I-DCGAN and TOPSIS-IFP:A simulation generation model for radiographic flaw detection images in light alloy castings and an algorithm for quality evaluation of generated images

The intelligent detection technology driven by X-ray images and deep learning represents the forefront of advanced techniques and development trends in flaw detection and automated evaluation of light alloy castings.However,the efficacy of deep learning models hinges upon a substantial abundance of flaw samples.The existing research on X-ray image augmentation for flaw detection suffers from shortcomings such as poor diversity of flaw samples and low reliability of quality evaluation.To this end,a novel approach was put forward,which involves the creation of the Interpolation-Deep Convolutional Generative Adversarial Network(I-DCGAN)for flaw detection image generation and a comprehensive evaluation algorithm named TOPSIS-IFP.I-DCGAN enables the generation of high-resolution,diverse simulated images with multiple appearances,achieving an improvement in sample diversity and quality while maintaining a relatively lower computational complexity.TOPSIS-IFP facilitates multi-dimensional quality evaluation,including aspects such as diversity,authenticity,image distribution difference,and image distortion degree.The results indicate that the X-ray radiographic images of magnesium and aluminum alloy castings achieve optimal performance when trained up to the 800th and 600th epochs,respectively.The TOPSIS-IFP value reaches 78.7%and 73.8%similarity to the ideal solution,respectively.Compared to single index evaluation,the TOPSIS-IFP algorithm achieves higher-quality simulated images at the optimal training epoch.This approach successfully mitigates the issue of unreliable quality associated with single index evaluation.The image generation and comprehensive quality evaluation method developed in this paper provides a novel approach for image augmentation in flaw recognition,holding significant importance for enhancing the robustness of subsequent flaw recognition networks.

RESEARCH AND PRACTICE ON NONDESTRUCTIVE FLAW DETECTION INSTALLATION FOR WIRE-CORE BELT

Electromagnetic self-induction theory and computer are adopted and study of online monitoring technique for wire-core belt is conducted, the study shows that there is direct proportion between distance Ⅰ of broken ends and output volt Ⅴ, when Ⅰ ≥60 mm, Ⅴ keeps constantly, the running speed v of wire-core belt has no big effect on output volt Ⅴ, there is inverse proportion between the height h from probe to the surface of the belt and output volt Ⅴ, when h≥30 mm, Ⅴ tends to be zero. Based on the test result, on-line monitoring installation is developed, the practice proved that the accuracy of broken wire monitoring can be above 95%, the monitoring accuracy of joint twitch can be 0 .04 Ⅴ/mm.

Statistic Learning-based Defect Detection for Twill Fabrics

Template matching methods have been widely utilized to detect fabric defects in textile quality control. In this paper, a novel approach is proposed to design a flexible classifier for distinguishing flaws from twill fabrics by statistically learning from the normal fabric texture. Statistical information of natural and normal texture of the fabric can be extracted via collecting and analyzing the gray image. On the basis of this, both judging threshold and template are acquired and updated adaptively in real-time according to the real textures of fabric, which promises more flexibility and universality. The algorithms are experimented with images of fault free and faulty textile samples.

Detection of Cracks in Aerospace Turbine Disks Using an Ultrasonic Phased Array C-scan Device

Crack detection in an aerospace turbine disk is essential for aircraft-quality detection.With the unique circular stepped structure and superalloy material properties of aerospace turbine disk,it is difficult for the traditional ultrasonic testing method to perform efficient and accurate testing.In this study,ultrasound phased array detection technology was applied to the non-destructive testing of aviation turbine disks:(i)A phased array ultrasonic c-scan device for detecting aerospace turbine disk cracks(PAUDA)was developed which consists of phased array ultrasonic,transducers,a computer,a displacement encoder,and a rotating scanner;(ii)The influence of the detection parameters include frequency,wave-type,and elements number of the ultrasonic phased array probe on the detection results on the near-surface and the far surface of the aerospace turbine disk is analyzed;(iii)Specimens with flat-bottom-hole(FBH)defects were scanned by the developed PAUDA and the results were analyzed and compared with the conventional single probe ultrasonic water immersion testing.The experiment shows that by using the ultrasonic phased array c-scan to scan the turbine disk the accuracy of the detection can be significantly improved which is of greater accuracy and higher efficiency than traditional immersion testing.

Investigation of Eddy Current Nondestructive Testing for Carbon Fiber-Reinforced Plastic （CFRP） Based on Electromagnetic Field Analysis

CFRP （carbon fiber reinforced plastic） is used extensively in aircraft and spacecraft structures, because of its excellent mechanical properties. Ultrasonic testing, which is used as a non-destructive testing technique for CFRP, requires a contact medium. In contrast, eddy current testing does not require a contact medium, and when used for CFRP testing it has advantages not available with other techniques. CFRP is a laminate, with each layer being anisotropically conductive, and the distribution of the induced eddy current is yet to be determined. Here, to determine the eddy current distribution in the detection of flaws in cross-ply CFRP （0°/90°） by using a cross-point probe, we performed an FEM （finite element method） analysis of electromagnetic fields. We investigated the nature of the flaw signals and the differences in eddy current distributions between materials with and without flaws.

Photodetection of the Quality on Internal Surface of Steel Pipe

In this paper,a photoelectric device is introduced,which is used in detecting the quality on internal surface of thin and long steel pipe.In this device,the CCTV lens is used for extract tile flaw information on internal surface of the pipe,and make IBM-PC/AT 486 computer as controlling and image processing system.By this instrument,the functions,such as the digital conversion of input information,image processing,classification of recognition and output display can be obtained.In the petroleum and chemical industry,by using this apparatus,we can detect the quality on internal surface of various metal pipes with real-time automatically.

Fuzzy detection for ultrasonic flaw inspectionof highly scattering materials

Fuzzy logic detection has been applied to the signal enhancement of ultrasonic flaw echoes from the structure noise due to nonflaw related scattering of ultrasound in highly scattering materials. Cross-correlation, phase difference and fractal dimension are used as signal characteristics in fuzzy logic detection. Experimental results show that this new method has better performance than the commonly used correlation detection.

Experimental Set-up of Laser Ultrasonic Techniques and Applications

A laser ultrasonics generation and non contact detection system has been developed. The weak generated ultrasonic signal of nanosecond duration and nanometer amplitude can be detected with a confocal Fabry Perot interferometer (CFPI). It can be applied to determination of elastic constants of material and flaw detection. The experimental results show that laser ultrasonic technique is practical and effective.