Aeroacoustics and Artificial Neural Network Modeling of Airborne Acoustic Emissions During High Kinetic Energy Thermal Spraying

Kamnis, Spyros; Malamousi, Konstantina; Marrs, Alex; Allcock, Bryan; Delibasis, Konstantinos K.

doi:10.1007/s11666-019-00874-0

Cited by 22 publications

(7 citation statements)

References 22 publications

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“…CoCrFeMnNi 0.8 V powder was fabricated with gas atomization; it is an R&D product of Castolin Eutectic. The spray setup was the same as that described in our previous works [16,23], with an HVOAF gun specially designed to spray a variety of materials. The torch used a mixture of hydrogen (up to 400 SLPM), air (up to 600 SLPM) and oxygen (up to 300 SLPM), depending on the mode of operation.…”

Section: Coatings Depositionmentioning

confidence: 99%

Microstructural Evaluation of Thermal-Sprayed CoCrFeMnNi0.8V High-Entropy Alloy Coatings

et al. 2023

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The aim of this work is to improve the understanding of the effect of the cooling rate on the microstructure of high-entropy alloys, with a focus on high-entropy alloy coatings, by using a combined computational and experimental validation approach. CoCrFeMnNi0.8V coatings were deposited on a steel substrate with high velocity oxy-air-fuel spray with the employment of three different deposition temperatures. The microstructures of the coatings were studied and compared with the microstructure of the equivalent bulk high-entropy alloy fabricated by suction casting and powder fabricated by gas atomization. According to the results, the powder and the coatings deposited by low and medium temperatures consisted of a BCC microstructure. On the other hand, the microstructure of the coating deposited by high temperature was more complex, consisting of different phases, including BCC, FCC and oxides. The phase constitution of the bulk high-entropy alloy included an FCC phase and sigma. This variation in the microstructural outcome was assessed in terms of solidification rate, and the results were compared with Thermo-Calc modelling. The microstructure can be tuned by the employment of rapid solidification techniques such as gas atomization, as well as subsequent processing such as high velocity oxy-air-fuel spray with the use of different spray parameters, leading to a variety of microstructural outcomes. This approach is of high interest for the field of high-entropy alloy coatings.

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Section: Coatings Depositionmentioning

confidence: 99%

Microstructural Evaluation of Thermal-Sprayed CoCrFeMnNi0.8V High-Entropy Alloy Coatings

et al. 2023

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“…In this direction, ML techniques with the ability to solve intricate and highly nonlinear processes have attracted worldwide researchers to use them for AE processing optimization, industrial monitoring and control. Different ML techniques such as ANNs and CNNs [175] have been used extensively due to their capability of learning from the past data and using them to predict the target variable more accurately. The basic functionality of the example CNN in figure 19 can be broken down into four key areas.…”

Section: Advances In Science and Technology To Meet Challengesmentioning

confidence: 99%

Roadmap on signal processing for next generation measurement systems

Iakovidis

Ooi

Kuang

et al. 2021

Meas. Sci. Technol.

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Signal processing is a fundamental component of almost any sensor-enabled system, with a wide range of applications across different scientific disciplines. Time series data, images, and video sequences comprise representative forms of signals that can be enhanced and analysed for information extraction and quantification. The recent advances in artificial intelligence and machine learning are shifting the research attention towards intelligent, data-driven, signal processing. This roadmap presents a critical overview of the state-of-the-art methods and applications aiming to highlight future challenges and research opportunities towards next generation measurement systems. It covers a broad spectrum of topics ranging from basic to industrial research, organized in concise thematic sections that reflect the trends and the impacts of current and future developments per research field. Furthermore, it offers guidance to researchers and funding agencies in identifying new prospects.

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“…Furthermore, Kamnis et al investigated the audio signal generated during HVOF thermal spraying with a single microphone placed inside of the spray booth [15]. Findings showed that changes in powder feed rate and standoff distance were detectable in the audio signals, and an acoustic model was compared to experimental data with reasonable similarity.…”

Section: Acoustic Monitoring Of Thermal Spraymentioning

confidence: 99%

“…Findings showed that changes in powder feed rate and standoff distance were detectable in the audio signals, and an acoustic model was compared to experimental data with reasonable similarity. Further, selected frequency ranges correlating to powder feeding rates and stand-off distances were used as inputs into a neural network model for predicting resultant coating microhardness based on aero-acoustic emissions [15].…”

Section: Acoustic Monitoring Of Thermal Spraymentioning

confidence: 99%

“…This study presents the first known research thrust into aero-acoustic monitoring of CS, although aeroacoustics of other thermal spray processes, including high-velocity oxygen fuel (HVOF) and plasma spray, have been studied. Blair, Kamnis, and Xi have shown that audio signals correlate to process parameters in other thermal spray techniques [14][15][16]. Audio signal monitoring has similarly been explored in many other manufacturing processes, including welding, 3D printing, and machining [17][18][19] .…”

Section: Introductionmentioning

confidence: 99%

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Aero-acoustic monitoring of cold spray additive manufacturing

Arkhipov

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Cold spray, or supersonic particle deposition, is an emerging additive manufacturing process used to develop material on target substrates. The process continues to evolve toward full-fledged, metal 3D-printing applications. As these developments are made, there is a growing need for non-destructive process monitoring. Cold spray is dictated by numerous process parameters. Process consistency is vital for the development of highstrength coatings with predictable and repeatable microstructural, thermo-mechanical, and 3D printing properties (e.g., predictable shape). Detection of unexpected parameter variations, anomalous events, and spray failures is critical for identifying process inconsistencies, minimizing machine downtime, and maximizing cost efficiency. In this study, airborne acoustic (i.e., aero-acoustic) emissions were monitored during the cold spray process to examine acoustically detectable spray parameters. Characteristics of aero-acoustic waves that emanate from free and impinging supersonic jets were investigated. The viability of using these characteristics as real-time metrics for cold spray additive manufacturing applications was explored. Results showed that changes in nozzle gas supply pressure, nozzle gas inlet temperature, and main gas flow rate were detectable in free-jet experiments via frequency spectrum analyses. The influence of robotic arm motion and coating buildup on airborne acoustic signal trends was evaluated during cold spray deposition procedures. Band power and other signal features were extracted from recorded audio signals to compare temporal behavior. During deposition experiments, powder feeding rate (PFR) and standoff distance (SOD) variations were identified by acoustic characteristics. Nozzle wear experiments revealed the aero-acoustic detectability of nozzle wear conditions and rates. Delamination failures during spray procedures were identified in comparisons between normal and anomalous cases. An alarm program was developed for delamination detection through the acoustic monitoring of multiple frequency ranges. Audio signal analyses indicated the feasibility of acoustic event detection as a real-time process monitoring technique for the cold spray process.

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Aeroacoustics and Artificial Neural Network Modeling of Airborne Acoustic Emissions During High Kinetic Energy Thermal Spraying

Cited by 22 publications

References 22 publications

Microstructural Evaluation of Thermal-Sprayed CoCrFeMnNi0.8V High-Entropy Alloy Coatings

Microstructural Evaluation of Thermal-Sprayed CoCrFeMnNi0.8V High-Entropy Alloy Coatings

Roadmap on signal processing for next generation measurement systems

Aero-acoustic monitoring of cold spray additive manufacturing

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