Microstructure, mechanical properties, and corrosion resistance of an explosively welded Mg–Al composite

Identification of damage in its early stage can have a great contribution in decreasing the maintenance costs and prolonging the life of valuable structures. Although conventional damage detection techniques have a mature background, their widespread application in industrial practice is still missing. In recent years the application of Machine Learning (ML) algorithms have been more and more exploited in structural health monitoring systems (SHM). Because of the superior capabilities of ML approaches in recognizing and classifying available patterns in a dataset, they have demonstrated a significant improvement in traditional damage identification algorithms. This review study focuses on the use of machine learning (ML) approaches in Ultrasonic Guided Wave (UGW)-based SHM, in which a structure is continually monitored using permanent sensors. Accordingly, multiple steps required for performing damage detection through UGWs are stated. Moreover, it is outlined that the employment of ML techniques for UGW-based damage detection can be subtended into two main phases: (1) extracting features from the data set, and reducing the dimension of the data space, (2) processing the patterns for revealing patterns, and classification of instances. With this regard, the most frequent techniques for the realization of those two phases are elaborated. This study shows the great potential of ML algorithms to assist and enhance UGW-based damage detection algorithms.

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Emergence of Machine Learning Techniques in Ultrasonic Guided Wave-based Structural Health Monitoring

This work is concerned with a structural health monitoring campaign of a 52-m wind turbine blade. Multiple artificial damages are introduced in the blade sequentially, and fatigue testing is conducted with each damage in sequence. Progressive fatigue-driven damage propagation is achieved, enabling investigations concerning detection of initiation and propagation of damage in the blade. Using distributed accelerometers, operational modal analysis is performed to extract the lower-order natural vibration modes of the blade, which are shown to not be sensitive to small damages in the blade. To enable monitoring of small damages, an active vibration monitoring system is used, comprised of an electrodynamic vibration shaker and distributed accelerometers. From the accelerometer data, frequency domain methods are used to extract features. Using the extracted features, outlier detection is performed to investigate changes in the measurements resulting from the introduced damages. Capabilities of using features based on the active vibration data for detection of initiation and progression of damage in a wind turbine blade during fatigue testing are investigated, showing good correlation between the observed damage progression and the calculated changes in the damage index.

A full-scale wind turbine blade monitoring campaign: detection of damage initiation and progression using medium-frequency active vibrations

The extraordinary combination of strength and ductility of multilayered materials makes them attractive in the various applications and industries (military, aerospace, energy industry etc.). In the present work, the investigated materials were joined into multilayered sheet using the explosive welding method. The three-layer material was made of two titanium sheets and one Armco iron sheet in between. Materials produced by explosive welding can easily be used in a simple deformation process, but more complex processes that employ a more complex mechanical state are still not sufficiently studied. The presented study analyzes the possibilities of using Ti - Armco - Ti sheet for the deep drawing process. For this purpose, the forming limit diagram (FLD) has been constructed and verified. FLD is one of the most important tools in the analysis of sheet metal forming processes. In the presented work the non-standard method (Erichsen test) coupled with Digital Image Correlation analysis was used. The obtained results confirmed that the method of producing the tested sheet and the morphology of the microstructure created have a direct impact on the deformation mechanisms. 

Application of the DIC System to Build a Forming Limit Diagram (FLD) of Multilayer Materials

Due to its exceptional advantages, such as high specific strength, high specific modulus, and good fatigue resistance, carbon-fiber-reinforced plastic (CFRP) is frequently utilized in aerospace, aviation, automotive, rail transportation, and other areas. Composite components typically need to be joined and integrated. In the equipment manufacturing industry, the most used methods for processing composite components are cutting, drilling, and surface treatment. The quality of CFRP is significantly impacted by traditional mechanical processing, causing flaws like delamination, burrs, and tears. Laser processing technology has emerged as a crucial method for processing CFRP for its high quality, non-contact, simple control, and automation features. The most recent research on the laser processing of CFRP is presented in this paper, supporting scientists and engineers who work in the field in using this unconventional manufacturing technique. This paper gives a general overview of the key features of laser processing technology and the numerous machining techniques available. The concepts and benefits of laser processing technology are discussed in terms of the material properties, mode of operation, and laser characteristics, as well as the methods to achieve high efficiency, low damage, and high precision. This paper reviews the research development of laser processing of carbon-fiber-reinforced plastics, and a summary of the factors affecting the quality of CFRP laser processing. Therefore, the research content of this article can be used as a theoretical basis for reducing thermal damage and improving the processing quality of laser-processed composite materials, while, on this basis, we analyze the development trend of CFRP laser processing technology.

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Development of Laser Processing Carbon-Fiber-Reinforced Plastic

When impact damage occurs in carbon fiber-reinforced plastic (CFRP) structures, it is barely visible but may cause significant degradation in the mechanical properties of the structure. Hence, a structural health monitoring (SHM) system that can be installed in CFRP mobility structures and is sensitive to impact damage is needed. In this study, we attempted to establish an SHM system based on ultrasonic guided waves, which are generated by inputting a broadband chirp signal into a film-like piezoelectric actuator. The relationship between impact damage size and maximum time-of-flight (ToF) delay was investigated for three types of CFRP plates: woven, non-woven, and hybrid laminates. As a result, it was found that the maximum ToF delay increased linearly with an increase in the damage size for all CFRP laminates. Moreover, the amplitude of the A0 mode was found to be significantly affected by the damage length in the wave propagation direction. Thus, this SHM method using chirp ultrasonic waves can quantitatively evaluate the size and extent of the impact damage in CFRP laminates.

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Impact Damage Detection Using Chirp Ultrasonic Guided Waves for Development of Health Monitoring System for CFRP Mobility Structures

Multilayered aluminum and titanium base composites reinforced with 18%Ni maraging steel sheets were fabricated using single-shot explosive welding technique. Explosive welding conditions for moderate bonding, such as collision velocity and the kinetic energy loss by each collision of multilayered plates, are calculated using finite difference analysis. The estimated conditions can be achieved regulating stand-off between plates and using the multilayered plates with almost the same mass per unit area. Both aluminum and titanium base composites aged after welding showed high tensile strength compared with the composites aged before welding. The ultimate tensile strength of each composite is discussed based on the rule of mixture.

A. Chiba

Papers

Impact Damage Detection Using Chirp Ultrasonic Guided Waves for Development of Health Monitoring System for CFRP Mobility Structures

Fabrication of maraging steel base multilayered composites using single-shot explosive welding technique