature vector; carrying out migration enhancement analysis on the pipeline body damage feature vector and the medium state feature vector to generate a migration enhancement feature vector; and generating a corresponding safety early warning signal according to a comparison result of the migration enhancement feature vector and a preset dynamic threshold parameter. According to the invention, a multi-sensor space-time fusion and migration enhancement analysis technology is adopted, real damage signals can be accurately identified, and dynamic threshold early warning can be realized.

Description

Technical Field

[0001] The present invention relates to the field of safety monitoring of pressure pipeline engineering, and in particular to a dynamic monitoring method for the safety state of crude oil storage and transportation for pressure pipelines. Background Art

[0002] At present, the safety monitoring of crude oil transportation pipelines faces the challenge of coexistence of multi-source interferences. Conventional detection technologies are difficult to effectively distinguish environmental factors such as seismic waves and wave impacts from signals generated by real pipeline damages, resulting in a high false alarm rate of the monitoring system.

[0003] Traditional solutions mostly adopt a single-parameter threshold alarm mechanism. By deploying a vibration sensor array to monitor abnormal vibrations of the pipeline and combining spectral analysis with fixed parameters to identify crack propagation characteristics.

[0004] When traditional solutions are applied to complex interference environments, the sensitivity of a single sensing mode is insufficient, the fixed threshold cannot adapt to changes in the rheology of the medium, and traditional signal processing algorithms lack the ability of dynamic fusion of multi-dimensional features. These problems lead to a significant decrease in the reliability of existing systems when dealing with compound working conditions of sudden pressure difference and sulfide corrosion. Summary of the Invention

[0005] To solve the above problems, the present invention provides a dynamic monitoring method for the safety state of crude oil storage and transportation for pressure pipelines, which adopts multi-sensor spatio-temporal fusion and migration enhancement analysis technologies, and can accurately identify real damage signals and achieve dynamic threshold warning.

[0006] The above object can be achieved by the following solutions: A dynamic monitoring method for the safety state of crude oil storage and transportation for pressure pipelines, including obtaining multi-modal sensing data collected by a plurality of sensor nodes with a preset distribution interval, where the multi-modal sensing data includes vibration waveforms, ultrasonic reflection signals, and pressure gradient parameters; performing signal spatio-temporal fusion processing on the multi-modal sensing data to generate environmental interference compensation parameters; constructing a dynamic compensation model based on the environmental interference compensation parameters, and outputting a pipeline body damage feature vector and a medium state feature vector; performing migration enhancement analysis on the pipeline body damage feature vector and the medium state feature vector to generate a migration enhancement feature vector; and generating a corresponding safety warning signal according to the comparison result between the migration enhancement feature vector and a preset dynamic threshold parameter.

[0007] Optionally, the signal spatio-temporal fusion processing further includes: removing the interference noise components matched by a preset seismic wave template from the vibration waveform to obtain a purified vibration spectrum; extracting the envelope morphological features of the ultrasonic reflection signal to generate a circumferential damage index; correcting the circumferential damage index according to the change slope of the pressure gradient parameter and outputting a standardized vibration spectrum; performing time-frequency domain superposition on the purified vibration spectrum and the standardized vibration spectrum to generate the environmental interference compensation parameter.

[0008] Optionally, the generating of the safety warning signal includes: obtaining the temperature-viscosity mapping table and the corrosion rate reference value in the historical operation and maintenance data of the pipeline; adjusting the allowable range of transient pressure fluctuation in the preset dynamic threshold parameter according to the predicted value of the medium viscosity in the migration-enhanced feature vector; triggering a warning signal when the pipeline wall thickness loss rate in the migration-enhanced feature vector exceeds 1.5 times the corrosion rate reference value.

[0009] Optionally, the removing of the interference noise components includes: identifying the vibration arrival time difference between adjacent sensor nodes to generate a phase shift matrix; constructing a direction filter using the phase shift matrix to isolate the internal damage vibration of the pipeline from the external environment vibration; extracting the internal damage vibration frequency components after isolation to generate the purified vibration spectrum.

[0010] Optionally, after outputting the standardized vibration spectrum, it further includes: calculating the attenuation coefficient of the pressure gradient parameter in the axial direction of the pipeline to generate a flow rate mutation index; triggering the leakage signal in the safety warning signal when the flow rate mutation index exceeds the preset leakage determination baseline.

[0011] Optionally, after generating the circumferential damage index, it further includes: superimposing the ultrasonic reflection signal intensity distribution maps of different sensor nodes to generate a three-dimensional damage cloud map; correcting the weight distribution coefficient of the circumferential damage index based on the density gradient direction of the three-dimensional damage cloud map.

[0012] Optionally, the migration-enhanced analysis includes: obtaining the wave impact spectrum characteristics in a preset marine pipeline fluctuation database; performing frequency domain convolution on the wave impact spectrum characteristics and the current pipeline vibration waveform to generate a composite damage sensitive factor; activating the sulfide corrosion monitoring mode when the correlation coefficient between the composite damage sensitive factor and the migration-enhanced feature vector is greater than 0.75.

[0013] Optionally, the activating of the sulfide corrosion monitoring mode includes: collecting the pipeline surface electrolytic potential data and performing weighted fusion with the predicted value of the sulfur content in the medium state feature vector; generating a dynamic corrosion rate curve and comparing the slope of the dynamic curve with a preset safety threshold in real time.

[0014] Optionally, the trigger warning signal includes: when the warning signal is triggered, synchronously sending the azimuth coordinate index of the three-dimensional damage cloud map to a preset emergency control terminal; activating a corresponding acoustic-optic positioning device according to the azimuth coordinate index to generate a leakage point navigation mark.

[0015] Based on the same inventive concept, the present invention also provides a dynamic monitoring system for the safety state of crude oil storage and transportation for pressure pipelines. The system includes: a data acquisition module for acquiring multi-modal sensing data collected by a plurality of sensor nodes with a preset distribution spacing, where the multi-modal sensing data includes vibration waveforms, ultrasonic reflection signals, and pressure gradient parameters; a signal processing module for performing signal spatio-temporal fusion processing on the multi-modal sensing data to generate an environmental interference compensation parameter; a feature analysis module for constructing a dynamic compensation model based on the environmental interference compensation parameter and outputting a pipeline body damage feature vector and a medium state feature vector; a migration enhancement module for performing migration enhancement analysis on the pipeline body damage feature vector and the medium state feature vector to generate a migration enhancement feature vector; and a decision output module for generating a corresponding safety warning signal according to the comparison result between the migration enhancement feature vector and a preset dynamic threshold parameter.

[0016] Compared with the prior art, the present invention has the following advantages: 1. The present invention significantly improves the accuracy of fault feature identification through spatio-temporal fusion of multi-source information; compared with the single-sensor monitoring method, the collaborative processing of multi-modal sensing data effectively suppresses environmental noise interference, improves the signal-to-noise ratio of the signal, and ensures the accurate extraction of weak fault features.

[0017] 2. Adopting a dynamic threshold adjustment mechanism; breaking through the limitations of the traditional fixed warning mode, through migration enhancement analysis, the rheological parameters of the medium and the stress change trend are associated in real time, the response speed of the leakage determination baseline is improved, and the false alarm and missed alarm phenomena under complex working conditions are significantly reduced.

[0018] 3. Realizing three-dimensional assessment of defects through a three-dimensional damage characterization system; through the spatial superposition and weight optimization of ultrasonic reflection signals, the resolution of the generated damage cloud map reaches the millimeter level, the circumferential damage index diagnosis accuracy is improved, and reliable data support is provided for pipeline safety assessment.

[0019] Other features and advantages of the present invention will be described in the following specification, and, in part, will be obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention can be realized and obtained by the structures pointed out in the specification, claims, and drawings. Description of the Drawings

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.

[0021] Figure 1 It is a schematic flowchart of the dynamic monitoring method for the safety state of crude oil storage and transportation facing pressure pipelines in the embodiment of the present invention.

[0022] Figure 2 It is a schematic diagram of the comparison of filtered signals in the embodiment of the present invention.

[0023] Figure 3 It is a schematic diagram of the dynamic threshold adjustment mechanism in the embodiment of the present invention.

[0024] Figure 4 It is a schematic diagram of the three-dimensional damage cloud map in the embodiment of the present invention.

[0025] Figure 5 It is a schematic structural diagram of the dynamic monitoring system for the safety state of crude oil storage and transportation facing pressure pipelines in the embodiment of the present invention. Specific embodiments

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments of the present invention belong to the scope of protection of the present invention.

[0027] Refer to Figure 1 , an embodiment of the present invention proposes a dynamic monitoring method for the safety state of crude oil storage and transportation facing pressure pipelines. By using multi-sensor spatio-temporal fusion and migration enhancement analysis technology, it can accurately identify real damage signals and achieve dynamic threshold warning.

[0028] The method of this embodiment specifically includes: Obtain multi-modal sensing data collected by multiple sensor nodes with a preset distribution spacing. The multi-modal sensing data includes vibration waveforms, ultrasonic reflection signals, and pressure gradient parameters; Specifically, the multi-modal sensing data specifically refers to three types of heterogeneous measurement values synchronously collected by each sensing node. The vibration waveform refers to the continuous curve of the amplitude change over time generated by the mechanical vibration on the surface of the object recorded by the sensor. The ultrasonic reflection signal describes the acoustic wave characteristics reflected by internal defects or interfaces of the detected material after the sensor emits high-frequency acoustic waves. The pressure gradient parameter is the change rate of the fluid pressure difference between measurement points relative to the axial distance of the pipeline.

[0029] Perform signal spatio-temporal fusion processing on the multi-modal sensing data to generate environmental interference compensation parameters; Specifically, the signal spatio-temporal fusion processing refers to the algorithmic process of jointly analyzing multi-source sensing data with spatio-temporal correlation. The environmental interference compensation parameters specifically refer to the set of correction factors extracted through fusion processing.

[0030] Construct a dynamic compensation model based on the environmental interference compensation parameters, and output the pipeline body damage feature vector and the medium state feature vector; Specifically, the dynamic compensation model refers to a calibration system with environmental parameter self-adaptation ability established using a recurrent neural network. The pipeline body damage feature vector specifically refers to the mathematical expression generated by convolutional feature extraction of the fused data after compensation. The medium state feature vector is the projection of the feature space established through the compensation model, characterizing the abnormal state parameters of the flowing medium inside the pipeline.

[0031] Perform migration enhancement analysis on the pipeline body damage feature vector and the medium state feature vector to generate a migration enhancement feature vector; Specifically, the migration enhancement analysis refers to a heterogeneous feature fusion strategy based on the migration learning framework. The migration enhancement feature vector is the projection of a fourteen-dimensional composite feature space generated through collaborative training, containing three types of key parameters for cross-domain fusion.

[0032] Generate corresponding safety warning signals according to the comparison result between the migration enhancement feature vector and the preset dynamic threshold parameters.

[0033] Specifically, monitor the medium viscosity in real time and compare it with the temperature database, and automatically adjust the pressure fluctuation limit when the environmental temperature deviates from the standard parameters; synchronously track the degradation degree of the pipeline wall thickness, and trigger a safety warning signal when the loss rate is abnormal.

[0034] Optionally, the steps of performing signal spatio-temporal fusion processing on the multi-modal sensing data to generate environmental interference compensation parameters include: Eliminate the interference noise components matched by the preset seismic wave template in the vibration waveform to obtain a purified vibration spectrum; Specifically, identify the vibration arrival time difference between adjacent sensor nodes, generate a phase shift matrix, and use the phase shift matrix to construct a direction filter to isolate the internal damage vibration of the pipeline from the external environmental vibration, such as Figure 2As shown, for the comparison between the original signal and the filtered signal, the internal damage vibration frequency components after isolation are extracted to generate the purified vibration spectrum.

[0035] Extract the envelope morphological features of the ultrasonic reflection signal to generate the circumferential damage index; Specifically, process the ultrasonic reflection signal, plot the morphological features of its signal envelope, and calculate the peak interval variance of the envelope morphological features and the pulse decay rate , and use the formula to generate the circumferential damage index DI , where , are pre-calibrated material characteristic coefficients.

[0036] Correct the circumferential damage index according to the change slope of the pressure gradient parameter and output the standardized vibration spectrum; Specifically, read the real-time pressure change rate collected by the pressure gradient sensor . When the real-time pressure change rate exceeds the preset threshold , perform the dynamic correction operation , where is the pressure correction coefficient, and the standardized damage index, that is, the standardized vibration spectrum is obtained.

[0037] Perform time-frequency domain superposition on the purified vibration spectrum and the standardized vibration spectrum to generate the environmental interference compensation parameter.

[0038] Specifically, perform time-frequency superposition on the purified vibration spectrum and the standardized vibration spectrum to construct the environmental interference compensation parameter , where , are the weighting coefficients, is the time-domain window function. By fusing the time-domain damage characteristics and the frequency-domain vibration characteristics, a composite compensation parameter with anti-interference is generated.

[0039] Exemplarily, the 5th monitoring node located on the subsea pipeline detects an abnormal vibration with an amplitude of 0.3 mm, and the time difference measured between adjacent nodes . After constructing the direction filter, the 8 Hz low-frequency vibration component caused by the impact of ocean waves is successfully filtered out, and the 45 Hz characteristic frequency related to crack propagation is retained. The ultrasonic system measures the peak interval variance of the envelope , combined with the current pressure change rate , and the corrected circumferential damage index After time-frequency superposition, a compensation parameter with a significant characteristic peak is formed, accurately triggering a secondary warning. The beneficial effects of this verification example are reflected in effectively distinguishing real damage from environmental vibration, dynamically correcting the algorithm to improve the accuracy of damage determination, and significantly enhancing the monitoring reliability under complex working conditions through multi-feature fusion.

[0040] Optionally, according to the comparison result between the migration-enhanced feature vector and the preset dynamic threshold parameter, generating a safety warning signal includes: Obtain the temperature-viscosity mapping table and the corrosion rate reference value in the historical operation and maintenance data of the pipeline; Specifically, retrieve the temperature-viscosity mapping table recorded during the pipeline operation cycle from the database, which stores the matching relationship between temperature values and the viscosity values of the corresponding media. At the same time, extract the average corrosion rate reference value measured in the most recent 12 months, which is calculated by dividing the change in the wall thickness of the pipe detected regularly by the ultrasonic thickness gauge each month by the time interval.

[0041] According to the predicted value of the medium viscosity in the migration-enhanced feature vector, adjust the allowable range of transient pressure fluctuation in the preset dynamic threshold parameter; Specifically, through the predicted value of the medium viscosity , match the closest temperature value in the temperature-viscosity mapping table. When the temperature value changes by more than 5°C compared to the current ambient temperature, update the allowable range of transient pressure fluctuation ， Where represents the medium viscosity under standard working conditions, is the designed static pressure value of the pipeline. As Figure 3 shown, it is a schematic diagram of the dynamic threshold adjustment mechanism.

[0042] When the pipeline wall thickness loss rate in the migration-enhanced feature vector exceeds the preset threshold, trigger a warning signal.

[0043] Specifically, continuously monitor the wall thickness loss rate in the migration-enhanced feature vector, where the wall thickness loss rate is calculated by dividing the difference between the measured current wall thickness and the initial thickness by the operation time. When it is detected that the wall thickness loss rate exceeds 1.5 times the corrosion rate reference value, trigger a warning signal.

[0044] Exemplarily, the ambient temperature of a certain submarine oil pipeline drops suddenly by 8°C to 5°C, and the system detects that rises from the normal state of 48 to 62. According to the temperature-viscosity mapping table, the medium viscosity corresponding to 7°C under standard working conditions is 51, and it is calculated that , which is 40% wider than the original threshold of 4.2. At this time, the monitoring shows that the wall loss rate reaches 0.28, while the corrosion rate reference value of this pipe section is 0.15, activating the secondary warning. The beneficial effect of this verification example is reflected in that the dynamic adjustment mechanism flexibly changes the criterion according to the medium state, avoiding false alarms under low-temperature and high-viscosity conditions and giving early warnings in a timely manner at the initial stage of accelerating corrosion, achieving differential and precise monitoring.

[0045] Optionally, the step of removing the interference noise component matched by the preset seismic wave template in the vibration waveform to obtain the purified vibration spectrum includes: Identifying the vibration arrival time difference between adjacent sensor nodes to generate a phase shift matrix; Specifically, first identify the vibration waveform arrival time difference recorded by adjacent sensor nodes set on the pipe surface with a spacing of L, calculate the phase shift matrix between adjacent nodes, and the phase shift matrix is composed of the vibration wave propagation time differences of each pair of sensors, where the time difference is obtained by comparing the trigger moments of the rising edges of the vibration waveforms.

[0046] Applying the phase shift matrix Constructing a direction filter , which separates the internal pipe damage vibration and the external environment vibration based on the vibration wave propagation direction characteristics, where f represents the vibration frequency component, is the exponential function with base e, j is the imaginary unit whose square is equal to negative one, and is used to represent the quadrature component of the phase in signal analysis.

[0047] Extracting the isolated internal damage vibration frequency component to generate the purified vibration spectrum.

[0048] Specifically, by performing a frequency-domain convolution operation on the original vibration waveform and the direction filter , where is the Fourier transform result of the vibration waveform, represents the convolution operation.

[0049] Optionally, the change slope of the pressure gradient parameter corrects the circumferential damage index, and the output of the standardized vibration spectrum further includes: Calculating the attenuation coefficient of the pressure gradient parameter in the axial direction of the pipe to generate a flow mutation index; Specifically, obtaining the pressure gradient sensor array's segmented measurement data in the axial direction of the pipe, where the length of each detection segment is . For the kth detection segment, calculate the pressure gradient at the current moment, where The calculation formula is , where and are respectively the maximum and minimum pressure gradient values detected in the most recent N cycles, is the average pressure gradient for the corresponding time period, is the total sampling duration.

[0050] When the flow mutation index exceeds the preset leakage determination baseline, the leakage signal in the safety warning signal is triggered.

[0051] Specifically, when it is detected that the flow mutation index exceeds the preset leakage determination baseline, the leakage signal is triggered.

[0052] Exemplarily, in a certain crude oil pipeline, at the 8th detection section, it is measured that within , corresponding to . During a continuous 12-minute sampling period, it is recorded that , , , . It is calculated that . When the preset , 0.00061 exceeds the baseline and triggers the leakage signal.

[0053] Optionally, after extracting the envelope morphological features of the ultrasonic reflection signal and generating the circumferential damage index, it further includes: Overlaying the ultrasonic reflection signal intensity distribution maps of different sensor nodes to generate a three-dimensional damage cloud map; Specifically, the ultrasonic reflection signal intensity values Si collected at N detection nodes distributed on the pipeline surface are normalized to obtain , where i represents the i-th sensor node. The normalized signal intensity is subjected to spatial interpolation operation according to the sensor position coordinates to construct a three-dimensional data matrix , where is the interpolation weight of the i-th sensor at the spatial point (x, y, z), and the calculation formula is , represents the Euclidean distance between this spatial point and the i-th sensor, takes 20% of the pipeline diameter, is the exponential function with the real number e as the base. As shown in Figure 4 , it is a schematic diagram of the three-dimensional damage cloud map effect.

[0054] Based on the density gradient direction of the three-dimensional damage cloud map, the weight distribution coefficient of the circumferential damage index is corrected.

[0055] Specifically, through the three-dimensional damage cloud map, calculate its density gradient vectors in the axial, circumferential, and radial directions of the pipeline , where represents the change rate of damage density along the pipeline length, represents the density gradient of circumferential angle change, reflects the damage distribution characteristics of radial penetration depth. Based on the gradient vector, the weight distribution coefficient is corrected to set a new weight , where V is the vector of stress concentration tendency of pipeline material, is the symbol discrimination function. For the product result of two vectors, the direction correlation characteristics of the two can be judged, is the old weight.

[0056] Optionally, the migration enhancement analysis of the pipeline body damage feature vector and the medium state feature vector includes: Obtain the wave impact spectrum characteristics in the marine pipeline fluctuation database; Specifically, collect the wave height and impact pressure data for 3 consecutive hours through a marine environment monitoring buoy, and use Fourier transform to convert it into a frequency-domain waveform, and then take the first 10 main frequency points to construct a wave impact spectrum feature matrix .

[0057] Perform frequency-domain convolution on the wave impact spectrum characteristics and the current pipeline vibration waveform to generate a composite damage sensitivity factor; Specifically, obtain the measured value of the current pipeline vibration acceleration sensor, and convert it into a displacement waveform through quadratic integration and perform a 1024-point fast Fourier transform to obtain the vibration spectrum . Perform the frequency-domain convolution operation , select the maximum amplitude of the convolution result and the weighted sum of the third harmonic component as the composite damage sensitivity factor .

[0058] When the correlation coefficient between the composite damage sensitivity factor and the migration enhancement feature vector is greater than 0.75, activate the sulfide corrosion monitoring mode.

[0059] Specifically, obtain the processed enhanced feature vector , and form a reference template for pattern recognition. Calculate the covariance in the Pearson correlation coefficient formula β and divided by the standard deviations of the two , , , when continues to be greater than 0.75 for 5 sampling periods, trigger the sulfide corrosion monitoring mode, where and are the data of the i-th sampling point of the composite damage sensitivity factor and the migration feature vector respectively, represents the mean value of the migration enhancement feature vector.

[0060] Optionally, activating the sulfide corrosion monitoring mode includes: Collecting the electrolytic potential data on the pipeline surface and performing weighted fusion with the predicted sulfur content value in the medium state feature vector; Specifically, a three-electrode array is arranged at equal intervals on the outer wall of the pipeline, and a silver / silver chloride reference electrode is used to continuously collect the surface potential difference. The potential measuring instrument records the electrolytic potential EP at a frequency of once per minute. The electrolytic potential is standardized, and the calculation formula is , where in the formula and are taken from the potential extreme value database during the pipeline service period. Obtain the predicted sulfur content value in the medium state feature vector , which is converted to through logarithmic transformation for weighted fusion , and the coefficient weights are determined according to the entropy weight analysis of the ten-year corrosion case database.

[0061] Generating a dynamic corrosion rate curve and comparing the slope of the dynamic curve with a preset safety threshold in real time.

[0062] Specifically, when establishing the corrosion rate model, a window sliding mechanism is used to process the real-time data stream. The fusion index sequence of a six-hour period is intercepted every ten minutes for second-order polynomial fitting to obtain the dynamic corrosion rate curve. The model slope is updated and calculated three times per hour. When the instantaneous slope is continuously higher than the 0.15 mm / year threshold twice, a secondary alarm mechanism is triggered, and this threshold is based on specification settings.

[0063] Optionally, triggering the warning signal includes: When the warning signal is triggered, synchronously send the azimuth coordinate index of the three-dimensional damage cloud map to a preset emergency control terminal; Specifically, the vertex coordinate set of the corrosion concentration area in the three-dimensional damage cloud map is extracted through an edge computing node, and the graph algorithm is used to delimit the range of the dangerous area centered on each vertex, generating an azimuth coordinate index composed of the pipeline mileage, circumferential angle, and axial depth.

[0064] Activating the corresponding acoustic-optic positioning device according to the azimuth coordinate index to generate a leakage point navigation mark.

[0065] Specifically, the emergency control terminal analyzes the received coordinate index , driving the annular LED array and ultrasonic transmitter arranged in the corresponding pipe section, where the LED light strip indicates the leakage azimuth in a red-blue alternating flashing mode according to the circumferential angle , and the ultrasonic emission pulse interval varies with the depth Geometric ratio adjustment. Meanwhile, the millimeter-wave radar carried by the mobile inspection robot matches the coordinate parameters in real time and generates dynamic navigation marks according to the pipeline mileage , and generates dynamic navigation marks through a path optimization algorithm. The specific method is to calculate the optimal approach route , where , are the current pose parameters of the robot. This planning logic can be compared with the map pathfinding strategy of autonomous vehicles.

[0066] Based on the same inventive concept, as Figure 5 shown, the present invention also provides a dynamic monitoring system for the safety state of crude oil storage and transportation in pressure pipelines. The system includes: A data acquisition module, configured to acquire multi-modal sensing data collected by a plurality of sensor nodes with a preset distribution interval. The multi-modal sensing data includes vibration waveforms, ultrasonic reflection signals, and pressure gradient parameters; A signal processing module, which performs signal spatio-temporal fusion processing on the multi-modal sensing data to generate an environmental interference compensation parameter; A feature analysis module, which constructs a dynamic compensation model based on the environmental interference compensation parameter and outputs a pipeline body damage feature vector and a medium state feature vector; A migration enhancement module, which performs migration enhancement analysis on the pipeline body damage feature vector and the medium state feature vector to generate a migration enhancement feature vector; A decision output module, which generates a corresponding safety warning signal according to the comparison result between the migration enhancement feature vector and a preset dynamic threshold parameter.

[0067] It should be noted that the electrical connections between the above-mentioned units do not necessarily represent direct connections of the lines. Indirect connection methods, as long as the purpose of the present invention is achieved, are applicable to the embodiments of the present invention. The above are only exemplary embodiments of the present invention, and the scope of the present invention cannot be limited thereby.

[0068] That is, all equivalent changes and modifications made in accordance with the teachings of the present invention still fall within the scope covered by the present invention. Those skilled in the art will easily think of other implementation schemes of the present invention after considering the specification and practice of the disclosure. This application aims to cover any variations, uses, or adaptive changes of the present invention, and these variations, uses, or adaptive changes follow the general principles of the present invention and include common general knowledge or conventional technical means in the technical field not recorded in the present invention.

Claims

1. A dynamic monitoring method for the safety state of crude oil storage and transportation in pressure pipelines, characterized in that, The method includes: Obtaining multi-modal sensing data by acquiring vibration waveforms, ultrasonic reflection signals, and pressure gradient parameters collected by multiple sensor nodes with a preset distribution spacing; Performing signal spatio-temporal fusion processing on the multi-modal sensing data to generate environmental interference compensation parameters; Performing feature extraction and projection on the environmental interference compensation parameters to generate a pipeline body damage feature vector and a medium state feature vector, where the medium state feature vector includes a predicted sulfur content value; Performing migration enhancement analysis on the pipeline body damage feature vector and the medium state feature vector to generate a migration enhancement feature vector, and the migration enhancement feature vector includes a pipeline wall thickness loss rate; Comparing the migration enhancement feature vector with preset dynamic threshold parameters to generate a safety warning signal, and the safety warning signal includes a leakage signal and a warning signal.

2. The dynamic monitoring method for the safety state of crude oil storage and transportation facing pressure pipelines according to claim 1, wherein, Performing signal spatio-temporal fusion processing on the multi-modal sensing data to generate environmental interference compensation parameters includes: Removing interference noise components in the vibration waveform matched by a preset seismic wave template to obtain a purified vibration spectrum; Extracting the envelope shape feature of the ultrasonic reflection signal to generate a circumferential damage index; Obtaining a change slope through the pressure gradient parameter to correct the circumferential damage index and output a standardized vibration spectrum; Performing time-frequency domain superposition on the purified vibration spectrum and the standardized vibration spectrum to generate environmental interference compensation parameters.

3. A dynamic monitoring method for the safety status of crude oil storage and transportation facing pressure pipelines according to claim 1, characterized in that, The generating of the safety warning signal includes: Obtaining pipeline historical operation and maintenance data; based on the migration enhancement feature vector, adjusting the preset dynamic threshold parameter range to obtain a new dynamic threshold parameter range; Comparing the pipeline wall thickness loss rate in the migration enhancement feature vector with a preset threshold to generate a warning signal.

4. A dynamic monitoring method for the safety status of crude oil storage and transportation for pressure pipelines according to claim 2, characterized in that, The removing of the interference noise components to obtain a purified vibration spectrum includes: Obtaining the vibration arrival time of adjacent sensor nodes, calculating the time difference, and generating a phase shift matrix; Using the phase shift matrix to construct a direction filter to isolate internal damage vibration of the pipeline from external environment vibration; Extracting the internal damage vibration frequency components after isolation to generate a purified vibration spectrum.

5. The dynamic monitoring method for the safety state of crude oil storage and transportation for pressure pipelines according to claim 2, characterized in that, After outputting the standardized vibration spectrum, it further includes: Calculating the attenuation coefficient of the pressure gradient parameter in the pipeline axial direction to generate a flow rate mutation index; Comparing the flow rate mutation index with a preset leakage determination baseline to trigger the leakage signal in the safety warning signal.

6. The dynamic monitoring method for the safety state of crude oil storage and transportation facing pressure pipelines according to claim 2, wherein, After generating the circumferential damage index, it further includes: Overlaying the intensity distribution maps generated by ultrasonic reflection signals of different sensor nodes to generate a three-dimensional damage cloud map; Analyzing the density gradient direction of the three-dimensional damage cloud map to generate an optimized weight distribution coefficient of the circumferential damage index.

7. The dynamic monitoring method for the safety state of crude oil storage and transportation facing pressure pipelines according to claim 1, wherein, The migration enhancement analysis includes: Obtaining a preset marine pipeline wave database to obtain wave impact spectrum characteristics; Performing frequency domain convolution on the wave impact spectrum characteristics and the current pipeline vibration waveform to generate a composite damage sensitivity factor; Generating a sulfide corrosion monitoring mode by comparing the correlation coefficient between the composite damage sensitivity factor and the migration enhancement feature vector with a preset safety threshold.

8. A dynamic monitoring method for the safety status of crude oil storage and transportation oriented to pressure pipelines according to claim 7, characterized in that, The generating of the sulfide corrosion monitoring mode includes: Collect the electrolytic potential data on the surface of the collection pipeline and perform weighted fusion with the predicted sulfur content value in the medium state feature vector to generate a dynamic corrosion rate curve, and compare the slope of the dynamic corrosion rate curve with a preset safety threshold in real time to generate a sulfide corrosion monitoring mode.

9. The dynamic monitoring method for the safety state of crude oil storage and transportation facing pressure pipelines according to claim 3, characterized in that The steps of triggering the warning signal include: When the warning signal is triggered, synchronously send the azimuth coordinate index to a preset emergency control terminal; activate the corresponding sound and light positioning device to generate a leakage point navigation mark.

10. A dynamic monitoring system for the safety status of crude oil storage and transportation in pressure pipelines, characterized in that, The system includes: A data acquisition module for acquiring multi-modal sensing data collected by a plurality of sensor nodes with a preset distribution spacing; A signal processing module for performing signal spatio-temporal fusion processing on the multi-modal sensing data to generate an environmental interference compensation parameter; A feature analysis module for constructing a dynamic compensation model through the environmental interference compensation parameter and outputting a pipeline body damage feature vector and a medium state feature vector; A migration enhancement module for performing migration enhancement analysis on the pipeline body damage feature vector and the medium state feature vector to generate a migration enhancement feature vector; A decision output module for generating a corresponding safety warning signal according to the comparison result between the migration enhancement feature vector and the preset dynamic threshold parameter.

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