Replicated multi-channel sensors for decucing ink thicknesses in color printing devices

Abstract

A method and computing system are proposed for deducing ink thickness variations from solid-state multi-sensor measurements performed online on a printing press or printer. The computed ink thickness variations enable controlling the ink deposition and therefore the color accuracy. Ink thickness variations are expressed as ink thickness variation factors incorporated into an ink thickness variation and sensor response enhanced spectral prediction model. The ink thickness variation computing system comprises multi-channel sensor devices (e.g. red, green, blue, near infra-red), a processing module, and a computing system. The multi-channel sensor devices are replicated over the width of the print sheet. Preferably embodied by Single Photon Avalanche Diodes (SPADs), due to their high-speed acquisition capabilities, they provide responses according to the reflectance of small area segments within a print sheet. The processing module accumulates the digital sensor responses and forwards them to the computing system, which deduces the ink thickness variations.

1 . A method for computing ink thickness variations for the control of printing devices, the method being based on an ink thickness variation and sensor response enhanced spectral prediction model, said method comprising calibration steps and, during print operation, online ink thickness variation computation steps, where the calibration steps comprise the calculation of ink transmittances, and where the ink thickness variation computation steps comprise fitting of ink thickness variations by minimizing a distance metric between predicted multi-channel sensor responses and acquired multi-channel sensor responses, said predicted multi-channel sensor responses being computed according to the ink thickness variation and sensor response enhanced spectral prediction model, and said. acquired multi-channel sensor responses being generated by light reflected on a print sheet.  
   
   
       2 . The method of  claim 1 , where the print sheet is moving and the multi-channel sensor devices, due to their high-speed acquisition capabilities, provide responses according to the reflectance of small area segments within the print sheet, and where the calibration steps also comprise, in order to account for ink spreading, fitting of effective surface coverage curves mapping nominal to effective surface coverages of single ink halftones in different superposition conditions.  
   
   
       3 . The method of  claim 1 , comprising also during said print operation online calibration steps, said online calibration steps comprising a step of fitting effective surface coverage curves mapping nominal to effective surface coverages of single ink halftones in different superposition conditions by acquisition of sensor responses from polychromatic halftones.  
   
   
       4 . The method of  claim 1 , where the thickness variation and sensor response enhanced spectral prediction model comprises as solid colorant transmittance of at least two superposed solid inks the transmittance of each of the superposed inks raised to the power of a product of variables, one variable being the superposition condition dependent ink thickness and the other variable being the ink thickness variation factor.  
   
   
       5 . The method of  claim 1 , where the inks are the cyan, magenta, yellow, and black inks and where the thickness variation and sensor response enhanced spectral prediction model operates simultaneously in the visible and near infra-red wavelength range domain.  
   
   
       6 . The method of  claim 1 , where the ink thickness variation computation steps also comprise the step of online recording of reference thickness variations and where the computed ink thickness variations are ink thickness variations normalized in respect to the reference ink thickness variations.  
   
   
       7 . The method of  claim 1 , where, in addition to the calibration and recalibration steps, the step of acquiring during print operation reference sensor responses from a reference print under reference settings and of deducing corresponding reference effective surface coverages is performed, where the sensor responses are predicted with the deduced reference effective surface coverages, and where the computed ink thickness variations represent ink thickness variations in respect to the reference print.  
   
   
       8 . The method of  claim 1 , where said multi-channel sensor devices are based on single photon avalanche diodes (SPADs) which capture during print operation light reflected by said small area segments within the print page.  
   
   
       9 . The method of  claim 8 , where light emitting diodes (LEDs) emit light that is directed towards the print sheet, where part of said light penetrates the print sheet, is reflected by the sheet's substrate and captured by said SPAD sensor devices.  
   
   
       10 . An ink thickness variation computing system for the control of printers, respectively printing presses operable for the online computation of ink thickness variations during print operation, said ink thickness variation computing system comprising multi-channel sensor devices, a processing module, and a computing system, where the multi-channel sensor devices respond at different spectral sensibility ranges within the visible and near infra-red wavelength range, where the multi-channel sensor devices, due to their high-speed acquisition capabilities, provide responses according to the reflectance of small area segments within a print sheet, where the processing module receives the responses from said multi-channel sensor devices and forwards them to the computing system, which according to an ink thickness variation and sensor response enhanced spectral prediction model deduces said ink thickness variations.  
   
   
       11 . The ink thickness variation computing system of  claim 10 , where said multi-channel sensor devices are based on single photon avalanche diodes (SPADs) which capture light reflected by said small area segments within the print sheet.  
   
   
       12 . The ink thickness variation computing system of  claim 11 , where single photon avalanche diodes photon count acquisition times range between 200 nanoseconds and 10 milliseconds.  
   
   
       13 . The ink thickness variation computing system of  claim 11 , where the processing module comprises a multiplexer, a fast logic, a pulse counter and a microcontroller, where the multiplexer is operable for selecting the SPAD whose pulses are counted, where the pulse counter is operable for counting the pulses received from the SPADs and where the microcontroller is operable for storing the resulting pulse count and for transmitting it to the computing system.  
   
   
       14 . The ink thickness variation computing system of  claim 11 , where light emitting diodes (LEDs) emit light that is directed towards the print sheet, where part of said light penetrates the print sheet, is reflected by the sheet's substrate and captured by said SPAD sensor devices.  
   
   
       15 . The ink thickness variation computing system of  claim 11 , where white light is filtered by filters having different spectral sensibilities within the visible and near infra-red wavelength range and directed towards the print sheet, where part of said filtered light penetrates the print sheet, is reflected by the print sheet's substrate and captured by said SPAD sensor devices.  
   
   
       16 . The ink thickness variation computing system of  claim 11 , where white light illuminates an area segment of said print sheet, is reflected by said area segment, is filtered by filters having different spectral sensibilities within the visible and near infra-red wavelength range and is captured by said SPAD sensor devices.  
   
   
       17 . The ink thickness variation computing system of  claim 11 , where one input and one output polarizing filters discard part of said light that is specularly reflected at the surface of said moving print sheet.  
   
   
       18 . The ink thickness variation computing system of  claim 10  forming together with an additional print actuation parameter driving module an online ink regulation system operable for controlling according to the deduced ink thickness variations the amount of ink deposited onto a substrate.  
   
   
       19 . The ink thickness variation computing system of  claim 18 , where controlling the amount of ink deposited onto a substrate is performed in case of a printed press by ink feed, in case of an ink jet printer by a function selected from the set of droplet ejection control and droplet count, in case of an electrophotographic printer by a function selected from the set of toner transfer and fusing and in case of a thermal transfer, respectively dye sublimation printer, by controlling head element temperature profiles.  
   
   
       20 . The ink thickness variation computing system of  claim 10 , where the inks are the cyan, magenta, yellow, and black inks and where said thickness variation and sensor response enhanced spectral prediction model operates in the visible and near infra-red wavelength range.  
   
   
       21 . The ink thickness variation computing system of  claim 10 , where said computing system also performs an online refined calibration of said thickness variation and sensor response enhanced spectral prediction model by deducing paper reflectances of said print sheets and by fitting according to the multi-channel sensor responses effective surface coverage curves mapping nominal to effective surface coverages of single ink halftones in different superposition conditions.  
   
   
       22 . The ink thickness variation computing system of  claim 10 , where said computing system also records reference thickness variations and where the computed ink thickness variations are ink thickness variations normalized in respect to the reference ink thickness variations.  
   
   
       23 . The ink thickness variation computing system of  claim 10 , where said computing system also records reference sensor responses from a reference print under reference settings, deduces corresponding reference effective surface coverages, and predicts sensor responses with the deduced reference effective surface coverages and where the computed ink thickness variations represent ink thickness variations in respect to the reference print.