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Application of the WI is demonstrated using different sets of the experimental data. In most machinery gearboxes, excitation near the second harmonic and higher commonly promotes heavy gear wear (Scheffer and Girdhar, 2004). For diagnostic purposes, these transients are detected by the wavelets earlier than the conventional vibration methods at a region of a single frequency where the majority of transient characteristics are

Figure 9 Application of the WI is demonstrated using different sets of the experimental data. In most machinery gearboxes, excitation near the second harmonic and higher commonly promotes heavy gear wear (Scheffer and Girdhar, 2004). For diagnostic purposes, these transients are detected by the wavelets earlier than the conventional vibration methods at a region of a single frequency where the majority of transient characteristics are

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Figure 1 TRDT in actual AH-64D (top) and TRDT test stand at USC (bottom) (see online version for colours) The components or articles subject to testing on the drive-train include: forward hanger bearing (FHB), aft. hanger bearing (AHB), intermediate gearbox (IGB), tail rotor gearbox (TGB) and the TRSP. The drive-train consists of a total of four shafts, which are purposely misaligned within the acceptable safe limits of two degrees for radial loading on the bearings. Three of the shafts have the FHB, AHB, and IGB components passing through them. The fourth shaft is on a vertical stabiliser between both IGB and TGB. The configuration, instrumentation, stiffness, and structure comply with military standards.
Figure 1 TRDT in actual AH-64D (top) and TRDT test stand at USC (bottom) (see online version for colours) The components or articles subject to testing on the drive-train include: forward hanger bearing (FHB), aft. hanger bearing (AHB), intermediate gearbox (IGB), tail rotor gearbox (TGB) and the TRSP. The drive-train consists of a total of four shafts, which are purposely misaligned within the acceptable safe limits of two degrees for radial loading on the bearings. Three of the shafts have the FHB, AHB, and IGB components passing through them. The fourth shaft is on a vertical stabiliser between both IGB and TGB. The configuration, instrumentation, stiffness, and structure comply with military standards.
Figure 2 TGB internal components (see online version for colours) In the field however, TGB is known to be susceptible to grease leaking from its output seal (Goodman et al., 2010). Motivating this study was the fact that the Army replaced the entire TGB at the first sight of grease leaks. This natural occurring field-fault has contributed to the aircraft not being available for flight operations.
Figure 2 TGB internal components (see online version for colours) In the field however, TGB is known to be susceptible to grease leaking from its output seal (Goodman et al., 2010). Motivating this study was the fact that the Army replaced the entire TGB at the first sight of grease leaks. This natural occurring field-fault has contributed to the aircraft not being available for flight operations.
Figure 3 Movement of grease through static mast of TGB, (a) 120 minutes of testing (b) 145 minutes of testing (see online version for colours)
Figure 3 Movement of grease through static mast of TGB, (a) 120 minutes of testing (b) 145 minutes of testing (see online version for colours)
Table 1 Threshold levels of some CI algorithms implemented by MSPU 4 Wavelet analysis 4.1 Wavelet transform
Table 1 Threshold levels of some CI algorithms implemented by MSPU 4 Wavelet analysis 4.1 Wavelet transform
Figure 5 Representation of the Morlet wavelet (see online version for colours) The mathematical description of the Morlet wavelet is given in equation (11). For a successful transform, the mother wavelet satisfies the admissibility condition as shown in equations (12) and (13) (Su et al., 2010). The wavelet function adopted in the analysis is non-orthogonal. Numerous mother wavelets have been broadly investigated in the literature. However, Morlet has been shown to accuratley represent signals in condition monitoring applications because of its similarities to the intermittent impulses, which are the symptoms of faults in machinery diagnostics applications (Rafiee et al., 2010; Lin and Qu, 2000). In this work, Morlet is chosen as the mother wavelet. A Morlet wavelet is presented graphically in Figure 5 as an exponential decaying cosine function that satisfies the regularity condition (Fugal, 2000).
Figure 5 Representation of the Morlet wavelet (see online version for colours) The mathematical description of the Morlet wavelet is given in equation (11). For a successful transform, the mother wavelet satisfies the admissibility condition as shown in equations (12) and (13) (Su et al., 2010). The wavelet function adopted in the analysis is non-orthogonal. Numerous mother wavelets have been broadly investigated in the literature. However, Morlet has been shown to accuratley represent signals in condition monitoring applications because of its similarities to the intermittent impulses, which are the symptoms of faults in machinery diagnostics applications (Rafiee et al., 2010; Lin and Qu, 2000). In this work, Morlet is chosen as the mother wavelet. A Morlet wavelet is presented graphically in Figure 5 as an exponential decaying cosine function that satisfies the regularity condition (Fugal, 2000).
Figure 7 TGB CI responses over the whole period of testing (see online version for colours) The x-axis in Figure 7 is the discrete time samples. It represents the life time of the gearbox experiment, which is 480 hours. The samples have been distributed over different hours and days depending on the time of the test. Actual numbers are not represented on the scale for conciseness. The Y-axis is divided into two portions: primary and secondary to have all the Cls plotted.
Figure 7 TGB CI responses over the whole period of testing (see online version for colours) The x-axis in Figure 7 is the discrete time samples. It represents the life time of the gearbox experiment, which is 480 hours. The samples have been distributed over different hours and days depending on the time of the test. Actual numbers are not represented on the scale for conciseness. The Y-axis is divided into two portions: primary and secondary to have all the Cls plotted.
igure 8 Progress of CWT during gearbox testing: three days before failure (top) and two days before failure (bottom) (see online version for colours) igure 9 Progress of CWT during gearbox testing: one day before failure (top) and the day of failure (bottom) (see online version for colours)
igure 8 Progress of CWT during gearbox testing: three days before failure (top) and two days before failure (bottom) (see online version for colours) igure 9 Progress of CWT during gearbox testing: one day before failure (top) and the day of failure (bottom) (see online version for colours)
Table 2 Averaged WI value from all acquisitions taken on a single day
Table 2 Averaged WI value from all acquisitions taken on a single day
gure 11 Comparison between averaged conventional TGB CIs and averaged WI during the last four days of testing (see online version for colours)
gure 11 Comparison between averaged conventional TGB CIs and averaged WI during the last four days of testing (see online version for colours)
Wavelet analyis is presented as a promising approach for an additional feature in the MSPU of the AH-64 helicopter. The results propose a new index with useful characteristics in its sensitivity to gear wear and may facilitate in earlier fault detection for the TGB. This proposed WI shows its ability to react to vibrational energy through
Wavelet analyis is presented as a promising approach for an additional feature in the MSPU of the AH-64 helicopter. The results propose a new index with useful characteristics in its sensitivity to gear wear and may facilitate in earlier fault detection for the TGB. This proposed WI shows its ability to react to vibrational energy through
Related topics:
EngineeringComputer ScienceCondition MonitoringManufacturing EngineeringContinuous wavelet transform
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