... parameter is varied, the system undergoes a series of bifurcations leading to characteristically different nonlinear oscillations. Through the application of nonlinear time series analysis to pressure and flame (CH* chemiluminescence) intensity time traces, these oscillations are characterized as periodic...

... to obtain a time series of pressure with a high bandwidth and, therefore, statistically representative average fluctuations at the blade passing frequency. The probe is water cooled by a high pressure cooling system and uses a conventional piezoresistive pressure sensor, which yields, therefore, both time...

... symbolic dynamic filtering by optimally partitioning the time series data of sensor observation. The objective here is to mask the effects of sensor noise level variation and magnify the system fault signatures. In this regard, the concepts of feature extraction and pattern classification are used...

... fraction fuel burnt) for an n -heptane fueled engine is performed for a test point near the misfire condition. The return map of the time series of CA50 cycle values reveals the deterministic and random portions of dynamics near misfire occurring in an HCCI engine. A symbol-statistic approach is also used...

... detection technique, which is based on Bayesian forecasting and dynamic linear models (DLMs). Bayesian forecasting enables the calculation of conditional probabilities, whereas DLMs are a mathematical tool for time series analysis. The combination of the two methods can be used to calculate probability...

... is represented through time series plots, time-delay phase plots, and Poincaré maps. The results indicate that as the tailpipe friction factor is lowered, the system undergoes a transition from steady combustion through oscillating combustion to an intermittent combustion with chaotic characteristics before...