23 Acoustic Emission in Coatings—A Review
271
Wang et al. [11] introduced acoustic emission technology into the microhardness
indentation method when evaluating the toughness of the nickel-based alloy coating
which was made by the vacuum melting method. The slope of accumulated energy
counts (En) versus the load (P) was used as a parameter for qualitative determination
of toughness. The larger the slope of the En-P straight line, the worse the toughness
of the coating.
Sause et al. [12] conducted four-point bending experiments on nickel-coppercoated CFRP (carbon-fiber reinforced plastic). The process was divided into three
stages: crack initiation, crack propagation and stratification by the combination of
pattern recognition techniques and power spectrum analysis. RMS and acoustic emission localization can accurately distinguish the failure of coating and plastic substrate.
The combination of pattern recognition technology and power spectrum analysis may
be a powerful tool for identifying failure mechanisms in mixed materials, and AE
analysis can often be used as an important tool for health monitoring and quality
assurance of mixed materials.
Yang et al. [13] used AE technology as an auxiliary tool to judge the time point of
coating crack initiation and matrix plastic deformation, and more accurately tested
the fracture toughness of the material, when measuring the fracture toughness of
chromium coating.
Gallego et al. [14] also used this technique to study the bonding strength of
galvanized steel. When testing the mechanical properties of materials, AE is often
used as an indicator of different deformations or failure stages. Since it can often
detect the changes in materials earlier, more accurate values can be obtained.
To sum up, in the study of metal coatings, the role played by AE can be roughly
classified into three. First, it can be used as an auxiliary tool to indicate the time
points of deformation or failure when evaluating the mechanical properties. Second,
the energy of AE signal was directly used as a parameter to evaluate the properties.
Third, the whole failure process was segmented by the signal processing tool, and
then with the help of SEM, the failure process of the coating was revealed.
23.3 Ceramic Coatings
Ceramic coatings, which are made by in-situ reaction, vapor deposition and other
methods, are widely used because of its characteristics of wear resistance, corrosion
resistance, anti-adhesion, high hardness and high temperature resistance.
Song et al. [15] evaluated the bonding strength of the coating by means of pressing
experiment combined with AE technology. According to the time distribution curve
of characteristic parameters such as energy, RMS, counts and amplitude of the signal,
it can be found that energy was more sensitive to the failure of the coating, which
was most suitable for evaluating the bonding strength of the coating. The trend of
amplitude with time can better reflect the crack propagation process in the ceramic
coatings.
271
Wang et al. [11] introduced acoustic emission technology into the microhardness
indentation method when evaluating the toughness of the nickel-based alloy coating
which was made by the vacuum melting method. The slope of accumulated energy
counts (En) versus the load (P) was used as a parameter for qualitative determination
of toughness. The larger the slope of the En-P straight line, the worse the toughness
of the coating.
Sause et al. [12] conducted four-point bending experiments on nickel-coppercoated CFRP (carbon-fiber reinforced plastic). The process was divided into three
stages: crack initiation, crack propagation and stratification by the combination of
pattern recognition techniques and power spectrum analysis. RMS and acoustic emission localization can accurately distinguish the failure of coating and plastic substrate.
The combination of pattern recognition technology and power spectrum analysis may
be a powerful tool for identifying failure mechanisms in mixed materials, and AE
analysis can often be used as an important tool for health monitoring and quality
assurance of mixed materials.
Yang et al. [13] used AE technology as an auxiliary tool to judge the time point of
coating crack initiation and matrix plastic deformation, and more accurately tested
the fracture toughness of the material, when measuring the fracture toughness of
chromium coating.
Gallego et al. [14] also used this technique to study the bonding strength of
galvanized steel. When testing the mechanical properties of materials, AE is often
used as an indicator of different deformations or failure stages. Since it can often
detect the changes in materials earlier, more accurate values can be obtained.
To sum up, in the study of metal coatings, the role played by AE can be roughly
classified into three. First, it can be used as an auxiliary tool to indicate the time
points of deformation or failure when evaluating the mechanical properties. Second,
the energy of AE signal was directly used as a parameter to evaluate the properties.
Third, the whole failure process was segmented by the signal processing tool, and
then with the help of SEM, the failure process of the coating was revealed.
23.3 Ceramic Coatings
Ceramic coatings, which are made by in-situ reaction, vapor deposition and other
methods, are widely used because of its characteristics of wear resistance, corrosion
resistance, anti-adhesion, high hardness and high temperature resistance.
Song et al. [15] evaluated the bonding strength of the coating by means of pressing
experiment combined with AE technology. According to the time distribution curve
of characteristic parameters such as energy, RMS, counts and amplitude of the signal,
it can be found that energy was more sensitive to the failure of the coating, which
was most suitable for evaluating the bonding strength of the coating. The trend of
amplitude with time can better reflect the crack propagation process in the ceramic
coatings.