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W. Zhang et al.
When the material is damaged by external or internal forces, it will release energy
in the form of elastic waves [5, 6]. This is the acoustic emission phenomenon. The
technique of using the acoustic emission sensor to collect the acoustic emission
signals generated in this process and analyze the damage state is Acoustic emission
detection technology. Compared with traditional nondestructive testing technology,
AE testing has the advantages of dynamic detection and real-time monitoring of
defects, and is not sensitive to the working environment [7].
The AE signal comes from the damage defect itself, so the evaluation of the test
results also depends on the analysis of the corresponding AE signal characteristics of
different damage modes of the structural material. A large number of research show
that AE technology is very sensitive to the degree of steel structure crack damage
[8–12], which means that it is feasible to apply AE technology to the detection and
online monitoring of fatigue crack growth status. Based on the characteristics of the
AE signal, Li [8] constructed a theoretical model of the AE signal generated when the
fatigue cracks of the tooth surface of the gears expanded, which theoretically proved
the feasibility of the acoustic emission technology for detecting fatigue wear. Mengyu
[9] Conducted an AE study on the fatigue crack growth process of Q345R steel, and
established the relationship between the AE count rate and energy rate and the fatigue
crack growth rate, which provided a basis for the assessment of the remaining life
of Q345R steel; Crivelli [10] applied AE testing in fatigue detection of gear tooth
roots, providing support on the feasibility of system state tracking using continuous
acoustic emission. Md Yeasin Bhuiyan [11] researched the effect of the acoustic
emission sensor on the acoustic emission waveforms from fatigue crack growth in
a thin aerospace specimen, It has been shown that the piezoelectric wafer active
sensor transducer successfully captured the fatigue crack-related acoustic emission
waveforms in the thin plate. AE Signal evolution is highly related to the physical
boundary conditions of the cracks as well as the fatigue crack growth mechanism.
Xie [12] and others also proved the feasibility of applying AE technology to fatigue
damage detection by studying the crack initiation and propagation process of multilayer tokamak magnets. This paper studied the relationship between fatigue crack
propagation process and acoustic emission signal parameters for TC4 titanium alloy
materials for aeroengines. In order to more clearly characterize the acoustic emission
signal during the crack propagation of TC4 titanium alloy, this study selects energy
and technical parameters for analysis, and analyzes the spectrum of the acoustic
emission signal by FFT transformation.
19.2 Methods and Experimental Test Set-Ups
The material used in the test was a TC4 titanium alloy belonging to an equiaxed
martensitic (α + β) two-phase titanium alloy, and the chemical composition is shown
in Table 19.1. According to the provisions of GB/T228.1-2010, a compact pull-up
sample was produced, as shown in Figs. 19.1 and 19.2, according to the GBT63892000 crack extension standard [13], crack propagation test.
W. Zhang et al.
When the material is damaged by external or internal forces, it will release energy
in the form of elastic waves [5, 6]. This is the acoustic emission phenomenon. The
technique of using the acoustic emission sensor to collect the acoustic emission
signals generated in this process and analyze the damage state is Acoustic emission
detection technology. Compared with traditional nondestructive testing technology,
AE testing has the advantages of dynamic detection and real-time monitoring of
defects, and is not sensitive to the working environment [7].
The AE signal comes from the damage defect itself, so the evaluation of the test
results also depends on the analysis of the corresponding AE signal characteristics of
different damage modes of the structural material. A large number of research show
that AE technology is very sensitive to the degree of steel structure crack damage
[8–12], which means that it is feasible to apply AE technology to the detection and
online monitoring of fatigue crack growth status. Based on the characteristics of the
AE signal, Li [8] constructed a theoretical model of the AE signal generated when the
fatigue cracks of the tooth surface of the gears expanded, which theoretically proved
the feasibility of the acoustic emission technology for detecting fatigue wear. Mengyu
[9] Conducted an AE study on the fatigue crack growth process of Q345R steel, and
established the relationship between the AE count rate and energy rate and the fatigue
crack growth rate, which provided a basis for the assessment of the remaining life
of Q345R steel; Crivelli [10] applied AE testing in fatigue detection of gear tooth
roots, providing support on the feasibility of system state tracking using continuous
acoustic emission. Md Yeasin Bhuiyan [11] researched the effect of the acoustic
emission sensor on the acoustic emission waveforms from fatigue crack growth in
a thin aerospace specimen, It has been shown that the piezoelectric wafer active
sensor transducer successfully captured the fatigue crack-related acoustic emission
waveforms in the thin plate. AE Signal evolution is highly related to the physical
boundary conditions of the cracks as well as the fatigue crack growth mechanism.
Xie [12] and others also proved the feasibility of applying AE technology to fatigue
damage detection by studying the crack initiation and propagation process of multilayer tokamak magnets. This paper studied the relationship between fatigue crack
propagation process and acoustic emission signal parameters for TC4 titanium alloy
materials for aeroengines. In order to more clearly characterize the acoustic emission
signal during the crack propagation of TC4 titanium alloy, this study selects energy
and technical parameters for analysis, and analyzes the spectrum of the acoustic
emission signal by FFT transformation.
19.2 Methods and Experimental Test Set-Ups
The material used in the test was a TC4 titanium alloy belonging to an equiaxed
martensitic (α + β) two-phase titanium alloy, and the chemical composition is shown
in Table 19.1. According to the provisions of GB/T228.1-2010, a compact pull-up
sample was produced, as shown in Figs. 19.1 and 19.2, according to the GBT63892000 crack extension standard [13], crack propagation test.