## 4 Results and Discussion  
Our objective was to derive a reliable vibration-based health indicator (HI), capable of monitoring the real-time lubricating condition of the toggle clamping system of a plastic injection molding machine. The experimental procedures mandated that the toggle clamping system be repeatedly clamped and unclamped for a total of 530 cycles. The toggle was completely re-lubricated for 40 s at the start of testing and thereafter at cycles 150, 330, and 530. These re-lubrication points were selected by the experienced machine operator as at these points screeching sounds were detected. The re-lubrication of the toggle clamping system resulted in the subsiding of the screeching sound. Given that lubricant both deteriorates and depletes over time, it was expected that the lubrication condition would be inversely related to the increasing cycle number. A reliable condition monitoring health indicator should hence be able to identify the optimal timing for addition of lubricant to the toggle clamping system. The same HI should also be able to capture the gradual degradation of the lubrication condition resulting from progressive cycles. Tribological researchers have shown that surface velocity is inversely proportional to coefficient of friction [32; 33]. Additionally, it has been widely accepted that frictional force is proportional to normal force [34]. It can therefore be postulated that the toggle clamping system is susceptible to its highest frictional forces during its clamping and unclamping periods, since its surface velocity during these periods is relatively low while being subjected to extremely high clamping forces. It is therefore reasonable to surmise that lubricant failure or depletion will first be manifested in either or both of these periods. Given this hypothesis, the vibration generated during these two periods were extracted and analyzed using time domain, frequency domain, and structural response analyses. Figure 6 shows the results of the time domain analysis of the clamping and unclamping periods. The RMS algorithm was used to extract a descriptive health indicator to monitor the lubrication condition of the toggle clamping system. The vertical dotted blue lines indicate where lubricant was added to the toggle. Analysis of both the clamping and unclamping periods showed a seemingly random distribution of the health indicator (\(HI_{RMS}\)) values over the duration of the experiment. Since the RMS algorithm is best suited to capture changes in the amplitude of time series data, it is evident that vibrational signatures relating to the lubrication condition of the toggle clamping system did not manifest in the form of increasing acceleration magnitude only, rendering the RMS time domain indicator not suitable for condition monitoring. Figure 7 shows the results of the frequency domain analysis of the clamping and unclamping periods. In this analysis, the FFT algorithm was used to transform the time domain vibration into its frequency domain representation. This transformation showed that the characteristic frequencies of the vibration generated during the clamping and unclamping periods appeared to be in the frequency range of 335 Hz to 342 Hz. The FC algorithm was then used to derive a health indicator to monitor the lubricating condition of the toggle clamping system. The FC algorithm monitored the changes of the characteristic frequency of the vibration signal generated during each cycle. By observing the resulting plots, subtle changes to the data distribution were observed throughout the experiment. Particularly, the FC health indicator (\(HI_{FC}\)) for the clamping period displayed more activity than for the corresponding unclamping period. The displayed behavior, however, poorly responded to the addition of lubricant to the toggle clamping system, displaying no consistent trend indicative of lubricant degradation.