Image forming apparatus
US-2015160594-A1 · Jun 11, 2015 · US
US9367005B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9367005-B2 |
| Application number | US-201414295851-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jun 4, 2014 |
| Priority date | Jun 4, 2014 |
| Publication date | Jun 14, 2016 |
| Grant date | Jun 14, 2016 |
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An operational imaging device and method using a predetermined set of operating parameter determining (OPD) equations forming an OPD equation set for providing one or more operational parameter values for processing of a media sheet. The OPD equation set, stored in the operational imaging device, is solved using values for a set of N variables measured by an operational sensor set in the operational imaging device. Each equation solution determines a value for one of the operating parameters. The OPD equation set is generated by a training system using a continuum training engine. A training data set containing measured variable values of the set of N variables is collected using by a training sensor set. The training data set includes empirical best match data values for the one or more operational parameters based on a comparison of a model image to images produced by a training imaging device.
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What is claimed is: 1. In an imaging device, a method of determining one or more operating parameters for processing a media sheet by a processing device in the imaging device, the method comprising: storing in memory of the imaging device a predetermined set of OPD equations incorporating a predetermined set of N variables related to the media sheet and the processing thereof by the processing device of the imaging device wherein each OPD equation corresponds to one operating parameter of the one or more operating parameters; providing an operational sensor set having a plurality of sensors for the imaging device for measuring a value of each variable in the set of N variables, the operational sensor set in operative communication with a controller for providing corresponding output signals representative of the measured values for the set of N variables; converting the received output signals into the N measured variable values; solving the set of OPD equations using the received N measured variable values to determine the one or more operating parameters; and, processing the media sheet with the processing device using the determined one or more operating parameters, wherein each equation in the predetermined set of OPD equations is a polynomial equation. 2. In an operational imaging device having an operational sensor set for measuring values of a predetermined set of N variables related to a media sheet and the processing thereof by a processing device of the operational imaging device, a method of determining one or more operating parameters for processing the media sheet by the processing device in the imaging device, the method comprising: storing in memory of the imaging device a predetermined set of OPD equations incorporating the predetermined set of N variables related to the media sheet and the processing thereof by the processing device of the imaging device wherein each OPD equation corresponds to one operating parameter of the one or more operating parameters; measuring, using the operational sensor set, a value of each variable in the set of N variables, the operational sensor set providing corresponding output signals representative of the measured values for the set of N variables, the operational sensor set being in operative communication with a controller; and at the controller: converting the output signals received from the operational sensor set into measured normalized variable values for the set of N variables; solving the OPD equation set using the measured normalized variable values to determine one operating parameter for each OPD equation in the OPD equation set; and, processing the media sheet with the processing device using the operating parameters determined from the solving of the OPD equation set, wherein each equation in the OPD equation set is a polynomial equation. 3. The method of claim 2 , wherein the operational sensor set includes one or more sensors for making a direct sensor measurement of a characteristic of the media sheet. 4. The method of claim 2 , wherein the operational sensor set includes one or more sensors for measuring a temperature, a relative humidity and a machine state. 5. The method of claim 2 , wherein the operational sensor set includes one or more sensors for making a subsystem response measurement. 6. The method of claim 2 , wherein each equation of the OPD equation set is truncated so that the remaining terms in each equation of the OPD equation set have coefficients of a larger absolute value when compared to the coefficients of the terms truncated therefrom. 7. The method of claim 2 , wherein the OPD equation set stored in memory is generated by: determining the one or more operating parameters to be used by an operational imaging device in processing the media sheet; determining the number of variables in the set of N variables needed to determine the one or more operating parameters; providing a training sensor set for measuring the set of N variables and providing corresponding output signals therefor; providing fuser temperature, fuser energy and transfer voltage data for reproducing a best match to a predetermined model image on a predetermined media type; using the training sensor set to measure the set of N variables with a known sample of each media type in a media set and a training imaging device and providing fuser temperature, fuser energy and transfer voltage best match data to create a corresponding training data set for the operational imaging device; inputting the training data set into a continuum training engine; and generating, using the continuum training engine and training data set, the OPD equation for each operating parameter in the one or more operating parameters forming the OPD equation set. 8. The method of claim 7 , wherein the continuum training engine is one of a neural network, a nonlinear regression engine, and a Bayesian network. 9. A method of operating parameter determination for use in processing a media sheet in an operational imaging device, the method comprising: establishing one or more operating parameters to be used in the operational imaging device; determining a number of variables N needed to determine each of the one or more operating parameters; providing a training sensor set for measuring each of the N variables and providing corresponding output signal therefor; providing a media set having a plurality of media types; using the training sensor set to measure the N variables with a known sample of each media type in the media set and a training imaging device to create a training data set, wherein the measuring includes taking multiple measurements of each of the N variables; inputting the training data set into a continuum training engine; generating, using the continuum training engine and training data set, an operating parameter determining (OPD) equation for each of the one or more operating parameters incorporating corresponding N variable terms to create an OPD equation set for use with an operational set of sensors corresponding to the training sensor set; and in the operational imaging device: storing in memory the OPD equation set; providing the operational sensor set in operable communication with the operational imaging device, the operational sensor set measuring a value of each variable in the set of N variables and providing corresponding output signals for the measured N variables for the sheet of media to be processed; converting the received output signals into N measured normalized variable values; solving the each equation in the OPD equation set using the N measured normalized variable values to determine a corresponding one or more operating parameter values; using the determined one or more operating parameter values to process the media sheet in the operational imaging device. 10. The method of claim 9 , wherein the measuring of multiple measurements of each of the N variables by the training sensor set occurs at a plurality of predetermined temperature and relative humidity combinations. 11. The method of claim 9 , wherein the processing device is an electrophotographic printer and the set of N variables comprises temperature, relative humidity, electrical impedance magnitude, electrical impedance phase, gloss, bending stiffness, optical transmission mean, and optical transmission deviation, and, further wherein, the operational sensor set includes sensors for measuring the set of N variables. 12. The method of claim 11 , wherein the set of N variables further includes a media feed base resistance, and, further wherein the operational sensor set includes a sensor for measuring the media feed base re
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