초록 ▼

Methods and systems for analyzing engine unbalance conditions are disclosed. In one embodiment, a method includes receiving vibrational data from a plurality of locations distributed over an engine and a surrounding engine support structure, and inputting the vibrational data into a neural network i

Methods and systems for analyzing engine unbalance conditions are disclosed. In one embodiment, a method includes receiving vibrational data from a plurality of locations distributed over an engine and a surrounding engine support structure, and inputting the vibrational data into a neural network inverse model. The neural network inverse model establishes a relationship between the vibrational data and an unbalance condition of the engine, and outputs diagnostic information indicating the unbalance condition of the engine. In a further embodiment, a method further includes subjecting the vibrational data to a Fast Fourier Transformation to extract a desired once per revolution vibrational data prior to input to the neural network inverse model.

대표청구항 ▼

What is claimed is: 1. A system of analyzing an engine unbalance condition, composing: at least one sensor for collecting vibration sensed data; a processor adapted for receiving, analyzing, and extracting diagnostic information from the sensed data, the diagnostic information including an unbalanc

What is claimed is: 1. A system of analyzing an engine unbalance condition, composing: at least one sensor for collecting vibration sensed data; a processor adapted for receiving, analyzing, and extracting diagnostic information from the sensed data, the diagnostic information including an unbalance magnitude and an angular location as a function of a rotational frequency of the engine; data link for linking the diagnostic information; and a neural network adapted to receive and analyze the diagnostic information from the data link, wherein the status of engine unbalance is determined and presented by the neural network. 2. The system of claim 1, wherein the data link further includes a databus and a WiFi circuit. 3. The system of claim 1, wherein the processor is adapted to input the vibration sensed data in a time domain format into a neural network inverse model. 4. The system of claim 1, wherein the processor is adapted to input the vibration sensed data in a complex frequency domain format into a neural network inverse model. 5. The system of claim 1, wherein the processor is adapted to subject the vibration sensed data to a Fast Fourier Transformation. 6. The system of claim 1, wherein the processor is adapted to extract a desired once per revolution vibration sensed data. 7. The system of claim 1, wherein the processor is adapted to subject the vibration sensed data to a Wavelet Transformation. 8. The system of claim 1, wherein the neural network is adapted to establish a relationship between the vibration sensed data and an unbalance condition of the engine using at least one of a multilayer perceptron neural network model and a support vector machine neural network model. 9. The system of claim 1, wherein the neural network is adapted to establish a relationship between the vibration sensed data from a plurality of locations within one defined area to that of a plurality of locations within another defined area using at least one of a multilayer perceptron neural network model and a support vector machine neural network model. 10. The system of claim 1, wherein the neural network is adapted to be trained including adjusting model parameters such that application of a set of inputs and outputs reaches a desired state of definition defined by acceptable error tolerances. 11. The system of claim 1, wherein the neural network is adapted to be trained including using vibration sensed data generated using an engine that is subject to at least one of residual unbalances and applied trial weight unbalances. 12. A system of analyzing an engine unbalance condition, comprising: means for collecting vibration sensed data; means for receiving, analyzing, and extracting diagnostic information from the sensed data, the diagnostic information including an unbalance magnitude and an angular location as a function of a rotational frequency of the engine; means for data linking the diagnostic information;and means for receiving and analyzing the data linked diagnostic information, wherein the status of engine unbalance is determined. 13. The system of claim 12, wherein the receiving, analyzing, and extracting diagnostic information means is adapted to input the vibration sensed data in a time domain format into a neural network inverse model. 14. The system of claim 12, wherein the receiving, analyzing, and extracting diagnostic information means is adapted to input the vibration sensed data in a complex frequency domain format into a neural network inverse model. 15. The system of claim 12, wherein the receiving and analyzing the data linked diagnostic information means is adapted to establish a relationship between the vibration sensed data and an unbalance condition of the engine using at least one of a multilayer perceptron neural network model and a support vector machine neural network model. 16. The system of claim 12, wherein the receiving and analyzing the data linked diagnostic information means is adapted to establish a relationship between the vibration sensed data from a plurality of locations within one defined area to that of a plurality of locations within another defined area using at least one of a multilayer perceptron neural network model and a support vector machine neural network model. 17. The system of claim 12, wherein the receiving and analyzing the data linked diagnostic information means is adapted to be trained including adjusting model parameters such that application of a set of inputs and outputs reaches a desired state of definition defined by acceptable error tolerances. 18. The system of claim 12, wherein the receiving and analyzing the data linked diagnostic information means is adapted to be trained including using vibration sensed data generated using an engine that is subject to at least one of residual unbalances and applied trial weight unbalances.