Method and system for detecting pulsed eddy current of thermal power pipeline with coating layer

Abstract

The invention discloses a pulsed eddy current detection method and system for a thermal power pipeline with a coating layer, and relates to the technical field of pulsed eddy current nondestructive detection.The pulsed eddy current detection method comprises the steps that pulsed eddy current detection simulation and experiment are conducted under the condition of a three-dimensional simulation model and a test piece, and excitation current waveform, amplitude and frequency parameters are determined; an induced voltage signal is collected, peak values, time points and attenuation characteristics are extracted, the corresponding relation between the wall thickness, the coating layer thickness and the welding seam structure and detection signals is constructed, a parameterized database is constructed, and temperature correction is completed; and optimizing a sensor structure and a signal acquisition scheme according to a parameterized database, obtaining detection data in a pipeline operation state, completing two-dimensional imaging of wall thickness distribution and welding seam positioning, and forming detection information covering a straight pipe, an elbow and a welding seam area. According to the method, wall thickness detection and welding seam positioning of the thermal power pipeline under the conditions of a thick wall and a thick coating layer are achieved through the full-process design of test piece modeling, simulation experiment and imaging collection.

Description

Technical Field

[0001] This invention relates to the field of pulsed eddy current nondestructive testing technology, specifically to a pulsed eddy current testing method and system for thermal power pipelines with cladding layers. Background Technology

[0002] In recent years, with the continuous increase in the scale and operating pressure of thermal power units, high-strength alloy steel materials have been widely used for pressure-bearing components such as main steam pipelines, reheat pipelines, and feedwater pipelines, covered with insulation layers and metal protective skins up to 100 mm thick. To ensure the safety and economy of the units, online monitoring technology for pipeline corrosion and wall thinning has gradually attracted attention. Pulsed Eddy Current (PEC) testing, as an emerging non-destructive testing method, has advantages such as continuous spectrum, strong penetration ability, and no need for coupling medium, and has been applied to some extent in petrochemical pipelines, aerospace structural components, and other fields. This method, through pulsed current excitation and multi-frequency response analysis, can assess material thickness and defects without direct contact with the base material, and is gradually becoming a research hotspot, with preliminary applications and standards formed both domestically and internationally.

[0003] However, existing pulsed eddy current testing technology still has several limitations under the complex operating conditions of thermal power units. First, for thick-walled pipes exceeding 70mm in wall thickness and those with coating thicknesses exceeding 200mm, the sensitivity of existing methods is significantly insufficient, making it difficult to effectively identify deep corrosion. Second, existing methods are mostly limited to ambient temperature conditions, making it difficult to adapt to stable operation in the high-temperature environment of thermal power units (hundreds of degrees Celsius). Temperature disturbances lead to signal attenuation and distortion, making it impossible to maintain detection accuracy under actual operating conditions. Third, under conditions of coating and protective layer coverage, existing technologies generally require the removal of part of the outer layer for localized inspection, increasing maintenance workload and operational risks. Furthermore, for the detection and location of pipe welds, existing methods often fail to consider the influence of weld geometry and material inhomogeneity, resulting in the inability to accurately identify the weld location and the surrounding wall thickness distribution. In summary, current technology has not yet formed a feasible solution for full-coverage online inspection of thermal power pipelines under high-temperature, thick-walled, and thick-coating conditions, and it is even more impossible to achieve unified processing of weld location and wall thickness imaging. These are all technical bottlenecks that urgently need to be addressed. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by this invention is that the existing pulse eddy current detection method for thermal power pipelines has insufficient detection sensitivity under thick wall and thick cladding layer conditions, cannot adapt to high temperature operating environment, cannot simultaneously obtain weld position and wall thickness information, and how to achieve wall thickness imaging and weld positioning of thermal power pipelines without stopping the machine or removing the cladding layer.

[0006] To address the aforementioned technical problems, this invention provides the following technical solution: a pulsed eddy current detection method for thermal power plant pipelines with cladding, comprising: constructing a three-dimensional simulation model and fabricating corresponding physical specimens based on the dimensions, material, cladding thickness, and weld type of the operating pipeline of the thermal power unit; the specimens include straight pipes, elbows, and pipe sections with welds, externally covered with insulation layers and protective skins of varying thicknesses, and a heating device is set up to form multiple operating conditions; conducting pulsed eddy current detection simulation and experiments under the three-dimensional simulation model and specimen conditions to determine the excitation current waveform, amplitude, and frequency parameters; acquiring induced voltage signals and extracting peak values, time points, and attenuation characteristics; constructing the correspondence between wall thickness, cladding thickness, weld structure, and detection signals; constructing a parameterized database and completing temperature correction; optimizing the sensor structure and signal acquisition scheme based on the parameterized database; acquiring detection data under pipeline operating conditions; completing two-dimensional imaging of wall thickness distribution and weld location; forming detection information covering the straight pipe, elbow, and weld areas; and generating detection records and data archives corresponding to the operating conditions.

[0007] As a preferred embodiment of the pulse eddy current detection method for coated thermal power pipelines described in this invention, the construction of the three-dimensional simulation model includes parametric modeling of the pipeline outer diameter, wall thickness, material conductivity and magnetic permeability, coating thickness and material, and weld geometry, and setting an electromagnetic parameter gradient band in the weld area to simulate the non-uniform characteristics of the weld fusion zone and heat-affected zone.

[0008] As a preferred embodiment of the pulse eddy current detection method for thermal power pipelines with cladding layers described in this invention, the pulse eddy current detection simulation and experiment under the conditions of a three-dimensional simulation model and test specimens includes the fabrication of physical test specimens including straight pipe specimens with a length of 1.5 meters to 2 meters, 90° elbow specimens, and specimens containing circumferential welds and longitudinal welds, which are externally covered with a glass wool or rock wool insulation layer with a thickness of 100 mm to 300 mm, and an aluminum plate or galvanized iron sheet protective skin is installed on the outer layer.

[0009] As a preferred embodiment of the pulse eddy current detection method for thermal power pipelines with cladding layers described in this invention, the pulse eddy current detection simulation and experiment under the conditions of a three-dimensional simulation model and a test specimen includes: the excitation current adopts a rectangular pulse waveform, and the parameters include the pulse peak current, pulse width and rise time; and a simulation database of the relationship between induced voltage and wall thickness is constructed by combining multiple sets of wall thickness, cladding layer thickness and protective skin thickness.

[0010] As a preferred embodiment of the pulse eddy current detection method for thermal power pipelines with cladding layers described in this invention, the acquisition of induced voltage signals and extraction of peak values ​​includes peak voltage, peak occurrence time, zero-point transition time, early logarithmic slope, and late attenuation constant. Baseline correction, bandpass filtering, and wavelet denoising are introduced during signal processing to obtain feature vectors for wall thickness inversion.

[0011] As a preferred embodiment of the pulse eddy current detection method for thermal power pipelines with cladding layers described in this invention, the sensor structure includes a coaxial spiral coil, a differential symmetrical coil, and a multi-turn coil. Different sensor structures are used for the detection of straight pipes, elbows, and welds. The induction coil signal is processed by a preamplifier and a filter circuit and then input to a 16-bit or higher analog-to-digital converter for acquisition.

[0012] As a preferred embodiment of the pulsed eddy current detection method for thermal power pipelines with cladding layers described in this invention, the two-dimensional imaging and weld positioning include: unfolding the detection path into a two-dimensional planar diagram of the pipeline, displaying the wall thickness information in the form of color gradients or numerical annotations, marking the weld position with dashed lines or symbols after being identified by the probe array response template, and introducing a geometric compensation algorithm in the elbow and reducer areas to achieve wall thickness mapping.

[0013] Another objective of this invention is to provide a pulsed eddy current detection system for thermal power pipelines with cladding layers. This system can acquire detection data under pipeline operating conditions by optimizing the sensor structure and signal acquisition scheme based on a parameterized database, complete two-dimensional imaging of wall thickness distribution and weld location, and form detection information covering straight pipes, bends and weld areas. This solves the problem that current pulsed eddy current detection methods for thermal power pipelines cannot simultaneously acquire weld location and wall thickness information.

[0014] As a preferred embodiment of the pulse eddy current detection system for coated thermal power pipelines described in this invention, the system comprises: a modeling and specimen module, a simulation and experiment module, and an acquisition and imaging module. The modeling and specimen module is used for parametric modeling and physical specimen fabrication of the operating pipelines of thermal power units, covering straight pipes, elbows, and welded pipe sections, and adding external insulation layers and protective skins to form an object base capable of simulating different operating conditions. The simulation and experiment module is used to conduct pulse eddy current detection simulation and experimental research under modeling and specimen conditions, determine excitation current parameters, acquire induced signals and extract features, establish a database relating wall thickness, coating thickness, weld structure, and signals, and complete temperature correction. The acquisition and imaging module is used to optimize the sensor structure and acquisition scheme under the guidance of the parametric database, acquire detection data under operating conditions, achieve two-dimensional imaging of wall thickness distribution and weld location, and form corresponding detection records and data archives.

[0015] Another object of the present invention is to provide a pulse eddy current detection device for coated thermal power pipelines, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the pulse eddy current detection method for coated thermal power pipelines.

[0016] Another object of the present invention is to provide a storage medium for pulse eddy current detection of coated thermal power pipelines, wherein a computer program is stored thereon, and when the computer program is executed by a processor, the steps of the pulse eddy current detection method for coated thermal power pipelines are implemented.

[0017] The beneficial effects of this invention are as follows: The pulse eddy current detection method for coated thermal power pipelines provided by this invention introduces multi-source parameters such as pipeline size, material, coating thickness, and weld type during the modeling and specimen preparation stages. A three-dimensional simulation model is established, and physical specimens containing straight pipes, elbows, and welds are fabricated. Insulation layers and protective skins of varying thicknesses are added externally, and a heating device is used to simulate various operating conditions, thus ensuring the representativeness and diversity of subsequent research objects. In the simulation and experimental stages, by comparing the pulse eddy current signals under model and specimen conditions, the waveform, amplitude, and frequency range of the excitation current are determined. Peak values, characteristic times, and attenuation parameters are extracted, establishing a quantitative mapping relationship between wall thickness, coating thickness, and weld structure. A temperature correction model is used to address signal distortion issues under high-temperature environments, ultimately forming a parameterized database. In the acquisition and imaging stages, the sensor topology and acquisition link are optimized based on the database. Detection data is acquired under pipeline operating conditions, achieving two-dimensional imaging of wall thickness distribution and weld area localization. Detection information is extended to straight pipe, elbow, and weld sections, and combined with data storage, a digital detection archive corresponding to the operating conditions is formed. Overall, this invention achieves a complete inspection path for thick-walled pipes and thick coating layers through multi-level integration of modeling, simulation, experimentation, and imaging, laying a solid technical foundation for subsequent equipment development and field application. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is an overall flowchart of a pulse eddy current detection method for thermal power pipelines with cladding provided in Embodiment 1 of the present invention. Detailed Implementation

[0020] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0021] Example 1, referring to Figure 1 As an embodiment of the present invention, a method for pulsed eddy current detection of a thermal power pipeline with a cladding layer is provided, comprising: S1: Based on the dimensions, materials, coating thickness, and weld type of the operating pipelines of thermal power units, a three-dimensional simulation model is constructed and corresponding physical specimens are made. The specimens include straight pipes, elbows, and pipe sections with welds. The outside is covered with insulation layers and protective skin of different thicknesses, and heating devices are set up to form multiple operating conditions.

[0022] Furthermore, before implementing this method, a comprehensive survey of typical operating pipelines in thermal power units is conducted, covering key components such as main steam pipes, reheat steam pipes, feedwater pipes, and bypass pipes. Detailed records are kept of basic parameters including outer diameter, wall thickness, material, electrical conductivity, magnetic permeability, and cladding material and thickness. The pipe diameters involved generally range from 100mm to 1000mm, and the wall thicknesses range from 3mm to 100mm. Commonly used materials include high-temperature alloy steels such as P91, T23, and 12Cr1MoVG. Common cladding materials are aluminum plates, galvanized iron sheets, and stainless steel sheaths, with thicknesses ranging from 50mm to 300mm. The survey of weld types also needs to cover various structural forms such as circumferential welds, longitudinal welds, and reducing joint welds to ensure the comprehensiveness and representativeness of the subsequent research.

[0023] After parameter collection, different types of pipelines were categorized into typical operating condition classes, including straight thick-walled pipes at normal temperature, thick-walled pipes operating at high temperature, elbows and reducers, pipes with thick outer cladding and multiple protective layers, and complex pipe sections containing welds. For each of these categories, representative dimensional combinations and structural features were extracted as the basis for subsequent simulation modeling and physical specimen fabrication. In the simulation study phase, a three-dimensional model was established using electromagnetic field finite element analysis software. The model includes the pipe body, cladding, external air domain, and excitation coil module. The interface region between the pipe and cladding was locally meshed with a cell division accuracy of no less than one-twentieth of the wall thickness. The air domain boundary used magnetic insulation or infinite element conditions to ensure the convergence and stability of the eddy current field calculation. For the coil part, helical coils, differential coils, and wrap-around coils were constructed to compare the signal response variations under different excitation methods.

[0024] In terms of physical specimen fabrication, straight pipe, elbow, and welded pipe sections were designed based on simulation parameters. Straight pipe specimens were designed with lengths between 1.5 and 2 meters, outer diameters of φ200mm, φ400mm, and φ600mm, and wall thicknesses of 10mm, 30mm, 60mm, and 100mm respectively. Elbow specimens featured 90° elbow structures with wall thicknesses of 30mm and 60mm. Welded pipe specimens included circumferential and longitudinal welds, with weld bevels processed according to common power plant welding techniques. Artificial corrosion defects were added to some specimens, with defect depths of 10%, 20%, and 30% of the wall thickness, and length dimensions controlled between 50mm and 200mm to ensure the controllability and repeatability of defect parameters.

[0025] After the specimens were processed, they were covered with insulation layers and protective skins of varying thicknesses. The insulation materials were primarily glass wool and rock wool, with thicknesses of 100mm, 200mm, and 300mm respectively. The outer protective skins consisted of 0.8mm thick aluminum plates and 1.0mm and 1.5mm thick galvanized iron sheets. During installation, the support structures and fixing methods commonly used in actual power plants were employed to ensure the specimens closely resembled their on-site covering condition. Heating systems were also installed on some specimens to simulate high-temperature operating environments. Heating methods included resistance heating or induction heating, with a temperature control range from room temperature to 600℃. Thermocouple measuring points were evenly distributed on the outer wall of the pipes and the outer surface of the covering layer, with a spacing of 0.5 meters between the measuring points to create a complete temperature field distribution.

[0026] S2: Conduct pulsed eddy current detection simulation and experiment under three-dimensional simulation model and specimen conditions, determine the excitation current waveform, amplitude and frequency parameters, collect induced voltage signals and extract peak value, time point and attenuation characteristics, construct the correspondence between wall thickness, cladding thickness and weld structure and detection signal, construct parameterized database and complete temperature correction.

[0027] Furthermore, in the simulation study phase of this method, a comprehensive model including the pipe, cladding layer, outer protective skin, air domain, and excitation / induction coil is first established on a three-dimensional finite element electromagnetic field platform. The material parameters for the pipe section are selected from typical thermal power unit steels, including P91, T23, and 12Cr1MoVG, and temperature dependence curves of conductivity and relative permeability are established for different operating temperatures. The cladding layer uses a non-conductive material model such as glass wool or rock wool, and the outer protective skin is set as aluminum plate or galvanized iron sheet, with differentiated modeling in the thickness direction. The air domain boundary is treated using magnetic insulation or infinite element conditions. The excitation current uses a pulse waveform, the expression of which is: , in, This represents the function of excitation current as a function of time. Represents a time variable; Indicates the peak pulse current; Represents a rectangular pulse function; Indicates the start time of the pulse; This indicates the pulse duration. The current signal covers frequency components from DC to above 100kHz, thus ensuring signal penetration.

[0028] During the simulation calculation, different wall thicknesses were considered. Coating thickness Protective skin thickness and excitation parameters A multi-factor parameter matrix is ​​constructed for system solution. For each set of parameters, the induced voltage signal is calculated. And extract its characteristic values, including peak voltage. Peak occurrence time Zero-point transition time And the slope parameters for the early and late stages. To facilitate establishing the relationship between wall thickness and signal characteristics, the following sensitivity definition is introduced: , in, Indicates wall thickness sensitivity. Indicates the sensitivity of the coating layer; Represents the characteristic parameters of any measurable signal (such as...) wait); These are reference values ​​for the benchmark specimen; This represents the partial derivative of the eigenvalue with respect to the pipe wall thickness; This represents the partial derivative of the eigenvalue with respect to the coating thickness. Through numerical differencing and smoothed spline fitting, a continuous curve showing the sensitivity as a function of multiple parameters can be obtained, establishing a quantitative coupling relationship between wall thickness and coating thickness on the detection results.

[0029] It should be noted that, for the weld area, the weld toe, reinforcement height, and bevel structure are explicitly established in the simulation model, and an electromagnetic parameter gradient band is introduced in the heat-affected zone, whose conductivity distribution is defined as: , in, Indicates the local electrical conductivity of the weld area; Indicates the electrical conductivity of the base material; This represents the attenuation coefficient of weld conductivity; The weighting function describes the transition from the weld center to the base metal. This is achieved by calculating the disturbance in the eddy current density distribution near the weld. and induced voltage distortion This allows us to obtain the correspondence between weld structure parameters and signal characteristics.

[0030] In subsequent data processing, the simulation results are jointly analyzed in the time and frequency domains to extract early diffusion characteristics, late attenuation constants, and spectral centroid parameters. Through multiple regression and response surface modeling, a clear quantitative relationship is established between wall thickness, cladding thickness, weld geometry parameters, and sensitivity indicators, thus forming a complete parameterized simulation database to provide a basis for subsequent process optimization and on-site testing.

[0031] It should also be noted that after completing the survey of the test objects and the modeling of the specimens, a simulation study of the pulsed eddy current detection characteristics was conducted using the established three-dimensional models of typical pipelines and physical specimen parameters. In the finite element electromagnetic field platform, the geometric dimensions, cladding thickness, and material parameters of different straight pipes, elbows, and weld structures were imported into the simulation environment one by one, and combined with the configured helical coil, differential coil, and winding coil models, an overall electromagnetic coupling system was established. To simulate the actual excitation process, a pulsed waveform current was used as the input, and its expression is: , in, This represents the function of excitation current as a function of time. Represents a time variable; Indicates the peak pulse current; Represents a rectangular pulse function; Indicates the start time of the pulse; This indicates the pulse duration. The excitation signal has a wide frequency spectrum, covering DC to over 100kHz, enabling the model to penetrate the cladding layer.

[0032] Based on the above excitation conditions, calculations are performed for different wall thicknesses. Coating thickness and the thickness of the protective skin The induced voltage signal under The signal differences between straight pipe, elbow, and welded pipe sections were compared. To quantify the influence of geometric and material parameters on the test results, a sensitivity function was introduced: , in, Indicates wall thickness sensitivity; Indicates the sensitivity of the coating layer; Represents the characteristic parameters of any measurable signal (such as...) wait); These serve as reference values ​​for the baseline specimen. Through numerical difference and fitting methods, the influence curves of wall thickness and cladding thickness on signal characteristics can be obtained, thus forming a parametric database that corroborates the designed specimen.

[0033] For the weld region, based on a fabricated specimen containing an artificial weld, an electromagnetic property gradient is introduced into the simulation model to describe the non-uniformity of the weld fusion zone and heat-affected zone. Its conductivity distribution is expressed as: , in, Indicates the local electrical conductivity of the weld area; Indicates the electrical conductivity of the base material; This represents the attenuation coefficient of weld conductivity; The weighting function is used to describe the transition from the weld center to the base material. By comparing the inductive signals of models with and without welds, the perturbation of the eddy current density distribution near the weld is extracted. and induced voltage distortion This allows us to obtain the mapping relationship between weld geometry and detection sensitivity.

[0034] In the post-simulation processing, the time-domain signal for each set of parameters is fitted in sections for early and late periods. The early response is represented by a power function: , in, The near-surface response coefficient; This represents a time variable. Late responses are described in exponential form: , in, For deep response coefficients; It is the attenuation constant; This represents the base of the natural logarithm. By fitting parameters... With wall thickness Coating thickness By establishing the corresponding relationship, we can obtain the variation law of sensitivity with depth diffusion, and cross-validate it with specimens of different wall thicknesses and different coating layers to ensure that the simulation results are consistent with the physical modeling.

[0035] After completing the simulation study and obtaining the quantitative laws governing the eddy current field distribution caused by wall thickness, cladding thickness, and weld structure, the experimental verification and process parameter optimization stage commenced. The experimental portion was conducted based on the fabricated physical specimens, including straight pipes, elbows, and pipe sections with welds, maintaining a diversity of cladding material and thickness combinations. The experimental platform consisted of a pulsed eddy current excitation module, a signal conditioning module, an acquisition module, and a temperature control device. The excitation module outputs an adjustable current waveform, the signal conditioning module provides multi-stage amplification and filtering, the acquisition module ensures quantization accuracy of at least 16 bits, and the temperature control device simulates the high-temperature operating conditions of the pipeline using a resistance heating element. The experimental steps were conducted in groups based on wall thickness, cladding thickness, and protective coating material. Under each group's conditions, the excitation frequency, pulse width, and current amplitude were adjusted individually to obtain the corresponding induced voltage time-domain curves and spectral characteristics.

[0036] To systematically evaluate the impact of different experimental conditions on detection performance, a comprehensive detection sensitivity index is defined. : , in, This indicates the overall detection sensitivity index; This indicates the change in the signal peak value relative to the reference specimen; Reference peak voltage; This represents the offset of a signal's characteristic time point (such as the change in zero-point transition time). For reference time value; and These are weighting coefficients used to balance the contributions of amplitude and time characteristics in sensitivity evaluation. Different parameter combinations are adjusted... and This allows for the construction of sensitivity matrices covering different specimen types, thereby forming optimization criteria for process parameters.

[0037] During the experiment, parameter scanning was first performed on straight tube specimens with different wall thicknesses. The excitation current amplitude was gradually increased and the pulse width was changed to observe the changing trend of the induced signal. Subsequently, the experiment was repeated under different cladding thicknesses (100mm, 200mm, 300mm) and different protective coating materials (aluminum, galvanized iron sheet), and the changes in the early slope and late decay constant of the signal were statistically analyzed. The experimental results were compared and analyzed with simulation data to verify the wall thickness sensitivity. With coating sensitivity To ensure consistency and correct for differences caused by environmental factors, in weld specimen experiments, a multi-point scan of the weld area is performed by moving the probe to extract the disturbance voltage distribution. Furthermore, a correspondence between the weld and the geometric features was established to ensure that the weld positioning parameters were calibrated under experimental conditions.

[0038] In the temperature effect experiment, the specimen was heated to a certain temperature using a heating device. and Three operating points were used to measure the changes in the induced signal at different temperatures, and a temperature correction factor was introduced. : , in, Indicates temperature as Eigenvalues ​​at time; These are the corresponding characteristic values ​​at room temperature; This is a temperature correction factor, the value of which varies with changes in the material's electrical conductivity and magnetic permeability. The correction factor, obtained experimentally, can convert test results under high-temperature conditions into benchmark values ​​comparable to those under normal temperature conditions.

[0039] Through the above experimental procedures, a process database covering multi-dimensional parameters such as wall thickness, cladding thickness, weld geometry, and temperature was obtained. This database not only maintains consistency with the physical specimen design and simulation patterns, but also defines a comprehensive detection sensitivity index. This allows for direct comparison of experimental results with simulation results. Ultimately, supported by this experimental database, it is possible to extract the optimal excitation current amplitude, frequency range, probe structure, and signal processing window suitable for different operating conditions, thereby providing basic process parameters for subsequent equipment design and field applications.

[0040] After optimizing the experimental process parameters, the next stage is sensor design and signal acquisition. This stage begins by clarifying the parameter requirements for different detection objects (straight pipes, elbows, welds, and thick-coated pipes) based on the established specimen and simulation / experiment database. This leads to the structural design of various types of pulsed eddy current probes. The sensor coils adopt a replaceable modular design, including three topologies: coaxial spiral coils, differential symmetrical coils, and multi-turn coils, used for straight pipe wall thickness measurement, elbow and irregular structure detection, and weld area positioning, respectively. The coil parameters must meet the constraints of the obtained process database during design; for example, the number of turns N, inner diameter D, axial height H, and wire diameter d are all determined through dual calibration using simulation results and the experimental sensitivity matrix.

[0041] In terms of electrical design, a shielded cable is used to connect the excitation module and the sensor coil to avoid electromagnetic interference on site. The induction coil signal enters the conditioning module through a low-noise preamplifier, where two stages of amplification and bandpass filtering are implemented to ensure that the signal amplitude is within the effective range of the analog-to-digital converter. The signal acquisition module uses an analog-to-digital converter with a resolution of 16 bits or higher and a sampling frequency of 500 kHz or higher, capable of capturing the pulsed eddy current response spectrum from DC to 100 kHz. In actual deployment, an air gap (liftoff) is maintained between the sensor probe and the pipe surface. The size of the gap is determined by the thickness of the cladding layer, and a position sensing element is installed inside the probe to record the actual relative position of the probe and the pipe, ensuring that subsequent signal processing can be correlated to the corresponding detection point.

[0042] To establish a signal standardization mechanism for different detection locations, a normalized response function is introduced: , in, This represents the normalized response signal; Indicates the induced voltage signal; This represents the reference signal of the reference specimen under the same conditions; This represents the gain factor of the conditioning link. Normalization eliminates system differences caused by different probes and gain levels, making the signals comparable.

[0043] In the design of the weld seam positioning sensor, a local coil array arrangement is adopted, with multiple small coil units arranged along the circumference of the pipe. The induced signal of the i-th coil is defined as... By superimposing and differentiating all coil signals, the characteristic response of the weld seam is obtained: , in, This represents the synthesized response signal for weld inspection. This represents the induced signal of the i-th coil; This represents the weighting coefficient of the corresponding coil; The total number of coils. By selecting an appropriate weight distribution, the disturbance characteristics of the weld area can be enhanced and the background response of the non-weld area can be suppressed, thereby achieving higher accuracy weld positioning.

[0044] In the signal acquisition stage, the acquisition module not only records the original voltage curve, but also simultaneously extracts feature values, including peak voltage. Peak occurrence time Zero-point transition time The early and late decay constants were also determined. To ensure data consistency, all signals were pre-filtered and synchronized using software algorithms and stored as timestamps to establish a pipeline detection signal database. This database corresponds to the simulation output and experimental results.

[0045] S3: Based on the parameterized database, optimize the sensor structure and signal acquisition scheme, acquire detection data under pipeline operation conditions, complete two-dimensional imaging of wall thickness distribution and weld location, form detection information covering straight pipes, elbows and weld areas, and generate detection records and data archives corresponding to operating conditions.

[0046] Furthermore, after completing sensor design and signal acquisition, the next stage is signal processing and feature extraction. This stage, based on the established detection signal database, systematically processes the acquired pulsed eddy current induced voltage curves. First, within the time domain, the induced voltage signal... Baseline correction and filtering are performed. Baseline correction achieves zero mean by removing DC bias and low-frequency drift; filtering uses a bandpass filter to retain effective spectral components in the range from DC to 100kHz. The preprocessed signal is denoted as... Its definition is: , in, This represents the filtered signal; Indicates the induced voltage signal; Indicates the mean of the signal; This represents the bandpass filter operator.

[0047] In the feature extraction stage, the peak voltage is first determined. Peak occurrence time Zero-point transition time And define the feature vector: , in, It is the signal feature vector; Peak voltage; This refers to the time when the peak occurs; The transition time is zero point. Represents the logarithmic slope of the signal in its early stages; This represents the attenuation slope in the later stages of the signal. By comparing the eigenvectors under different operating conditions, it is possible to distinguish the signal differences caused by variations in wall thickness, cladding thickness, and weld disturbances.

[0048] To establish the correspondence between wall thickness or corrosion depth and characteristic parameters, a wall thickness inversion function is introduced: , in, This represents the estimated pipe wall thickness; Indicates the first One feature parameter; No. Each signal characteristic parameter, and Similar to each other, used for interactive items; These are the constant term, the coefficient of the linear term, and the coefficient of the quadratic interaction term in the regression model, respectively. This represents the dimension of the feature vector. This function is obtained through experimental calibration and fitting with simulation data, and is used for quantitative calculation of wall thickness in actual testing.

[0049] In the frequency domain analysis section, Perform a Fast Fourier Transform (FFT) to obtain the spectrum. And extract the energy center frequency. With spectrum bandwidth : , in, Indicates the frequency of the energy center of mass; Indicates the spectrum bandwidth; Indicates frequency.

[0050] To address signal distortion caused by cladding deformation, interference from surrounding pipelines, and temperature fluctuations, an anti-interference algorithm is introduced in this stage. The anti-interference processing consists of two parts: first, wavelet transform is used to perform multi-scale decomposition of the signal to remove noise components; second, local correction is performed using the correlation between adjacent measuring points, defined by the formula: , in, For the revised first Point eigenvalues; These are the original eigenvalues; These are the characteristic values ​​of adjacent measuring points; This is a correction coefficient. This method can reduce the impact of single-point anomalies and improve the overall stability of the data.

[0051] Ultimately, all signal features are stored in matrix form, forming a mapping database between wall thickness and feature vectors. This database maintains consistency with simulation patterns and experimental data, and forms a closed loop with the acquisition hardware, providing core input for subsequent wall thickness imaging and weld location.

[0052] It should be noted that after signal processing and feature extraction, the process proceeds to the wall thickness imaging and weld location stage. The goal of this stage is to transform the obtained feature parameters and wall thickness inversion results into intuitive and usable imaging information, and to clearly mark the weld location. First, an unfolded view of the pipeline is constructed in the data processing software, unfolding the detection path into a two-dimensional plane according to the geometric coordinates of the pipeline's outer wall. The system maps the output wall thickness data point by point onto the unfolded view according to the spatial acquisition sequence, and displays the wall thickness distribution through color gradients or partitioned numerical annotations. The color scale uses a gradient from cool to warm colors from thick to thin, making it easy to distinguish different wall thickness areas. For scenarios requiring precise readings, a numerical annotation method can also be used, displaying absolute or relative wall thickness information in a small square corresponding to each sampling point.

[0053] While achieving wall thickness imaging, to address the localization needs of the weld area, a weld identification template is established using the characteristic response signals acquired by a dedicated weld probe and combined with extracted disturbance features. In the imaging results, the scanning path corresponding to the weld is automatically identified and marked, and the system highlights it on the unfolded image using dashed lines, shadows, or symbols to distinguish the weld area from the base material area. After the weld marking is completed, the local wall thickness distribution near the weld can also be overlaid, thus forming a direct correlation between the weld and wall thickness in the two-dimensional unfolded image.

[0054] For complex structures such as elbows and reducers, the imaging software incorporates a spatial compensation algorithm during data coordinate transformation to align the probe's motion trajectory with the pipe's geometric model. This ensures that the wall thickness results for bends or transition areas are accurately mapped to the corresponding areas in the unfolded diagram. For long straight pipe sections, the system supports continuous scanning mode, and the imaging results can be displayed as scrolling bars or segmented stitching, thus covering the entire pipe section.

[0055] After weld positioning is completed, the system also supports secondary analysis of weld signals, such as calculating the difference between the weld zone signal and the base material zone signal, or identifying repetitive features of the weld area by comparing multiple scan results. These processing results are stored in the database along with the wall thickness imaging data to form a complete inspection archive, providing basic data support for subsequent operational status analysis, maintenance plan formulation, and pipeline life assessment.

[0056] It should also be noted that after completing wall thickness imaging and weld location, this method is further extended to high-temperature online detection and field application. The detection method and equipment are transferred from the experimental environment to the actual operating environment of a thermal power unit, enabling pipeline inspection without shutting down the system or removing the cladding. In field application, the operating conditions of the target pipe are first confirmed, recording the operating pressure, steam temperature, external ambient temperature, and cladding structure of the unit where the pipeline is located, ensuring that the detection conditions correspond to the database parameters from the experimental stage. Subsequently, sensor probes are arranged along a preset detection path outside the target pipe section. The probes are positioned using high-temperature resistant flexible supports and fixing fixtures. The fixture surface is made of heat-insulating and electromagnetic interference-resistant materials to ensure stable sensor operation in high-temperature environments.

[0057] During data acquisition, both the excitation module and the signal acquisition module are integrated into a portable on-site cabinet. The cabinet is equipped with forced air cooling and insulation, and establishes a wired or wireless connection with the data terminal in the unit control room to achieve real-time data transmission. During the detection process, the system continuously records the sensed signals and performs real-time feature extraction. The processing software simultaneously calculates the wall thickness and performs two-dimensional imaging, dynamically displaying the pipe wall thickness distribution and weld location on the monitoring screen. For signal attenuation that may occur under high-temperature operating conditions, the software uses a temperature correction database established in-system for real-time compensation, ensuring that the imaging results are consistent with those under normal temperature conditions.

[0058] In weld inspection scenarios, the sensor probe performs local scanning along the weld path, and the software automatically matches the weld feature signal template to mark the weld location. For long-distance pipelines, the system adopts a segmented scanning and data stitching strategy, allowing operators to sequentially inspect multiple sections on-site. The data is then automatically stitched together into a continuous pipeline wall thickness map via a data processing platform. In complex environments, such as densely populated pipeline areas or near supports, inspectors can select probes of different sizes or coil structures to perform local scanning, ensuring complete coverage.

[0059] Upon completion of the inspection, the system generates a field application inspection report, which includes the inspection time, inspection path, equipment parameters, wall thickness imaging, weld location diagram, and inspection data files. All data is simultaneously uploaded to the power plant's equipment management platform, forming a traceable digital inspection archive. In subsequent operation and maintenance, this archive can be used to compare inspection results at different time points, enabling corrosion trend tracking and lifespan prediction. This method does not require the removal of the cladding layer or unit shutdown during field application, significantly reducing maintenance costs while ensuring inspection coverage and data continuity during pipeline operation, providing technical support for the full lifespan management of thermal power unit pipelines.

[0060] Example 2, one embodiment of the present invention, provides a pulsed eddy current detection system for thermal power pipelines with cladding, including a modeling and specimen module, a simulation and experiment module, and an acquisition and imaging module.

[0061] The modeling and specimen module is used for parametric modeling and physical specimen fabrication of operating pipelines of thermal power units, covering straight pipes, elbows, and welded pipe sections, and adding external insulation layers and protective skins to form an object basis that can simulate different operating conditions. The simulation and experiment module is used to conduct pulsed eddy current detection simulation and experimental research under modeling and specimen conditions, determine excitation current parameters, collect induced signals and extract features, establish a database of the relationship between wall thickness, cladding thickness, weld structure and signals, and complete temperature correction. The acquisition and imaging module is used to optimize sensor structure and acquisition scheme under the guidance of the parametric database, acquire detection data under operating conditions, realize two-dimensional imaging of wall thickness distribution and weld location, and form corresponding detection records and data archives.

[0062] This embodiment also provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the pulse eddy current detection method for thermal power pipelines with cladding layers proposed in the above embodiment.

[0063] This embodiment also provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements the pulse eddy current detection method for thermal power pipelines with cladding layers proposed in the above embodiment.

[0064] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0065] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0066] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0067] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0068] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for pulsed eddy current detection in thermal power pipelines with cladding, characterized in that, include: Based on the dimensions, materials, coating thickness, and weld type of the operating pipelines of thermal power units, a three-dimensional simulation model was constructed and corresponding physical specimens were made. The specimens included straight pipes, elbows, and pipe sections with welds. The outside was covered with insulation layers and protective skin of different thicknesses, and heating devices were set up to form multiple operating conditions. Under the conditions of three-dimensional simulation model and test piece, pulsed eddy current detection simulation and experiment were carried out to determine the excitation current waveform, amplitude and frequency parameters, collect induced voltage signal and extract peak value, time point and attenuation characteristics, construct the correspondence between wall thickness, cladding layer thickness and weld structure and detection signal, construct parameterized database and complete temperature correction. Based on the parameterized database, the sensor structure and signal acquisition scheme are optimized to obtain the detection data under the pipeline operation status, complete the two-dimensional imaging of wall thickness distribution and weld location, form detection information covering straight pipes, elbows and weld areas, and generate detection records and data archives corresponding to the operating conditions.

2. The pulse eddy current detection method for thermal power pipelines with cladding as described in claim 1, characterized in that: The construction of the three-dimensional simulation model includes, Parametric modeling was performed on the pipe outer diameter, wall thickness, material conductivity and magnetic permeability, cladding thickness and material, and weld geometry. An electromagnetic parameter gradient band was set in the weld area to simulate the non-uniform characteristics of the weld fusion zone and heat-affected zone.

3. The pulse eddy current detection method for coated thermal power pipelines as described in claim 1 or 2, characterized in that: The simulation and experiment of pulsed eddy current detection under three-dimensional simulation model and specimen conditions includes, The physical specimens include straight pipe specimens with a length of 1.5 to 2 meters, 90° elbow specimens, and specimens containing circumferential and longitudinal welds. The specimens are covered with a glass wool or rock wool insulation layer with a thickness of 100 mm to 300 mm, and an aluminum plate or galvanized iron sheet is installed on the outer layer for protection.

4. The pulse eddy current detection method for thermal power pipelines with cladding as described in claim 3, characterized in that: The simulation and experiment of pulsed eddy current detection under three-dimensional simulation model and specimen conditions includes, The excitation current adopts a rectangular pulse waveform, and the parameters include the peak pulse current, pulse width and rise time. A simulation database of the relationship between induced voltage and wall thickness is constructed by combining multiple sets of wall thickness, cladding layer thickness and protective skin thickness.

5. The pulse eddy current detection method for thermal power pipelines with cladding as described in claim 1, characterized in that: The process of acquiring the induced voltage signal and extracting the peak value includes, Peak voltage, peak occurrence time, zero transition time, early logarithmic slope, and late decay constant are obtained, and baseline correction, bandpass filtering, and wavelet denoising are introduced during signal processing to obtain eigenvectors for wall thickness inversion.

6. The pulse eddy current detection method for thermal power pipelines with cladding as described in claim 1, characterized in that: The sensor structure includes, Coaxial spiral coils, differential symmetrical coils, and multi-turn coils are used, and different sensor structures are adopted for the detection of straight pipes, elbows, and welds. The induction coil signal is processed by a preamplifier and a filter circuit and then input into a 16-bit or higher analog-to-digital converter for acquisition.

7. The pulse eddy current detection method for thermal power pipelines with cladding as described in claim 1, characterized in that: The two-dimensional imaging and weld seam positioning include, The detection path is unfolded into a two-dimensional plan view of the pipeline. The wall thickness information is displayed in the form of color gradient or numerical annotation. The weld position is identified by the probe array response template and marked with dashed lines or symbols. A geometric compensation algorithm is introduced in the elbow and reducer areas to realize the wall thickness mapping.

8. A pulsed eddy current detection system for coated thermal power pipelines, employing the pulsed eddy current detection method for coated thermal power pipelines as described in any one of claims 1 to 7, characterized in that: It includes a modeling and specimen module, a simulation and experiment module, and a data acquisition and imaging module; The modeling and specimen module is used to perform parametric modeling and physical specimen fabrication of operating pipelines of thermal power units, covering straight pipes, elbows and welded pipe sections, and adding external insulation layers and protective skin to form an object basis that can simulate different operating conditions; The simulation and experiment module is used to carry out simulation and experimental research on pulsed eddy current detection under modeling and specimen conditions, determine excitation current parameters, collect induction signals and extract features, establish a database between wall thickness, cladding thickness and weld structure and signals, and complete temperature correction. The acquisition and imaging module is used to optimize the sensor structure and acquisition scheme under the guidance of the parameterized database, acquire detection data in operation, realize two-dimensional imaging of wall thickness distribution and weld location, and form corresponding detection records and data archives.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the pulse eddy current detection method for thermal power pipelines with cladding as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the pulse eddy current detection method for thermal power pipelines with cladding as described in any one of claims 1 to 7.

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