Process Diagnostics and Online Monitoring and Control

  • Pierre L. Fauchais
  • Joachim V. R. Heberlein
  • Maher I. Boulos


Whatever maybe the spray process, the user expects that coating thickness and weight tolerances are respected, the reproducibility of coating microstructure and reliability of service properties are at least good and, if possible, excellent. Good quality control of coatings, before (powders… substrate preparation), during, and after the spray process presents many benefits: reduced rework, predictable performance and life linked to coatings, and high reproducibility with narrow variability. This chapter defines first what are coatings repeatability, reliability, and reproducibility and place the process control relatively to the other different errors observed in a production unit. A brief history of the influence of the spray process monitoring on coating quality is presented, with the spray process parameters that should and could be controlled. The high-energy jet characterizations (temperatures, velocities, turbulences, electrodes erosion), developed in laboratories, are presented. Sensors able to work in the harsh environment of spray both and developed since the nineties are then described. They include enthalpy probes, sensors for hot and cold in-flight particles, to measure their trajectories distribution, their steady or transient temperatures, velocities, and diameters either as ensemble (large measurement volume) or local measurements. Measurements of the coating under formation (hot gases flux, temperature, stress development, thickness) are then considered. The use of robots, artificial neural networks (ANN), and fuzzy logic (FL) to monitor and further control coating generation is then discussed. Finally, this chapter presents a few measurements that are used in laboratories and are very important for a better understanding of coatings generation such as particle vaporization, particle flattening and splat formation, and high-energy jet–liquid interaction.


Particle Temperature Cold Spray Spray Process High Velocity Oxygen Fuel Spray Pattern 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Artificial neural network


Atmospheric plasma spraying


Coherent anti-stokes Raman spectroscopy


Coupled charged device


Computational fluid dynamic


Cinema-stereoscopic particle image spectroscopy


Continuous wave


Direct current


Detonation gun


Fast fourier transformation


Fuzzy logic


High-velocity air fuel flame


High-velocity oxy-fuel flame


Camera intensified coupled charged device camera


Internal diameter (mm)


Infra red


Laser Adhesion Test


Laser Doppler anemometry


Laser-induced fluorescence


Local thermodynamic equilibrium


Melting index


Total molten volume ensemble


Molten volume flux


Neodymium-doped yttrium aluminum garnet: Nd:Y3Al5O12


Near infrared sensor


Orthogonal-plane cinema-stereoscopic particle image spectroscopy


Personal computer


Plasma computer tomography


Particle image velocimetry


Planar laser-induced fluorescence


Particle shape imaging


Radio frequency


Spray and deposit control


Scanning electron microscopy


Spray stream melting index


Thermal barrier coating


Transistor–transistor logic


Vacuum plasma spraying


Yttria-stabilized zirconia


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Pierre L. Fauchais
    • 1
  • Joachim V. R. Heberlein
    • 2
  • Maher I. Boulos
    • 3
  1. 1.Sciences des Procédés Céramiques et de Traitements de Surface (SPCTS)Université de LimogesLimogesFrance
  2. 2.Department of Mechanical EngineeringUniversity of MinnesotaMinneapolisUSA
  3. 3.Department of Chemical EngineeringUniversity of SherbrookeSherbrookeCanada

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