In-flight Particle Characteristics Research Articles

Reliability of plasma-sprayed coatings: monitoring the plasma spray process and improving the quality of coatings

As for every coating technology, the reliability and reproducibility of coatings are essential for the development of the plasma spraying technology in industrial manufacturing. They mainly depend on the process reliability, equipment and spray booth maintenance, operator training and certification, implementation and use of consistent production practices and standardization of coating testing. This paper deals with the first issue, that is the monitoring and control of the plasma spray process; it does not tackle the coating characterization and testing methods. It begins with a short history of coating quality improvement under plasma spray conditions over the last few decades, details the plasma spray torches used in the industry, the development of the measurements of in-flight and impacting particle parameters and then of sensors. It concludes with the process maps that describe the interrelations between the operating parameters of the spray process, in-flight particle characteristics and coating properties and with the potential of in situ monitoring of the process by artificial neural networks and fuzzy logic methods.

Influence of HVOF spraying parameters on the corrosion resistance of WC–CoCr coatings in strong acidic environment

High-velocity oxy-fuel (HVOF) spray techniques can produce cermet coatings for applications that require corrosion resistant surfaces. The aim of this study was to investigate the influence of different oxygen/fuel ratios on velocity and temperature of flying particles and establish the effects on the coatings quality in relation to the corrosion behavior of HVOF WC–CoCr coating in a 0.1N HCl. The results show that in-flight particle characteristics have a significant effect on the porosity, hardness and corrosion resistance. The highest corrosion resistance is obtained with those parameters that allow a sufficient melting of the agglomerates while minimizing the decarburization of the WC particles.

Quality Prediction of Twin Wire Arc Sprayed Coatings Using Acoustic Emission Analysis

In this work, acoustic emission analysis is utilized in the twin wire arc spraying (TWAS) process to study the influence of the adjustable process parameters on the simultaneously obtained acoustic signals at the nozzle and at the substrate. The amplitude of recorded signals at the substrate was in general much higher than those recorded at the nozzle. At the substrate side, the amplitude of emitted acoustic signals is dependent on feedstock materials and is higher when using solid wires. The acoustic signals were recorded at the spraying gun for different gas pressures without arc ignition (as dry runs) in order to reveal the effect of the arc on the emitted acoustic signals. A correlation between controllable parameters, the acoustic signals, and the obtained in-flight particle characteristics was observed. This work contributes to the online control of TWAS processes and is one of many proposed publications in the research field of the conducted acoustic emission analysis.

Enhancement of amorphous phase formation in alumina–YSZ coatings deposited by suspension plasma spray process

In the present work on pseudo-eutectic alumina–yttria stabilized zirconia (YSZ) composite, the influence of spray parameters on amorphous phase formation during suspension plasma spray deposition is investigated. Several variables were evaluated as the most probable key factors influencing the amorphous phase formation. These variables include powder feed size, in-flight particle characteristics (temperature and velocity), spraying robot travel speed, preheating the substrate, number of deposition passes and the presence of bond coat. It was found that larger particle size, higher robot speed and substrate preheating lead to larger amounts of amorphous phase. Moreover, it is shown that particle velocity and temperature need to be reasonably low to get greater amorphous content while the presence of a bond coat has no significant influence on the amorphous phase formation. In contrast, increasing the number of deposition passes is detrimental to this phase. This work also discusses some correlations observed between the amorphous phase content and the in-flight particle characteristics and coating grain sizes.

Improving the Generalization Ability of an Artificial Neural Network in Predicting In-Flight Particle Characteristics of an Atmospheric Plasma Spray Process

This paper presents the application of the artificial neural network into an atmospheric plasma spray process for predicting the in-flight particle characteristics, which have significant influence on the in-service coating properties. One of the major problems for such function-approximating neural network is over-fitting, which reduces the generalization capability of a trained network and its ability to work with sufficient accuracy under a new environment. Two methods are used to analyze the improvement in the network’s generalization ability: (i) cross-validation and early stopping, and (ii) Bayesian regularization. Simulations are performed both on the original and expanded database with different training conditions to obtain the variations in performance of the trained networks under various environments. The study further illustrates the design and optimization procedures and analyzes the predicted values, with respect to the experimental ones, to evaluate the performance and generalization ability of the network. The simulation results show that the performance of the trained networks with regularization is improved over that with cross-validation and early stopping and, furthermore, the generalization capability of the networks is improved; thus preventing any phenomenon associated with over-fitting.

Adhesion Strength of HVOF Sprayed IN718 Coatings

The adhesion strength of high-velocity oxyfuel thermally sprayed coatings is of prime importance when thick coatings are to be sprayed in repair applications. In this study, relationships between process parameters, particle in-flight characteristics, residual stresses, and adhesion strength were explored. The most important process parameters that influence HVOF sprayed IN718 coating adhesion strength on IN718 substrate material were identified. Residual stress distributions were determined using the modified layer removal method, and adhesion strength was measured using an in-house-developed tensile test. Relationships between process parameters, particle in-flight characteristics, coating microstructure, and adhesion strength were established. Particle temperature, particle velocity, substrate preparation, and deposition temperature were identified as critical parameters to attain high adhesion strength. Controlling these parameters can significantly improve the adhesion strength, thus enabling thick coatings to be sprayed for repair applications.

Artificial Neural Network application for predicting in-flight particle characteristics of an atmospheric plasma spray process

Thermal spray consists of a group of coating processes that are used to apply metal or non-metallic coatings to protect a functional surface or to improve its performance. There are some 40 processing parameters that define the overall coating quality and these must be selected in an optimized fashion to manufacture a coating that exhibits desirable properties. The proper combination of processing variables is critical since these influence the cost as well as the coating characteristics. Because of this high number of processing parameters, a major challenge is to have full control over the system and to understand parameter interdependencies, correlations and their individual effects on the in-flight particle characteristics, which have significant influence on the in service coating properties. This paper proposes an approach, based on the Artificial Neural Network (ANN) method, to play this role and illustrates the model's design, network optimization procedures, the database handling and expansion steps, and analysis of the predicted values, with respect to the experimental ones, in order to evaluate the network's performance.

Relationships Between Process Parameters, Microstructure, and Adhesion Strength of HVOF Sprayed IN718 Coatings

Fundamental understanding of relationships between process parameters, particle in-flight characteristics, and adhesion strength of HVOF sprayed coatings is important to achieve the high coating adhesion that is needed in aeronautic repair applications. In this study, statistical Design of Experiments (DoE) was used to identify the most important process parameters that influence adhesion strength of IN718 coatings sprayed on IN718 substrates. Special attention was given to the parameters combustion ratio, total gas mass flow, stand-off distance and external cooling, since these parameters were assumed to have a significant influence on particle temperature and velocity. Relationships between these parameters and coating microstructure were evaluated to fundamentally understand the relationships between process parameters and adhesion strength.

Intelligent system for prediction and control: Application in plasma spray process

Parametric drifts and fluctuations occur during plasma spraying. These drifts and fluctuations originate primarily from electrode wear and intrinsic plasma jet instabilities. One challenge is to control the manufacturing process by identifying the parameter interdependencies, correlations and individual effects on the in-flight particle characteristics. Such control is needed through methods that (i) consider the interdependencies that influence process variability and that also (ii) quantify the processing parameter-process response relationships. Due to the large amplitudes of the drifts and fluctuations, the strategy to adopt would depend on the required corrections to apply to the in-flight particle characteristics. Artificial intelligence is a pertinent tool to reach this objective. The system is flexible in order to permit a full control based on pre-defined rules aiming at maintaining at constant values in-flight particle characteristics (average surface temperature and velocity) by adjusting in real time the arc current intensity, the total plasma gas flow and the hydrogen content whatever the fluctuations.

Sensors in Spray Processes

This paper presents what is our actual knowledge about sensors, used in the harsh environment of spray booths, to improve the reproducibility and reliability of coatings sprayed with hot or cold gases. First are described, with their limitations and precisions, the different sensors following the in-flight hot particle parameters (trajectories, temperatures, velocities, sizes, and shapes). A few comments are also made about techniques, still under developments in laboratories, to improve our understanding of coating formation such as plasma jet temperature measurements in non-symmetrical conditions, hot gases heat flux, particles flattening and splats formation, particles evaporation. Then are described the illumination techniques by laser flash of either cold particles (those injected in hot gases, or in cold spray gun) or liquid injected into hot gases (suspensions or solutions). The possibilities they open to determine the flux and velocities of cold particles or visualize liquid penetration in the core of hot gases are discussed. Afterwards are presented sensors to follow, when spraying hot particles, substrate and coating temperature evolution, and the stress development within coatings during the spray process as well as the coating thickness. The different uses of these sensors are then described with successively: (i) Measurements limited to particle trajectories, velocities, temperatures, and sizes in different spray conditions: plasma (including transient conditions due to arc root fluctuations in d.c. plasma jets), HVOF, wire arc, cold spray. Afterwards are discussed how such sensor data can be used to achieve a better understanding of the different spray processes, compare experiments to calculations and improve the reproducibility and reliability of the spray conditions. (ii) Coatings monitoring through in-flight measurements coupled with those devoted to coatings formation. This is achieved by either maintaining at their set point both in-flight and certain spray parameters (spray pattern, coating temperature…), or defining a good working area through factorial design, or using artificial intelligence based on artificial neural network (ANN) to predict particle in-flight characteristics and coating structural attributes from the knowledge of processing parameters.

Different spray processes for different Al2O3 coating properties

Among the different coating technologies, a thermal spray has a leading position because of its versatility: an extremely wide variety of materials can be deposited to protect back materials from wear, corrosion, thermal flux, etc. For example, atmospheric plasma spray is a rather well-established process but some other ones, such as flame technology, can also be used with lower economical impact. After a respective optimization of the processing parameters, both plasma and wire flame thermal processes were tested to form Al2O3 coatings. For each process, in-flight particle conditions, coating cross-section micro-structures and coating properties were successively determined. The experimental parameters were correlated to in-flight particle characteristics and to coating micro-structure and compared to resulting coating features. The evolution of particle velocity and temperature showed well-marked trends and the mean values were dependent on the spray process. The results emphasized the difference of spray system in terms of kinetic and thermal transfers to the particles. Then, the differences observed on in-flight particle characteristics can be used to explain the differences observed in coating properties, such as porosity content and hardness.

Comparison of In-Flight Particle Properties, Splat Formation, and Coating Microstructure for Regular and Nano-YSZ Powders

The relationship between atmospheric pressure plasma spray parameters and in-flight particle characteristics was determined. The morphologies of individual splats and the coating microstructure were studied for different stand-off distances and arc currents. Coating cross-sectional analysis showed that the total porosity of the coating increased with decreasing arc current, and increasing stand-off distance. Two different materials were used: the regular (r-YSZ) feed stock and the nano size (n-YSZ) agglomerated powder. The results illustrate that the r-YSZ coating has higher total porosity at higher arc currents than n-YSZ coating. The splat flattening degree and circularity was examined at different substrate temperatures for both powders. The results indicate that the flattening degree increased at high temperatures for the two materials, but the values for n-YSZ were higher than those for the r-YSZ. This study showed the operating regimes in which the use of n-YSZ yields improved coating properties.

Estimation of Molten Content of the Spray Stream from Analysis of Experimental Particle Diagnostics

Particle melting is one of the key issues in air plasma spray processing of high temperature ceramics such as Yttria Stabilized Zirconia (YSZ). The significance of assessing, monitoring, and controlling the molten content in spray stream on achieving an efficient process and reproducible coating characteristics and properties is known. This study aims to estimate the molten content of the spray stream (as an ensemble) from experimental measurement of in-flight (individual) particle characteristics. In a previous study by Streibl et al. the presence of melting signature in the particle temperature distribution was observed, which has been confirmed by simulation and through independent experimental observation by Mauer et al. Based on this observation, the particle temperature distribution could be delineated into the different achievable particle states in-flight (unmolten, partially molten, and completely molten) to a first approximation. This in-turn would enable estimation of the molten content in the spray stream. Thus obtained percentage molten content (referred in this study as Spray Stream Melting Index—SSMI) has been observed to correlate well with the experimentally measured deposition efficiency for a wide range of process conditions and feedstock characteristics. The implications of estimating SSMI for other materials and processes are also discussed.

Mullite and Mullite/ZrO2-7wt.%Y2O3 Powders for Thermal Spraying of Environmental Barrier Coatings

Mullite and mullite/ZrO2-7wt.%Y2O3 coatings could be thought among the main protective layers for environment barrier coatings (EBCs) to protect Si-based substrates in future gas turbine engines. Considering that feedstock of the compound powder is not commercially available, two powder processing routes Spray Drying (SD) and Flame Spheroidization (FS) were implemented for both types of powders. For each method the particle size, the morphology, and microstructure of the powder particles was determined. In addition, the effect of the heat treatment on the powder crystallinity and microstructure of FS powders was also investigated. To evaluate their suitability as feedstock materials, the powders were plasma sprayed and their in-flight particle characteristics monitored for coatings production. The powder morphology was correlated to the in-flight particle characteristics and splat morphology to gain insight about into the influence of powder characteristics on the coating formation.

In-flight and upon impact particle characteristics modelling in plasma spray process

In Atmospheric plasma spray process, the in-flight particle characteristics such as their particle size, velocity and surface temperature influence significantly their flight duration and consequently their melting degree. The knowledge of the correlations between process parameters and in-flight particle characteristics is very important for optimizing the coating qualities. Artificial neural networks was trained and optimized to establish the relationships linking in-flight particle average diameter and process parameters to in-flight particle average velocity and surface temperature. Then, the established ANN relationships permitted to determine the in-flight particle average velocity and surface temperature versus their diameter for given process parameters. These predicted average velocity and surface temperature data were then used to determine the time for complete melting of the particle and its dwell-time before impact by an analytical model for given operating conditions.

Effect of in-flight particle characteristics on the coating properties of atmospheric plasma-sprayed 8mol% Y2O3–ZrO2 electrolyte coating studying by artificial neural networks

Abstract In-flight particle characteristics (surface temperature and velocity upon impact) are among the most important parameters which influence the coating microstructures and properties in atmospheric plasma spraying (APS) process. The purpose of this paper is to study hydrogen fraction used as secondary plasma forming gas on the in-flight particle surface temperature and by extension on the coating microstructures of atmospheric plasma-sprayed 8 mol% yttria stabilized zirconia electrolyte coatings implementing in particular artificial neural networks (ANN). Then, the predicted in-flight particle characteristics were on the one hand compared to experimental values and on the other hand correlated to some of the coating structural attributes (porosity and gas specific permeability). The predicted results were in good accordance with the experimental data. Results showed that the H 2 flow rate had obvious influence on particle temperature and had almost no significant effect on particle velocity. Increasing the particle temperatures induced dense coating microstructure and improved the gas-tightness performance.

Yttria-stabilized zirconia in-flight particle characteristics under vacuum plasma spray conditions

This paper deals with the diagnostic yttria-stabilized zirconia (YSZ) in-flight particles in Vacuum Plasma Spray (VPS) process using an optical measurement device. Particle velocity, temperature and diameter were correlated to spray distance under a fixed chamber pressure of about 14 kPa. Experiments were carried out with a two-color pyrometer. Results show that correlations can be satisfactory described with linear relationships. Particle velocity and temperature decrease when increasing spray distance whereas particle diameter exhibits a linear increase with the spray distance.

Artificial neural networks implementation in plasma spray process: Prediction of power parameters and in-flight particle characteristics vs. desired coating structural attributes

Artificial neural networks (ANN) were implemented to predict atmospheric plasma spraying (APS) process parameters to manufacture a coating with the desired structural characteristics. The specific case of predicting power parameters to manufacture grey alumina (Al 2O 3–TiO 2, 13% by wt.) coatings was considered. Deposition yield and porosity were the coating structural characteristics. After having defined, trained and tested ANN, power parameters (arc current intensity, total plasma gas flow, hydrogen content) and resulting in-flight particle characteristics (average temperature and velocity) were computed considering several scenarios. The first one deals at the same time with the two structural characteristics as constraints. The others one deals with one structural characteristic as constraint while the other is fixed at a constant value.

In-situ TiB 2–Al 2O 3 formed composite coatings by atmospheric plasma spraying: Influence of process parameters and in-flight particle characteristics

In the present study, mechanically alloyed Al–12Si, B 2O 3 and TiO 2 powder was deposited onto an aluminum substrate using atmospheric plasma spraying (APS). The effects of mechanical alloying (MA) time and plasma parameters (arc current and primary/secondary/carrier gas flow rate) on in-situ reaction intensity and in-flight particle characteristics (temperature and velocity) have been investigated. It has been observed that MA time has a remarkable effect on powder morphology and relative amount of in-situ formed TiB 2 and γ-Al 2O 3. In-flight particle diagnostic measurements demonstrate that among the plasma parameters arc current has the strongest effect on in-flight particle velocity and temperature. Also, results indicate that in-flight particle velocity is more dominant than temperature on the relative amount of in-situ formed phases.

Effective Parameters in Axial Injection Suspension Plasma Spray Process of Alumina-Zirconia Ceramics

Suspension plasma spray (SPS) is a novel process for producing nano-structured coatings with metastable phases using significantly smaller particles as compared to conventional thermal spraying. Considering the complexity of the system there is an extensive need to better understand the relationship between plasma spray conditions and resulting coating microstructure and defects. In this study, an alumina/8 wt.% yttria-stabilized zirconia was deposited by axial injection SPS process. The effects of principal deposition parameters on the microstructural features are evaluated using the Taguchi design of experiment. The microstructural features include microcracks, porosities, and deposition rate. To better understand the role of the spray parameters, in-flight particle characteristics, i.e., temperature and velocity were also measured. The role of the porosity in this multicomponent structure is studied as well. The results indicate that thermal diffusivity of the coatings, an important property for potential thermal barrier applications, is barely affected by the changes in porosity content.