Detection method for quantitatively evaluating fatigue damage in pipeline through nonlinear ultrasonic technology

Abstract

The invention belongs to the technical field of nondestructive testing, and particularly relates to a detection method for quantitatively evaluating fatigue damage in a pipeline through a nonlinear ultrasonic technology. 316 stainless steel and SA335GRP-11 ferrite steel samples are adopted, a welding seam area is formed through V-shaped groove welding, fatigue loading is conducted, and actual pipeline fatigue damage is simulated; for the samples with different fatigue cycles, nonlinear response signals of the samples are obtained; fourier transform is carried out on the obtained signal to obtain an energy spectrum of the signal, and energy changes of the signal on a fundamental frequency band and a second harmonic frequency band are analyzed; and calculating a nonlinear coefficient, and analyzing a change rule of the nonlinear coefficient along with fatigue cycles, so that the evolution process of fatigue damage in the pipeline is evaluated. According to the method, energy is used for replacing the amplitude value, on the basis of the formula principle, integration is used for replacing the amplitude value to improve the intensity of the characterization nonlinear ultrasonic signal, the early stage of damage and the later stage of crack initiation are detected, and reliable guarantee is provided for safe operation of an industrial pipeline system.

Description

Technical Field

[0001] The present invention belongs to the technical field of non-destructive testing, and in particular relates to a method for quantitatively evaluating fatigue damage in a pipeline using a nonlinear ultrasonic technique. Background Art

[0002] In industrial production, pipeline systems are crucial equipment for transporting various fluids. They are widely used in the oil, natural gas, chemical, and metallurgical industries. They are also widely used in nuclear power plant systems in many coastal areas. In addition to the reactors, nuclear power plants primarily consist of numerous large-diameter metal pipes. These pipes are subject to long-term fluid erosion, corrosion, and mechanical stress, making them prone to wear, corrosion, and cracks. To ensure the safety and reliability of pipeline systems, regular pipeline inspections are essential.

[0003] When nuclear-grade pipeline materials are subjected to external loads, the initial signs of damage typically manifest as microscopic changes such as grain dislocations and microcrack propagation. Especially during the 70%-80% damage stage, the damage morphology is primarily microscopic, such as microcracks, holes, and fatigue cracks. These minor defects are often difficult to effectively identify using traditional inspection methods. However, existing conventional pipeline inspection technologies, such as linear ultrasonic testing, eddy current testing, electromagnetic testing, and radiographic testing, primarily target more obvious defects such as macrocracks, and their ability to detect early-stage microdamage or low-level cracks is relatively limited.

[0004] There have been some studies on nonlinear ultrasonic testing, and they are widely used. However, there are still some shortcomings in the existing research, mainly reflected in the following aspects: nonlinear harmonic signals are usually very weak, and there is a lack of consideration of the influence of complex factors on ultrasonic response, etc. Summary of the Invention

[0005] In response to the above technical problems, the present invention proposes a method for quantitatively evaluating fatigue damage in pipelines using nonlinear ultrasonic technology. Energy is used instead of amplitude, and based on the principle of the formula, integral is used instead of amplitude to improve the intensity of the nonlinear ultrasonic signal, and the early stage of damage and the late stage of crack initiation are detected, providing reliable protection for the safe operation of industrial pipeline systems.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is:

[0007] A nonlinear ultrasonic detection method for quantitatively assessing fatigue damage in pipelines uses 316 stainless steel and SA335 GRP-11 ferritic steel specimens. V-groove welding is used to form a weld area, which is then subjected to fatigue loading to simulate actual pipeline fatigue damage. Nonlinear response signals are obtained for specimens subjected to different fatigue cycles. The acquired signals are Fourier transformed to obtain their energy spectrum, and the energy variations in the fundamental and second harmonic frequency bands are analyzed. The nonlinear coefficient is calculated and its variation with fatigue cycles is analyzed to assess the evolution of fatigue damage in the pipeline.

[0008] The target welding area of ​​the sample is polished, and a V-shaped groove is processed before welding the same metal. When welding 316 stainless steel samples, the welding wire used is ER316L, with a size of Φ2.5mm and a weight of 5kg. When welding ferritic steel samples, the welding wire used is ER80S-G, with a size of Φ2.5mm and a weight of 1.5kg. After welding, the weld needs to be polished to determine the weld quality.

[0009] The yield strength of 316 stainless steel and ferritic steel specimens after welding is determined by subjecting standard specimens to tensile tests. Continuous fatigue loading is then applied to batch fatigue specimens of 316 stainless steel and ferritic steel until the specimens fracture due to fatigue or the preset number of cycles is reached. During the experiment, the specimens will undergo continuous loading and unloading within the set stress or strain range. This cyclic process will cause changes in the internal microstructure of the material, ultimately leading to material failure.

[0010] The square of the frequency domain signal amplitude spectrum obtained by Fourier transform is called the energy spectrum. The transfer efficiency of the fundamental wave and the second harmonic energy is calculated by the transfer integral method of the energy spectrum. The generation of higher harmonics is regarded as the transfer of sound wave energy from the low frequency band to the high frequency band. The energy transfer efficiency is used to characterize the nonlinear parameters of the specimen to quantitatively evaluate the degree of fatigue damage.

[0011] Nonlinear parameter calculation based on energy transfer is performed, and a mathematical model between the nonlinear coefficient and fatigue cycles is established: nonlinear ultrasonic testing experiments are carried out on the weld area and base material area of ​​the specimen respectively, and frequency-amplitude diagrams containing the fundamental wave and second harmonic at different positions with different fatigue cycles are obtained. The nonlinear coefficient Beta calculated by the energy integration method is compared with the traditional nonlinear coefficient calculated by the fundamental wave amplitude A1 and the second harmonic amplitude A2, and the comparison is made with the fatigue cycles to obtain the relationship between the fatigue degree and the nonlinear coefficient.

[0012] The RAM-5000SNAP nonlinear high-energy ultrasonic testing system outputs a high-energy sinusoidal pulse signal with a frequency of 5MHz. After impedance matching and filtering, it is loaded into a narrowband longitudinal wave straight probe with a center frequency of 5MHz. The probe is used with a plexiglass surface wave wedge as the transmitting sensor. The signal is coupled to the sample surface through a coupling agent and propagates along the near-surface. The receiving end is composed of a 10MHz narrowband ultrasonic probe and a corresponding wedge to form a receiving sensor to receive the propagated surface wave signal. The wedge is fully coupled to the probe and the sample with a coupling agent. The wedge spacing is adjustable to achieve measurement at different propagation distances. The received signal is bandpass filtered and sampled and displayed by a digital oscilloscope. The steady-state signal is windowed and fast Fourier transformed on the computer to obtain the fundamental wave amplitude A1 and the second harmonic amplitude A2, thereby calculating the relative nonlinear coefficient at different propagation distances.

[0013] When the propagation distance is fixed, the signal passes through the damaged area, and the measurement is repeated five times for each sample. The average value is taken as the detection result, and the nonlinear coefficient is normalized.

[0014] The optimal experimental conditions were determined to be 2MHz excitation, 4MHz reception, oil coupling and 40V excitation voltage.

[0015] The signal acquisition module is used to obtain the nonlinear response signal of the pipeline sample; the signal processing module is used to perform Fourier transform on the acquired signal, analyze the energy spectrum of the signal, and calculate the nonlinear coefficient; the data analysis module is used to analyze the variation pattern of the nonlinear coefficient under different fatigue cycles and perform quantitative assessment of fatigue damage.

[0016] The beneficial effects achieved by the present invention are:

[0017] This invention quantitatively analyzes the nonlinear response of materials through the energy transfer integral method, providing a novel and effective detection method for the early diagnosis of pipeline fatigue damage. This method enables early detection of internal pipeline fatigue damage, particularly in detecting early-stage damage such as cracks and microcracks in welds and base material areas. Furthermore, the detection method is applicable to a variety of pipeline materials and can provide effective assurance for pipeline safety in nuclear power plants, petrochemicals, and other fields, demonstrating broad application prospects and engineering value. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A schematic flow chart of a method for quantitatively evaluating fatigue damage in pipelines using a nonlinear ultrasonic technique provided by the present invention;

[0019] Figure 2 A simplified schematic diagram of a nonlinear ultrasonic surface wave detection system used in the present invention;

[0020] Figure 3A schematic diagram of the process of manufacturing a fatigue test piece for testing according to the present invention;

[0021] Figure 4 Flowchart of the test piece actually processed by the present invention;

[0022] Figure 5 This is a fitting effect diagram of the nonlinear coefficient of the system built by the present invention;

[0023] Figure 6 is the amplitude of the high-frequency signal at different excitation voltage levels;

[0024] Figure 7 The relationship curve between the double frequency amplitude and the fundamental frequency amplitude under different voltages;

[0025] Figure 8 The fundamental frequency domain waveform and local magnification diagram obtained in the experiment of the present invention;

[0026] Figure 9 The nonlinear ultrasonic results of 316 specimens with different fatigue cycles in the experimental results of the present invention are as follows;

[0027] Figure 10 These are the nonlinear ultrasonic results of the P11 specimens with different fatigue cycles of the present invention. DETAILED DESCRIPTION

[0028] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0029] This invention provides an optimized method for quantitatively assessing fatigue damage in pipelines using nonlinear ultrasonic technology, specifically focusing on the damage process in weld areas. This method belongs to the field of nondestructive testing. The method involves constructing a nonlinear ultrasonic surface wave detection system to detect the nonlinear response of the material during fatigue damage. Specimens were made of 316 stainless steel and SA335GRP-11 ferritic steel to simulate actual pipeline fatigue damage. The weld area was welded using a V-groove weld and subjected to fatigue loading. The evolution of the nonlinear characteristics at different fatigue cycles was studied. During the experiment, parameters such as frequency, coupling agent, and excitation voltage were optimized to minimize the nonlinear effects of the system and thus obtain accurate experimental data. Signal processing employed the energy transfer integral method. The energy spectrum of the signal was obtained through Fourier transform. The energy variations in the fundamental and second harmonic frequency bands were analyzed, and the nonlinear coefficient was calculated to quantify the evolution of fatigue damage. Furthermore, by analyzing the variations in the nonlinear coefficient at different fatigue cycles, the relationship between fatigue damage and nonlinear response was revealed, providing a quantitative basis for early diagnosis of fatigue damage and pipeline safety assessment. This invention provides an experimental basis for pipeline fatigue damage detection and assessment, helping to improve the reliability of long-term safe operation of pipelines.

[0030] A method for assessing pipeline fatigue damage based on nonlinear ultrasonic technology comprises: building a nonlinear ultrasonic surface wave detection platform, including a radio frequency pulse transmitter and receiver, a duplexer, a signal selector, a terminal load, a filter bank, piezoelectric probes of different frequencies, and a universal oscilloscope; using 316 stainless steel and SA335GRP-11 ferritic steel specimens, forming a weld area by V-groove welding, and performing fatigue loading to simulate actual pipeline fatigue damage; using the above detection platform to obtain nonlinear response signals of the specimens with different fatigue cycles; performing Fourier transform on the obtained signals to obtain energy spectra of the signals, and analyzing energy variations of the signals in the fundamental frequency and second harmonic frequency bands; calculating the nonlinear coefficient, and analyzing its variation with fatigue cycles, thereby assessing the evolution of fatigue damage in the pipeline.

[0031] The target welding area of ​​the specimen is polished and a V-groove is formed before welding the same metal. For welding 316 stainless steel specimens, the welding wire used is ER316L, 2.5 mm in diameter and weighing 5 kg. For welding P11 ferritic steel, the welding wire used is ER80S-G, 2.5 mm in diameter and weighing 1.5 kg. After welding, the weld seam is polished to determine its quality.

[0032] Tensile testing of standard specimens was performed to determine mechanical parameters such as the yield strength of the welded 316 and P11 materials. Continuous fatigue loading was then applied to a batch of fatigue specimens of 316 and P11 materials until the specimens fractured due to fatigue or reached a predetermined number of cycles. During the experiment, the specimens were subjected to continuous loading and unloading within a defined stress or strain range. This cyclical process causes changes in the material's internal microstructure, such as crack formation and propagation, ultimately leading to material failure.

[0033] During the experimental process, optimal testing parameters were established for nonlinear testing, and an appropriate nonlinear system testing process was selected. Specifically, when performing nonlinear ultrasonic testing on fatigue specimens, the impact of different testing parameters on the results needed to be considered. By selecting the optimal testing parameters, such as the excitation signal, coupling agent, excitation voltage level, and probe angle, the interference of system nonlinear effects was reduced, ensuring the effectiveness of the nonlinear ultrasonic signal.

[0034] The square of the frequency domain signal amplitude spectrum obtained by Fourier transform is called the energy spectrum. The signal processing method calculates the transfer efficiency of the fundamental wave and the second harmonic energy through the transfer integral method of the energy spectrum. The generation of higher harmonics is regarded as the transfer of sound wave energy from the low frequency band to the high frequency band. The energy transfer efficiency is used to characterize the nonlinear parameters of the specimen to quantitatively evaluate the degree of fatigue damage.

[0035] Among them, nonlinear parameter calculation based on energy transfer is carried out, and a mathematical model between the nonlinear coefficient and fatigue cycles is established to provide a quantitative basis for the early diagnosis of fatigue damage.

[0036] Specifically, nonlinear ultrasonic testing experiments were conducted on the weld and base metal areas of the specimens. Frequency-amplitude diagrams containing the fundamental wave and second harmonic were obtained at different locations at different fatigue cycles. The nonlinear coefficient Beta calculated using the energy integration method was compared with the traditional nonlinear coefficient calculated using the relative amplitude of the fundamental wave (subscript A 1) and the relative amplitude of the second harmonic (subscript A 2). The relationship between fatigue severity and the nonlinear coefficient was then determined by comparing the coefficients with the fatigue cycles.

[0037] A pipeline fatigue damage detection system based on nonlinear ultrasonic technology includes: a nonlinear ultrasonic surface wave detection platform for acquiring the nonlinear response signal of the pipeline sample; a signal processing module for performing Fourier transform on the acquired signal, analyzing the signal's energy spectrum, and calculating the nonlinear coefficient; and a data analysis module for analyzing the variation pattern of the nonlinear coefficient under different fatigue cycles and providing data support for the quantitative assessment of fatigue damage.

[0038] The detection platform includes a radio frequency pulse transmitter and receiver, a duplexer, a signal selector, a terminal load, a filter group, piezoelectric probes of different frequencies and a universal oscilloscope.

[0039] The data analysis module calculates the transfer efficiency of the fundamental wave and the second harmonic energy by the energy transfer integral method, obtains the nonlinear coefficient, and performs a quantitative assessment of fatigue damage.

[0040] The present invention provides a nonlinear ultrasonic surface wave method for optimizing detection of fatigue damage in external pipelines, which adopts the following technical solutions:

[0041] The first step was to build the system platform: a complete nonlinear ultrasonic testing system was constructed to measure the nonlinear coefficients of ultrasonic surface waves within a specific area of ​​the test specimen. This system, integrating high-performance RF pulse excitation, signal reception, and processing modules, effectively captured the nonlinear response characteristics caused by surface fatigue damage, providing a solid technical support and data foundation for subsequent damage assessment and diagnosis.

[0042] The second step is to process the specimens: To better reflect the fatigue damage of pipelines in actual nuclear power plants, we use the same material, 316 steel and SA335 GRP-11 ferritic steel, to prepare the specimens. To distinguish the weld and the base material area in the fatigue specimens, a V-shaped groove is punched in the weld area of ​​the specimen and welded completely. The weld is then polished smooth. The batches of specimens made of the two materials are subjected to staged fatigue tests until they break.

[0043] The third step is to develop the test system and design the test parameters: After completing the test, experimentally verify the influence of multiple different factors, such as frequency, coupling agent, excitation voltage, etc., to minimize the influence of system nonlinearity and obtain the best experimental conditions.

[0044] The fourth step is signal processing using the energy transfer integral method: First, the concept of energy spectrum is introduced. The square of the frequency domain signal amplitude spectrum obtained by Fourier transform is called the energy spectrum. In order to further study the law of energy change with frequency, the energy spectrum density is introduced. The energy of the nonlinear ultrasonic signal in the fundamental frequency band and the second harmonic frequency band can be expressed as the integral over the fundamental frequency amplitude range and the double frequency amplitude range, respectively. The nonlinear coefficient is then further standardized by the integral result.

[0045] The fifth step is quantitative study of fatigue damage defects: by applying the above detection method to specimens with different fatigue cycles, nonlinear response data under different fatigue states are collected respectively to study the changes in the nonlinear characteristics of the material under different fatigue cycles.

[0046] As a possible embodiment of the present invention, in this embodiment, the construction of a nonlinear ultrasonic surface wave detection platform includes:

[0047] An experimental system based on a complete platform including RF pulse transmitter and receiver, duplexer, signal selector, terminal load, filter bank, piezoelectric probes of different frequencies and general oscilloscope;

[0048] Based on high-frequency broadband surface waves excited by a wedge at a certain angle.

[0049] As a possible embodiment of the present invention, in this embodiment, the 316 stainless steel and SA335GRP-11 ferritic steel samples are V-groove welded to form a weld area, and fatigue loading is performed to simulate actual pipeline fatigue damage, including:

[0050] 316 stainless steel and SA335 GRP-11 ferritic steel, which are more common in nuclear power plant pipelines, were used as test specimen materials;

[0051] Based on the V-shaped groove punched at the welding part of the specimen for welding the same metal, and the specimen after surface grinding treatment, it can help to study the effects of weld and base material on fatigue damage separately;

[0052] Based on the nonlinear ultrasonic testing results of each fatigue stage of the specimen subjected to staged fatigue loading, it is possible to observe how the nonlinear characteristics of the material gradually change with the number of fatigue cycles. The specimen is processed until it breaks.

[0053] As a possible embodiment of the present invention, in this embodiment, the nonlinear response signal of the specimens with different fatigue cycles is obtained using the above-mentioned detection platform, including:

[0054] The impact of different frequencies, different coupling agents, different excitation voltages and other factors on signal transmission and reception during the experiment;

[0055] The most suitable experimental parameters for detecting fatigue damage were determined based on the results of multiple repeated experiments.

[0056] As a possible implementation manner of the present invention, in this implementation manner, performing Fourier transform on the acquired signal to obtain the energy spectrum of the signal, and analyzing energy changes of the signal in the fundamental frequency and second harmonic frequency bands, includes:

[0057] The excitation signal is a radio frequency pulse signal, which is regarded as a square-integrable continuous signal f(t) and subjected to Fourier transform. The square of its amplitude is the energy spectral density φ(ω):

[0058]

[0059] Where ω is the angular frequency, φ(ω) is the energy spectral density function at the angular frequency, f(t) is the excitation signal, and F(ω) is the spectrum obtained after Fourier transform.

[0060] According to Parseval's theorem, the total energy of ultrasound is the integral of the energy spectrum density function over the entire frequency range;

[0061] The energy spectrum is obtained by frequency domain conversion based on Fourier transform and the square of the amplitude spectrum of the frequency domain signal;

[0062] Analyze the energy variation of the signal between the fundamental frequency and the second harmonic frequency band based on the energy spectrum density;

[0063] Based on the energy integration in the fundamental and second harmonic frequency bands, the nonlinear coefficients under different fatigue cycles are obtained.

[0064] As a possible embodiment of the present invention, in this embodiment, calculating the nonlinear coefficient and analyzing its variation with fatigue cycles to evaluate the evolution of fatigue damage in the pipeline includes:

[0065] Based on the data of base metal and weld position detection under different fatigue cycles;

[0066] Nonlinear parameter calculation based on energy transfer;

[0067] Based on the experimental results under different fatigue cycles, a comprehensive nonlinear evaluation model was constructed to analyze the degree of fatigue damage and its development trend.

[0068] On the other hand, the present invention also provides a pipeline defect detection device, comprising:

[0069] A signal acquisition module is used to acquire a nonlinear response signal of a pipeline sample through a nonlinear ultrasonic surface wave detection platform;

[0070] The signal processing module calculates the nonlinear coefficient to analyze the variation pattern of the nonlinear coefficient under different fatigue cycles and provides data support for the quantitative evaluation of fatigue damage.

[0071] The principles and features of the present invention are described below with reference to the accompanying drawings. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention. Figure 1 A schematic flow chart of an optimized method for quantitative assessment of fatigue damage in pipelines using nonlinear ultrasonic technology is presented.

[0072] The specific implementation steps can be divided into:

[0073] Step 1: Building an experimental platform is the basis for accurate detection. Compared with nonlinear acoustic detection methods such as longitudinal wave second harmonic method and mixing detection method, surface waves have the advantages of concentrated energy on the surface of the structure and long propagation distance. It only needs to place excitation and receiving transducers on one side of the workpiece to evaluate the surface damage of the workpiece to be tested. It is suitable for the detection of damage such as corrosion and fatigue on the steel surface. Figure 2 Shown is a schematic diagram of the system built in this study.

[0074] The experimental platform includes a Ritec RAM-5000 RF pulse transmitter and receiver (model: Ritec RAM-5000), a signal selector (model: RS-5-G2), a terminator (model: RT-50), a filter bank (model: RLP / RHP), a 1MHz piezoelectric probe (model: V103-RB / 0.5), a 2MHz piezoelectric probe (model: CN2R-24), a 2.25MHz piezoelectric probe (model: V106-RB / 0.5), a 5MHz piezoelectric probe (model: V109-RB / 0.5), and a general-purpose oscilloscope (model: GDS-2102E). The RAM-5000SNAP system outputs a 5MHz high-energy sinusoidal pulse signal. After impedance matching and filtering, it is applied to a narrowband longitudinal wave straight probe with a center frequency of 5MHz. This probe is paired with an angled acrylic surface wave wedge as the transmitting sensor. The signal is coupled to the sample surface via a couplant and propagates near the surface. A 10MHz narrowband ultrasonic probe and the corresponding wedge constitute the receiving sensor, which receives the propagated surface wave signal. The wedges are fully coupled to the probe and specimen using a coupling agent, and the wedge spacing is adjustable to enable measurements at varying propagation distances. The received signal is bandpass filtered and sampled and displayed on a digital oscilloscope. The steady-state signal is windowed and Fast Fourier Transformed on a computer to obtain the fundamental amplitude A1 and the second harmonic amplitude A2, allowing calculation of the relative nonlinear coefficient at varying propagation distances. For a fixed propagation distance, the signal passes through the damaged area, and five repeated measurements are performed on each specimen. The average value is taken as the test result, and the nonlinear coefficient is normalized.

[0075] Step 2: To ensure that the specimens can reflect the fatigue damage of actual nuclear power plant pipelines, the preparation of the specimens and the experimental design are crucial. 316 stainless steel and SA335 GRP-11 ferritic steel are used as the specimen materials. These two materials are more common in nuclear power plant pipelines and can represent the fatigue damage behavior of different types of materials. Figure 3 、 Figure 4 Schematic diagrams showing the fatigue specimens of the manufactured batches are shown respectively.

[0076] Weld seam preparation: A V-shaped groove is created at the weld site of the specimen and the surface is ground. This simulates cracks and other defects in the weld seam, helping to study the effect of the weld on fatigue damage.

[0077] Fatigue test: After the specimen is processed, it is subjected to staged fatigue loading until it breaks. Through ultrasonic testing at each fatigue stage, it is possible to observe how the nonlinear characteristics of the material gradually change with the number of fatigue cycles. The classic stress-strain constitutive relationship can be described as:

[0078] σ=Eε

[0079] Among them, σ represents stress, E represents elastic modulus, and ε represents strain. In an ideal linear elastic material, the elastic modulus E is a constant and the material exhibits linear elasticity. P11 carbon steel is a low alloy steel, and 316 stainless steel is a high-strength austenitic stainless steel. Compared with P11, 316 has higher plasticity and more stable elastic behavior. P11 carbon steel has a lower yield strength, so it is easier to enter the plastic deformation stage under the action of force. Plastic deformation is manifested as a nonlinear relationship between stress and strain. Its constitutive relationship can be described by introducing the nonlinear elastic modulus C:

[0080] σ=Eε+Cε 2

[0081] Where σ represents stress, E represents elastic modulus, ε represents strain, and C represents nonlinear elastic modulus.

[0082] Step 3: Develop the test system and design the test parameters

[0083] In order to ensure the accuracy and reliability of the detection system, a complete test system was designed, and the influence of different parameters on system performance was verified through experiments. Figure 5 The fitting of the nonlinear coefficients of the system is shown to characterize its stability effect.

[0084] The impact of factors such as frequency, couplant, and excitation voltage: During the experiment, different frequencies, couplant types, and excitation voltages were tested to study their impact on signal transmission and reception. By adjusting these parameters, the nonlinear effects of the system can be reduced and the experimental results can be optimized.

[0085] Determination of optimal experimental conditions:

[0086] During the experiment, systematic parameter optimization was conducted on key factors affecting fatigue damage detection. First, piezoelectric probes of different frequencies were selected as excitation and receiving devices. The effects of frequency combinations such as 1MHz and 2MHz, 2MHz and 4MHz, and 2.25MHz and 5MHz on detection sensitivity and signal-to-noise ratio were tested. Repeated tests were then conducted to measure the sensitivity and stability of the nonlinear signal response to defects. Through repeated measurements and comparative analysis, it was found that the optimal nonlinear signal response was achieved when a frequency of 2MHz was used as the excitation source and a frequency of 4MHz was used as the receiving probe, showing higher sensitivity and stability. In addition, high-frequency probes were more sensitive to damage.

[0087] Secondly, regarding the selection of coupling agents, the experiment compared the coupling effects of commonly used coupling agents and engine oil. The results showed that engine oil, due to its good acoustic impedance matching and lubrication properties, significantly improved the ultrasonic energy transmission efficiency and signal stability when used as a coupling agent, enhancing the detection of fatigue damage.

[0088] In addition, the impact of excitation voltage levels was systematically tested, covering multiple voltage levels ranging from 2 to 70. When studying nonlinear acoustic phenomena, the use of high-power ultrasonic technology necessitates the selection of an appropriate excitation voltage. Excessively low excitation voltages prevent the acquisition of higher-resolution second harmonics, while excessively high voltages lead to the appearance of higher-order harmonics, which can affect the observation of nonlinear coefficients. Figure 7 Shows the voltage of A2 and A1 when changing the voltage value from 2 to 70. 2 The relationship between Figure 7 It can be seen that when the voltage is too low, the nonlinear coefficient β represented by the slopes of the two is greatly affected by the voltage. When the voltage level is too high, the nonlinear coefficient β shows a certain instability. Therefore, the optimal voltage should be selected at a medium level. Similarly, our analysis results based on the half-cycle phase difference show that the phase change reaches 180°, which has a high degree of credibility.

[0089] Figure 6 The amplitudes of A2 and A3 at different excitation voltage levels are shown. Figure 6 It can be seen that when the excitation voltage is low, the amplitude of A2 is greater than the third harmonic and the third harmonic grows slowly. Then, when the voltage exceeds a certain value, the amplitude of the third harmonic increases rapidly and increases to several times the amplitude of the second harmonic. Figure 6 As can be seen, the amplitude of the 45° voltage level is close to this fixed value, so we conservatively choose the 40° voltage level. And from the results of changing the phase by 180°, the repeatability and reliability of this result are relatively high.

[0090] When the voltage level is set at 40V, the excitation signal strength is moderate, which not only avoids the nonlinear distortion of the probe that may be caused by excessive voltage, but also ensures sufficient signal amplitude, thus achieving the best detection performance.

[0091] The entire optimization process employed repeated experiments to ensure the repeatability and reliability of the results. Detailed records were kept of the signal amplitude, signal-to-noise ratio, and nonlinear coefficient during each parameter change. Ultimately, comprehensive evaluation determined the optimal experimental conditions to be 2MHz excitation, 4MHz reception, oil coupling, and a 40V excitation voltage, providing reliable assurance for efficient and stable fatigue damage detection.

[0092] Step 4: Signal processing of energy transfer integration method:

[0093] In order to optimize and analyze nonlinear ultrasonic signals, the energy transfer integral method is introduced. Figure 8The fundamental wave frequency domain waveform and a zoomed-in image are shown. The fundamental wave peak value fluctuates significantly, as does the second harmonic peak value. Using the traditional nonlinear ultrasonic coefficient β to characterize the debonding defect size would significantly affect accuracy. Therefore, a method based on energy instead of amplitude is proposed.

[0094] Fourier transform, energy spectrum, and energy spectral density: The definition is as follows: The square of the frequency domain signal amplitude spectrum obtained by Fourier transform is called the energy spectrum, which represents the amount of energy within a unit frequency band and is represented by E. In order to further study the law of energy variation with frequency, the concept of energy spectral density is introduced. In this experiment, the RAM-5000SNAP nonlinear high-energy acoustic detection system is used. The excitation signal is an RF pulse signal, which is regarded as a square-integrable continuous signal f(t) and Fourier transform is performed. The square of its amplitude is the energy spectral density φ(ω):

[0095]

[0096] Where ω is the angular frequency, φ(ω) is the energy spectral density function at the angular frequency, f(t) is the excitation signal, and F(ω) is the spectrum obtained after Fourier transform.

[0097] According to Parseval's theorem, the total energy of ultrasound is the integral of the energy spectrum density function over the entire frequency range:

[0098]

[0099] Where E represents the total energy of the ultrasonic signal, F(ω) is the spectrum obtained after Fourier transform, φ(ω) is the energy spectral density function of the signal with respect to ω, and φ(f) is the energy spectral density function of the signal with respect to f. From the above formula, we can see that the energy of the nonlinear ultrasonic signal in the fundamental frequency band and the second harmonic frequency band can be expressed as the integral over the interval [f1, f2] and the interval [f3, f4], respectively, thus obtaining:

[0100]

[0101] Where φ(f) is the energy spectral density function of the signal with respect to f, [f1, f2] and [f3, f4] are the ranges of the fundamental frequency band and the second harmonic frequency band, respectively.

[0102] First, the Fourier transform is used to convert the time-domain signal into the frequency domain. By calculating the square of the frequency-domain signal's amplitude spectrum, the signal's energy spectrum is obtained. The energy spectrum reveals the signal's energy distribution across different frequency bands, helping to analyze the signal's nonlinear characteristics. The concept of energy spectral density is introduced to analyze the energy variation between the fundamental frequency and the second harmonic frequency band. This method allows for a quantitative description of the material's nonlinear effects as fatigue progresses, based on the perspective of energy transfer.

[0103] The energy integral is calculated and normalized over the fundamental and second harmonic frequency bands to obtain the nonlinear coefficient at different fatigue cycles. This coefficient can provide quantitative information about the damage extent and assist in fatigue damage assessment.

[0104] Step 5: Quantitative study of fatigue damage defects

[0105] Figure 9 and Figure 10 The nonlinear ultrasonic results of 316 and P11 specimens with different fatigue cycles are shown respectively. By performing nonlinear ultrasonic testing on specimens with different fatigue cycles, the evolution process of fatigue damage is quantitatively studied. The specific steps include:

[0106] Correlation between fatigue cycles and nonlinear parameters: By comparing the nonlinear coefficients at different fatigue cycles, the changes in the material's nonlinear characteristics are analyzed. As the fatigue cycles increase, the material's nonlinear response gradually intensifies, especially in the weld area, revealing the development trend of microcracks.

[0107] Nonlinear parameter calculation based on energy transfer: Using the energy transfer method, we analyze the transfer efficiency of the fundamental and second harmonic energy and establish a mathematical model between the nonlinear coefficient and fatigue cycles. This model can be used to provide a quantitative basis for early diagnosis of fatigue damage.

[0108] Quantitative Assessment of Fatigue Damage: Based on experimental results at different fatigue cycles, a comprehensive nonlinear assessment model is constructed to quantitatively analyze the length, location, and development trend of microcracks. This model provides a scientific basis for regular pipeline inspection, maintenance, and repair, ensuring the long-term operational safety of pipelines.

[0109] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for quantitatively evaluating fatigue damage in pipelines using nonlinear ultrasonic technology, characterized by: 316 stainless steel and SA335 GRP-11 ferritic steel specimens were used to form the weld area through V-groove welding and fatigue loading was applied to simulate actual pipeline fatigue damage. For specimens with different fatigue cycles, the nonlinear response signals of the specimens are obtained; the obtained signals are Fourier transformed to obtain the energy spectrum of the signals, and the energy changes of the signals in the fundamental frequency and second harmonic frequency bands are analyzed; The nonlinear coefficient is calculated and its variation with fatigue cycles is analyzed to evaluate the evolution of fatigue damage in the pipeline.

2. The method for quantitatively evaluating fatigue damage in pipelines using nonlinear ultrasonic technology according to claim 1 is characterized by: The target welding area of ​​the sample is polished, and a V-shaped groove is processed before welding the same metal. When welding 316 stainless steel samples, the welding wire used is ER316L, with a size of Φ2.5mm and a weight of 5kg. When welding ferritic steel samples, the welding wire used is ER80S-G, with a size of Φ2.5mm and a weight of 1.5kg. After welding, the weld needs to be polished to determine the weld quality.

3. The method for quantitatively evaluating fatigue damage in pipelines using nonlinear ultrasonic technology according to claim 1 is characterized by: The yield strength of 316 stainless steel and ferritic steel specimens after welding is determined by subjecting standard specimens to tensile tests. Continuous fatigue loading is then applied to batch fatigue specimens of 316 stainless steel and ferritic steel until the specimens fracture due to fatigue or the preset number of cycles is reached. During the experiment, the specimens will undergo continuous loading and unloading within the set stress or strain range. This cyclic process will cause changes in the internal microstructure of the material, ultimately leading to material failure.

4. The method for quantitatively evaluating fatigue damage in pipelines using nonlinear ultrasonic technology according to claim 1 is characterized by: The square of the frequency domain signal amplitude spectrum obtained by Fourier transform is called the energy spectrum. The transfer efficiency of the fundamental wave and the second harmonic energy is calculated by the transfer integral method of the energy spectrum. The generation of higher harmonics is regarded as the transfer of sound wave energy from the low frequency band to the high frequency band. The energy transfer efficiency is used to characterize the nonlinear parameters of the specimen to quantitatively evaluate the degree of fatigue damage.

5. The method for quantitatively evaluating fatigue damage in pipelines using nonlinear ultrasonic technology according to claim 1 is characterized in that: Nonlinear parameter calculation based on energy transfer is performed, and a mathematical model between the nonlinear coefficient and fatigue cycles is established: nonlinear ultrasonic testing experiments are carried out on the weld area and base material area of ​​the specimen respectively, and frequency-amplitude diagrams containing the fundamental wave and second harmonic at different positions with different fatigue cycles are obtained. The nonlinear coefficient Beta calculated by the energy integration method is compared with the traditional nonlinear coefficient calculated by the fundamental wave amplitude A1 and the second harmonic amplitude A2, and the comparison is made with the fatigue cycles to obtain the relationship between the fatigue degree and the nonlinear coefficient.

6. The method for quantitatively evaluating fatigue damage in pipelines using nonlinear ultrasonic technology according to claim 1 is characterized by: The RAM-5000SNAP nonlinear high-energy ultrasonic testing system outputs a high-energy sinusoidal pulse signal with a frequency of 5MHz. After impedance matching and filtering, it is loaded into a narrowband longitudinal wave straight probe with a center frequency of 5MHz. The probe is used with a plexiglass surface wave wedge as the transmitting sensor. The signal is coupled to the sample surface through a coupling agent and propagates along the near-surface. The receiving end is composed of a 10MHz narrowband ultrasonic probe and a corresponding wedge to form a receiving sensor to receive the propagated surface wave signal. The wedge is fully coupled to the probe and the sample with a coupling agent. The wedge spacing is adjustable to achieve measurement at different propagation distances. The received signal is bandpass filtered and sampled and displayed by a digital oscilloscope. The steady-state signal is windowed and fast Fourier transformed on the computer to obtain the fundamental wave amplitude A1 and the second harmonic amplitude A2, thereby calculating the relative nonlinear coefficient at different propagation distances.

7. The method for quantitatively evaluating fatigue damage in pipelines using nonlinear ultrasonic technology according to claim 6, characterized in that: When the propagation distance is fixed, the signal passes through the damaged area, and the measurement is repeated five times for each sample. The average value is taken as the detection result, and the nonlinear coefficient is normalized.

8. The method for quantitatively evaluating fatigue damage in pipelines using nonlinear ultrasonic technology according to claim 6, characterized in that: The optimal experimental conditions were determined to be 2MHz excitation, 4MHz reception, oil coupling and 40V excitation voltage.

9. The method for quantitatively evaluating fatigue damage in pipelines using nonlinear ultrasonic technology according to claim 1, characterized in that: The signal acquisition module is used to obtain the nonlinear response signal of the pipeline sample; the signal processing module is used to perform Fourier transform on the obtained signal, analyze the energy spectrum of the signal, and calculate the nonlinear coefficient; The data analysis module is used to analyze the variation of the nonlinear coefficient under different fatigue cycles and perform quantitative evaluation of fatigue damage.

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