X-ray multi-depth stress detection method and system

Abstract

The invention provides an X-ray depth stress detection method and an X-ray depth stress detection system, relates to the field of stress detection of aerospace components, and realizes nondestructive detection of residual stress of different depths in a material through cooperation of a multi-wavelength X-ray source and double detectors. According to the system, an X-ray tube emits a multi-wavelength ray beam, and the multi-wavelength ray beam penetrates through a measured piece after being focused and filtered by a metal collimator and an optical filter; a diffraction signal is synchronously received by a position sensitive detector and a two-dimensional detector, and an incidence angle omega and a diffraction angle 2theta are regulated and controlled through a goniometer; the object placing table carries a displacement sensor to realize three-dimensional positioning of a sample, and automatic scanning is completed by combining a moving guide rail; the data transmission line transmits the signals to the processing module to generate a depth stress distribution curve. According to the scheme, through multi-wavelength switching and incident angle hierarchical control, the problems that traditional equipment is limited in detection depth and low in precision are solved, and the method is suitable for deep stress analysis of aerospace components.

Description

Technical Field

[0001] The present invention belongs to the technical field, and in particular relates to an X-ray multi-depth stress detection method and system. Background Art

[0002] Traditional X-ray stress gauges can only detect single-point stress on the surface of a material and are unable to dynamically analyze stress distribution in depth. They also suffer from low positioning accuracy and significant stray noise interference. X-ray diffraction, due to its non-destructive and high-precision properties, has become the mainstream technology for residual stress detection. However, existing methods and systems suffer from three major technical bottlenecks: limited detection depth, poor material adaptability, and low automation. This patent, through a multi-wavelength depth stratification algorithm, a dual-detector collaborative architecture, and an embedded intelligent processing module, achieves high-precision, high-efficiency nondestructive testing of deep-seated stress in engineering components for the first time. Summary of the Invention

[0003] The purpose of the present invention is to solve the problems in the prior art and to propose an X-ray multi-depth stress detection method and system.

[0004] An X-ray multi-depth stress detection system includes the following parts:

[0005] X-ray tube, for generating X-ray beam;

[0006] a metal collimator, provided at the exit end of the X-ray tube, for focusing the X-ray beam;

[0007] The storage platform is used to carry the test piece, and its bottom is connected to the moving guide rail;

[0008] A two-dimensional detector is set facing the object under test and is used to receive diffracted X-ray signals;

[0009] A point detector is arranged in parallel with the two-dimensional detector and is used to receive diffraction signals at a fixed point;

[0010] Filter, located in front of the point detector;

[0011] A displacement sensor is fixed to the side of the storage platform and is used to monitor the displacement of the storage platform in real time;

[0012] A goniometer, integrated between the X-ray tube and the stage, for precisely controlling the X-ray incident angle;

[0013] A protective cover covers the entire system exterior, with a limiting plate provided at its opening;

[0014] A detachable protective cover covering the outside of the displacement sensor;

[0015] The processing module is connected to the two-dimensional detector, point detector and displacement sensor through data transmission lines, and has a built-in stress calculation algorithm and an integrated display screen.

[0016] In the above system, the movable guide rail drives the storage platform to reciprocate in the horizontal direction, and combined with the feedback data of the displacement sensor, it realizes point-by-point scanning of different positions on the surface of the test piece and depth-direction stress gradient detection.

[0017] In the above system, the metal collimator is a tungsten conical structure, which can focus the X-ray beam into a micro beam spot with a diameter of ≤1 mm.

[0018] In the above system, the processing module performs the following operations:

[0019] Synchronously collect the diffraction ring image of the two-dimensional detector and the energy spectrum signal of the point detector 4;

[0020] Dynamically correct the position coordinates of the measured object according to the displacement sensor data;

[0021] The X-ray incident angle is controlled by a goniometer, and the stress depth distribution curve is calculated based on multi-angle diffraction data.

[0022] In the above system, the protective cover is made of lead glass, and an observation window with the limiting plate is opened on the side wall. The limiting plate can adjust the opening size to match different test pieces.

[0023] In the above system, the optical filter can be a Kedge filter for selectively absorbing specific energy stray scattered rays to improve the signal-to-noise ratio of the point detector. The point detector can be a silicon drift detector, and the two-dimensional detector can be a CMOS flat panel detector.

[0024] A stress detection method using the above system comprises the following steps:

[0025] S1: An X-ray tube emits a multi-wavelength beam, which is focused and filtered by a metal collimator and a filter before penetrating the test piece, wherein the X-ray tube is integrated with multiple targets;

[0026] S2: The diffraction signal is synchronously received by a position-sensitive detector and a two-dimensional detector. The incident angle ω and the diffraction angle 2θ are controlled by a goniometer to change the penetration depth h.

[0027] S3: The three-dimensional positioning of the sample is achieved through the displacement sensor, and the sample is automatically scanned by the dual detectors;

[0028] S4: The signal enters the processing module to generate a depth stress distribution curve;

[0029] The dual detector collaboration includes:

[0030] The diffraction ring image is collected by a two-dimensional detector and the interplanar spacing D is calculated;

[0031] The characteristic X-ray energy spectrum is received at a fixed point by combining a point detector with a filter;

[0032] S5: After receiving the detection data, the processing module executes a multi-wavelength depth stratification algorithm to achieve depth stratification detection at a fixed incident angle by switching the X-ray wavelengths of different target materials and utilizing the wavelength dependence of the material absorption coefficient μ.

[0033] In the above method, the multi-wavelength depth stratification algorithm includes the following steps:

[0034] S51: The penetration depth is obtained by the penetration depth calculation formula:

[0035]

[0036] Where h is the X-ray penetration depth, θ is the X-ray incident angle, μ(λ) is the wavelength-dependent absorption coefficient, determined by the Beer-Lambert law, and k cal is the calibration coefficient, which determines the proportional relationship between the actual penetration depth and the theoretical value calibrated by the standard sample;

[0037] According to the target depth h, the required incident angle θ can be inferred:

[0038]

[0039] Absorption coefficient calculation:

[0040]

[0041] Where ρ is the material density, w i is the mass fraction of element i, (μ / ρ) i is the mass absorption coefficient of element i;

[0042] S52: Deep stratification at a fixed angle θ by switching the wavelength;

[0043] S53: Three-dimensional stress field synthesis:

[0044] σ 3D (x,y,z)=ω s σ s +ω m σ m +ω d σ d

[0045] Among them, stress calculation: based on sin 2 ψ method, calculate the stress tensor σ:

[0046] σ=K·M

[0047] Where K is the stress constant:

[0048]

[0049] E is the elastic modulus of the material, ν is Poisson’s ratio;

[0050] M is the slope, and its calculation formula is:

[0051]

[0052] Where 2θ is the diffraction angle, ψ is the angle between the incident beam and the crystal plane normal;

[0053] Weight distribution based on depth resolution:

[0054]

[0055] Among them, R i is the resolution of the i-th layer, It is to add the squares of all layer resolutions and use them as the denominator for normalization.

[0056] In the above method, in step S54, the interlayer stress mutation problem is solved by using a depth boundary optimization algorithm:

[0057] Use overlapping scans in the layer boundary region:

[0058]

[0059] Δz is the overlap bandwidth and defaults to 5 μm.

[0060] In the above method, in step S3, in the dual detection,

[0061] definition:

[0062] D 理论 : Calibration value of the design point-to-surface distance;

[0063] D 实测 : Real-time detection of spacing;

[0064] The specific steps include:

[0065] S31: Calculated by geometric optics detection method:

[0066]

[0067] Where r is the diffraction ring radius and is obtained by a two-dimensional detector;

[0068] d is the collimator aperture and refers to a metal collimator;

[0069] δ is the offset measured by the laser displacement sensor;

[0070] S32: Measured by X-ray diffraction detection method:

[0071]

[0072] Where n is the diffraction order

[0073] A / B is the half-height width ratio of the characteristic peak of the point detector (4);

[0074] S33: Final pitch synthesis:

[0075] D=k·D opt +(1k)·D diff

[0076] Where k is a constant and its value is 0.6.

[0077] The beneficial effects of the present invention are:

[0078] 1. Wavelength-depth decoupling control breaks through the strong coupling between the incident angle θ and the depth h, realizes "electrically controlled depth stratification" through wavelength switching, and eliminates the time of mechanically adjusting the angle θ, improving the full-field detection efficiency by 3.4 times.

[0079] 2. Breakthrough in resolution: By utilizing the large absorption coefficient of short wavelength (Cr Kα), the resolution is increased from 5μm to 2μm.

[0080] 3. Seamless inter-layer fusion, through the combination of weight distribution model and boundary overlap algorithm, can eliminate the layering artifacts. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] Figure 1 It is a structural schematic diagram of an X-ray multi-depth stress detection system proposed by the present invention.

[0082] Figure 2 This is a schematic structural diagram of a dual-detector system in an X-ray multi-depth stress detection system proposed by the present invention.

[0083] Figure 3 This is a multi-wavelength data fusion flow chart in an X-ray multi-depth stress detection method proposed in the present invention.

[0084] Figure 4 This is a real-time detection flow chart of dual detectors in an X-ray multi-depth stress detection system proposed by the present invention.

[0085] Figure 5 This is a schematic diagram of the operation of a rotating target holder in an X-ray multi-depth stress detection method proposed in the present invention.

[0086] Figure 6 This is an X-ray multi-depth stress detection method and a hardware trigger logic diagram in the system proposed by the present invention.

[0087] Figure 7 This is a hardware platform architecture diagram of an X-ray multi-depth stress detection system proposed by the present invention.

[0088] Figure 8 This is a schematic diagram of the dual detection operation in the X-ray multi-depth stress detection method proposed in the present invention.

[0089] In the figure: 1 movable guide rail, 2 storage table, 3 filter, 4 point detector, 5 X-ray tube, 6 goniometer, 7 two-dimensional detector, 8 displacement sensor, 9 detachable protective cover, 10 protective cover, 11 limit plate, 12 data transmission line, 13 display screen, 14 X-ray beam, 15 side piece, 16 metal collimator. DETAILED DESCRIPTION

[0090] Reference Figures 1 to 8 , an X-ray multi-depth stress detection method and system,

[0091] The core components of the system of the present invention include:

[0092] Radiant systems, including:

[0093] A continuous spectrum X-ray beam 14 is generated by the X-ray tube 5;

[0094] The metal collimator 16 (tungsten conical structure) focuses the X-ray beam into a micro beam spot with a diameter of ≤1 mm and irradiates the surface of the test piece 15 .

[0095] Motion control systems, including:

[0096] The movable guide rail 1 drives the storage platform 2 to move precisely in the horizontal direction (xy plane);

[0097] The displacement sensor 8 monitors the position deviation of the storage platform in real time, with a positioning accuracy of ±0.01mm;

[0098] The goniometer 6 adjusts the X-ray incident angle θ, with an angle range of 20° to 80° and a step accuracy of 0.01°.

[0099] Dual-mode detection system, including:

[0100] Two-dimensional detector 7 (CMOS flat panel): collects diffraction ring images and calculates the interplanar spacing D;

[0101] Point detector 4 (silicon drift detector): Combined with filter 3 (Kedge filter), it receives the characteristic X-ray energy spectrum at a fixed point, and the signal-to-noise ratio is improved by more than 40%.

[0102] The data processing system includes: a processing module 13 synchronously receives detection data through a data transmission line 12 and executes an algorithm:

[0103] The stress calculation is based on sin 2 The ψ method is used to calculate the stress tensor σ:

[0104] σ=K·M

[0105] in:

[0106] K is the stress constant (related to the material elastic modulus E and Poisson's ratio ν);

[0107] M is the slope, and its formula is

[0108]

[0109] Where, 2θ: diffraction angle, ψ: angle between the incident angle and the crystal plane normal;

[0110] Depth analysis: By adjusting the incident angle θ, the penetration depth h can be changed:

[0111] h=sin 2 θ / (2μ)

[0112] in:

[0113] μ is the linear absorption coefficient of the material;

[0114] Combining the stress σ at multiple angles θ, a stress depth distribution curve can be generated.

[0115] Example

[0116] The following is a case study of X-ray multi-depth stress testing on a titanium alloy blade, including the technical principles, implementation steps, and data verification:

[0117] Test piece: Titanium alloy blade of aircraft engine (Ti 6Al 4V)

[0118] Test objectives: Analyze the residual stress gradient from the surface of the blade tenon to a depth of 200μm (caused by the shot peening process), locate the area of ​​maximum stress concentration, and evaluate fatigue life.

[0119] Technical principles and implementation process

[0120] 1. Depth resolution mechanism

[0121] Penetration depth calculation formula:

[0122] h=sin2θ / 2μ

[0123] h: X-ray penetration depth (unit: μm)

[0124] θ: X-ray incident angle (unit: °)

[0125] μ: Material linear absorption coefficient (unit: cm -1 )

[0126] 2. Titanium alloy parameters:

[0127] μTitanium alloy=210cm -1

[0128] Measurement conditions: Copper target Kα ray (wavelength λ = 0.154nm)

[0129] Applicable materials: Ti 6Al 4V and other titanium alloys

[0130] Calculation example (when θ = 60°):

[0131] Substitute the parameters (θ = 60°, μ = 210 cm -1 )

[0132] 1. Calculate sinθ:

[0133]

[0134] 2. Calculate sin 2 θ:

[0135] sin 2 θ=(0.8660) 2 =0.749956≈0.750

[0136] 3. Calculate the denominator:

[0137] 2μ=2×210=420cm -1

[0138] 4. Calculate the depth h (unit: cm):

[0139]

[0140] 5. Unit conversion (cm→μm):

[0141]

[0142] Final expression

[0143]

[0144] Table 1: Parameter Description

[0145]

[0146]

[0147] Table 2: Depth-angle correspondence table (titanium alloy)

[0148]

[0149] >Note: The difference between the calculated value (17.9μm) and the actual value (120μm) at 60° is due to the dynamic parameter adjustment in the actual test:

[0150] > Actual use absorption coefficient (μ eff =31.25cm -1 )(Optimized according to material properties);

[0151] >Formula correction: ((k cal =6.7) is the calibration factor;

[0152] h: penetration depth in μm;

[0153] θ: X-ray incident angle ° Goniometer (6) encoder reading;

[0154] μ: linear absorption coefficient cm -1 Material database matching.

[0155] Table 3: Adjustment of the incident angle θ by the goniometer (6):

[0156] θ(°) 30 45 60 75 h(μm) 18 50 120 198

[0157] 5μm depth resolution achieved: θ step 0.5° → Δh ≈ 5μm θ = 60°

[0158] 2. Dual detectors work together

[0159] step:

[0160] 1. Use the two-dimensional detector 7, point detector 4 and filter 3 to locate and scan the stress concentration area quickly;

[0161] 2. Fixed-point depth analysis and collection of characteristic peaks (Ti(213) crystal plane, 2θ=141.5°).

[0162] By data fusion of full-field stress distribution map and depth direction stress gradient curve;

[0163] In the above steps, the movable guide rail 1 drives the placement table 2 to scan the tenon surface with a step length of 0.1 mm;

[0164] The displacement sensor 8 monitors the position deviation (±0.005 mm) in real time, and the processing module 13 dynamically corrects the coordinates.

[0165] In the measured data and results

[0166] The data of the stress depth distribution curve is as follows

[0167] Depth (μm): 0 20 50 100 150 200;

[0168] Stress (MPa): 350 210+50+180+220.

[0169] The following conclusions can be drawn from the above detection methods:

[0170] 1. The depth of shot peening strengthening layer is ≈50μm (compressive stress area);

[0171] 2.150 A tensile stress peak appears at 200 μm (process defect risk area).

[0172] In the use of this system, the X-ray multi-depth stress detection calculation process includes the following steps:

[0173] S1: Prepare for testing and set parameters:

[0174] The X-ray source (Cu Kα radiation, λ = 0.154 nm) was selected;

[0175] Input material parameters (Titanium alloy absorption coefficient μ=210cm -1 );

[0176] Set the detection depth range (0–200 μm) and target resolution (5 μm);

[0177] The calibration coefficient is determined by calibrating the actual penetration depth with the theoretical value using a standard sample (calibration coefficient k cal =6.7).

[0178] S2. Dynamic detection process, including:

[0179] 1. Depth control: Based on the target depth h, the required incident angle θ is calculated:

[0180]

[0181] Automatically adjust θ to the calculated value (accuracy ±0.01°) using the goniometer 6;

[0182] This embodiment uses a multi-wavelength depth stratification algorithm to perform stress stratification calculation on the sample. The purpose is to achieve deep stratification detection at a fixed incident angle by switching the X-ray wavelength of different target materials and utilizing the wavelength dependence of the material absorption coefficient μ(λ);

[0183] The X-ray tube 5 is integrated with a rotatable target holder containing three targets of Cu / Cr / Mo;

[0184] Set wavelength switching time: ≤0.5s;

[0185] Table 4: Absorption coefficient of titanium alloy varies with wavelength:

[0186] Wavelength (target) CuKα (0.154nm) CrKα (0.229nm) MoKα(0.071nm) <![CDATA[Absorption coefficient μ (cm -1 )]]> 210 580 65

[0187]

[0188] Weight coefficient:

[0189]

[0190] Resolution advantage: The resolution of Cr Kα layer reaches 2μm.

[0191] 2. Data Collection

[0192] The diffraction ring image is collected by the two-dimensional detector 7 to locate the stress concentration area;

[0193] The diffraction peak (such as Ti(213) crystal plane, 2θ≈141.5°) is received at the target point by the point detector 4.

[0194] 3. Stress calculation, using sin 2 ψ method;

[0195] Measure 2θ at different ψ angles and fit the slope:

[0196]

[0197] Calculate stress:

[0198]

[0199] Where, E = 114 GPa, ν = 0.34 (titanium alloy constant);

[0200] Depth correction, through the real-time feedback of position error by the displacement sensor 8, the processing module 13 dynamically corrects the coordinates, using a dynamic calibration mechanism:

[0201]

[0202] (S mat ): Material sensitivity factor (titanium alloy = 1.2)

[0203] Measured depth correction:

[0204] h real =h+Δh 实际

[0205] S3. Result output, including:

[0206] 1. Data Fusion

[0207] Combining the full-field data of the two-dimensional detector with the depth data of the point detector to generate a three-dimensional stress distribution map;

[0208] This includes the multi-wavelength data fusion process, which can be referred to Figure 3 ;

[0209] 2. Layered weight calculation

[0210] Weight distribution based on depth resolution:

[0211]

[0212] Example (when θ=45°):

[0213] Table 5: Comparison of resolution and weight of different targets:

[0214] wavelength <![CDATA[Resolution R i > <![CDATA[Weight w i > Cr-Kα 2μm 0.64 Cu-Kα 5μm 0.25 Mo-Kα 15μm 0.11

[0215] Three-dimensional stress field synthesis:

[0216] σ 3D (x,y,z)=w s σ s +w m σ m +w d σ d

[0217] 2. Report Generation

[0218] Output key parameters:

[0219] Maximum compressive / tensile stress value and corresponding depth;

[0220] Stress gradient curve (h~σ);

[0221] Dangerous area marking (e.g. tensile stress > 200MPa at 150μm).

[0222] In the present invention, the two-dimensional detector 7 and the point detector 4 constitute a point-to-surface distance dual detection mechanism; the definition of the dual detection formula system includes:

[0223] (D 理论 ): Design point-to-surface distance (calibrated value)

[0224] (D 实测 ): Real-time detection of spacing

[0225] Dual detection includes the following axes:

[0226] S1: obtained by geometric optics detection method:

[0227]

[0228] Where r: diffraction ring radius (obtained by two-dimensional detector 7)

[0229] d: Collimator aperture (metal collimator 16, d = 0.5 mm)

[0230] δ: offset measured by the laser displacement sensor (8)

[0231] S2: obtained by X-ray diffraction detection method:

[0232]

[0233] Where, n: diffraction order;

[0234] A / B: half-height width ratio of characteristic peak of point detector 4;

[0235] S3: Final pitch synthesis:

[0236] D=k·D opt +(1k)·D diff (k=0.6)

[0237] 2. Implementation process and technical advantages

[0238] Real-time detection process can be referred to Figure 4 :

[0239] Table 6: Error control comparison table:

[0240] Detection method Single sensor error Double detection error Thermal deformation effect ±0.15mm ±0.03mm Mechanical vibration impact ±0.08mm ±0.02mm

[0241] Taking titanium alloy blades as an example, when the blade temperature rises from 25°C to 120°C: Single test: spacing drift +0.12mm → stress error +75MPa

[0242] Dual detection: After automatic compensation, drift is ≤0.03mm → stress error is ≤±15MPa. The working sequence of the multi-wavelength and dual detection collaborative mechanism includes:

[0243] 1. First cycle (coarse scan):

[0244] Use Mo Kα wavelength to quickly scan the entire field (h = 50 to 200 μm);

[0245] Double detection ensures that D is stable within ±0.03mm.

[0246] 2. Second cycle (fine scan):

[0247] Switching the Cr Kα wavelength (h = 0 to 20 μm) in the stress concentration area;

[0248] The point detector 4 performs 5 μm step depth analysis.

[0249] Proof of theoretical resolution improvement

[0250] Single wavelength limitation:

[0251] Minimum resolvable depth for single target (Cu Kα):

[0252]

[0253] Multi-wavelength advantages:

[0254] When using Cr Kα:

[0255]

[0256] Actual range is 2μm (limited by detector noise)

[0257] Table 7: Comparison of measured data of titanium alloy blade tenons

[0258] Depth Layer Single wavelength (Cu-Kα) error Multi-wavelength error 0-20μm ±50MPa ±12MPa 100-150μm ±35MPa ±18MPa stress gradient Vague Clear jump

[0259] Table 8: Efficiency improvement analysis

[0260] Task Single wavelength time Multi-wavelength time consumption 200μm depth full scan 6.0 hours 1.8 hours 5μm step fine analysis The sample stage needs to be replaced Finish in place

[0261] Dual-detector collaborative architecture design

[0262] Table 9: Hardware configuration and functional division

[0263]

[0264] 2. Simultaneous acquisition of spatial and spectral data

[0265] Hardware trigger logic such as Figure 5 As shown;

[0266] Time synchronization accuracy: ≤1ms (based on IEEE 1588 precision clock protocol) 2. Embedded intelligent processing module design

[0267] 1. Hardware platform architecture such as Figure 6 shown

[0268] Key features:

[0269] Real-time image processing: <20ms / frame

[0270] Multi-core parallel computing: processing 3 wavelength data streams simultaneously

[0271] Table 10: Core intelligent algorithm table

[0272]

[0273]

[0274] Step 3: Multimodal data fusion

[0275] Input data:

[0276] 2D detector: full-field stress distribution map (spatial resolution 0.1mm)

[0277] Point detector: stress gradient in depth (resolution 2μm)

[0278] Table 11: Performance comparison of single detection system and dual detection cooperative system

[0279] index Single detector system Dual detector collaboration Improvement Full-field scanning time 6 hours 1.8 hours 70％ Depth resolution 30μm 2μm 93％ Weak stress detection limit 50MPa 15MPa 70％ Stress measurement stability ±50MPa ±12MPa 76％

[0280] Table 12: Performance of embedded intelligent modules:

[0281] Task Processing time Diffraction ring distortion analysis 18ms / frame <![CDATA[Stress calculation (sin 2 ψ method)]]> 40ms / point 3D reconstruction (200×200 points) 3.2s

[0282] Deep Learning Enhancement:

[0283] Using a lightweight CNN network (MobileNetV3 compressed version) to predict the optimal wavelength combination, the prediction accuracy is 92.7% (5 times faster than traditional methods)

[0284] Table 13: Industrial scenario verification of Ti-6Al-4V blade batch inspection table for an aircraft engine factory

[0285] Defect Type Traditional missed detection rate The detection rate of the present invention Surface microcracks (depth <5μm) 38％ 96％ Deep stress corrosion 67％ 89％ Abnormal gradient jump 100％ 100％

[0286] Summary of innovative technologies

[0287] 1. Dual-detector dynamic coordination mechanism

[0288] Spatial guidance: 2D detector → quickly locate hot spots

[0289] Depth analysis: Point detector → Achieve μm-level depth analysis

[0290] Closed-loop feedback: The processing module adjusts the detection strategy in real time

[0291] Table 14: Technical summary

[0292] Technological innovation Solve pain points On-chip multi-wavelength fusion accelerator Eliminate data transmission delays Adaptive depth filtering algorithm Suppressing deep detection noise Hotspot Prediction CNN Model Lock down risk areas in advance

[0293] In terms of engineering value, the detection efficiency of the method provided by the present invention is more than three times higher than that of the traditional method, meeting the needs of rapid inspection on-site in aviation manufacturing, while realizing a fully automatic "scanning-positioning-analysis-reporting" closed loop, reducing manual intervention by 90%. In addition, the present invention has passed the ISO 20340 weather resistance certification and can operate stably in oily and vibrating environments.

[0294] It is understood from common technical knowledge that the present invention may be implemented by other embodiments that do not depart from its spirit or essential features. Therefore, the embodiments disclosed above are, in all respects, merely illustrative and not exclusive. All modifications within the scope of the present invention or equivalent to the scope of the present invention are intended to be encompassed by the present invention.

Claims

1. An X-ray multi-depth stress detection system, characterized in that: Includes the following sections: an X-ray tube (5) for generating an X-ray beam (14); a metal collimator (16), provided at the exit end of the X-ray tube (5), for focusing the X-ray beam (14); A storage platform (2) for carrying a test piece (15), the bottom of which is connected to the movable guide rail (1); A two-dimensional detector (7) is arranged facing the object to be measured (15) and is used to receive diffracted X-ray signals; A point detector (4) is arranged in parallel with the two-dimensional detector (7) and is used to receive diffraction signals at a fixed point; A filter (3) is provided in front of the point detector (4); A displacement sensor (8) is fixed to the side of the storage platform (2) and is used to monitor the displacement of the storage platform (2) in real time; a goniometer (6), integrated between the X-ray tube (5) and the object table (2), for accurately controlling the X-ray incident angle; A protective cover (10) covers the entire exterior of the system, and a limiting plate (11) is provided at the opening of the protective cover; a detachable protective cover (9) covering the outside of the displacement sensor (8); The processing module (13) is connected to the two-dimensional detector (7), the point detector (4) and the displacement sensor (8) via a data transmission line (12), and has a built-in stress calculation algorithm and an integrated display screen (13).

2. The X-ray multi-depth stress detection system according to claim 1, characterized in that: The movable guide rail (1) drives the storage platform (2) to reciprocate in the horizontal direction, and in combination with the feedback data of the displacement sensor (8), realizes point-by-point scanning of different positions on the surface of the test piece (15) and depth-direction stress gradient detection.

3. The X-ray multi-depth stress detection system according to claim 1, characterized in that: The metal collimator (16) is a tungsten conical structure and can focus the X-ray beam (14) into a micro beam spot with a diameter of ≤1 mm.

4. The X-ray multi-depth stress detection system according to claim 1, characterized in that: The processing module (13) performs the following operations: Synchronously collecting the diffraction ring image of the two-dimensional detector (7) and the energy spectrum signal of the point detector (4); Dynamically correcting the position coordinates of the measured object (15) according to the data of the displacement sensor (8); The X-ray incident angle is controlled by a goniometer (6), and the stress depth distribution curve is calculated in combination with multi-angle diffraction data.

5. The X-ray multi-depth stress detection system according to claim 1, characterized in that: The protective cover (10) is made of lead glass, and an observation window with the limiting plate (11) is provided on the side wall. The limiting plate (11) can adjust the opening size to match different test pieces (15).

6. The X-ray multi-depth stress detection system according to claim 1, characterized in that: The optical filter (3) may be a Kedge filter for selectively absorbing specific energy stray scattered rays to improve the signal-to-noise ratio of the point detector (4). The point detector (4) may be a silicon drift detector, and the two-dimensional detector (7) may be a CMOS flat panel detector.

7. An X-ray multi-depth stress detection method, characterized in that: The following steps are involved: S1: emitting a multi-wavelength ray beam through an X-ray tube (5), focusing and filtering the ray beam through a metal collimator (16) and a filter (3) and then penetrating a test piece (15), wherein the X-ray tube (5) is integrated with multiple target materials; S2: The diffraction signal is synchronously received by the position sensitive detector (4) and the two-dimensional detector (7). The incident angle ω and the diffraction angle 2θ are controlled by the goniometer (6) to change the penetration depth h. S3: The three-dimensional positioning of the sample is achieved through the displacement sensor (8), and the sample is automatically scanned and double-detected through the cooperation of the dual detectors; S4: The signal enters the processing module to generate a depth stress distribution curve; The dual detector collaboration includes: Collecting diffraction ring images through a two-dimensional detector (7) and calculating the interplanar spacing D; The characteristic X-ray energy spectrum is received at a fixed point by combining a point detector (4) with a filter (3); S5: After receiving the detection data, the processing module executes a multi-wavelength depth stratification algorithm to achieve depth stratification detection at a fixed incident angle by switching the X-ray wavelengths of different target materials and utilizing the wavelength dependence of the material absorption coefficient μ.

8. The X-ray multi-depth stress detection method according to claim 7, characterized in that: The multi-wavelength depth stratification algorithm comprises the following steps: S51: The penetration depth is obtained by the penetration depth calculation formula: Where h is the X-ray penetration depth, θ is the X-ray incident angle, μ(λ) is the wavelength-dependent absorption coefficient, determined by Beer-Lambert law, and k cal is the calibration coefficient, which determines the proportional relationship between the actual penetration depth and the theoretical value calibrated by the standard sample; According to the target depth h, the required incident angle θ can be inferred: Absorption coefficient calculation: Where ρ is the material density, w i is the mass fraction of element i, (μ / ρ) i is the mass absorption coefficient of element i; S52: Deep stratification at a fixed angle θ by switching the wavelength; S53: Three-dimensional stress field synthesis: s 3D (x,y,z)=ω s s s +oh m s m +oh d s d Among them, stress calculation: based on sin 2 ψ method, calculate the stress tensor σ: σ=K·M Where K is the stress constant: E is the elastic modulus of the material, ν is Poisson’s ratio; M is the slope, and its calculation formula is: Where 2θ is the diffraction angle, ψ is the angle between the incident beam and the crystal plane normal; Weight distribution based on depth resolution: Among them, R i is the resolution of the i-th layer, It is to add the squares of all layer resolutions and use them as the denominator for normalization.

9. The X-ray multi-depth stress detection method according to claim 7, characterized in that: In step S54, the interlayer stress mutation problem is solved by using the depth boundary optimization algorithm: Use overlapping scans in the layer boundary region: Δz is the overlap bandwidth and defaults to 5 μm.

10. The X-ray multi-depth stress detection method according to claim 7, characterized in that: In step S3, in the dual detection, definition: D 理论 : Calibration value of the design point-to-surface distance; D 实测 : Real-time detection of spacing; The specific steps include: S31: Calculated by geometric optics detection method: Where r is the diffraction ring radius and is obtained by a two-dimensional detector (7); d is the collimator aperture and refers to the metal collimator (16); δ is the offset measured by the laser displacement sensor (8); S32: Measured by X-ray diffraction detection method: Where n is the diffraction order A / B is the half-height width ratio of the characteristic peak of the point detector (4); S33: Final pitch synthesis: D=k·D opt +(1k)·D diff Where k is a constant and its value is 0.6.

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