Contents
Chapter 6 Defect identification in FSW process
6.2 Identification of defects
6.2.1 Analysis of vertical force signal features
Vertical force or sometimes referred as plunging force is responsible for establishing proper contact between the tool shoulder and the workpiece material. A proper contact leads to proper frictional heat generation resulting in sufficient material heating and in turn material plasticization. Monitoring this parameter in real time would offer information regarding the process. The acquisition of vertical force signal and the related sensor and hard hardware are discussed in chapter 3 (section 3.7). The force signals acquired against Exp. No. 45, Exp. No. 35 and Exp. No. 65 are shown in Fig.
6.3.Among these three experiments Exp. No. 45 represent the defect free case with maximum UTS and the other two represents defective cases. From the figure it is evidential that the respective force magnitudes against the defective cases are higher compared to that of defect free case. It is to note that these experimental conditions are having same tool rotational speed of 1100 rev/min. Welding speed for defective cases is 36 mm/min whereas the same for defect free welding case is 132 mm/min. The variation in magnitude as well as trend of the force signals indicate towards anomaly during the process. The undulations in the signals against the defective cases are the indications of abnormal material flow within the weld zone. Abnormal material flow is the outcome of improper heat input that leads to improper material plasticization. The acquired signals can effectively represent the process flow behaviour and can be useful in monitoring the process for the desired outcome. Owing to these revelations the vertical force signals are analyzed for extraction of useful features for correlating to identification of defects.
Fig. 6.3 Vertical force signals against defective and defect free welding cases
The vertical force signals acquired during the welding experiments are analyzed with the developed WPT-HHT method as detailed in chapter 5, section 5.7. The method is carried one step further for computation of instantaneous phase and frequency from the IMFs of the force signals. The IMFs computed against Exp. No. 45 and Exp. No. 35 is
Defect identification in FSW process
shown in Fig. 6.4.In the figure C1 to C8 represents the IMFs of the coefficients extracted from WPT of the real-time vertical force signal acquired during FSW process. These functions represent the intrinsic behaviour of the force signals acquired during welding process. As the functions are represented with respect to time, time dependent monitoring of the process is possible. Any anomaly occurred during the process can be detected over time. In signal processing perspective, IMFs represents the fundamental oscillatory behaviour of the signal which represents the physical behaviour of the process from which the signal is acquired. In FSW process, as force signal show appreciable acceptance for monitoring the process behaviour, analyzing the signal through fundamental behaviour of the signal is advantageous for effective monitoring of the process. From the IMFs, it can be observed that the defective and defect free cases have appreciable difference in trend and magnitude. The instantaneous frequency spectra for the defective cases (Exp. No. 35, 65) and defect free welding cases (Exp. No. 45, 3 and 17) are shown in Fig. 6.5. From the spectra, it is clearly distinct that defect formation inside the weld increases the frequency of the signal, which can be detected with respect to time. Increase in force signal frequency with defect formation in the weld was also reported by (Boldsaikhan et al., 2011). The above analysis brings the impression that IMFs can be effective in detecting subsurface defects in friction stir welded joints without involving much complicated analysis.
Apart from the instantaneous frequency, instantaneous phase angles obtained from Hilbert transform of the IMFs also give a remarkable notion for detection of defects in the welded samples. Out of the 65 experimental cases, two cases (Exp. No. 35 and 65) were confirmed to have tunnel defect through mechanical cross sectioning method. Rest of the welded samples do not show any evidence of presence of internal defects. The computed instantaneous phase angles for defective and defect free welding cases are displayed in Fig. 6.6. In the figure, clear deviation of phase angles can be observed among defective and defect free welding cases. It is to note that, instantaneous phase of defective samples are towards negative scale and that of defect free samples are toward positive scale. The appreciable difference leads to the notion that the proposed approach can be an effective visual method for easy identification of defective welded samples through instantaneous phase angles. From the figure, it is witnessed that there is a distinct phase shift between the defective and defect free weld signals. In theory, accumulated phase shift of a signal can be viewed as the area under the curve between
Chapter 6
instantaneous time and instantaneous frequency of the signal. From Fig. 6.5, it is seen that area under the time-frequency curve for defective weld signal is higher than the one for defect free weld signal. This possibly introduces a phase shift in the faulty signal that brings deviation as compared with the phase of defect free signal. As it is observed that change in frequency is the outcome of the occurrence of the defect in the weld, which in turn brings the phase shift in the faulty signal. So, it is evidential that presence of defect also brings phase shift in the signal. Although, the physical interpretation of the particular change is difficult and further analysis is desirable in this regard for the generalization of the findings reported herewith.
(a) (b)
Fig. 6.4 IMFs computed against (a) Exp. No. 35 and (b) Exp. No. 45
Defect identification in FSW process
Fig. 6.5 Instantaneous frequency spectra for defective and defect free welds
Fig. 6.6Instantaneous phase angle plot for defective and defect free welds
A simple yet effective methodology has been proposed for identification of internal defects with vertical force signal features. The combined WPT-HHT method offers an accurate method for analyzing the vertical force signal for computation of instantaneous phase and instantaneous frequencies. These two features reveal a direct mean of classification of defective welds from defect free welds that can be regarded as indicators for internal defect detection. The proposed method is suitable for integration
Chapter 6
of machine intelligence and human intervention in the process is less making it less prone to human error.