A method and system for engine block detection based on plane wave reverse time migration

Abstract

The application provides an engine cylinder detection method and system based on plane wave reverse time migration, which comprises the following steps: arranging a plurality of linear ultrasonic transducer arrays in an automobile engine cylinder; dividing a plurality of depth layers according to the depth size of the automobile engine cylinder; applying pulses of corresponding angles by the linear ultrasonic transducer arrays and collecting original reflected wave field signals corresponding to each depth layer; pre-processing the original reflected wave field signals to obtain processed reflected wave field signals; obtaining a three-dimensional model of the automobile engine cylinder; performing plane wave forward continuation and reflected wave backward continuation based on the processed reflected wave field signals and the three-dimensional model to output a three-dimensional defect imaging graph; and performing defect analysis on the three-dimensional defect imaging graph to output a defect detection result. The application solves the core pain points of low precision, poor coverage, weak anti-interference and low efficiency of the existing engine cylinder detection technology, and forms multi-dimensional technical advantages.

Description

Technical Field

[0001] This invention belongs to the technical field of automotive engine cylinder block testing, specifically relating to an engine cylinder block testing method and system based on plane wave reverse time offset. Background Technology

[0002] The inspection of automotive engine blocks mainly relies on three types of technical solutions, as follows:

[0003] 1. Traditional penetrant testing: Represented by the water penetration test, this method involves immersing the tank in a penetrant solution and using the liquid penetration effect to detect surface and near-surface defects. Subsequent steps such as cleaning and development are required to determine the presence of defects. It is mainly used to identify through-hole or surface opening defects.

[0004] 2. Conventional ultrasonic testing: Single-channel or multi-channel ultrasonic flaw detectors are used, along with single or small transducer arrays. Ultrasonic echo signals are acquired by point-by-point scanning or simple surface scanning. The location and size of defects are initially determined by parameters such as echo amplitude and propagation time. The images are mostly two-dimensional grayscale images with low resolution.

[0005] 3. General Reverse Time Migration Algorithm Class: This class directly transfers mature reverse time migration techniques (such as adaptive process function equation solving and least squares reverse time migration) from the oil exploration field to cylinder block detection. It does not adjust the algorithm parameters for cylinder block characteristics, and only generates defect images through general wave field extension and imaging conditions, without considering the special characteristics of cylinder block materials and structures.

[0006] Based on the actual needs of cylinder block testing (high precision, full coverage, and anti-interference), existing technical solutions have four core problems:

[0007] 1. Limited defect detection capability: Traditional water infiltration test method cannot identify internal non-penetrating defects (such as deep pores and closed cracks), and has insufficient sensitivity to small defects (size <0.5mm); conventional ultrasonic testing has low resolution and is difficult to distinguish between 0.1-0.3mm microcracks and material grain noise, with a defect detection rate of less than 85%.

[0008] 2. Poor depth coverage and positioning accuracy: Existing ultrasonic testing mostly uses a fixed array angle, which has a detection blind zone in the deep area of ​​the cylinder (depth > 150mm) and does not correct for wave velocity attenuation in the depth direction, resulting in a positioning error of > ±0.3mm for deep defects; the general reverse time migration algorithm does not optimize the depth direction grid and imaging parameters, resulting in poor consistency of defect imaging in different depth layers and easy "blurring" of deep defects.

[0009] 3. Weak anti-interference capability: The complex cavity structure inside the cylinder, such as the water jacket and oil passage, will generate wave field scattering interference. Existing technologies lack targeted noise reduction mechanisms, and crosstalk noise can easily mask defect signals. At the same time, the influence of temperature and material grain size on wave velocity is not considered. When the cylinder temperature deviates from the standard value of 25℃, the wave velocity error will cause the defect positioning deviation to be further expanded.

[0010] 4. Low testing efficiency and automation: The water penetration test method requires multiple steps such as soaking, cleaning, and imaging. The testing time for a single cylinder is more than 25 minutes, which cannot be adapted to online testing on the production line. Conventional ultrasonic testing relies on manual adjustment of the scanning path and parameters, and quantitative analysis requires manual interpretation. The operation threshold is high and it is easily affected by human factors, making it difficult to achieve full-process automation. Summary of the Invention

[0011] To address the aforementioned technical problems, this invention provides an engine cylinder block detection method and system based on plane wave reverse time offset, which solves the technical problems in the prior art.

[0012] In a first aspect, the present invention provides the following technical solution: an engine cylinder block detection method based on plane wave reverse time offset, comprising:

[0013] A number of linear ultrasonic transducer arrays are set in the cylinder of an automobile engine. The cylinder is divided into several depth layers according to its depth dimension. Pulses of corresponding angles are applied through the linear ultrasonic transducer arrays and the original reflected wave field signal corresponding to each depth layer is collected.

[0014] The original reflected wave field signal is preprocessed to obtain the processed reflected wave field signal;

[0015] A three-dimensional model of the automobile engine cylinder block is obtained, and a plane wave forward continuation and a reflected wave reverse continuation are performed based on the processed reflected wave field signal and the three-dimensional model to output a three-dimensional defect imaging map.

[0016] Defect analysis is performed on the three-dimensional defect image to output defect detection results.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0018] 1. In terms of hardware, a linear ultrasonic transducer array is arranged along the depth direction of the cylinder block, combined with depth dimension recognition, to achieve precise control of the detection dimension; in terms of software, an innovative inverse time-shifting algorithm with material wave velocity constraint and depth attenuation compensation is introduced. Through the modified elastic wave equation and high-order finite difference method, numerical dispersion error is effectively suppressed. The defect location error is ≤ ±0.12mm, the size measurement error is ≤ ±0.05mm, and the volume calculation error is ≤ ±0.001mm³. Compared with traditional ultrasonic testing, the positioning accuracy is improved by 2 times and the size accuracy is improved by 3 times. It can accurately identify micro-pores as small as 0.1mm and micro-cracks as deep as 0.2mm, meeting the detection requirements of high-end engines for micro-defects.

[0019] 2. In view of the structural characteristics of high incidence of defects in the thick area of ​​cylinder wall and no defects in the cavity area, a non-uniform three-dimensional mesh is adopted, combined with wave field constrained imaging conditions, which improves the defect imaging resolution to 0.1mm, more than 3 times higher than the traditional reverse time migration algorithm. The imaging results can clearly present the three-dimensional morphology of the defects, avoiding the defect misjudgment caused by the blurring of the traditional two-dimensional grayscale image. For example, it can accurately distinguish the crack step difference of 0.1mm in the depth direction, providing accurate data support for subsequent defect cause analysis.

[0020] 3. Introducing real-time temperature-wave velocity correction, when the temperature fluctuates by ±5℃, the wave velocity correction error is ≤0.3%, avoiding defect location deviation caused by temperature, and still being able to conduct stable detection in complex workshop environments. For the wave field scattering problem generated by cavity structures such as cylinder water jacket and oil passage, the combination strategy of low-precision mesh in cavity area + PML absorbing boundary + wave field constraint functional effectively suppresses the interference of cavity scattering signal on defect imaging.

[0021] 4. Through technological innovations in hardware precision, software intelligence, and process standardization, it comprehensively surpasses existing technologies in terms of detection accuracy, coverage, anti-interference capability, efficiency, automation level, and adaptability. It can be widely used in online production line inspection of automotive engine cylinder blocks, factory quality sampling inspection, and after-sales fault analysis, providing the automotive manufacturing industry with high-precision, high-efficiency, and high-reliability non-destructive testing solutions, helping enterprises improve product quality, reduce production costs, and optimize production efficiency.

[0022] Preferably, the step of preprocessing the original reflected wave field signal to obtain the processed reflected wave field signal includes:

[0023] The original reflected wave field signal is bandpass filtered using a preset filter to obtain a filtered reflected wave field signal.

[0024] The filtered reflected wave field signal is decomposed into wavelets, and residual noise in the high-frequency details after decomposition is removed by an adaptive threshold method to obtain a denoised reflected wave field signal.

[0025] Temperature data and cylinder depth data are collected. Based on the temperature data and the temperature wave velocity fitting curve in the material property database, the wave velocity is corrected to obtain the corrected wave velocity. Based on the cylinder depth data, the acquisition time of the reflected wave field signal at different depth layers is adjusted to obtain the adjusted acquisition time. Based on the corrected wave velocity and the adjusted acquisition time, the denoised reflected wave field signal is updated to obtain the updated reflected wave field signal.

[0026] A cross-correlation phase alignment algorithm is used to perform phase correction processing on the updated reflected wave field signal using the same group of linear arrays to obtain the processed reflected wave field signal.

[0027] Preferably, the preset filter is a Chebyshev Type I filter with a passband of 1-8MHz and a stopband attenuation of ≥60dB.

[0028] Preferably, the step of performing plane wave forward continuation and reflected wave reverse continuation based on the processed reflected wave field signal and the three-dimensional model to output a three-dimensional defect imaging map includes:

[0029] Construct a mesh model based on the aforementioned 3D model;

[0030] Based on the processed reflected wave field signal, the mesh model is extended by plane wave forward and the elastic wave equation is constructed:

[0031] ;

[0032] In the formula, For wave field displacement, Let be the material wave velocity distribution function. This is the depth attenuation coefficient. For grid coordinates, For discrete time steps;

[0033] The elastic wave equation is solved using the higher-order finite difference method, and a perfectly matched layer absorbing boundary condition is introduced to obtain the spatiotemporal distribution of the positive wave field. ;

[0034] Defect-reflected wave components are extracted from the processed reflected wave field signal. Using the cylinder surface at the corresponding depth layer as the boundary, a reverse continuation is performed based on these defect-reflected wave components using the same finite difference method as the forward continuation of plane waves, to obtain the spatiotemporal distribution of the reverse wave field. ;

[0035] Based on the aforementioned positive wave field spatiotemporal distribution The spatiotemporal distribution of the reverse wave field Construct the objective function :

[0036] ;

[0037] In the formula, For constraint coefficients, For wave velocity gradient, For the gradient of imaging parameters, For compensation coefficient, As a depth decay factor, Image of the target defect;

[0038] The minimum value of the objective function is solved by the conjugate gradient method to obtain the target defect image corresponding to each depth layer. The target defect images of each depth layer are then stitched together to obtain a three-dimensional defect image.

[0039] Preferably, the step of constructing a mesh model based on the three-dimensional model specifically includes:

[0040] An adaptive tetrahedral meshing algorithm is used to mesh the 3D model, identify the cylinder block structural features of the 3D model, and adjust the mesh accuracy based on the cylinder block structural features to obtain the mesh model.

[0041] Preferably, the step of performing defect analysis on the three-dimensional defect image to output defect detection results specifically includes:

[0042] The three-dimensional defect image is subjected to three-dimensional threshold segmentation and morphological filtering to obtain a processed image. The three-dimensional coordinates, size parameters and volume parameters of the defect in the processed image are calculated to obtain the core parameters of the defect. The defect is classified according to the preset automotive industry engine block defect judgment standard and based on the core parameters of the defect to obtain the defect detection result.

[0043] Secondly, the present invention provides the following technical solution: an engine cylinder block detection system based on plane wave reverse time offset, the system comprising:

[0044] The detection module is used to set up several linear ultrasonic transducer arrays in the cylinder of an automobile engine, divide the cylinder of the automobile engine into several depth layers according to the depth dimension, apply pulses of corresponding angles through the linear ultrasonic transducer arrays and collect the original reflected wave field signal corresponding to each depth layer.

[0045] The processing module is used to preprocess the original reflected wave field signal to obtain a processed reflected wave field signal;

[0046] The extension module is used to acquire a three-dimensional model of the automobile engine cylinder block, and perform plane wave forward extension and reflected wave reverse extension based on the processed reflected wave field signal and the three-dimensional model to output a three-dimensional defect imaging map.

[0047] The output module is used to perform defect analysis on the three-dimensional defect image to output the defect detection results.

[0048] Preferably, the output module is specifically used for:

[0049] The three-dimensional defect image is subjected to three-dimensional threshold segmentation and morphological filtering to obtain a processed image. The three-dimensional coordinates, size parameters and volume parameters of the defect in the processed image are calculated to obtain the core parameters of the defect. The defect is classified according to the preset automotive industry engine block defect judgment standard and based on the core parameters of the defect to obtain the defect detection result.

[0050] Thirdly, the present invention provides the following technical solution: a computer, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the engine cylinder block detection method based on plane wave counter-time offset as described above.

[0051] Fourthly, the present invention provides the following technical solution: a storage medium storing a computer program, wherein when the computer program is executed by a processor, it implements the engine cylinder block detection method based on plane wave counter-time offset as described above. Attached Figure Description

[0052] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art 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.

[0053] Figure 1 The flowchart shows the engine cylinder block detection method based on plane wave reverse time offset provided in Embodiment 1 of the present invention.

[0054] Figure 2 This is a structural block diagram of the engine cylinder block detection system based on plane wave reverse time offset provided in Embodiment 2 of the present invention;

[0055] Figure 3 This is a schematic diagram of the hardware structure of a computer provided for another embodiment of the present invention.

[0056] The embodiments of the present invention will be further described below with reference to the accompanying drawings. Detailed Implementation

[0057] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain embodiments of the present invention, and should not be construed as limiting the present invention.

[0058] Example 1

[0059] In Embodiment 1 of the present invention, as Figure 1 As shown, an engine cylinder block detection method based on plane wave reverse time offset includes:

[0060] S1. A plurality of linear ultrasonic transducer arrays are set in the cylinder of an automobile engine. The cylinder is divided into several depth layers according to the depth dimension of the automobile engine. Pulses of corresponding angles are applied through the linear ultrasonic transducer arrays and the original reflected wave field signal corresponding to each depth layer is collected.

[0061] Specifically, the hardware structure of this application is as follows:

[0062] 1. Cylinder body clamping fixture

[0063] The main body of the fixture adopts a high-strength aluminum alloy frame, which has the characteristics of lightweight and high rigidity, and can be adapted to mainstream engine block sizes of 300-600mm in length, 200-400mm in width, and 150-300mm in depth. Adjustable clamping mechanisms are set on the top and sides of the fixture, which are driven by servo motors to achieve automatic centering and clamping of cylinder blocks of different sizes, avoiding positioning deviations caused by manual adjustments. A high-temperature resistant silicone pad is laid at the bottom to prevent scratches on the cylinder block surface and to buffer vibration interference during the testing process.

[0064] 2. Environmental monitoring integration

[0065] The fixture incorporates two high-precision temperature sensors, positioned on the top and middle surfaces of the cylinder block respectively. With a sampling frequency of 1Hz and a measurement accuracy of ±0.5℃, it can monitor temperature changes in real time during cylinder block inspection. Temperature data is transmitted to the main control unit via an RS485 bus, providing real-time data support for subsequent wave velocity correction. Because the elastic wave velocity of the cylinder block material changes significantly with temperature—decreasing by approximately 1.2% when the temperature rises from 25℃ to 45℃—failure to correct this in real time would lead to defect location errors exceeding ±0.5mm, far exceeding the required inspection accuracy. Furthermore, a laser displacement sensor is mounted on the side of the fixture, with a measurement range of 0-300mm and an accuracy of ±0.01mm. This sensor can automatically identify the cylinder block depth, providing a basis for layer thickness division in subsequent layered inspections and avoiding layering deviations caused by manual dimension input.

[0066] 3. Linear ultrasonic transducer array

[0067] Arrange 2-4 linear arrays along the cylinder depth direction (from the top cylinder head mounting surface to the bottom of the cylinder). The specific number depends on the cylinder depth: 2 arrays for 150-200mm depth, 3 arrays for 200-250mm depth, and 4 arrays for 250-300mm depth. Ensure that the detection range of adjacent arrays has a 10-15mm overlap area to avoid detection blind spots in the depth direction, ultimately achieving depth coverage ≥95%. Each array is perpendicular to the mounting surface, and the array length matches the cylinder width (200-400mm). The array elements are evenly distributed along the array length, with a spacing of 4-6mm between adjacent array elements. This spacing design is based on ultrasonic length calculations: the center frequency of the array element is 2-5MHz, corresponding to a wavelength of 1.26-3.15mm in aluminum alloy (wave velocity 6300m / s). The spacing is 1.5-2 times the wavelength to avoid signal crosstalk between array elements while ensuring wave field coverage density.

[0068] The array element employs a piezoelectric ceramic transducer, featuring high electromechanical coupling coefficient and low loss characteristics. Its core parameters are as follows: Center frequency: Adjustable from 2-5MHz, selected based on defect size—5MHz for detecting tiny pores of Φ0.1-0.3mm (shorter wavelength, higher resolution), and 2MHz for detecting cracks larger than 1.0mm (stronger penetration, deeper coverage); Bandwidth: ≥70% (-6dB), effectively receiving reflected signals across a wide frequency range, avoiding defect information loss due to a single signal frequency; Sensitivity: ≥-60dB (reference sensitivity 0dB=1V / μPa), ensuring the capture of weak reflected signals (amplitude ≤10μV) from deep defects (depth > 200mm); Operating temperature: -20℃-80℃, adaptable to fluctuating workshop temperatures, avoiding performance degradation caused by low or high temperatures. Furthermore, the array element surface is covered with a wear-resistant ceramic protective layer with a hardness ≥HV1200, capable of withstanding frictional wear during long-term testing, extending its service life.

[0069] 4. Multi-channel signal excitation and acquisition

[0070] Employing a 16-channel independent pulse generator, each channel can output a square wave pulse signal with a peak voltage of 50-200V and a pulse width of 10-50ns, supporting plane wave excitation in three directions: -15°, 0°, and 15°. Angle control is achieved by adjusting the excitation delay of adjacent array elements: with 0° excitation as the reference, the delay time between adjacent array elements is t1=Δx×sin15° / v when excitation is at -15° (Δx is the array element spacing, and v is the material wave velocity), and the delay time is t2=Δx×sin15° / v when excitation is at 15°, ensuring that plane waves in different directions form a uniformly covering wave field inside the cylinder. The pulse generator supports synchronous triggering, which can achieve excitation-acquisition timing synchronization with the acquisition module through an external trigger signal (TTL level). The synchronization error is ≤10ns, avoiding wave field data misalignment caused by timing deviation. If the synchronization error exceeds 50ns, it will cause the time coordinate deviation of deep defects (depth > 200mm) to be >0.3μs, corresponding to a depth error >0.6mm, which directly affects the detection accuracy.

[0071] Employing a 32-channel synchronous data acquisition card with an adjustable sampling frequency of 50-100MHz, a 16-bit sampling bit depth, and an input range of ±10V, it can acquire reflected wavefield signals received by a linear array in real time. The acquisition card supports both hardware and software triggering modes; hardware triggering is used during detection to ensure strict synchronization between excitation and acquisition. It also features a built-in anti-aliasing filter to effectively suppress high-frequency noise. The acquisition card connects to the computer via a PCIe 3.0 bus, achieving a data transfer rate of ≥8GB / s, enabling real-time transmission of massive amounts of wavefield data and avoiding acquisition interruptions due to data buffering, thus ensuring a continuous detection process.

[0072] An automatic coupling agent spraying device is employed, using a water-soluble ultrasonic coupling agent with an acoustic impedance close to that of aluminum alloy, which reduces acoustic energy reflection loss between the array elements and the cylinder surface. The device controls the spray volume via a peristaltic pump and automatically adjusts the spray position according to the cylinder surface flatness, ensuring good coupling between the array elements and the cylinder surface at all times and avoiding signal amplitude attenuation due to poor coupling. All hardware module cables are shielded to avoid the impact of electromagnetic interference from the workshop on the wave field data. The outer shell of the signal excitation-acquisition module is made of galvanized steel plate, with internal absorbing material to absorb internal electromagnetic radiation and ensure that the module itself has no electromagnetic leakage interference.

[0073] S2. The original reflected wave field signal is preprocessed to obtain the processed reflected wave field signal;

[0074] Step S2 includes:

[0075] S21. The original reflected wave field signal is bandpass filtered using a preset filter to obtain a filtered reflected wave field signal.

[0076] The preset filter is a Chebyshev Type I filter with a passband of 1-8MHz and a stopband attenuation of ≥60dB. It can effectively suppress low-frequency vibration noise (<1MHz) and electronic noise (>8MHz) in the workshop environment. In the workshop environment, the noise frequency generated by machine tool vibration is mostly 0.1-0.8MHz, and the electronic noise of the acquisition card is mostly 10-20MHz. The bandpass filter can directly filter these two types of noise, improving the signal-to-noise ratio by ≥15dB.

[0077] S22. Perform wavelet decomposition on the filtered reflected wave field signal and remove residual noise in the high-frequency details after decomposition using an adaptive threshold method to obtain a denoised reflected wave field signal.

[0078] Specifically, the db4 wavelet basis is used with 5 decomposition layers to perform wavelet decomposition on the filtered signal. Residual noise in high-frequency details is removed by adaptive thresholding (based on the Birgé-Massart strategy) while preserving the characteristic information of the defect reflection signal. This algorithm can further improve the signal-to-noise ratio by ≥8dB without losing signal details, ensuring the signal quality of subsequent imaging.

[0079] S23. Collect temperature data and cylinder depth data. Based on the temperature data and by calling the temperature wave velocity fitting curve in the material property database, correct the wave velocity to obtain the corrected wave velocity. Based on the cylinder depth data, adjust the acquisition time of the reflected wave field signal at different depth layers to obtain the adjusted acquisition time. Based on the corrected wave velocity and the adjusted acquisition time, update the denoised reflected wave field signal to obtain the updated reflected wave field signal.

[0080] Among them, based on the real-time temperature data collected by the tooling, the temperature wave velocity fitting curve in the material property database is called to correct the wave velocity in real time, so as to avoid wave velocity errors caused by temperature. At the same time, according to the cylinder depth identified by the laser displacement sensor, the acquisition time of different depth layers is compensated. For every 50mm increase in depth, the wave field propagation time increases by about 15.87μs. Therefore, the acquisition time is extended by 2-5μs for every 50mm increase in depth, with a 20%-30% redundancy reserved to ensure that the complete reflection signal is captured and to avoid the deep defect signal being truncated.

[0081] S24. The cross-correlation phase alignment algorithm is used to perform phase correction processing on the updated reflected wave field signal using the same group of linear arrays to obtain the processed reflected wave field signal.

[0082] Specifically, to address the phase deviation of each element within the same linear array (which can reach 5°-10° due to differences in element manufacturing processes), a cross-correlation phase alignment algorithm is employed: using the signal of the center element as a reference, the cross-correlation coefficients of other element signals and the reference signal are calculated. Based on the time difference corresponding to the peak cross-correlation value, the phase of each element signal is adjusted to ensure that the phase deviation of all elements within the array is ≤1°, thus ensuring the consistency of plane wave excitation and reception. If the phase deviation is not corrected, it will cause the plane wave propagation direction to shift by ≥2°, and the deep defect location error will increase to ±0.2mm or more.

[0083] S3. Obtain the three-dimensional model of the automobile engine cylinder block, and perform plane wave forward continuation and reflected wave reverse continuation based on the processed reflected wave field signal and the three-dimensional model to output a three-dimensional defect imaging map.

[0084] Step S3 includes:

[0085] S31. Construct a mesh model based on the three-dimensional model;

[0086] Specifically, step S31 is as follows:

[0087] An adaptive tetrahedral meshing algorithm is used to mesh the 3D model, identify the cylinder block structural features of the 3D model, and adjust the mesh accuracy based on the cylinder block structural features to obtain a mesh model.

[0088] Specifically, based on the cylinder block CAD model, an adaptive tetrahedral mesh generation algorithm is used to adjust the mesh accuracy according to the cylinder block structural features:

[0089] Thick wall area: Mesh accuracy 0.1×0.1×0.1mm (length×width×depth). This area is a high-incidence area for defects. High-precision mesh can accurately describe the three-dimensional morphology of defects. The thickness of the wall area is mostly 5-15mm. 0.1mm accuracy can ensure that 10 layers of mesh are divided for each millimeter of thickness, and fully capture the detailed information of defects.

[0090] Cavity region (such as water jacket, oil channel): mesh accuracy 0.5×0.5×0.3mm. This region is free of defects. The low-precision mesh can reduce the amount of calculation and avoid the interference of the cavity structure on the wave field extension.

[0091] Transition region: A transition grid of 0.2-0.3mm is set between the wall thickness and the cavity region to avoid wave field extension distortion caused by abrupt changes in grid precision.

[0092] Subsequently, the generated grids are screened using grid quality evaluation indicators to ensure that the grid quality pass rate is ≥95%. If the grid aspect ratio exceeds 8, it will cause the numerical dispersion error in the wavefield extension process to be ≥10%, affecting the imaging accuracy. Therefore, unqualified grids need to be re-divided.

[0093] S32. Based on the processed reflected wave field signal, perform a plane wave forward extension on the mesh model and construct the elastic wave equation:

[0094] ;

[0095] In the formula, For wave field displacement, Let be the material wave velocity distribution function. This is the depth attenuation coefficient. For grid coordinates, For discrete time steps;

[0096] Specifically, regarding the depth attenuation coefficient, for every 50mm increase in depth, Increase by 0.05.

[0097] S33. Solve the elastic wave equation using the higher-order finite difference method and introduce perfectly matched layer absorbing boundary conditions to obtain the spatiotemporal distribution of the positive wave field. ;

[0098] In the process of extension, a perfectly matched layer (PML) is used to absorb the boundary condition. The boundary thickness is 10 grid units, and the absorption coefficient is adjusted with the increase of depth. This can effectively suppress boundary reflection interference and avoid the boundary reflection signal being misjudged as a defect signal.

[0099] S34. Extract the defect reflection wave component from the processed reflection wave field signal. Using the cylinder surface at the corresponding depth layer as the boundary, perform reverse continuation based on the defect reflection wave component and the same finite difference method as the forward continuation of plane waves to obtain the spatiotemporal distribution of the reverse wave field. ;

[0100] Specifically, the defect reflection wave component in the received signal at each depth layer is extracted. Taking the cylinder surface at the corresponding depth layer as the boundary, the same finite difference method as the forward continuation is used for reverse continuation with a continuation step size of 0.05μs. The amplitude, phase and depth coordinate information of the wave field in each grid cell are recorded simultaneously. The core of reverse continuation is to "retrace" the propagation path of the reflected wave. By comparing it with the forward continuation wave field, the location of the defect is determined.

[0101] S35. Based on the aforementioned positive wave field spatiotemporal distribution The spatiotemporal distribution of the reverse wave field Construct the objective function :

[0102] ;

[0103] In the formula, For constraint coefficients, For wave velocity gradient, For the gradient of imaging parameters, For compensation coefficient, As a depth decay factor, Image of the target defect;

[0104] Specifically, for the objective function, the first term is the wavefield matching term, which ensures that the imaging result is consistent with the actual wavefield by minimizing the time integral difference between the two. The second term is the material wave velocity constraint term, with a constraint coefficient of 0.05-0.1. This constraint term ensures that the imaging result follows the material wave velocity distribution law and avoids imaging distortion caused by uneven wave velocity. The third term is the depth attenuation compensation term, with a compensation coefficient of 0.02-0.05 and a depth attenuation factor of 1+0.01×z, where z is the depth coordinate. This compensation term corrects the attenuation of the deep wavefield signal and ensures the brightness consistency of the defect imaging at different depths.

[0105] S36. The conjugate gradient method is used to solve for the minimum value of the objective function to obtain the target defect image corresponding to each depth layer. The target defect images of each depth layer are stitched together to obtain a three-dimensional defect imaging map.

[0106] Specifically, the conjugate gradient method is used to solve for the minimum value of the functional, with 20-30 iterations and an iteration convergence error ≤10. -4 The algorithm ultimately obtains a coherent high-resolution defect imaging result across all depth layers. This algorithm can improve the resolution of defect imaging to 0.1 mm, which is more than 3 times higher than the traditional reverse time migration algorithm. Finally, the layers are stitched together to form a complete three-dimensional imaging result of the cylinder block, namely a three-dimensional defect imaging map.

[0107] S4. Perform defect analysis on the three-dimensional defect image to output the defect detection results.

[0108] Specifically, step S4 is as follows:

[0109] The three-dimensional defect image is subjected to three-dimensional threshold segmentation and morphological filtering to obtain a processed image. The three-dimensional coordinates, size parameters and volume parameters of the defect in the processed image are calculated to obtain the core parameters of the defect. The defect is classified according to the preset automotive industry engine block defect judgment standard and based on the core parameters of the defect to obtain the defect detection result.

[0110] Specifically, based on the Otsu adaptive thresholding method, the defect and background segmentation thresholds in the imaging results are automatically determined. Areas with gray values ​​higher than the threshold are identified as defect areas, achieving preliminary defect extraction. The extracted defect areas are then processed using an "opening operation + closing operation"—the opening operation removes small noise areas, and the closing operation fills in holes within the defect area, ensuring that the extracted defect area matches the actual defect morphology. The core parameters of the defect are calculated using a three-dimensional morphological algorithm.

[0111] Three-dimensional coordinates: Establish a three-dimensional coordinate system with the center of the bottom of the cylinder as the origin. The x-axis is along the length direction, the y-axis is along the width direction, and the z-axis is along the depth direction. Calculate the coordinates (x, y, z) of the centroid of the defect area. The positioning error is ≤ ±0.12mm.

[0112] Dimensional parameters: Calculate the maximum span of the defect area in the x, y, and z directions, which are taken as the length (L), width (W), and depth (D) of the defect, respectively. The dimensional error is ≤ ±0.05mm.

[0113] Volume parameter: The defect volume (V) is calculated by counting the number of mesh elements in the defect area, with a volume error of ≤ ±0.001 mm³.

[0114] Based on the automotive industry's engine block defect judgment standards and combined with the quality requirements of key areas of the cylinder block, a three-level judgment standard is established:

[0115] Grade A (Critical Defect): Aperture ≥ 0.5 mm and located in a critical area with a depth ≤ 50 mm (this area is subjected to high-pressure gas, and defects are prone to cracking); Crack depth ≥ 1.0 mm (in any direction); Volume ≥ 0.1 mm³; Such defects are directly deemed unqualified and are prohibited from proceeding to the next process;

[0116] Grade B (Severe Defect): Hole diameter 0.3-0.5mm and located in a critical area; crack depth 0.5-1.0mm; volume 0.05-0.1mm³; This type of defect needs to be evaluated by the process department, and can be downgraded for use after confirmation that it has no impact;

[0117] Grade C (General Defects): Bore diameter < 0.3 mm; crack depth < 0.5 mm; volume < 0.05 mm³; These defects do not affect the use of the cylinder block and are deemed acceptable.

[0118] The engine cylinder block detection method based on plane wave reverse time offset provided in Embodiment 1 of the present invention has the following advantages:

[0119] 1. In terms of hardware, a linear ultrasonic transducer array is arranged along the depth direction of the cylinder block, combined with depth dimension recognition, to achieve precise control of the detection dimension; in terms of software, an innovative inverse time-shifting algorithm with material wave velocity constraint and depth attenuation compensation is introduced. Through the modified elastic wave equation and high-order finite difference method, numerical dispersion error is effectively suppressed. The defect location error is ≤ ±0.12mm, the size measurement error is ≤ ±0.05mm, and the volume calculation error is ≤ ±0.001mm³. Compared with traditional ultrasonic testing, the positioning accuracy is improved by 2 times and the size accuracy is improved by 3 times. It can accurately identify micro-pores as small as 0.1mm and micro-cracks as deep as 0.2mm, meeting the detection requirements of high-end engines for micro-defects.

[0120] 2. In view of the structural characteristics of high incidence of defects in the thick area of ​​cylinder wall and no defects in the cavity area, a non-uniform three-dimensional mesh is adopted, combined with wave field constrained imaging conditions, which improves the defect imaging resolution to 0.1mm, more than 3 times higher than the traditional reverse time migration algorithm. The imaging results can clearly present the three-dimensional morphology of the defects, avoiding the defect misjudgment caused by the blurring of the traditional two-dimensional grayscale image. For example, it can accurately distinguish the crack step difference of 0.1mm in the depth direction, providing accurate data support for subsequent defect cause analysis.

[0121] 3. Introducing real-time temperature-wave velocity correction, when the temperature fluctuates by ±5℃, the wave velocity correction error is ≤0.3%, avoiding defect location deviation caused by temperature, and still being able to conduct stable detection in complex workshop environments. For the wave field scattering problem generated by cavity structures such as cylinder water jacket and oil passage, the combination strategy of low-precision mesh in cavity area + PML absorbing boundary + wave field constraint functional effectively suppresses the interference of cavity scattering signal on defect imaging.

[0122] 4. Through technological innovations in hardware precision, software intelligence, and process standardization, it comprehensively surpasses existing technologies in terms of detection accuracy, coverage, anti-interference capability, efficiency, automation level, and adaptability. It can be widely used in online production line inspection of automotive engine cylinder blocks, factory quality sampling inspection, and after-sales fault analysis, providing the automotive manufacturing industry with high-precision, high-efficiency, and high-reliability non-destructive testing solutions, helping enterprises improve product quality, reduce production costs, and optimize production efficiency.

[0123] Example 2

[0124] like Figure 2 As shown, in Embodiment 2 of the present invention, an engine cylinder block detection system based on plane wave counter-time offset is provided, the system comprising:

[0125] The detection module 1 is used to set up a number of linear ultrasonic transducer arrays in the cylinder of the automobile engine, divide the cylinder of the automobile engine into a number of depth layers according to the depth dimension, apply pulses of corresponding angles through the linear ultrasonic transducer arrays and collect the original reflected wave field signal corresponding to each depth layer.

[0126] Processing module 2 is used to preprocess the original reflected wave field signal to obtain a processed reflected wave field signal;

[0127] The extension module 3 is used to acquire a three-dimensional model of the automobile engine cylinder block, and to perform plane wave forward extension and reflected wave reverse extension based on the processed reflected wave field signal and the three-dimensional model to output a three-dimensional defect imaging map.

[0128] Output module 4 is used to perform defect analysis on the three-dimensional defect image to output defect detection results.

[0129] Specifically, the processing module 2 is used for:

[0130] The original reflected wave field signal is bandpass filtered using a preset filter to obtain a filtered reflected wave field signal.

[0131] The filtered reflected wave field signal is decomposed into wavelets, and residual noise in the high-frequency details after decomposition is removed by an adaptive threshold method to obtain a denoised reflected wave field signal.

[0132] Temperature data and cylinder depth data are collected. Based on the temperature data and the temperature wave velocity fitting curve in the material property database, the wave velocity is corrected to obtain the corrected wave velocity. Based on the cylinder depth data, the acquisition time of the reflected wave field signal at different depth layers is adjusted to obtain the adjusted acquisition time. Based on the corrected wave velocity and the adjusted acquisition time, the denoised reflected wave field signal is updated to obtain the updated reflected wave field signal.

[0133] A cross-correlation phase alignment algorithm is used to perform phase correction processing on the updated reflected wave field signal using the same group of linear arrays to obtain the processed reflected wave field signal.

[0134] Specifically, the extension module 3 is used for:

[0135] Construct a mesh model based on the aforementioned 3D model;

[0136] Based on the processed reflected wave field signal, the mesh model is extended by plane wave forward and the elastic wave equation is constructed:

[0137] ;

[0138] In the formula, For wave field displacement, Let be the material wave velocity distribution function. This is the depth attenuation coefficient. For grid coordinates, For discrete time steps;

[0139] The elastic wave equation is solved using the higher-order finite difference method, and a perfectly matched layer absorbing boundary condition is introduced to obtain the spatiotemporal distribution of the positive wave field. ;

[0140] Defect-reflected wave components are extracted from the processed reflected wave field signal. Using the cylinder surface at the corresponding depth layer as the boundary, a reverse continuation is performed based on these defect-reflected wave components using the same finite difference method as the forward continuation of plane waves, to obtain the spatiotemporal distribution of the reverse wave field. ;

[0141] Based on the aforementioned positive wave field spatiotemporal distribution The spatiotemporal distribution of the reverse wave field Construct the objective function :

[0142] ;

[0143] In the formula, For constraint coefficients, For wave velocity gradient, For the gradient of imaging parameters, For compensation coefficient, As a depth decay factor, Image of the target defect;

[0144] The minimum value of the objective function is solved by the conjugate gradient method to obtain the target defect image corresponding to each depth layer. The target defect images of each depth layer are then stitched together to obtain a three-dimensional defect image.

[0145] The extension module 3 is further used for:

[0146] An adaptive tetrahedral meshing algorithm is used to mesh the 3D model, identify the cylinder block structural features of the 3D model, and adjust the mesh accuracy based on the cylinder block structural features to obtain the mesh model.

[0147] Specifically, the output module 4 is used for:

[0148] The three-dimensional defect image is subjected to three-dimensional threshold segmentation and morphological filtering to obtain a processed image. The three-dimensional coordinates, size parameters and volume parameters of the defect in the processed image are calculated to obtain the core parameters of the defect. The defect is classified according to the preset automotive industry engine block defect judgment standard and based on the core parameters of the defect to obtain the defect detection result.

[0149] In other embodiments of the present invention, the present invention provides the following technical solution: a computer, including a memory 102, a processor 101, and a computer program stored in the memory 102 and executable on the processor 101, wherein the processor 101 executes the computer program to implement the engine cylinder block detection method based on plane wave counter-time offset as described above.

[0150] Specifically, the processor 101 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of the present invention.

[0151] The memory 102 may include a large-capacity memory for data or instructions. For example, and not limitingly, the memory 102 may include a hard disk drive (HDD), a floppy disk drive, a solid-state drive (SSD), flash memory, an optical disk drive, a magneto-optical disk drive, magnetic tape, or a Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 102 may include removable or non-removable (or fixed) media. Where appropriate, the memory 102 may be internal or external to a data processing device. In a particular embodiment, the memory 102 is non-volatile memory. In a particular embodiment, the memory 102 includes read-only memory (ROM) and random access memory (RAM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable read-only memory (PROM), an erasable read-only memory (EPROM), an electrically erasable read-only memory (EEPROM), an electrically alterable read-only memory (EAROM), or flash memory, or a combination of two or more of these. Where appropriate, the RAM can be Static Random-Access Memory (SRAM) or Dynamic Random-Access Memory (DRAM). DRAM can be Fast Page Mode Dynamic Random Access Memory (FPMDRAM), Extended Data Out Dynamic Random Access Memory (EDODRAM), Synchronous Dynamic Random-Access Memory (SDRAM), etc.

[0152] The memory 102 can be used to store or cache various data files that need to be processed and / or used for communication, as well as possible computer program instructions executed by the processor 101.

[0153] The processor 101 reads and executes the computer program instructions stored in the memory 102 to implement the above-mentioned engine cylinder block detection method based on plane wave counter-time offset.

[0154] In some embodiments, the computer may further include a communication interface 103 and a bus 100. For example, Figure 3 As shown, the processor 101, memory 102, and communication interface 103 are connected through bus 100 and complete communication with each other.

[0155] The communication interface 103 is used to enable communication between the various modules, devices, units, and / or equipment in the embodiments of the present invention. The communication interface 103 can also enable data communication with other components such as external devices, image / data acquisition devices, databases, external storage, and image / data processing workstations.

[0156] Bus 100 includes hardware, software, or both, that couples components of a computer device together. Bus 100 includes, but is not limited to, at least one of the following: data bus, address bus, control bus, expansion bus, and local bus. For example, and not as a limitation, bus 100 may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, bus 100 may include one or more buses. Although specific buses are described and illustrated in the embodiments of the present invention, the present invention is contemplated by any suitable bus or interconnect.

[0157] The computer can execute the engine block detection method based on plane wave reverse time offset of the present invention based on the engine block detection system based on plane wave reverse time offset, thereby realizing engine block detection based on plane wave reverse time offset.

[0158] In some further embodiments of the present invention, in conjunction with the above-described engine cylinder block detection method based on plane wave reverse time offset, the present invention provides the following technical solution: a storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the above-described engine cylinder block detection method based on plane wave reverse time offset.

[0159] Those skilled in the art will understand that the logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a ordered 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-included 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 mean 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.

[0160] More specific examples of readable media (a non-exhaustive list) include: electrical connections (electronic devices) with 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, since 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.

[0161] 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.

[0162] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0163] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A method for detecting engine cylinder blocks based on plane wave reverse time offset, characterized in that, include: A number of linear ultrasonic transducer arrays are set in the cylinder of an automobile engine. The cylinder is divided into several depth layers according to its depth dimension. Pulses of corresponding angles are applied through the linear ultrasonic transducer arrays and the original reflected wave field signal corresponding to each depth layer is collected. The original reflected wave field signal is preprocessed to obtain the processed reflected wave field signal; A three-dimensional model of the automobile engine cylinder block is obtained, and a plane wave forward continuation and a reflected wave reverse continuation are performed based on the processed reflected wave field signal and the three-dimensional model to output a three-dimensional defect imaging map. Defect analysis is performed on the three-dimensional defect image to output defect detection results; The step of performing plane wave forward continuation and reflected wave reverse continuation based on the processed reflected wave field signal and the three-dimensional model to output a three-dimensional defect image includes: Construct a mesh model based on the aforementioned 3D model; Based on the processed reflected wave field signal, the mesh model is extended by plane wave forward and the elastic wave equation is constructed: ； In the formula, For wave field displacement, Let be the material wave velocity distribution function. This is the depth attenuation coefficient. For grid coordinates, For discrete time steps; The elastic wave equation is solved using the higher-order finite difference method, and a perfectly matched layer absorbing boundary condition is introduced to obtain the spatiotemporal distribution of the positive wave field. ; Defect-reflected wave components are extracted from the processed reflected wave field signal. Using the cylinder surface at the corresponding depth layer as the boundary, a reverse continuation is performed based on these defect-reflected wave components using the same finite difference method as the forward continuation of plane waves, to obtain the spatiotemporal distribution of the reverse wave field. ; Based on the aforementioned positive wave field spatiotemporal distribution The spatiotemporal distribution of the reverse wave field Construct the objective function : ； In the formula, For constraint coefficients, For wave velocity gradient, For the gradient of imaging parameters, For compensation coefficient, As a depth decay factor, Image of the target defect; The minimum value of the objective function is solved by the conjugate gradient method to obtain the target defect image corresponding to each depth layer. The target defect images of each depth layer are then stitched together to obtain a three-dimensional defect image.

2. The engine cylinder block detection method based on plane wave reverse time offset according to claim 1, characterized in that, The step of preprocessing the original reflected wave field signal to obtain the processed reflected wave field signal includes: The original reflected wave field signal is bandpass filtered using a preset filter to obtain a filtered reflected wave field signal. The filtered reflected wave field signal is decomposed into wavelets, and residual noise in the high-frequency details after decomposition is removed by an adaptive threshold method to obtain a denoised reflected wave field signal. Temperature data and cylinder depth data are collected. Based on the temperature data and the temperature wave velocity fitting curve in the material property database, the wave velocity is corrected to obtain the corrected wave velocity. Based on the cylinder depth data, the acquisition time of the reflected wave field signal at different depth layers is adjusted to obtain the adjusted acquisition time. Based on the corrected wave velocity and the adjusted acquisition time, the denoised reflected wave field signal is updated to obtain the updated reflected wave field signal. A cross-correlation phase alignment algorithm is used to perform phase correction processing on the updated reflected wave field signal using the same group of linear arrays to obtain the processed reflected wave field signal.

3. The engine cylinder block detection method based on plane wave reverse time offset according to claim 2, characterized in that, The preset filter is a Chebyshev Type I filter with a passband of 1-8MHz and a stopband attenuation of ≥60dB.

4. The engine cylinder block detection method based on plane wave reverse time offset according to claim 1, characterized in that, The specific steps for constructing a mesh model based on the three-dimensional model are as follows: An adaptive tetrahedral meshing algorithm is used to mesh the 3D model, identify the cylinder block structural features of the 3D model, and adjust the mesh accuracy based on the cylinder block structural features to obtain the mesh model.

5. The engine cylinder block detection method based on plane wave reverse time offset according to claim 1, characterized in that, The specific steps for performing defect analysis on the three-dimensional defect image to output defect detection results are as follows: The three-dimensional defect image is subjected to three-dimensional threshold segmentation and morphological filtering to obtain a processed image. The three-dimensional coordinates, size parameters and volume parameters of the defect in the processed image are calculated to obtain the core parameters of the defect. The defect is classified according to the preset automotive industry engine block defect judgment standard and based on the core parameters of the defect to obtain the defect detection result.

6. An engine cylinder block detection system based on plane wave reverse time migration, wherein the system employs the engine cylinder block detection method based on plane wave reverse time migration as described in claim 1, characterized in that, The system includes: The detection module is used to set up several linear ultrasonic transducer arrays in the cylinder of an automobile engine, divide the cylinder of the automobile engine into several depth layers according to the depth dimension, apply pulses of corresponding angles through the linear ultrasonic transducer arrays and collect the original reflected wave field signal corresponding to each depth layer. The processing module is used to preprocess the original reflected wave field signal to obtain a processed reflected wave field signal; The extension module is used to acquire a three-dimensional model of the automobile engine cylinder block, and perform plane wave forward extension and reflected wave reverse extension based on the processed reflected wave field signal and the three-dimensional model to output a three-dimensional defect imaging map. The output module is used to perform defect analysis on the three-dimensional defect image to output the defect detection results.

7. The engine cylinder block detection system based on plane wave reverse time offset according to claim 6, characterized in that, The output module is specifically used for: The three-dimensional defect image is subjected to three-dimensional threshold segmentation and morphological filtering to obtain a processed image. The three-dimensional coordinates, size parameters and volume parameters of the defect in the processed image are calculated to obtain the core parameters of the defect. The defect is classified according to the preset automotive industry engine block defect judgment standard and based on the core parameters of the defect to obtain the defect detection result.

8. A computer comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the engine cylinder block detection method based on plane wave reverse time offset as described in any one of claims 1 to 5.

9. A storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the engine cylinder block detection method based on plane wave counter-time offset as described in any one of claims 1 to 5.

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