Detection probe type selection method for near-field blind area of rough machining surface of steel casting

Abstract

The invention relates to the technical field of steel casting ultrasonic detection, and discloses a steel casting rough machining surface near-field blind area detection probe type selection method which comprises the following steps: step 1, determining performance parameters needing ultrasonic flaw detection according to a steel casting application scene and a to-be-cast structural shape; 2, model selection parameters of probes are obtained according to the performance parameters, and the probes adopt angle probes and bicrystal probes; 3, respectively evaluating the model selection parameters of the probe according to the model selection mode, and obtaining the model selection data of the probe; 4, the selected probe is adopted to detect the steel casting according to the detection mode, a detection result is obtained, and the model selection mode is optimized according to the detection result; and 5, templating the optimized model selection mode to form a probe model selection index. According to the invention, the detection difficulty is reduced, the precision and comprehensiveness of ultrasonic flaw detection are improved, and the detection efficiency is improved.

Description

Technical Field

[0001] The invention relates to the technical field of ultrasonic detection of steel castings, and in particular to a method for selecting a probe for detecting near-field blind spots on a rough-machined surface of a steel casting. Background Art

[0002] Steel castings are an indispensable component in industries such as construction machinery, railway vehicles, and ships. Their internal quality is a key evaluation indicator for these products. This quality not only impacts subsequent processing but also final assembly and use.

[0003] Steel castings, as crucial components in industrial manufacturing, have rigorous and complex production processes, with ultrasonic flaw detection being a key step in ensuring the internal quality of steel castings. However, in actual production, even after undergoing conventional ultrasonic flaw detection, steel castings still suffer from a high incidence of internal defects on the machined surfaces.

[0004] One reason is that, during current ultrasonic testing, the surface to be inspected is roughly machined, with machining allowances based on the drawings. This creates a near-field blind spot, which inevitably creates the risk of missed or misdetected flaws.

[0005] Secondly, due to the production process, steel castings often exhibit characteristics such as loose and uneven microstructures, coarse grains, and poor acoustic transparency. These characteristics can cause scattered reflections during ultrasonic testing, resulting in grass-like echoes that reduce the signal-to-noise ratio and interfere with the accurate identification of defect waves. Partial contour echoes and delayed deformation waves can further increase non-defect signals, especially when dealing with unusual or complex steel castings. Rough surfaces also generate some reflected echoes, further complicating identification. This results in insufficient performance for existing ultrasonic testing, making it difficult to reduce the risk of misjudgments and missed detections, impacting both inspection efficiency and product quality. Summary of the Invention

[0006] The present invention aims to provide a method for selecting a near-field blind spot detection probe for rough-machined surfaces of steel castings, so as to solve the problem in the prior art that misjudgment and missed detection are prone to occur during ultrasonic detection of surface defects of steel castings, thus affecting product quality and detection efficiency.

[0007] To achieve the above object, the present invention adopts the following technical solution: a method for selecting a near-field blind spot detection probe for a rough-machined surface of a steel casting, comprising the following steps:

[0008] Step 1: Determine the performance parameters that require ultrasonic testing based on the applicable scenario of the steel casting and the structural shape to be cast;

[0009] Step 2: Obtaining the selection parameters of the probe according to the performance parameters, wherein the probe adopts an angle probe and a dual-element probe;

[0010] Step 3: Evaluate the selection parameters of the probe according to the set selection method to obtain the probe selection data;

[0011] Step 4: Use the selected probe type to test the steel casting according to the set detection method, obtain the test results, and optimize the selection method based on the test results;

[0012] Step 5: Template the optimized selection method to form the probe selection index.

[0013] The principles and advantages of this solution are:

[0014] Traditional ultrasonic flaw detection of steel castings focuses on near-surface flaw detection. Therefore, straight probes designed specifically for surface flaw detection are often used. These probes, with their shallow detection depth and high accuracy, are recognized as ideal for surface flaw detection in steel castings. This choice is based on established specifications and long-standing application experience for straight probes in these inspection tasks.

[0015] However, with the significant increase in structural complexity of steel castings, the surfaces directly accessible to inspection with a straight probe are becoming increasingly difficult to reach. This not only reduces inspection accuracy, but even with multi-angle and multi-directional testing, blind spots and missed areas are easily left, which in turn affects the quality pass rate of steel castings, significantly reduces the reliability of test results, and leads to a surge in product returns. Furthermore, this inspection method increases the workload, making the inspection process more complex and cumbersome, and making it difficult to ensure comprehensive inspection coverage and stable results.

[0016] Therefore, this solution breaks with inherent logic and abandons the traditional approach of relying on high-precision straight probes. Instead, it adopts a detection strategy that combines angle probes with dual-element probes. Although angle probes are slightly inferior to straight probes in detection accuracy, their detection capabilities are sufficient to meet the needs of rough-machined surfaces and near-field blind spots of steel castings. With their unique tilt angle, angle probes can more flexibly handle the surfaces of complex steel castings, achieving a wider detection range and effectively avoiding blind spots and omissions, thereby significantly improving the accuracy and completeness of detection. This innovative solution not only optimizes detection results and reduces detection difficulty, but also ensures the comprehensiveness and stability of detection work, effectively improving detection efficiency.

[0017] Furthermore, in step 1, the performance parameters include detection area, machining allowance, detection pressure, and energy concentration.

[0018] Furthermore, in step 2, according to the selected performance parameters, the selection parameters include probe frequency, probe chip size, probe refraction angle tangent value and focal length.

[0019] Furthermore, in step 3, the selection method includes the following sub-steps:

[0020] Step 3.1, evaluate the probe frequency, probe chip size, and probe refraction angle tangent of the angle probe to obtain the selection data of the angle probe;

[0021] In step 3.2, the probe frequency, probe element size, and focal length of the dual-element probe are evaluated to obtain the selection data for the dual-element probe.

[0022] Furthermore, in step 3.1, the evaluation of the angle probe includes the following sub-steps:

[0023] Step 3.1.1, analyze the selection parameters of the selected angle probe and find that the common influencing factor of the selection parameters is the near-field length;

[0024] Step 3.1.2, obtain the changing trend of each selection parameter based on the near-field length;

[0025] Step 3.1.3: Obtain the selection data of the corresponding angle probe according to the applicable scenario and structural shape of the steel casting, and use this as the basis for selection.

[0026] Furthermore, in step 3.2, the dual element probe evaluation includes the following sub-steps:

[0027] Step 3.2.1: Select the probe frequency value corresponding to the dual-element probe based on the energy concentration required for ultrasonic testing and the detection area;

[0028] Step 3.2.2: Select the corresponding dual-crystal probe size based on the detection area required for ultrasonic testing.

[0029] Step 3.2.3, select the focal length of the corresponding dual crystal probe according to the machining allowance of the ultrasonic flaw detection steel casting;

[0030] In step 3.2.4, based on the selection parameters obtained above, the selection data of the dual crystal probe is obtained according to the applicable scenario of the steel casting and the structural shape to be cast.

[0031] Furthermore, in step 3.1.1, according to the expression of near-field length:

[0032] N=Fs / πλs×cosβ / cosα-L1× (tanα / tanβ) (Formula 1);

[0033] Where N is the approach length; Fs is the probe chip size, and Fs = a × b; λs is the wavelength of the S wave in steel; β is the shear wave refraction angle; tanβ = K value, which is the tangent value of the probe refraction angle; α is the incident angle of the probe; L1 is the distance from the incident point to the wave source;

[0034] According to Snell's law, that is, α = αL, α can be calculated, αL = arcsin (CL1 / Cs2×sinβ) (Equation 2);

[0035] Where CL1 is the L-wave velocity in the organic glass of the oblique probe, which is 2730 mm / s; Cs2 is the shear wave velocity, which is 3230 mm / s; αL is the L-wave incident angle.

[0036] In step 3.1.2, according to formula 2, the changing trend of each selection parameter of the angle probe can be obtained as follows:

[0037] For the probe frequency, the higher the frequency, the larger the near-field length N value;

[0038] For the probe chip size, the larger the chip size, the larger the near-field length N value;

[0039] As for the K value, the larger the K value is, the smaller the near-field length N is.

[0040] Furthermore, in step 3.1.3, when comprehensively selecting the selection data of the angle probe, it is necessary to consider avoiding ultrasonic testing in the near field area.

[0041] Furthermore, in step 3.2.3, the focal length is determined by the wafer tilt angle of the dual-element probe, and the corresponding tilt angle is selected according to the machining allowance to obtain the corresponding focal length value.

[0042] Furthermore, in step 4, the detection method includes the following sub-steps:

[0043] Step 4.1, select at least three artificial defects of appropriate depth on the test block;

[0044] Step 4.2: Create a DAC curve or AVG curve based on the selected defect to test the selected probe;

[0045] Step 4.3, verifying the tested probe on a rough-machined steel casting product to obtain a verification result;

[0046] Step 4.4, optimize the selection method based on the verification results. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 The figure is a flow chart of a method for selecting a probe for detecting near-field blind spots on a rough-machined surface of a steel casting according to the present invention. DETAILED DESCRIPTION

[0048] The following is further described in detail through specific implementation methods:

[0049] Example 1

[0050] This embodiment is basically as shown in the attached Figure 1As shown in the figure, a method for selecting a probe for detecting near-field blind spots on rough-machined surfaces of steel castings is used. The method selects an appropriate detection probe based on the detection requirements and forms a quick selection standard based on this. This improves the detection efficiency of the probe and reduces false detections and missed detections, thereby improving the ultrasonic detection capabilities of steel castings, improving product quality, and reducing product quality complaints. This selection method includes the following steps:

[0051] S1, determine the performance parameters that require ultrasonic testing based on the applicable scenario of the steel casting and the structural shape to be cast.

[0052] In this embodiment, the applicable scenarios include the use environments of steel castings, such as railway vehicles and ships. In these application areas, different performance requirements are placed on steel castings, and the corresponding required steel casting indicators will also vary. For example, in the shipbuilding field, they are required to have strong corrosion resistance, high strength, and toughness to effectively resist seawater erosion and extend their service life. In railway vehicles, on the other hand, more emphasis is placed on wear resistance and stability, and corrosion resistance is not as high as in ships. Therefore, the performance requirements of steel castings are specifically determined based on the use environment to ensure that the steel castings can meet specific use requirements. At the same time, due to the wide range of applications of steel castings, they can be cast according to the required assembly structure, making them more flexible. However, their flexible casting method also leads to their varied structures and more complex special-shaped structures. This makes it difficult to achieve comprehensive and effective detection when performing ultrasonic flaw detection on steel castings, which can easily lead to false detection and missed detection.

[0053] Therefore, this embodiment combines the applicable scenarios and complex structural shapes of steel castings to determine the performance parameters required for ultrasonic flaw detection. Within these selected performance parameters, the corresponding performance parameters are selected based on the specific scenario and shape, ensuring accurate and rapid selection. In this embodiment, the performance parameters include detection area, machining allowance, detection pressure, and energy concentration.

[0054] S2, obtaining the selection parameters of the probe according to the performance parameters, wherein the probe adopts an angle probe and a dual crystal probe.

[0055] In this embodiment, a combination of an angle probe and a dual-crystal probe is used to detect near-surface defects in steel castings (i.e., near-field blind zone defects). Since ultrasonic flaw detection of steel castings primarily targets near-surface defects, a straight probe is typically used. Furthermore, because a straight probe is primarily used to detect surface defects, its detection depth is shallow but its detection accuracy is high. Therefore, it is considered the most suitable probe for surface flaw detection of steel castings. Therefore, in ultrasonic flaw detection, the conventional wisdom is to use a straight probe.

[0056] However, as the structural shapes of steel castings become more and more complex, the inspection surfaces that can be used for inspection are increasingly difficult to be directly detected by straight probes, resulting in reduced inspection accuracy. Even if inspections are carried out in multiple directions and on multiple surfaces, it is easy to form inspection blind spots and missed inspection areas, resulting in a decrease in the quality pass rate of existing steel castings, making it difficult to effectively ensure inspection accuracy, and causing a surge in the number of returned products. In addition, it will increase the inspection workload, making the inspection process more cumbersome, and making it difficult to ensure the comprehensiveness and stability of the inspection. Therefore, this solution breaks the conventional inspection thinking and does not use a straight probe that has a greater advantage in inspection accuracy. Instead, it uses a combination of an oblique probe and a dual crystal probe for inspection. When performing near-field blind spot inspection on the rough-machined surface of a steel casting, the inspection accuracy of the oblique probe can meet the requirements of near-field inspection of the rough-machined surface. Since the oblique probe has a certain inclination angle, it can be used to inspect the surface of a steel casting with a complex structure. Its detection range is wider and more flexible, effectively avoiding inspection blind spots and missed inspection areas, thereby improving the accuracy and comprehensiveness of inspection.

[0057] According to the angle probe and dual crystal probe used, after determining the performance parameters, the probe selection parameters are obtained. In this embodiment, the probe selection parameters mainly include the probe frequency, the probe crystal size, the probe refraction angle tangent value and the focal length.

[0058] S3, evaluating the selection parameters of the probe according to the set selection method, and obtaining the probe selection data.

[0059] In this embodiment, the selection method mainly includes the following sub-steps:

[0060] S3.1. Evaluate the probe frequency, probe chip size, and probe refraction angle tangent (K value) of the angle probe to obtain selection data for the angle probe.

[0061] The evaluation method for the oblique probe includes the following sub-steps:

[0062] S3.1.1. Analyze the selection parameters of the selected angle probe and find that the common influencing factor of the selection parameters is the near-field length.

[0063] Since the parameters of angle probes affect the length of the near-field, and since the sound pressure in the near-field has maximum and minimum values, the sound beam should avoid detecting within this range during flaw detection. The parameters selected based on performance parameters include probe frequency f, probe element size, and K value. Therefore, based on the selected parameters of angle probes, it can be seen that the common factor affecting their detection capabilities is the near-field length N value.

[0064] Specifically, according to the shear wave acoustic field theory, the near-field length of the shear wave acoustic field in steel can be calculated as follows:

[0065] N=Fs / πλs×cosβ / cosα-L1× (tanα / tanβ) (Formula 1);

[0066] Where N is the near-field length; Fs is the probe chip area, that is, the chip size, and Fs = a × b; λs is the wavelength of the S wave in steel; β is the shear wave refraction angle; tanβ = K value, which is the tangent value of the probe refraction angle; α is the incident angle of the probe; and L1 is the distance from the incident point to the wave source.

[0067] At the same time, according to Snell's law, that is, the law of refraction, the incident angle α can be calculated.

[0068] That is, α=αL, then according to

[0069] sinαL / CL1=sinβ / Cs2;

[0070] The transformation yields αL = arcsin(CL1 / Cs2×sinβ) (Equation 2);

[0071] Where CL1 is the L-wave velocity in the organic glass of the oblique probe, which is 2730 mm / s; Cs2 is the shear wave velocity, which is 3230 mm / s; αL is the L-wave incident angle.

[0072] Equation 2 shows that the near-field length N in steel is related to the probe frequency f, the probe chip size Fs, the K value, and the β value. Therefore, the selection parameters of the angle probe can be quickly evaluated based on the near-field length, thereby obtaining the most suitable angle probe for detection.

[0073] S3.1.2, obtain the changing trend of each selection parameter based on the near-field length. According to formula 2, the changing trend of each selection parameter of the angle probe can be obtained as follows:

[0074] a. For the probe frequency f of an angle probe, the higher the frequency, the larger the near-field length N. The specific evaluation method is as follows:

[0075] According to Equation 1, when the probe Fs and K values ​​are the same, the near-field length N is significantly different when the probe frequency f is different. In this embodiment, two angle probes with specifications of 2.5Z10×16K1 (L1=8) and 5Z10×16K1 (L1=8) are used as examples for description.

[0076] For the oblique probe with specifications of 2.5Z10×16K1, its main parameters are: chip area Fs = 10×16; probe frequency f = 2.5MHz = 2.5×106Hz; since tanβ = K value, β = arctanK = 45°.

[0077] According to formula 2, α = arcsin (CL1 / Cs2×sinβ)

[0078] =arcsin(2730 / 3230×sin45°)

[0079] =36.7°

[0080] According to the formula wavelength λ = C / f (Formula 3), where C is the wave speed and f is the frequency.

[0081] Then we can calculate λ=3230×10 3 mm / s÷(2.5×10 6 Hz)

[0082] =1.292mm

[0083] Based on Equation 1, the near-field length N for this specification can be calculated as 28.8 mm. Similarly, the near-field length N for a 5Z10×16K1 (L1=8) probe can be calculated as 63.6 mm. This comparative analysis leads to the conclusion that the higher the probe frequency f, the longer the near-field length in steel.

[0084] b. For the angle probe chip size, the larger the chip size, the larger the near-field length N value. The specific evaluation method is as follows:

[0085] In this embodiment, the chip size is the chip area Fs. Due to different chip sizes, the distance L1 from the incident point to the actual wave source varies for different probes. For example, for two probes with the same probe K value and probe frequency f, the measured L1 values ​​for 2.5Z10×10K2 and 2.5Z13×13K2 are 10 mm and 12 mm, respectively. According to Equation 1, their near-field lengths in steel are calculated to be 11.1 mm and 21.5 mm, respectively. This indicates that the larger the chip size, the longer the near-field length.

[0086] c. For the K value of the angle probe, the larger the K value, the smaller the near-field length N value. The specific evaluation method is as follows:

[0087] In this embodiment, for probes with the same probe frequency f and chip size but different K values, their L1 is also the same. The larger the K value, the larger the L1. For example, for a probe with a specification of 2.5Z10×10K1, L1 is 8mm; and for a probe with a specification of 2.5Z10×10K2.5, L1 is 12mm. According to Formula 1, the lengths of the near-field zones in steel can be calculated to be 15.8mm and 8.7mm respectively. Therefore, it can be concluded that the larger the K value, the smaller the near-field length N. Therefore, the corresponding K value can be selected according to the near-field length requirements. At the same time, the K value also needs to be comprehensively selected in combination with the processing allowance. Generally speaking, a larger K value (K2.5 or above) is selected for a smaller allowance, and a smaller K value (K1.5 or K1 or below) is selected for a larger allowance.

[0088] S3.1.3. Obtain the selection data of the corresponding angle probe based on the applicable scenario and structural shape of the steel casting and use it as the basis for selection.

[0089] Combining the above three determination methods and comprehensively selecting the angle probe model data, it is necessary to avoid performing ultrasonic flaw detection in the near field. Generally speaking, for probes with larger chip sizes, such as chip sizes of 13×13mm or 10×16mm, it is not advisable to choose higher frequency probes, such as those with frequencies greater than 5MHz.

[0090] S3.2. Evaluate the probe frequency, probe element size, and focal length of the dual element probe to obtain selection data for the dual element probe.

[0091] Dual element probes, also known as split probes, feature two elements within a single housing. When these two elements are combined to detect longitudinal waves, the probe is called a longitudinal wave dual element probe or a dual element straight probe. In a dual element probe, one element transmits and reflects sound waves, while the other receives these reflected waves.

[0092] The dual-element probe incorporates a highly absorbent and insulating layer within the probe, effectively isolating the transmitting and receiving circuits and preventing interference and blockage between the transmitted sound waves and the echo. This not only narrows the pulse signal, improving resolution, but also eliminates the problem of reflected noise generated between the transmitting element and the delay line entering the receiving element. Furthermore, both the transmitting and receiving probes are equipped with delay lines, further reducing the detection blind zone and significantly enhancing the detection capability of near-surface defects. Furthermore, both elements of the dual-element probe are tilted at a specific angle. This design ensures that the transmitting and receiving beams intersect, defining a prismatic zone. This zone is the inspection area, which is crucial for flaw detection. Defects within the prismatic zone reflect strong signals. For defects of the same size, the reflection signal is strongest when the defect is located in the center of the prismatic zone and relatively weaker when located at the edge.

[0093] Based on the above dual element probe design principles, the selection parameters of dual element probes are evaluated. The selection parameters are combined with performance parameters to determine the probe frequency, probe element size, and focal length.

[0094] In this embodiment, evaluating the dual crystal probe includes the following sub-steps:

[0095] S3.2.1. Select the probe frequency value corresponding to the dual-element probe based on the energy concentration required for ultrasonic testing and the detection area.

[0096] The frequency of ultrasound transmission largely determines the detection capabilities of ultrasonic flaw detection. High frequencies result in shorter wavelengths, better beam directionality, smaller diffusion angles, and more concentrated energy, resulting in stronger detection of small defects, better resolution, and more accurate defect location. However, high-frequency ultrasound attenuates more in materials and has poorer penetration, and vice versa.

[0097] S3.2.2. Select the corresponding dual-element probe size based on the size of the detection area required for ultrasonic testing.

[0098] Analysis of the design principles of dual-element probes reveals that flaw detection with dual-element probes primarily depends on the probe's energy concentration zone and has no direct relationship to the size of the crystal element. The crystal size of a dual-element probe is directly related to the size of the workpiece's detection area. When the detection area is large, a probe with a larger crystal size, such as φ10mm, φ14mm, or φ20mm, is recommended to improve detection efficiency. When the detection area is small, or when the surface has a certain curvature, a probe with a smaller crystal size is recommended to reduce coupling loss.

[0099] S3.2.3. Select the focal length of the dual-element probe corresponding to the machining allowance of the ultrasonically inspected steel casting.

[0100] The focal length is determined by the tilt angle of the crystal element of the dual-element probe. The corresponding tilt angle is selected according to the machining allowance to obtain the corresponding focal length value.

[0101] The two crystals of the dual crystal probe are tilted at a certain angle, and the transmitting and receiving sound beams will inevitably intersect, forming a prismatic area, which is the inspection area. The defect reflection signal in the prismatic area is strong. For defects of the same size, the reflection signal is strongest when the defect is located in the center of the prismatic area, and relatively weak when it is located at the edge of the prismatic area. During actual ultrasonic testing, the appropriate inclination angle θ should be selected according to the machining allowance of the steel casting product. The smaller θ is, the deeper the depth of F from the detection surface (that is, the deeper the focal depth is), and the larger the acoustic focal length is, which is conducive to the detection of workpieces with larger machining allowances; the larger θ is, the shallower the depth of F from the detection surface (that is, the shallower the focal depth is), and the smaller the acoustic focal length is, which is conducive to the detection of workpieces with smaller machining allowances.

[0102] S3.2.4. Based on the above-obtained selection parameters, obtain the selection data of the dual-crystal probe according to the applicable scenario of the steel casting and the structural shape to be cast.

[0103] S4, using the selected probe type to inspect the steel casting according to the set inspection method, obtaining the inspection results, and optimizing the selection method based on the inspection results.

[0104] The detection method includes the following sub-steps:

[0105] S4.1, select at least three artificial defects of appropriate depth on the test block. In this embodiment, the artificial defects can be set as, for example, flat-bottomed holes, transverse holes, or rectangular grooves.

[0106] S4.2, create a DAC curve or AVG curve based on the selected defect to test the selected probe;

[0107] S4.3, verify the tested probe on a rough-machined steel casting product and obtain verification results;

[0108] S4.4, optimize the selection method based on the verification results.

[0109] S5: Template the optimized selection method to form the probe selection index, which is applied in actual ultrasonic flaw detection.

[0110] The above-mentioned ultrasonic flaw detection of steel castings and the selection of probes were applied to steel castings. According to actual data feedback, ultrasonic detection can effectively detect defects within the processing allowance range and effectively carry out repairs. According to product quality production statistics, the product return rate has dropped from an average of 1.3 times / month to 0.2 times / month, and customer feedback complaints have dropped from 24 times to 0 times, greatly improving the accuracy and comprehensiveness of ultrasonic flaw detection.

[0111] In this embodiment, in the surface ultrasonic detection of steel castings, even if multiple and repeated flaw detection tests are performed, there will still be a large number of defective products during the product quality acceptance of steel castings, resulting in a high product return rate. At this time, it is considered that the problem is insufficient detection accuracy, and thus ways to improve the detection accuracy are sought. However, after more research and analysis, we have made a breakthrough discovery that when performing ultrasonic flaw detection on the surface of steel castings, although its detection indicators can meet the current process qualification requirements during the production of steel castings, since each steel casting will be used in different field equipment in the future, the performance requirements of the steel castings will vary depending on the use environment. Even if a single steel casting meets the detection requirements during ultrasonic flaw detection, it may not meet the needs of its actual application environment, resulting in problems such as inaccurate detection and a high return rate.

[0112] Secondly, in the prior art, surface flaw detection of steel castings generally uses standardized straight probes. This is because straight probes are already used for ultrasonic surface testing of castings, offer higher detection accuracy, and can meet initial testing requirements. Therefore, replacing standard straight probes is not a common practice. However, when using straight probes, since they penetrate perpendicularly through the detectable surface, detection must be completed through the detectable surface. However, with the increasing complexity and shape of steel castings, the detectable surface area is more limited, making direct detection difficult. Even if detectable surfaces can be created through further processing, more processing steps and repeated operations are required, resulting in material loss. Furthermore, the detection performance of straight probes varies depending on the performance testing requirements of steel castings, and high accuracy is not the only requirement. Consequently, even with the more accurate straight probes used in existing ultrasonic flaw detection, there are still many areas of missed detection and false detection.

[0113] Therefore, this solution breaks with the standardization regulations and adopts an oblique probe with a lower detection accuracy but a more flexible detection area as the ultrasonic flaw detection equipment. When conducting near-field surface inspection of steel castings, the detection accuracy of the oblique probe can meet the inspection requirements. At the same time, during the inspection, this solution combines the actual application scenarios of steel castings to conduct a targeted analysis of the required performance requirements, thereby determining the corresponding inspection needs, and comprehensively selecting the probe model that meets the inspection requirements for inspection, so that it can better meet the inspection requirements of different performance requirements, thereby improving the comprehensiveness, accuracy and effectiveness of the inspection, being more in line with the actual use environment, effectively improving the overall quality of steel castings, and reducing product return rates. Moreover, this solution can quickly and effectively select probes and improve inspection efficiency.

[0114] The above is only an embodiment of the present invention, and the common knowledge such as the specific technical solutions and / or characteristics in the solution are not described in detail here. It should be pointed out that for those skilled in the art, without departing from the technical solution of the present invention, several variations and improvements can be made, which should also be regarded as the scope of protection of the present invention, and these will not affect the effect of the implementation of the present invention and the practicality of the patent. The scope of protection required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the description can be used to interpret the content of the claims.

Claims

1. A method for selecting a near-field blind spot detection probe for a rough-machined surface of a steel casting, characterized in that: The following steps are involved: Step 1: Determine the performance parameters that require ultrasonic flaw detection based on the applicable scenario of the steel casting and the structural shape to be cast; Step 2, obtaining the selection parameters of the probe according to the performance parameters, wherein the probe adopts an oblique probe and a dual crystal probe; Step 3, evaluating the selection parameters of the probes according to the set selection method, and obtaining the probe selection data; Step 4, using the selected probe type to test the steel casting according to the set testing method, obtaining the test results, and optimizing the selection method according to the test results; Step 5, template the optimized selection method to form the probe selection index.

2. The method for selecting a near-field blind spot detection probe for a rough-machined surface of a steel casting according to claim 1, characterized in that: In step 1, the performance parameters include detection area, machining allowance, detection pressure and energy concentration.

3. The method for selecting a near-field blind spot detection probe for a rough-machined surface of a steel casting according to claim 2, characterized in that: In step 2, according to the selected performance parameters, the selection parameters include probe frequency, probe chip size, probe refraction angle tangent value and focal length.

4. The method for selecting a near-field blind spot detection probe for a rough-machined surface of a steel casting according to claim 3, characterized in that: In step 3, the selection method includes the following sub-steps: Step 3.1, evaluating the probe frequency, probe chip size, and probe refraction angle tangent value of the angle probe to obtain selection data of the angle probe; Step 3.2, evaluate the probe frequency, probe chip size and focal length of the dual crystal probe to obtain the selection data of the dual crystal probe.

5. The method for selecting a near-field blind spot detection probe for a rough-machined surface of a steel casting according to claim 4, characterized in that: In step 3.1, the evaluation of the angle probe includes the following sub-steps: Step 3.1.1, analyzing the selection parameters of the selected angle probe, and obtaining that the common influencing factor of the selection parameters is the near field length; Step 3.1.2, obtaining the variation trend of each selection parameter according to the near field length; Step 3.1.3, obtain the selection data of the corresponding angle probe according to the applicable scenario and structural shape of the steel casting, and use this as the basis for selection.

6. The method for selecting a near-field blind spot detection probe for a rough-machined surface of a steel casting according to claim 4, characterized in that: In step 3.2, the dual element transducer evaluation consists of the following sub-steps: Step 3.2.1, select the probe frequency value of the corresponding dual crystal probe according to the energy concentration required for ultrasonic flaw detection and the detection area; Step 3.2.2, select the corresponding dual crystal probe size according to the detection area required for ultrasonic flaw detection; Step 3.2.3, selecting the focal length of the corresponding dual crystal probe according to the machining allowance of the ultrasonic flaw detection steel casting; Step 3.2.4, based on the above-obtained selection parameters, obtain the selection data of the dual crystal probe according to the applicable scenarios of the steel castings and the structural shape to be cast.

7. The method for selecting a near-field blind spot detection probe for a rough-machined surface of a steel casting according to claim 5, characterized in that: In step 3.1.1, according to the expression of near field length: N=Fs / πλs×cosβ / cosα-L1× (tanα / tanβ) (Formula 1); Where, N is the near field length; Fs is the wafer size of the probe, and Fs = a × b; λs is the wavelength of the S wave in steel; β is the shear wave refraction angle; tanβ = K value, which is the tangent value of the probe refraction angle; α is the incident angle of the probe; L1 is the distance from the incident point to the wave source; According to Snell's law, that is, α = αL, α can be obtained, αL = arcsin (CL1 / Cs2×sinβ) (Formula 2); Where, CL1 is the L wave speed in the organic glass of the oblique probe, which is 2730 mm / s; Cs2 is the shear wave speed, which is 3230 mm / s; αL is the L wave incident angle; In step 3.1.2, according to formula 2, the change trend of each selection parameter of the angle probe can be obtained as follows: For the frequency of the angle probe, the higher the frequency, the larger the near-field length N value; For the chip size of the oblique probe, the larger the chip size, the larger the near-field length N value; For the K value of the angle probe, the larger the K value, the smaller the near-field length N value.

8. The method for selecting a near-field blind spot detection probe for a rough-machined surface of a steel casting according to claim 5, characterized in that: In step 3.1.3, it is also necessary to consider avoiding ultrasonic flaw detection in the near field when comprehensively selecting the selection data of the angle probe.

9. The method for selecting a near-field blind spot detection probe for a rough-machined surface of a steel casting according to claim 6, characterized in that: In step 3.2.3, the focal length is determined by the chip tilt angle of the dual-crystal probe. The corresponding tilt angle is selected according to the processing allowance to obtain the corresponding focal length value.

10. The method for selecting a near-field blind spot detection probe for a rough-machined surface of a steel casting according to claim 1, characterized in that: In step 4, the detection method includes the following sub-steps: Step 4.1, select at least three artificial defects of appropriate depth on the test block; Step 4.2, making a DAC curve or an AVG curve according to the selected defect to test the selected probe; Step 4.3, verifying the tested probe on the rough-machined steel casting product; obtaining the verification result; Step 4.4, optimize the selection method based on the verification results.

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