Abstract: A method for analyzing vibration including: acquiring a vibration signal; isolating a vibration signal event in the acquired signal; determining a frequency of a damped sinusoid of the vibration signal event, wherein the damped sinusoid characterizes the vibration signal event, and using the characteristic damped sinusoid to identify an occurrence of the vibration signal event in another vibration signal.

Abstract: A method for monitoring engine performance includes sampling exhaust gas temperature associated with a turbine engine over an interval of operational time of the turbine engine. The method further includes applying a first test to identify statistical outliers on the sampled exhaust gas temperature data and removing identified statistical outliers from the sampled exhaust gas temperature data. Subsequently, the method includes applying a second test to identify step changes in slope of the exhaust gas temperature data and dividing the interval of operational time into one or more segments based upon the identified step changes. Finally, the method includes determining a slope for each segment and combining the segments to obtain a rate of performance deterioration of the turbine engine.

Abstract: A method for facilitating an optimization of a control space in n dimensions is provided. The control space includes a plurality of points, and the method includes removing at least one hyperplane of the control space, and perturbing the remaining points of the control space to lessen errors relative to the control space prior to the removal of at least one hyperplane.

Abstract: A system and method for automatically predicting timing and costs of future service events in a life cycle of a product. A database contains a plurality of service information and performance information for the product. A statistical analyzer automatically analyzes the plurality of processed service information to determine a plurality of compartment failure information. A performance deterioration rate analyzer automatically analyzes the performance deterioration rate of the product from the plurality of service information and performance information. A simulator, automatically simulates a distribution of future service events in the life cycle of the product and predicts the costs of the service events according to the plurality of compartment failure information and the performance deterioration rate analysis.

Abstract: A system and method for predicting timing of future service events of a product. A database contains a plurality of service information and performance information for the product. A statistical analyzer analyzes the plurality of processed service information to determine a plurality of compartment failure information. A performance deterioration rate analyzer analyzes the performance deterioration rate of the product from the plurality of service information and performance information. A simulator, simulates a distribution of future service events of the product according to the plurality of compartment failure information and the performance deterioration rate analysis.

Abstract: System, method and computer-readable medium for baseline modeling a product or process. A service database contains process data. A preprocessor processes the data into a predetermined format. A baseline modeling component builds a baseline model from the preprocessed data, wherein the baseline model relates process performance variables as a function of process operating conditions.

Abstract: System, method and computer product for baseline modeling a product or process. A service database contains process data. A preprocessor processes the data into a predetermined format. A baseline modeling component builds a baseline model from the preprocessed data, wherein the baseline model relates process performance variables as a function of process operating conditions.

Abstract: System, method and computer product for baseline modeling a product or process. A service database contains process data. A preprocessor processes the data into a predetermined format. A baseline modeling component builds a baseline model from the preprocessed data, wherein the baseline model relates process performance variables as a function of process operating conditions.

Abstract: A method for facilitating an optimization of a control space in n dimensions is provided. The control space includes a plurality of points, and the method includes removing at least one hyperplane of the control space, and perturbing the remaining points of the control space to lessen errors relative to the control space prior to the removal of at least one hyperplane.

Abstract: System, method and computer product for baseline modeling a product or process. A service database contains process data. A preprocessor processes the data into a predetermined format. A baseline modeling component builds a baseline model from the preprocessed data, wherein the baseline model relates process performance variables as a function of process operating conditions.

Abstract: A method and system for planning repair or overhaul of an aircraft engine. This invention retrieves engine configuration data for a plurality of life limited parts for the aircraft engine, retrieves service requirement data for at least one of the plurality of life limited parts for the aircraft engine, and automatically determines a remaining life for the at least one of the plurality of life limited parts of the aircraft engine from the configuration data and the service requirement data.

Abstract: The present invention discloses a method and system for detecting and correcting an erroneous exposure generated during x-ray imaging of a patient. In the present invention, x-ray imaging settings for imaging the patient are selected. X-ray beam quality and x-ray quantity values are generated from the selected x-ray imaging settings. An exposure rate is predicted from the x-ray beam quality and x-ray quantity values. The patient is then exposed to an x-ray beam having the generated x-ray beam quality and x-ray quantity values. The total exposure is then determined and compared to the predicted exposure rate. The comparison is then used to determine if the patient is being exposed at an erroneous level. If the exposure is at a correct level, then the exposure is completed. However, if the exposure is not at a correct level, then the exposure is stopped and adjusted to a new exposure level.