Faulty nozzle estimation device, faulty nozzle estimation method and program, printing device, and method for manufacturing printed matter

Abstract

Provided are: a defective nozzle estimation device, a defective nozzle estimation method, and program which accurately estimate defective nozzles; a printing device; and a method for manufacturing printed matter. The present invention acquires the nozzle-direction position of an image defect of printed matter due to a defective nozzle in imaging data, acquires nozzle mapping information, which is the relationship between the positions of a plurality of nozzles of the inkjet head and the nozzle-direction pixel of the imaging data, corrects the nozzle mapping information by using the nozzle mapping correction information for correcting the nozzle-direction positional relationship of at least two among the print medium, the inkjet head, and the scanner, and estimates at least one defective nozzle candidate by using the corrected nozzle mapping information.

Description

[Technical Field]

[0001] The present invention relates to a defective nozzle estimation device, a defective nozzle estimation method and program, a printing device, and a method for producing printed material, and more particularly to a technique for estimating defective nozzles from multiple nozzles in an inkjet head. [Background technology]

[0002] Inkjet printing devices commonly use a process in which a specific pattern is output and an image of the printed matter of the output pattern is captured by an imaging device to check the condition of the printed matter. In particular, because the condition of the nozzles of an inkjet head changes before and after printing and cleaning due to the influence of solidified ink and other factors, it is necessary to periodically output a detection pattern to check the condition of the nozzles.

[0003] For example, Patent Document 1 discloses an image inspection device that detects faulty nozzles in an inkjet head from read image data of a pattern for detecting faulty nozzles recorded using a single-pass inkjet printing device, saves a history of the detection results, detects image defects in a printed image from read image data of the printed image recorded using the inkjet printing device, and compares information about the image defects with historical information about the faulty nozzles to identify the faulty nozzles that caused the image defects. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 6576316 Summary of the Invention [Problem to be solved by the invention]

[0005] However, the image inspection device described in Patent Document 1 has a problem in that the accuracy of estimating defective nozzles decreases due to a deviation in the relative positional relationship between the nozzles and the imaging device during printing.

[0006] For example, in a sheet-fed press, when imaging after drying, shrinkage of the substrate due to drying can cause variations in the positional relationship between pages, particularly in variable printing, etc. Also, in a continuous feed press that prints on roll paper, etc., compared to a sheet-fed press, meandering of the substrate occurs during printing, which can cause a shift in the relative positional relationship between the nozzle and the imaging device.

[0007] The present invention has been made in consideration of the above circumstances, and aims to provide a defective nozzle estimation device, a defective nozzle estimation method and program, a printing device, and a method for manufacturing printed matter that accurately estimate defective nozzles. [Means for solving the problem]

[0008] One aspect of a defective nozzle estimation device for achieving the above object is a defective nozzle estimation device for estimating defective nozzles in an inkjet head of a single-pass printing device that includes an inkjet head having a plurality of nozzles arranged in the nozzle direction, a scanner having a plurality of reading pixels arranged in the nozzle direction, and a relative movement mechanism that moves the inkjet head, the scanner, and a printing medium relatively in a relative movement direction that intersects with the nozzle direction, and that prints a printed material on the printing medium by ejecting ink from the nozzles of the inkjet head based on original print data toward the printing medium that has been moved relatively in the relative movement direction, and that reads the printed material with the reading pixels of the scanner, the defective nozzle estimation device comprising at least one processor and at least one memory that stores instructions to be executed by the at least one processor, and the at least one processor is configured to The defective nozzle estimation device acquires image data based on an image captured by a scanner, acquires reference image data based on original print data or a reference image of a reference print captured by a scanner, and compares the image data with the reference data to obtain the nozzle-direction positions of image defects on the print caused by defective nozzles in the image data. The device acquires nozzle mapping information, which is a correspondence between the positions of multiple nozzles and pixel positions in the nozzle direction of the image data. The device acquires nozzle mapping correction information that corrects the nozzle-direction positional relationship of at least two of the print medium, inkjet head, and scanner. The device corrects the nozzle mapping information using the nozzle mapping correction information. The corrected nozzle mapping information is used to estimate at least one defective nozzle candidate that is the cause of the image defect on the print. According to this aspect, defective nozzles can be accurately estimated. A defective nozzle is a nozzle that cannot eject ink normally and causes image defects. The reference print can be, for example, a non-defective print without image defects among prints printed based on the original print data.

[0009] The nozzle mapping correction information preferably includes information on the edge position of the print medium in the nozzle direction in the image data, which makes it possible to correct the positional relationship in the nozzle direction between the print medium and the scanner in the nozzle mapping information.

[0010] The nozzle mapping correction information preferably includes information on the position on the printing medium in the nozzle direction of ink ejected from a specific nozzle of the inkjet head in the imaging data, which makes it possible to correct the positional relationship in the nozzle direction between the printing medium and the scanner in the nozzle mapping information.

[0011] The nozzle mapping correction information preferably includes information about the thickness of the print medium, which allows correction of the positional relationship between the print medium and the scanner in the nozzle direction based on the nozzle mapping information.

[0012] When there are multiple estimated faulty nozzle candidates, it is preferable that at least one processor acquires first corrected captured data based on a first corrected captured image obtained by a scanner of a first corrected printout that has been printed after a first correction process has been performed to suppress image defects caused by a first faulty nozzle candidate that is at least one of the multiple faulty nozzle candidates, and determines whether or not the first faulty nozzle candidate is a faulty nozzle based on the first corrected captured data. This makes it possible to determine whether or not the first faulty nozzle candidate is a faulty nozzle.

[0013] Preferably, when the at least one processor determines that the first faulty nozzle candidate is not a faulty nozzle, the at least one processor acquires second corrected captured data based on a second corrected captured image obtained by a scanner of a second corrected printout that has been printed after a second correction process has been performed to suppress image defects caused by a second faulty nozzle candidate that is different from the first faulty nozzle candidate, and determines whether or not the second faulty nozzle candidate is a faulty nozzle based on the second corrected captured data. This makes it possible to determine whether or not the second faulty nozzle candidate is a faulty nozzle when the first faulty nozzle candidate is not a faulty nozzle.

[0014] Preferably, when there are multiple estimated defective nozzle candidates, at least one processor performs a correction process to suppress image defects caused by a defective nozzle candidate selected from the multiple defective nozzle candidates multiple times so that each of the multiple defective nozzle candidates is selected at least once, obtains multiple corrected captured data based on multiple corrected captured images obtained by a scanner of multiple corrected printouts printed using the multiple corrected print data obtained by the multiple correction processes, and determines whether or not each of the multiple defective nozzle candidates is a defective nozzle based on the multiple corrected captured data. This makes it possible to determine whether or not each of the multiple defective nozzle candidates is a defective nozzle.

[0015] Preferably, the printing device includes multiple inkjet heads, and the at least one processor acquires nozzle mapping information for each of the multiple inkjet heads, thereby making it possible to estimate defective nozzle candidates even when the printing device includes multiple inkjet heads.

[0016] One aspect of a printing device for achieving the above object is a printing device that includes the above-mentioned defective nozzle estimation device, an inkjet head having a plurality of nozzles arranged in the nozzle direction, a scanner having a plurality of reading pixels arranged in the nozzle direction, and a relative movement mechanism that moves the inkjet head, the scanner, and a printing medium in a relative movement direction, and that prints a printed material on the printing medium by ejecting ink from the nozzles of the inkjet head based on original print data toward the printing medium that has been moved in the relative movement direction, and that reads the printed material with the reading pixels of the scanner. According to this aspect, it is possible to accurately estimate defective nozzles while printing the printed material.

[0017] One aspect of a defective nozzle estimation method for achieving the above object is a defective nozzle estimation method for estimating defective nozzles in an inkjet head of a single-pass printing device that includes an inkjet head having a plurality of nozzles arranged in the nozzle direction, a scanner having a plurality of reading pixels arranged in the nozzle direction, and a relative movement mechanism that relatively moves the inkjet head, the scanner, and a printing medium in a relative movement direction that intersects with the nozzle direction, and that prints a printed material on the printing medium by ejecting ink from the nozzles of the inkjet head based on original print data toward the printing medium that has been relatively moved in the relative movement direction, and that reads the printed material with the reading pixels of the scanner, the defective nozzle estimation method comprising: an imaging data acquisition step of acquiring imaging data based on an image of the printed material captured by the scanner; and an imaging data acquisition step of acquiring reference imaging data based on the original print data or a reference image of a reference printed material captured by the scanner. This defective nozzle estimation method includes a reference data acquisition step of acquiring reference data, an image defect position acquisition step of comparing image data with the reference data to acquire the nozzle direction position of an image defect in a printed product caused by a defective nozzle in the image data, a nozzle mapping information acquisition step of acquiring nozzle mapping information which is the correspondence between the positions of multiple nozzles and pixel positions in the nozzle direction of the image data, a nozzle mapping correction information acquisition step of acquiring nozzle mapping correction information which corrects the nozzle direction positional relationship of at least two of the print medium, the inkjet head, and the scanner, a nozzle mapping information correction step of correcting the nozzle mapping information using the nozzle mapping correction information, and a defective nozzle candidate estimation step of using the corrected nozzle mapping information to estimate at least one defective nozzle candidate that is the cause of the image defect in the printed product. According to this aspect, defective nozzles can be estimated with high accuracy.

[0018] One aspect of a method for manufacturing a printed material to achieve the above object is a method for manufacturing a printed material, which includes a printing process in which a single-pass printing device includes an inkjet head having multiple nozzles arranged in the nozzle direction, a scanner having multiple reading pixels arranged in the nozzle direction, and a relative movement mechanism for relatively moving the inkjet head, the scanner, and the printing medium in a relative movement direction intersecting the nozzle direction, and ejects ink from the nozzles of the inkjet head based on original printing data onto the printing medium moved relatively in the relative movement direction, an image defect detection process in which image defect detection is performed on the printed material by comparing the captured data with reference data, the defective nozzle estimation method, and a correction process in which correction processing is performed on the original printing data to suppress image defects caused by at least one candidate defective nozzle. According to this aspect, defective nozzles can be accurately estimated and correction processing can be performed while the printed material is being printed, thereby reducing waste when manufacturing the printed material.

[0019] One aspect of a program for achieving the above object is a program for causing a computer to execute the above-mentioned defective nozzle estimation method. This aspect may also include a computer-readable non-transitory storage medium on which this program is recorded. According to this aspect, defective nozzles can be estimated with high accuracy. [Effects of the Invention]

[0020] According to the present invention, defective nozzles can be estimated with high accuracy. [Brief explanation of the drawings]

[0021] [Figure 1] FIG. 1 is a diagram showing the overall configuration of an inkjet printing apparatus. [Figure 2] FIG. 2 is a plan view showing the nozzle surface of the inkjet head. [Figure 3] FIG. 3 is a plan view showing the reading surface of the scanner. [Figure 4] FIG. 4 is a block diagram showing the configuration of a control system of the inkjet printing apparatus. [Figure 5] FIG. 5 is a block diagram showing the configuration of the defective nozzle estimation device. [Figure 6] FIG. 6 is a diagram showing an example of the relationship between the imaging data and the reference data. [Figure 7] FIG. 7 is a diagram showing an example of the relationship between the imaging data when the nozzle mapping information is acquired and the imaging data when the defective nozzle is estimated. [Figure 8] FIG. 8 is a diagram showing an example of the relationship between the imaging data and the reference data based on the corrected nozzle mapping information. [Figure 9] FIG. 9 is a flowchart showing the process of the defective nozzle estimating method performed by the defective nozzle estimating device 100. [Figure 10] FIG. 10 is a block diagram showing the configuration of a defective nozzle estimation device. [Figure 11] FIG. 11 is a flowchart showing the process of the defective nozzle estimation method performed by the defective nozzle estimation device. [Figure 12] FIG. 12 is a block diagram showing the configuration of a defective nozzle estimation device. [Figure 13] FIG. 13 is a flowchart showing the process of the defective nozzle estimation method performed by the defective nozzle estimation device. [Figure 14] FIG. 14 is a flowchart showing the process of the method for producing a printed matter. [Figure 15] FIG. 15 is a flowchart showing the details of the correction process. [Figure 16] FIG. 16 is a diagram for explaining the correction process. [Figure 17] FIG. 17 is a diagram for explaining the correction process. [Figure 18] FIG. 18 is a diagram for explaining the correction process. [Figure 19] FIG. 19 is a flowchart showing the details of the correction process. [Figure 20] FIG. 20 is a diagram for explaining the correction process. DETAILED DESCRIPTION OF THE INVENTION

[0022] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0023] First Embodiment [Overall configuration of inkjet printing device] FIG. 1 is an overall configuration diagram of an inkjet printing apparatus 10. In FIG. 1, the X, Y, and Z directions are perpendicular to one another, the X and Y directions are horizontal, and the Z direction is vertical. The inkjet printing apparatus 10 is a printing apparatus that prints an image on a long substrate 12 (an example of a printing medium) using a single pass method. The substrate 12 in this embodiment is roll paper.

[0024] The substrate 12 may be a transparent medium having impermeability used in flexible packaging. Having impermeability means that even if the pretreatment liquid and ink described below adhere to the surface, they do not penetrate into the interior. Flexible packaging refers to packaging made of a material that deforms depending on the shape of the packaged item. Transparency means that the visible light transmittance is 30% or more, preferably 70% or more.

[0025] As shown in FIG. 1, the inkjet printing device 10 includes a feed roll 14, a take-up roll 16, a conveying section 20, a treatment liquid application section 30, a treatment liquid drying section 32, an image recording section 34, an ink drying section 42, and an imaging section 44.

[0026] [Transportation section] The delivery roll 14 includes a rotatably supported reel (not shown). The substrate 12 before an image is printed is wound in a roll shape around the reel. The take-up roll 16 includes a rotatably supported reel (not shown). One end of the substrate 12 is connected to the reel.

[0027] The conveying section 20 includes a plurality of guide rollers 22. The plurality of guide rollers 22 are arranged at positions where the conveying direction of the substrate 12 turns back, and at positions facing the conveying section 20, the treatment liquid application section 30, the treatment liquid drying section 32, the image recording section 34, the ink drying section 42, and the imaging section 44. The conveying section 20 also includes a feed motor (not shown) that drives the reel of the feed roll 14 to rotate, and a take-up motor (not shown) that drives the reel of the take-up roll 16 to rotate.

[0028] The conveying unit 20 rotates the reel of the feed roll 14 using a feed motor, causing the substrate 12 to be fed from the feed roll 14. The conveying unit 20 also rotates the reel of the take-up roll 16 using a take-up motor, causing the printed substrate 12 to be wound onto the take-up roll 16.

[0029] In the transport section 20, the substrate 12 delivered from the delivery roll 14 is guided by a plurality of guide rollers 22, and is transported in this order through the treatment liquid application section 30, the treatment liquid drying section 32, the image recording section 34, the ink drying section 42, and the imaging section 44. In this way, the substrate 12 is guided by the plurality of guide rollers 22 along the transport path from the delivery roll 14 to the take-up roll 16, and is transported in a roll-to-roll manner.

[0030] The transport unit 20 corresponds to a relative movement mechanism that moves the image recording unit 34 and the imaging unit 44 relative to the substrate 12 in a relative movement direction. In the example shown in Fig. 1, the relative movement direction is the Y direction.

[0031] The conveying unit 20 also includes a rotary encoder (not shown) that outputs an encoder value corresponding to the rotation of any one of the guide rollers 22, for example.

[0032] A plurality of guide rollers 22 are arranged downstream of the delivery roll 14 on the transport path of the substrate 12. The substrate 12 delivered from the delivery roll 14 is turned around in the transport direction by the plurality of guide rollers 22 and guided to the treatment liquid application section 30.

[0033] [Treatment liquid application section] The treatment liquid application unit 30 applies a pretreatment liquid to the printing surface of the substrate 12. The pretreatment liquid contains a flocculant that acts to aggregate components contained in the ink. Examples of the flocculant include acidic compounds, polyvalent metal salts, and cationic polymers. The pretreatment liquid of this embodiment is an acidic liquid that contains an acid as a flocculant.

[0034] The treatment liquid application unit 30 uses an application roller (not shown) to uniformly apply the pretreatment liquid to the printing surface of the substrate 12. The amount of pretreatment liquid to be applied may be an amount that appropriately aggregates the ink applied by the image recording unit 34. The treatment liquid application unit 30 may apply the pretreatment liquid using a head that ejects the pretreatment liquid by an inkjet method.

[0035] [Treatment liquid drying section] A treatment liquid drying unit 32 is disposed downstream of the treatment liquid application unit 30 on the transport path of the substrate 12. The treatment liquid drying unit 32 dries the pretreatment liquid applied to the printing surface of the substrate 12.

[0036] The treatment liquid drying section 32 can be configured using known heating means such as a heater, or air blowing means using air blowing such as a dryer, or a combination of these. Examples of heating means include a method in which a heating element such as a heater is placed on the side opposite the printed surface of the substrate 12, a method in which warm or hot air is applied to the printed surface of the substrate 12, or a heating method using an infrared heater, and a combination of these may also be used.

[0037] Furthermore, the temperature of the printing surface of the substrate 12 varies depending on the type of material, thickness, etc. of the substrate 12, the environmental temperature, etc. Therefore, it is preferable to provide a measurement unit that measures the temperature of the printing surface of the substrate 12 and a control mechanism that feeds back the temperature value measured by the measurement unit to the treatment liquid drying unit 32, and to dry the pretreatment liquid while controlling the temperature. A contact or non-contact thermometer is preferable as the measurement unit that measures the temperature of the printing surface of the substrate 12.

[0038] Alternatively, the solvent may be removed using a solvent removal roller, etc. In another embodiment, an air knife is used to remove excess solvent from the substrate 12.

[0039] [Image Recording Unit] An image recording unit 34 is disposed downstream of the treatment liquid drying unit 32 on the transport path of the substrate 12. The image recording unit 34 applies ink by inkjet printing to the printing surface of the substrate 12 to which the pretreatment liquid has been applied, thereby recording an image. Water-based ink is used. Water-based ink refers to ink in which a coloring material such as a dye or pigment is dissolved or dispersed in water and a water-soluble solvent. In this example, seven colors of ink are applied: black ink, cyan ink, magenta ink, yellow ink, orange ink, green ink, and violet ink.

[0040] The image recording unit 34 includes inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V, which are line heads. The inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V are arranged at regular intervals along the transport path of the substrate 12. The inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V each include a nozzle surface 38 (see FIG. 2), and are arranged so that the nozzle surface 38 faces the substrate 12. A plurality of nozzles 40 (see FIG. 2) that eject ink are arranged on the nozzle surface 38 over a length equal to or greater than the width in a direction perpendicular to the substrate transport direction (the X direction in FIG. 1).

[0041] Inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V record color images by applying water-based black ink, cyan ink, magenta ink, yellow ink, orange ink, green ink, and violet ink containing black, cyan, magenta, yellow, orange, green, and violet colorants, respectively, from nozzles 40 onto the printing surface of substrate 12. The ink applied to the printing surface of substrate 12 is coagulated by a pretreatment liquid that has been applied to the printing surface in advance.

[0042] The timing at which each of the inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V ejects ink droplets is synchronized with an encoder value obtained from a rotary encoder of the conveyance unit 20. In this way, the image recording unit 34 generates a print by a so-called single-pass method, by performing a single scan on the substrate 12 conveyed in the Y direction by the conveyance unit 20.

[0043] Here, the image recording unit 34 is configured to apply seven colors of ink: four basic color inks (black, cyan, magenta, and yellow) and three special color inks (orange, green, and violet), but other configurations are of course possible. For example, in addition to the four basic colors, different special colors such as red, green, and violet may be added, or additional colors such as black, cyan, magenta, yellow, orange, green, violet, and white may be used. Light color inks such as light cyan and light magenta may also be used.

[0044] [Inkjet head] FIG. 2 is a plan view showing the nozzle surface 38 of the inkjet head 36K. As shown in FIG. 2, a plurality of nozzles 40 are arranged on the nozzle surface 38 in the nozzle direction. In the example shown in FIG. 2, the nozzle direction is the X direction. For simplicity of illustration, FIG. 2 shows an example in which the plurality of nozzles 40 are arranged in a row in the nozzle direction. However, the plurality of nozzles 40 may be arranged two-dimensionally on the nozzle surface 38. The two-dimensionally arranged plurality of nozzles 40 essentially constitute a single nozzle row when orthogonally projected onto a straight line along a direction perpendicular to the relative movement direction between the inkjet head 36K and the substrate 12 (projected nozzle row). In this embodiment, the direction perpendicular to the relative movement direction between the inkjet head 36K and the substrate 12 (an example of an intersecting direction) is defined as the nozzle direction, and the density of the nozzles 40 in the nozzle direction is defined as the printing resolution. As an example, the printing resolution in the nozzle direction of the inkjet head 36K is 1200 dpi (dots per inch).

[0045] The inkjet heads 36C, 36M, 36Y, 36O, 36G, and 36V have the same configuration as the inkjet head 36K.

[0046] [Ink drying section] Returning to the explanation of Figure 1, an ink drying unit 42 is disposed downstream of the image recording unit 34 on the transport path of the substrate 12. The ink drying unit 42 dries the ink applied to the printing surface of the substrate 12. The ink drying unit 42 can be configured in the same manner as the treatment liquid drying unit 32.

[0047] [Imaging unit] An imaging unit 44 is disposed downstream of the ink drying unit 42 on the transport path of the substrate 12. The imaging unit 44 includes a scanner 46.

[0048] The scanner 46 is a scanner capable of acquiring scanned image data represented by image signals of red, green, and blue color components. The scanner 46 has a scanning surface 48 (see FIG. 3 ) and is disposed so that the scanning surface 48 faces the substrate 12. The scanner 46 is a line sensor in which a plurality of light receiving elements 50R, 50G, and 50B (examples of scanning pixels, see FIG. 3 ) are arranged in one direction on the scanning surface 48. The line sensor may be, for example, a charge coupled device (CCD) sensor or a complementary metal oxide semiconductor (CMOS) sensor. The scanner 46 optically scans an image printed on the substrate 12 using inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V with the plurality of light receiving elements 50R, 50G, and 50B, and generates RGB (red, green, blue) image data based on the scanned image.

[0049] 3 is a plan view showing the reading surface 48 of the scanner 46. As shown in FIG. 3, the reading surface 48 has a plurality of light receiving elements 50R for reading red images, a plurality of light receiving elements 50G for reading green images, and a plurality of light receiving elements 50B for reading blue images, each arranged in the nozzle direction (X direction). Here, the reading resolution of the scanner 46 in the nozzle direction is lower than the printing resolution of each of the inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V. As an example, the reading resolution of the scanner 46 in the nozzle direction is 300 dpi.

[0050] The imaging unit 44 may include a light source that irradiates illumination light onto the image printed on the substrate 12. The imaging unit 44 may also be arranged immediately after the image recording unit 34 on the transport path of the substrate 12, and may be configured to read the ink before it dries.

[0051] 1, a plurality of guide rollers 22 are arranged downstream of the imaging unit 44 on the transport path of the substrate 12. The substrate 12 is turned back in the transport direction by the plurality of guide rollers 22 and guided to the winding roll 16. The winding roll 16 winds the substrate 12, which is a printed material, onto a reel.

[0052] Although the inkjet printing device 10 saves space by using multiple guide rollers 22 to fold back the transport direction of the substrate 12, the substrate 12 may also be transported in a fixed direction from the delivery roll 14 to the take-up roll 16.

[0053] [Inkjet Printing Device Control System] 4 is a block diagram showing the configuration of a control system of the inkjet printing apparatus 10. The inkjet printing apparatus 10 includes a user interface 60, a storage unit 62, an integrated control unit 64, a transport control unit 66, a treatment liquid application control unit 68, a treatment liquid drying control unit 70, an image recording control unit 72, an ink drying control unit 74, an imaging control unit 76, and a defective nozzle identification device 100.

[0054] The user interface 60 includes an input unit (not shown) for the user to operate the inkjet printing apparatus 10, and a display unit (not shown) for presenting information to the user. The input unit is, for example, an operation panel that accepts input from the user. The display unit is, for example, a display that displays image data and various information. By using the user interface 60, the user can cause the inkjet printing apparatus 10 to print a desired image.

[0055] The storage unit 62 stores programs for controlling the inkjet printing apparatus 10 and information necessary for executing the programs. The storage unit 62 is configured by a non-transitory storage medium such as a hard disk (not shown) or various semiconductor memories.

[0056] The overall control unit 64 includes a processor (not shown), which performs various processes in accordance with programs stored in the storage unit 62 and performs overall control of the overall operation of the inkjet printing apparatus 10. The configuration of the processor of the overall control unit 64 is similar to that of the processor 102 (see FIG. 5) described below.

[0057] The conveyance control unit 66 controls a motor (not shown) of the conveyance unit 20 to convey the substrate 12 in the conveyance direction by the conveyance unit 20. , processing The sheet is transported in the order of the chemical liquid application unit 30, the treatment liquid drying unit 32, the image recording unit 34, the ink drying unit 42, and the imaging unit 44. The transport control unit 66 also acquires an encoder value from a rotary encoder (not shown).

[0058] The treatment liquid application control unit 68 controls the application roller and the like of the treatment liquid application unit 30 to apply the pretreatment liquid evenly to the printing surface of the substrate 12 .

[0059] The treatment liquid drying control unit 70 controls the heating means and the like of the treatment liquid drying unit 32 to dry the pretreatment liquid applied to the substrate 12 .

[0060] The image recording control unit 72 controls the ejection of ink from the inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V based on the original print data. The image recording control unit 72 causes the inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V to eject ink droplets of black, cyan, magenta, yellow, orange, green, and violet, respectively, toward the substrate 12 in synchronization with the encoder values ​​acquired via the conveyance control unit 66. As a result, a color image is printed on the printing surface of the substrate 12, and the substrate 12 becomes a "printed matter."

[0061] The image recording control unit 72 may also have a function to correct the original print data to suppress image defects caused by nozzles 40 that cannot eject ink normally (faulty nozzles). One example is a function to compensate by performing a correction process that stops ink ejection from the faulty nozzle and increases the volume of ink droplets from multiple nozzles 40 adjacent to the faulty nozzle.

[0062] The ink drying control unit 74 controls the heating means and the like of the ink drying unit 42 to dry the ink applied to the substrate 12 .

[0063] The imaging control unit 76 controls the imaging by the scanner 46, thereby causing the imaging unit 44 to read the image of the substrate 12 (printed matter). The imaging control unit 76 causes the scanner 46 to read the image printed on the substrate 12 in synchronization with the encoder value acquired via the conveyance control unit 66.

[0064] [Faulty nozzle estimation device] The defective nozzle estimation device 100 includes a defect inspection device 80. The defect inspection device 80 is a device that detects image defects in printed matter. The defective nozzle estimation device 100 is a device that estimates which of the nozzles 40 of the inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V are defective, using the image defects in the printed matter detected by the defect inspection device 80. A defective nozzle is a nozzle 40 that cannot eject ink normally, and which causes image defects.

[0065] 5 is a block diagram showing the configuration of the defective nozzle estimating device 100. As shown in FIG.

[0066] The memory 104 stores instructions to be executed by the processor 102. The processor 102 executes the instructions stored in the memory 104. The processor 102 operates in accordance with the control program and control data stored in the memory 104, and controls the defective nozzle estimation device 100 overall.

[0067] The hardware structure of the processor 102 is various processors as follows: The various processors include a CPU (Central Processing Unit), which is a general-purpose processor that executes software (programs) and functions as various processing units, a GPU (Graphics Processing Unit), which is a processor specialized for image processing, a programmable logic device (PLD), which is a processor whose circuit configuration can be changed after manufacture such as an FPGA (Field Programmable Gate Array), and a dedicated electrical circuit, which is a processor having a circuit configuration designed specifically for executing specific processing such as an ASIC (Application Specific Integrated Circuit).

[0068] Processor 102 may consist of one of these various processors, or may consist of two or more processors of the same or different types (e.g., multiple FPGAs, or a combination of a CPU and an FPGA, or a combination of a CPU and a GPU).

[0069] Furthermore, the hardware structure of these various processors is, more specifically, an electric circuit made up of a combination of circuit elements such as semiconductor elements.

[0070] As shown in FIG. 5, the processor 102 includes an imaging data acquisition unit 105, a reference data acquisition unit 106, a data comparison unit 107, an image defect position acquisition unit 108, a nozzle mapping information acquisition unit 109, a nozzle mapping correction information acquisition unit 110, a nozzle mapping information correction unit 112, and a defective nozzle candidate estimation unit 114.

[0071] The imaging data acquisition unit 105 , the reference data acquisition unit 106 , and the data comparison unit 107 constitute a defect inspection device 80 .

[0072] The imaging data acquisition unit 105 acquires imaging data based on an image of a printed matter captured by the scanner 46. The imaging data may be the captured image itself, data obtained by subjecting the captured image to image processing, or data obtained by converting the resolution of the captured image.

[0073] The reference data acquisition unit 106 acquires the original print data as reference data. The reference data acquisition unit 106 may acquire reference captured data based on a reference captured image of a reference printout captured by the scanner 46 as reference data. The reference printout is, for example, a good printout without image defects among printouts to be printed based on the original print data. The reference captured data may be the reference captured image itself, data obtained by subjecting the reference captured image to image processing, or data obtained by converting the resolution of the reference captured image. The reference data acquisition unit 106 acquires the reference data from, for example, the storage unit 62 or the memory 104.

[0074] The data comparison unit 107 detects image defects on the printed matter by comparing the image data acquired by the image data acquisition unit 105 with the reference data acquired by the reference data acquisition unit 106. Image defects include streaks and missing ink. Here, the data comparison unit 107 aligns the image data with the reference data and detects image defects on the printed matter from the difference between the aligned image data and the reference data. It is preferable to calculate the difference between the image data and the reference data after matching the resolution of the image data with the resolution of the reference data. The data comparison unit 107 may align the image data with the reference data using nozzle mapping information, which will be described later.

[0075] Furthermore, the defect inspection device 80 classifies the printed matter into good prints and bad prints according to the degree of the image defect detected by the data comparison unit 107. The inkjet printing device 10 may perform a stamping process using a stamper (not shown) on the defective prints on the substrate 12.

[0076] The image defect position acquisition unit 108 acquires the position of an image defect on a printed matter caused by a faulty nozzle in image data based on an image of the printed matter captured by the scanner 46. In the first embodiment, the image defect position acquisition unit 108 particularly acquires the position of the image defect in the nozzle direction. The data comparison unit 107 detects image defects by comparing the image data with reference data. Therefore, the image defect position acquisition unit 108 can acquire the position of the image defect in the image data from the image data and information about the image defect.

[0077] The nozzle mapping information acquisition unit 109 acquires nozzle mapping information. The nozzle mapping information is information that indicates the correspondence between the positions of the multiple nozzles 40 of each of the inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V and the pixel positions in the nozzle direction of the imaging data. In other words, the nozzle mapping information is information provided for each of the inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V. The nozzle mapping information is stored in advance in the memory 104.

[0078] The nozzle mapping correction information acquisition unit 110 acquires multiple pieces of nozzle mapping correction information for correcting the nozzle mapping information for each of the inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V. Each piece of nozzle mapping correction information is information for correcting the positional relationship between the nozzle directions of at least two of the substrate 12, a corresponding one of the inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V, and the scanner 46. For example, the nozzle mapping correction information for the inkjet head 36K is information for correcting the positional relationship between the nozzle directions of at least two of the substrate 12, the inkjet head 36K (an example of a first inkjet head), and the scanner 46.

[0079] The nozzle mapping information correction unit 112 corrects the nozzle mapping information acquired by the nozzle mapping information acquisition unit 109, using the nozzle mapping correction information acquired by the nozzle mapping correction information acquisition unit 110. For example, the nozzle mapping information correction unit 112 corrects the nozzle mapping information of the inkjet head 36K, using the nozzle mapping correction information of the inkjet head 36K.

[0080] The defective nozzle candidate estimation unit 114 uses the nozzle mapping information corrected by the nozzle mapping information correction unit 112 to estimate at least one defective nozzle candidate that is the cause of the image defect.

[0081] In the inkjet printing apparatus 10, the defective nozzle estimation device 100 is configured to include the defect inspection device 80, but the defect inspection device 80 and the defective nozzle estimation device 100 may also be provided separately.

[0082] [Nozzle mapping information] The nozzle mapping information is information that indicates the correspondence between the positions of the plurality of nozzles 40 of each of the inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V and the pixel positions in the nozzle direction of the imaging data. In other words, the nozzle mapping information is information that indicates which pixel of the imaging data, based on the captured image read by the scanner 46, is imaged as a dot ejected from which nozzle 40.

[0083] For the sake of explanation, the nozzles 40 of each of the inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V are assigned nozzle numbers 1, 2, 3, . . . in order from one end of the nozzle direction to the other.

[0084] For example, by continuously ejecting ink from nozzles 40 of the inkjet head 36K that are spaced apart sufficiently in the captured image, a black line extending in the transport direction is printed on the substrate 12. By obtaining image data by reading this line using the scanner 46 and detecting which of the light receiving elements 50R, 50G, and 50B read the printed line, it is possible to obtain, for the inkjet head 36K, the correspondence between the nozzle number of the nozzle 40 that ejected ink and each pixel of the image data.

[0085] This process is performed by discharging ink from one nozzle 40 out of every 100 nozzles 40 of inkjet head 36K, for example, to print a plurality of lines (chart) extending in the transport direction at equal intervals in the nozzle direction. By reading these lines with scanner 46, it becomes possible to estimate the positions of light-receiving elements 50R, 50G, and 50B in the image data at which the lines from each nozzle 40 of inkjet head 36K will be printed. The same applies to inkjet heads 36C, 36M, 36Y, 36O, 36G, and 36V.

[0086] The nozzle mapping information is stored, for example, as a table indicating which pixel of the imaging data corresponds to which line segment of each nozzle 40. The nozzle mapping information may also store pixel positions of the imaging data for nozzles 40 spaced at regular intervals. The nozzle mapping information stored in this manner may be converted into a linear format for use.

[0087] Furthermore, the nozzle mapping information may only hold information indicating which pixel position in the imaging data corresponds to the line segment formed by the nozzles 40 at both ends in the nozzle direction. For the nozzle mapping information held in this manner, the pixel position in the imaging data for each nozzle 40 may be interpolated, assuming that the nozzles 40 between both ends are all equally spaced.

[0088] In a single-pass inkjet printing device 10, the nozzle 40 that outputs each pixel in the nozzle direction in the reference data is always fixed. Therefore, it is possible to determine which nozzle 40 among the multiple nozzles 40 outputs the reference data. Meanwhile, it is possible to determine which pixel position in the captured data corresponds to the line segment formed by each nozzle 40 using nozzle mapping information. Therefore, it is possible to determine which pixel position in the captured data corresponds to which pixel in the nozzle direction in the reference data.

[0089] Figure 6 shows the image data D S1 and standard data D R 6 is a diagram showing an example of the relationship between the reference data D R The left end in the nozzle direction is printed by the nozzle 40 with nozzle number 2, and the right end in the nozzle direction is printed by the nozzle 40 with nozzle number 1000.

[0090] Here, the nozzle mapping information is used to generate the image data D S1 The fifth pixel corresponds to the area printed by the nozzles 40 with nozzle numbers 2 and 3, and the image data D S1It is known that the 100th pixel of the image corresponds to the area printed by the nozzles 40 with nozzle numbers 999 and 1000. For the areas between these, it is sufficient to perform interpolation to make the pixels correspond to the nozzle numbers.

[0091] In this way, by using the nozzle mapping information, the imaging data D S1 and standard data D R By creating nozzle mapping information for each of the inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V or for each ink color, it becomes possible to calculate which nozzle 40 of each of the inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V corresponds to the position in the nozzle direction (nozzle position) of the nozzle 40.

[0092] [Nozzle mapping correction information] The nozzle mapping correction information is information for correcting the nozzle mapping information, specifically, information for correcting the positional relationship of the nozzle directions of at least two of the substrate 12, one of the inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V, and the scanner 46.

[0093] The nozzle mapping correction information is, for example, information on the edge position in the nozzle direction of the substrate 12 in the imaging data. This nozzle mapping correction information is information for correcting the positional relationship between the substrate 12 and the scanner 46 in the nozzle direction, and is information for correcting the influence of meandering of the substrate 12.

[0094] The nozzle mapping correction information acquisition unit 110 detects the edges of the substrate 12 from the image data, calculates the difference between the edge position when the nozzle mapping information was acquired and the edge position during printing (when estimating defective nozzles), and generates nozzle mapping correction information for correcting the effects of meandering of the substrate 12. The nozzle mapping information correction unit 112 corrects the nozzle mapping information using this nozzle mapping correction information, making it possible to estimate the nozzle positions of the inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V regardless of the effects of meandering of the substrate 12.

[0095] Figure 7 shows the image data D when the nozzle mapping information was acquired. S1 and the image data D when estimating the defective nozzle S2 7 is a diagram showing an example of the relationship between the image data D S2 The edge position of the substrate 12 is represented by the image data D S1 The nozzle mapping correction information is shifted by three pixels in the −X direction from the edge position of the substrate 12. Therefore, the nozzle mapping correction information is information that corrects the nozzle mapping information by −3 pixels.

[0096] The nozzle mapping information corrector 112 corrects the nozzle mapping information using this nozzle mapping correction information.

[0097] FIG. 8 shows the image data D based on the corrected nozzle mapping information. S2 and standard data D R As shown in FIG. 8, the corrected nozzle mapping information is used to calculate the image data D S2 The second pixel of the image data D corresponds to the area printed by the nozzles 40 with nozzle numbers 2 and 3. S2 It can be seen that the 97th pixel corresponds to the area printed by the nozzles 40 with nozzle numbers 999 and 1000.

[0098] The nozzle mapping correction information for correcting the effects of meandering of the substrate 12 may, of course, be based on information other than the edge position of the substrate 12. For example, in the case of a transparent substrate, for which it is difficult to obtain the edge position, ink may be ejected from one nozzle 40 (an example of a specific nozzle) at the left or right end of each of the inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V to form a line segment extending in the transport direction on the substrate 12, and information on the nozzle direction position of the formed line segment (an example of the nozzle direction position on the print medium) may be used. The nozzle mapping correction information can be generated by calculating the difference between the nozzle direction position of the line segment when the nozzle mapping information is obtained and the nozzle direction position of the line segment when the defective nozzle is estimated. The nozzle mapping correction information in this case also corrects the nozzle direction positional relationship between the substrate 12 and the scanner 46. Using this nozzle mapping correction information makes it possible to correct the effects of meandering of the substrate 12, as in the case of the substrate edge.

[0099] Furthermore, meandering correction may be performed based on the meandering information. For example, inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V may be moved by the amount of meandering, or the original print data may be shifted for printing. When performing meandering correction, marks such as registration marks are output at the edge of the printout outside the image area, measurements for meandering correction are performed, and the movement amounts of inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V and the shift amount of the original print data are determined and corrected. In this case, the correction amounts can be used as nozzle mapping correction information. In this case, the nozzle mapping correction information is information that corrects the positional relationship in the nozzle direction between the substrate 12 and each of the inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V, and information that corrects the positional relationship in the nozzle direction between each of the inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V and the scanner 46.

[0100] The nozzle mapping correction information may be information for correcting the nozzle mapping information according to the thickness of the substrate 12. Because the distance between the scanner 46 and the guide roller 22 is constant, the distance between the scanner 46 and the printed surface of the substrate 12 varies depending on the thickness of the substrate 12. Therefore, when the scanner 46 reads a printed matter printed on the substrate 12, differences in the thickness of the substrate 12 cause a slight deviation from the focal length of the scanner 46, resulting in scaling within the captured data. Since scaling of the captured data causes deviations in the nozzle mapping information, the nozzle mapping information correction unit 112 corrects the nozzle mapping information according to the thickness of the substrate 12, enabling more accurate alignment. In this case, the nozzle mapping correction information is information for correcting the positional relationship between the substrate 12 and the scanner 46 in the nozzle direction.

[0101] The nozzle mapping information acquisition unit 109 may be configured to acquire a plurality of pieces of nozzle mapping information according to the thickness of the substrate 12. The plurality of pieces of nozzle mapping correction information according to the thickness of the substrate 12 is information for correcting the positional relationship between the substrate 12 and the scanner 46 in the nozzle direction.

[0102] As a specific example, to determine the correspondence between the position of each nozzle 40 during printing and the pixel position in the nozzle direction of the image data, a chart in which only specific nozzles 40 eject ink or a chart in which only specific nozzles 40 do not eject ink is printed on the substrate 12, and when the printed chart is read by the scanner 46, the position in the image data where the ink dots ejected from the specific nozzles 40 appear is calculated, and nozzle mapping information, which is the correspondence between the position of the nozzles 40 and the pixel position in the nozzle direction of the image data, is calculated. This calculation is performed for each thickness of the substrate 12, and multiple pieces of nozzle mapping information are stored, and the nozzle mapping information is switched depending on the thickness of the substrate 12 when inspection is performed. This switching makes it possible to deal with slight deviations in the correspondence due to the thickness of the substrate 12.

[0103] The process in which the nozzle mapping information acquisition unit 109 acquires a plurality of pieces of nozzle mapping information according to the thickness of the substrate 12 is included in the concept of correcting the nozzle mapping information according to the thickness of the substrate 12.

[0104] [Method for estimating defective nozzles] 9 is a flowchart showing the processing of the faulty nozzle estimation method by the faulty nozzle estimation device 100. The faulty nozzle estimation method is stored in memory 104 as a faulty nozzle estimation program to be executed by a computer, and is realized when the processor 102 executes the faulty nozzle estimation program.

[0105] In step S1 (an example of an imaging data acquisition step), the imaging data acquisition unit 105 of the processor 102 acquires imaging data based on an image of a printed matter captured by the scanner 46 via the general control unit 64.

[0106] In step S2 (an example of a reference data obtaining step), the reference data obtaining unit 106 obtains original print data or reference captured data as reference data.

[0107] In step S3 (an example of an image defect position acquisition step), the data comparison unit 107 of the processor 102 detects image defects on the printed matter by comparing the imaging data acquired in step S1 with the reference data acquired in step S2. Furthermore, the image defect position acquisition unit 108 of the processor 102 acquires the nozzle direction position of the image defect on the printed matter in the imaging data.

[0108] In step S4 (an example of a nozzle mapping information acquisition step), the nozzle mapping information acquisition unit 109 acquires the nozzle mapping information from the memory 104.

[0109] In step S5 (an example of a nozzle mapping correction information acquisition step), the nozzle mapping correction information acquisition unit 110 acquires nozzle mapping correction information. Here, the nozzle mapping correction information is information about the edge position of the substrate 12 in the nozzle direction in the imaging data. The nozzle mapping correction information acquisition unit 110 acquires the imaging data via the overall control unit 64, and detects the edge position of the substrate 12 from the imaging data. The nozzle mapping correction information acquisition unit 110 also acquires information about the edge position when the nozzle mapping information was acquired. The information about the edge position when the nozzle mapping information was acquired is stored in, for example, the memory 104. Furthermore, the nozzle mapping correction information acquisition unit 110 calculates the difference between the edge position of the substrate 12 acquired from the imaging data and the edge position when the nozzle mapping information was acquired, and generates the nozzle mapping correction information.

[0110] In step S6 (an example of a nozzle mapping information correcting step), the nozzle mapping information corrector 112 corrects the nozzle mapping information acquired in step S4 using the nozzle mapping correction information acquired in step S5.

[0111] In step S7 (an example of a defective nozzle candidate estimation process), the defective nozzle candidate estimation unit 114 uses the nozzle mapping information corrected in step S6 to calculate the position in the nozzle direction of the image defect acquired in step S3, and estimates the position of at least one defective nozzle candidate that is the cause of the image defect from each of the nozzles 40 of inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V.

[0112] When the substrate 12, which is roll paper, is transported, if the substrate 12 deforms due to application and drying of ink, if the distance between the image recording unit 34 and the imaging unit 44 increases, or if the substrate 12 meanders due to a local deterioration in the transport accuracy of the transport unit 20, the nozzle mapping information will be shifted due to the influence of the meandering. If a shift occurs, it will affect the accuracy of estimating the position of the faulty nozzle, and there is a possibility that the correct faulty nozzle position will not be included in the estimated candidates for the faulty nozzle position.

[0113] Therefore, the inkjet printing device 10 detects the edge of the substrate 12, calculates the difference between the edge position of the substrate 12 when the nozzle mapping information was acquired and the edge position of the substrate 12 during printing, generates nozzle mapping correction information to correct for the effect of meandering, and performs the correction. This makes it possible to estimate the nozzle position regardless of the effect of meandering of the substrate 12. By creating nozzle mapping information and nozzle mapping correction information for each inkjet head 36C, 36M, 36Y, 36O, 36G, and 36V or for each ink color, it becomes possible to calculate which nozzle position of inkjet heads 36C, 36M, 36Y, 36O, 36G, and 36V corresponds to an image defect. This improves the accuracy of nozzle estimation and reduces waste.

[0114] <Second embodiment> An inkjet printing apparatus according to a second embodiment will be described. Note that parts common to the inkjet printing apparatus 10 according to the first embodiment are given the same reference numerals, and detailed description thereof will be omitted.

[0115] [Faulty nozzle estimation device] The inkjet printing apparatus 10 according to the second embodiment includes a defective nozzle estimation device 120. The defective nozzle estimation device 120 is a device that estimates the color of ink ejected by a defective nozzle among the nozzles 40 of the inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V (inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V that have a defective nozzle) using image defects in a printed matter detected by the defect inspection device 80.

[0116] Fig. 10 is a block diagram showing the configuration of the faulty nozzle estimation device 120. As shown in Fig. 10, the processor 102 of the faulty nozzle estimation device 120, like the faulty nozzle estimation device 100, comprises an imaging data acquisition unit 105, a reference data acquisition unit 106, a data comparison unit 107, and an image defect position acquisition unit 108. Furthermore, the processor 102 of the faulty nozzle estimation device 120 comprises a pixel value acquisition unit 126 and a faulty nozzle candidate estimation unit 114.

[0117] The pixel value acquisition unit 126 acquires the amount of variation in pixel values ​​of the imaging data at the position of the image defect. The amount of variation is expressed as the difference between a first pixel value of the imaging data at the position of the image defect and a second pixel value of the reference data at a position corresponding to the position of the image defect. Here, the position corresponding to the position of the image defect in the reference data refers to the same position as the position of the image defect in the imaging data in the reference data aligned with the imaging data.

[0118] Here, the pixel value acquisition unit 126 acquires the first pixel value and the second pixel value and calculates the difference between them. The pixel value acquisition unit 126 may acquire the first pixel value and the second pixel value by aligning the imaging data with the reference data. The alignment between the imaging data and the reference data may be performed using the nozzle mapping information of the first embodiment.

[0119] Furthermore, the defective nozzle candidate estimation unit 114 includes a learning model 128. The learning model 128 is a trained model that outputs the ink color of a defective nozzle when at least the amount of variation in pixel values ​​of the imaging data at the position of the image defect is given as input. The learning model 128 is configured, for example, by a neural network. In this case, the learning model 128 is a trained model that outputs the ink color of a defective nozzle when the amount of variation in pixel values ​​of the imaging data at the position of the image defect and the pixel value of the reference data at a position corresponding to the position of the image defect are given as input.

[0120] The pixel values ​​of the reference data input to the learning model 128 are values ​​with the same resolution as the resolution of the captured image data. Therefore, if the print resolution of the reference data is higher than the read resolution of the captured image data, the pixel values ​​of the reference data are set to the average value of the pixel values ​​in the nozzle direction of the area including the image defect. For example, if the reference data is original print data, and the print resolution is 1200 dpi and the read resolution is 300 dpi, the pixel values ​​of the reference data are set to the average value of the area of ​​four adjacent nozzles including the image defect.

[0121] The learning model 128 is generated by learning learning data that is a set of the amount of variation in pixel values ​​of the imaging data at the position of an image defect caused by a known defective nozzle 40, the pixel value of the reference data at the position of the image defect, and the color of ink of the defective nozzle 40. The learning model 128 may also be generated by learning learning data that is a set of the amount of variation in pixel values ​​of the imaging data at the position of a pseudo image defect created by a nozzle 40 that does not eject ink, the pixel value of the reference data at the position of the pseudo image defect, and the color of ink of the nozzle 40 that does not eject ink. The learning data may also be acquired from the amount of variation in pixel values ​​of the imaging data of a halftone image in which the application of a specific color of ink is switched on and off instead of the pseudo image defect.

[0122] The amount of variation can be obtained as the difference between the first pixel value and the second pixel value. The pixel value of the reference data at a position corresponding to the position of the image defect is the second pixel value. Therefore, the learning model 128 may be a trained model that receives the first pixel value and the second pixel value as input and outputs the color of ink from a defective nozzle. In this case, the learning model 128 is generated by learning learning data that includes, for example, a set of pixel values ​​of the imaging data at the position of an image defect caused by a known defective nozzle 40, pixel values ​​of the reference data, and the color of ink from the defective nozzle 40.

[0123] The defective nozzle candidate estimation unit 114 inputs the amount of variation in pixel values ​​of the captured data at the position of the image defect into the learning model 128, and causes it to estimate at least one defective nozzle candidate that is the cause of the image defect in the printed product.

[0124] [Method for estimating defective nozzles] FIG. 11 is a flowchart showing the process of the defective nozzle estimation method performed by the defective nozzle estimation device 120.

[0125] In step S11, the imaging data acquisition unit 105 of the processor 102 acquires, via the general control unit 64, imaging data based on an image of a printed matter captured by the scanner 46.

[0126] In step S12 (an example of a reference data obtaining step), the reference data obtaining unit 106 obtains original print data or reference captured data as reference data.

[0127] In step S13 (an example of an image defect position acquisition step), the data comparison unit 107 detects image defects on the printed matter by comparing the imaging data acquired in step S11 with the reference data acquired in step S12. Furthermore, the image defect position acquisition unit 108 acquires the nozzle direction position of the image defect on the printed matter in the imaging data.

[0128] In step S14 (an example of a first pixel value acquisition step and an example of a second pixel value acquisition step), the pixel value acquisition unit 126 acquires the amount of variation in the pixel value of the imaging data at the position of the image defect. Here, the pixel value acquisition unit 126 acquires a first pixel value of the imaging data at the position of the image defect and a second pixel value of the reference data at a position corresponding to the position of the image defect, and calculates the amount of variation.

[0129] Step S15 (Faulty nozzle candidate estimation) process In one example of (a), the defective nozzle candidate estimation unit 114 estimates the color of at least one defective nozzle candidate that is the cause of the image defect in the printed matter from the amount of variation in pixel values ​​of the imaging data at the position of the image defect, using the learning model 128. Here, the defective nozzle candidate estimation unit 114 inputs the amount of variation calculated in step S14 and the second pixel value acquired in step S14 into the learning model 128, causing it to estimate the color of ink in the defective nozzle.

[0130] When printing using seven colors of ink (black ink, cyan ink, magenta ink, yellow ink, orange ink, green ink, and violet ink) as in this embodiment, it is difficult to narrow down the seven colors to one from the three RGB channel output signals of the scanner 46, and there is a problem in that the number of estimated candidate ink colors for the defective nozzle also increases. In contrast, according to this embodiment, the candidate colors can be narrowed down by using the learning model 128.

[0131] Generally, as the number of colors increases, it becomes difficult to narrow down the color of a defective nozzle from the image data of a typical three-channel imaging device with red, green, and blue color components, and complex algorithms are required. Furthermore, an algorithm must be created for each color combination used, which takes a great deal of time to design and adjust the algorithm.

[0132] However, by using a learning model 128 that collects and learns data on the amount of fluctuation in pixel values ​​when a nozzle 40 of each color ink becomes defective, it is possible to significantly reduce the amount of work required to create an algorithm, and also to create an algorithm with high performance.

[0133] Furthermore, although the present embodiment presents an example of estimating colors using the learning model 128, color matching may also be used to determine color by referencing pixel values ​​at defect locations in the captured image data. For example, if a large variation in the blue pixel value is detected among red, green, and blue pixel values, it is possible to narrow down the color candidates to gray, yellow, and orange because the image defect occurs when yellow-based ink has a large impact on the blue pixel value. Furthermore, it is also possible to make a judgment based on multiple pixel values ​​among the red, green, and blue pixel values. For example, if all red, green, and blue pixel values ​​are affected, it is possible to narrow down the color candidates to black and white, and if the impact on red and blue pixel values ​​is dominant, it is possible to narrow down the color candidates to violet.

[0134] By further performing color matching estimation on the output of the learning model 128, it becomes possible to estimate the color of the defective nozzle candidate with high accuracy.

[0135] In this example, the scanner 46 has red, green, and blue channels, but other color channels may be used. Also, if a spectrophotometric camera is used, more accurate color estimation can be achieved.

[0136] <Third embodiment> An inkjet printing apparatus according to a third embodiment will be described. Note that parts common to the inkjet printing apparatus 10 according to the first and second embodiments are given the same reference numerals, and detailed description thereof will be omitted.

[0137] [Faulty nozzle estimation device] The inkjet printing apparatus 10 according to the third embodiment includes a defective nozzle estimating device 130.

[0138] FIG. 12 shows the defective nozzle estimation device 1 3 12 is a block diagram showing the configuration of the defective nozzle estimation device 1. 3 The processor 102 of FIG. 0 includes an imaging data acquisition unit 105, a reference data acquisition unit 106, a data comparison unit 107, an image defect position acquisition unit 108, a nozzle mapping information acquisition unit 109, a nozzle mapping correction information acquisition unit 110, a nozzle mapping information correction unit 112, a faulty nozzle candidate estimation unit 114, and a pixel value acquisition unit 126. The faulty nozzle candidate estimation unit 114 also includes a learning model 128.

[0139] [Method for estimating defective nozzles] FIG. 13 is a flowchart showing the process of the defective nozzle estimation method performed by the defective nozzle estimation device 130.

[0140] In Fig. 13, the processes of steps S1 to S7 are the same as those of the first embodiment described using Fig. 9. By the processes of steps S1 to S7, the position of the defective nozzle candidate in the nozzle direction can be estimated.

[0141] In Fig. 13, the processes of steps S1 to S3 and steps S14 to S15 are the same as those of the second embodiment described with reference to Fig. 11. The processes of steps S1 to S3 and steps S14 to S15 make it possible to estimate the color of the candidate faulty nozzle.

[0142] As described above, by narrowing down the defective nozzle position candidates and color candidates, the final defective nozzle candidates can be narrowed down to "number of nozzle position candidates x number of color candidates."

[0143] Here, candidate nozzle positions for defective nozzles are estimated before candidate colors are estimated, but candidate nozzle positions may be estimated after candidate colors are estimated.

[0144] <Fourth embodiment> [Method for producing printed matter] 14 is a flowchart showing the processing of a method for producing a printed matter. The method for producing a printed matter is stored in the storage unit 62 as a printed matter production program to be executed by a computer, and is realized by the processor of the integrated control unit 64 executing the printed matter production program. In this embodiment, an example will be described in which, when there are multiple estimated defective nozzle candidates, a correction process is performed to suppress image defects caused by the defective nozzle candidates and identify the defective nozzle.

[0145] In step S21 (an example of a print source data obtaining step), the central control unit 64 obtains the print source data of the printout from the storage unit 62.

[0146] In step S22 (an example of a printing step), the integrated control unit 64 prints a printed matter based on the original print data acquired in step S1. That is, the image recording control unit 72 ejects ink droplets from the nozzles 40 of the inkjet heads 36K, 36C, 36M, 36Y, 36O, 36G, and 36V toward the substrate 12 based on the original print data, in synchronization with the encoder value acquired via the conveyance control unit 66.

[0147] In step S23 (an example of an imaging data acquisition step), the integrated control unit 64 controls the imaging control unit 76 to acquire imaging data of the printed material to be inspected for defects from the scanner 46. That is, the imaging control unit 76 causes the scanner 46 to read the image printed on the substrate 12 in synchronization with the encoder value acquired via the conveyance control unit 66. The imaging data acquisition unit 105 acquires the image read by the scanner 46 as imaging data.

[0148] In step S24 (an example of an image defect detection process), the data comparison unit 107 detects image defects in the print by comparing the captured image data with the original print data. The data comparison unit 107 may also detect image defects in the print by comparing the captured image data with previously acquired reference data.

[0149] In step S25, the defect inspection device 80 determines whether or not there is an image defect in the printed matter based on the detection result in step S24.

[0150] If it is determined that the printed matter has an image defect, the inkjet printing apparatus 10 performs the process of step S26. In step S26 (an example of a defective nozzle estimation process), the defective nozzle estimation device 100 estimates the defective nozzle. The defective nozzle estimation is performed, for example, by the process of the flowchart shown in FIG.

[0151] The process of step S1 in the flowchart shown in Fig. 13 is the same as the process of step S23 in the flowchart shown in Fig. 14, and may be omitted here. Also, when the original print data is used as the reference data, the process of step S2 in the flowchart shown in Fig. 13 is the same as the process of step S21 in the flowchart shown in Fig. 14, and may be omitted here.

[0152] Once the estimation of the defective nozzles is complete, in step S27 (an example of a correction process), the inkjet printing apparatus 10 performs a correction process on the defective nozzles. The correction process will be described in detail later.

[0153] If it is determined in step S25 that there are no image defects in the printed matter, or if correction processing has been performed in step S27, the process proceeds to step S28. In step S28, the central control unit 64 determines whether printing has finished. If printing of all printed matter has finished, the process of this flowchart ends. If printing is to continue, the process proceeds to step S22, and the same process is repeated.

[0154] [Correction Processing] FIG. 15 is a flowchart showing the details of the correction process in step S27 of the flowchart shown in FIG.

[0155] In step S31, the integrated control unit 64 selects a first defective nozzle candidate, which is at least one of the defective nozzle candidates estimated in step S26.

[0156] In step S32, the integrated control unit 64 controls the image recording control unit 72 to generate first corrected original print data that has been subjected to a first correction process that suppresses image defects caused by the first defective nozzle candidate 40 selected in step S31. The first correction process is, for example, a process that stops ink ejection from the first defective nozzle candidate 40 and increases the amount of ink ejection from the nozzle 40 adjacent to the first defective nozzle candidate.

[0157] In step S33, the central control unit 64 causes the first corrected printout to be printed using the first corrected original print data that has been subjected to the first correction process.

[0158] In step S34, the imaging data acquisition unit 105 acquires first corrected imaging data based on the first corrected imaging image obtained by the scanner 46 reading the first corrected printed matter printed in step S33.

[0159] In step S35, the data comparison unit 107 detects image defects in the first corrected print by comparing the first corrected captured data acquired in step S34 with the first corrected original print data generated in step S32.

[0160] In step S36, the defect inspection device 80 determines whether or not there is an image defect in the first corrected printed product. If it is determined that there is an image defect in the first corrected printed product, the process returns to step S31, and the integrated control unit 64 selects a second faulty nozzle candidate, which is at least one of the faulty nozzle candidates estimated in step S26. The second faulty nozzle candidate is a faulty nozzle candidate different from the first faulty nozzle candidate.

[0161] In step S32, the integrated control unit 64 controls the image recording control unit 72 to generate second corrected original print data that has undergone a second correction process to suppress image defects caused by the second defective nozzle candidate 40 selected in step S31. The second correction process is, for example, a process that stops ink ejection from the second defective nozzle candidate 40 and increases the ink ejection amount from the nozzle 40 adjacent to the second defective nozzle candidate. Here, the first defective nozzle candidate is treated as a normal nozzle 40, and the first correction process is not performed on it.

[0162] Thereafter, steps S33 to S35 are performed using the second corrected original print data. That is, in step S33, the central control unit 64 causes a second corrected printout to be printed using the second corrected original print data that has been subjected to the second correction process. In step S34, the image data acquisition unit 105 acquires second corrected image data based on the second corrected image obtained by the scanner 46 reading the second corrected printout printed in step S33. In step S35, the data comparison unit 107 compares the second corrected image data acquired in step S34 with the second corrected original print data generated in step S32 to detect image defects in the second corrected printout.

[0163] Then, if it is determined in step S36 that there is an image defect in the second corrected print, the process returns to step S31 again. In step S31, the integrated control unit 64 selects a third faulty nozzle candidate that is at least one of the faulty nozzle candidates estimated in step S26, and that is different from the first faulty nozzle candidate and the second faulty nozzle candidate. The processes of steps S32 to S36 are then performed on the third faulty nozzle candidate. Here, the first faulty nozzle candidate and the second faulty nozzle candidate are treated as normal nozzles 40, and the first correction process and the second correction process are not performed.

[0164] If it is determined in step S36 that there are no image defects, the process proceeds to step S38. In step S38, the integrated control unit 64 identifies the defective nozzle candidate currently undergoing correction processing as a defective nozzle and confirms the correction processing. Next, the process proceeds to step S28 in the flowchart shown in FIG. 14. In the subsequent printing process in step S22, printing is performed using the corrected original print data at that time.

[0165] The processing of this flowchart may be performed by the defective nozzle estimation device 100.

[0166] 16 to 18 are diagrams for explaining the correction process according to the fourth embodiment, and are diagrams showing an outline of the substrate 12 being transported through the image recording unit 34 and the imaging unit 44. FIG.

[0167] 16, 1000 indicates a defective printed matter P D This shows how defective print P D The substrate 12 downstream of the conveying path is printed with a defect-free print P G 1002 shown in FIG. 16 is the first defective printed matter P D 4 shows the state in which the light has reached the imaging unit 44.

[0168] 1004 shown in FIG. 17 is a diagram for illustrating a process for producing a first corrected print P using the first corrected original print data that has been subjected to the first correction process. C1The first corrected printed matter P C1 The substrate 12 downstream of the conveying path has a defective printed matter P D 1006 shown in FIG. 17 is the first corrected print P C1 4 shows the state in which the light has reached the imaging unit 44.

[0169] First corrected print P C1 If there is no image defect in the first corrected original print data, the nozzle 40 of the first defective nozzle candidate is identified as the defective nozzle. C1 On the other hand, the first corrected print P C1 If there is an image defect in the second corrected print P, the second corrected print P is produced using the second corrected original print data that has been subjected to the second correction process. C2 Start printing.

[0170] 1008 shown in FIG. 18 is a second corrected print P C2 The second corrected print P C2 The substrate 12 downstream of the conveyance path is provided with the first corrected printed matter P C1 1010 shown in FIG. 18 is the second corrected print P C2 4 shows the state in which the light has reached the imaging unit 44.

[0171] Second corrected print P C2 If there is no image defect in the second corrected original print data, the nozzle 40 of the second defective nozzle candidate is identified as the defective nozzle. C2 On the other hand, the second corrected print P C2 If there is a defect in the nozzle 40, printing of the third corrected print is started using the third corrected print original data that has been subjected to the third correction process. Thereafter, the correction process is performed sequentially on the nozzles 40 that are candidate for defective nozzles until a print without defects is printed.

[0172] When there are many candidate defective nozzles, it takes time to correct the correct defective nozzle, which can lead to a problem of increased substrate 12 waste. According to this embodiment, correction processing is performed sequentially on multiple candidate defective nozzles 40, and the corrected printout is inspected for image defects. If the true defective nozzle is corrected, the image defect is corrected and a normal image is printed. Therefore, when the image defect disappears in the inspection results, it is possible to identify the corrected candidate defective nozzle as the true defective nozzle. Therefore, it is possible to reduce waste of the substrate 12 until the defective nozzle is corrected.

[0173] <Fifth embodiment> [Correction Processing] FIG. 19 is a flowchart showing the details of the correction process in step S27 of the flowchart shown in FIG.

[0174] In step S41, the integrated control unit 64 selects a first defective nozzle candidate, which is at least one of the defective nozzle candidates estimated in step S26.

[0175] In step S42, the integrated control unit 64 controls the image recording control unit 72 to generate first corrected original print data that has been subjected to a first correction process that suppresses image defects caused by the first defective nozzle candidate 40 selected in step S41. As in the fourth embodiment, the first correction process is a process that, for example, stops ink ejection from the first defective nozzle candidate 40 and increases the amount of ink ejection from the nozzle 40 adjacent to the first defective nozzle candidate.

[0176] In step S43, the central control unit 64 causes the first corrected printout to be printed using the first corrected original print data that has been subjected to the first correction process.

[0177] In step S44, the integrated control unit 64 determines whether or not all of the defective nozzle candidates estimated in step S26 have been selected. If all of the candidates have not been selected, the process returns to step S41 and the same processing is repeated.

[0178] That is, in step S41, the central control unit 64 selects a second faulty nozzle candidate different from the first faulty nozzle candidate, generates second corrected original print data that has been subjected to a second correction process that suppresses image defects caused by the nozzle 40 of the second faulty nozzle candidate, and causes the printer to print a second corrected printed material using the second corrected original print data. Subsequently, the central control unit 64 repeats the process for the third faulty nozzle candidate, the fourth faulty nozzle candidate, ..., etc. In this way, the central control unit 64 performs the correction process that suppresses image defects caused by a faulty nozzle candidate selected from the multiple faulty nozzle candidates multiple times so that each of the multiple faulty nozzle candidates is selected at least once, and causes the printer to print multiple corrected printed materials using the multiple corrected print data obtained by the multiple correction processes.

[0179] If it is determined in step S44 that all of the faulty nozzle candidates have been selected, the process proceeds to step S45. In step S45, the faulty nozzle estimating device 100 acquires first through n-th corrected captured data based on the first through n-th corrected captured images read by scanner 46, respectively, of the first, second, third, ..., n-th corrected printed matter printed in step S43.

[0180] In step S46, the defective nozzle estimation device 100 detects image defects in the first to nth corrected prints, respectively, by comparing the first to nth corrected imaging data acquired in step S45 with the first to nth corrected original printing data generated in step S42.

[0181] In step S47, the defective nozzle estimation device 100 determines whether or not there are image defects in the first corrected print to the nth corrected print, and identifies as defective nozzles candidate defective nozzles for which the corrected original print data of corrected prints without image defects has undergone correction processing, and in the subsequent printing process of step S22, printing is performed using that corrected original print data.

[0182] The processing of this flowchart may be performed in the defect inspection device 80.

[0183] 20 is a diagram for explaining the correction process according to the fifth embodiment, and is a diagram showing an outline of the substrate 12 being transported through the image recording unit 34 and the imaging unit 44. In FIG. 20, the first corrected print P is produced using the first corrected print original data to the nth corrected print original data that have been subjected to the first correction process to the nth correction process, respectively. C1 ~ 5th Correction Print P C5 The figure shows how to print the above.

[0184] The defective nozzle estimation device 100 generates a first corrected print P C1 ~ 5th Correction Print P C5 By inspecting the image data read in order by the scanner 46, a corrected printout without image defects can be obtained.

[0185] As described above, by printing multiple corrected printouts in which correction processing has been performed at least once on multiple candidate defective nozzle nozzles 40 and inspecting the image defects of the multiple corrected printouts, it is possible to identify the true defective nozzles among the candidate defective nozzles. Therefore, it is possible to reduce waste of the substrate 12 until the defective nozzles are corrected.

[0186] <Other> Although an example of a printing device that prints on a roll-shaped substrate 12 has been described here, the present invention is also applicable to a printing device that prints on a sheet-shaped printing medium.

[0187] The technical scope of the present invention is not limited to the scope described in the above embodiments. The configurations and the like in each embodiment can be appropriately combined with each other within the scope that does not deviate from the spirit of the present invention. [Explanation of symbols]

[0188] 10...Inkjet printing device 12...Base material 14...Feed roll 16...Winding roll 20...Transport unit 22...Guide roller 30...Processing liquid application section 32... Processing liquid drying section 34...Image recording unit 36C...inkjet head 36G...inkjet head 36K...inkjet head 36M...inkjet head 36O...Inkjet head 36Y...inkjet head 38...Nozzle surface 40...Nozzle 42...Ink drying section 44...imaging unit 46...Scanner 48...Reading surface 50B...Photodetector 50G...Photodetector 50R...Photodetector 60...User Interface 62...Storage section 64...General control unit 66...Transport control unit 68... Treatment liquid application control section 70... Processing liquid drying control unit 72...Image recording control unit 74...Ink drying control unit 76...imaging control unit 80...Defect inspection device 100...Faulty nozzle estimation device 102...Processor 104...Memory 105...imaging data acquisition unit 106...Reference data acquisition unit 107...Data comparison section 108...Image defect position acquisition unit 109...Nozzle mapping information acquisition unit 110...Nozzle mapping correction information acquisition unit 112...Nozzle mapping information correction unit 114...Faulty nozzle candidate estimation unit 120...Faulty nozzle estimation device 126...Pixel value acquisition unit 128…Learning Model 130...Faulty nozzle estimation device D R …reference data D S1 ...imaging data D S2 ...imaging data P C1 ~P C5 ...1st corrected print to 5th corrected print P D ...Defective printouts P G ...defect-free print S1 to S7, S11 to S15... Each step of the defective nozzle estimation method S21 to S28: Each step in the manufacturing process for printed matter S31 to S38, S41 to S47... Each step of the correction process

Claims

1. a single-pass printing device that includes an inkjet head having a plurality of nozzles arranged in a nozzle direction, a scanner having a plurality of reading pixels arranged in the nozzle direction, and a relative movement mechanism that moves the inkjet head, the scanner, and a printing medium relative to each other in a relative movement direction that intersects with the nozzle direction, and that prints a printed material on the printing medium by ejecting ink from the nozzles of the inkjet head based on original print data, and that reads the printed material with the reading pixels of the scanner, the single-pass printing device estimating a defective nozzle of the inkjet head, at least one processor; at least one memory storing instructions for execution by said at least one processor; Equipped with The at least one processor acquiring imaging data based on an image of the printed matter captured by the scanner; acquiring reference image data based on the original print data or a reference image of a reference print captured by the scanner as reference data; By comparing the imaging data with the reference data, the position in the nozzle direction of the image defect in the printed matter caused by the faulty nozzle in the imaging data is obtained; acquiring nozzle mapping information, which is a correspondence relationship between the positions of the plurality of nozzles and pixel positions in the nozzle direction of the imaging data, and which is stored in advance in the at least one memory; acquiring nozzle mapping correction information for correcting a positional relationship in the nozzle direction between at least two of the print medium, the inkjet head, and the scanner; correcting the nozzle mapping information using the nozzle mapping correction information; using the corrected nozzle mapping information to estimate at least one candidate defective nozzle that is the cause of the image defect in the printed product; Faulty nozzle estimation device.

2. the nozzle mapping correction information includes information on an edge position of the printing medium in the nozzle direction in the imaging data; The defective nozzle estimation device according to claim 1 .

3. the nozzle mapping correction information includes information on a position on the printing medium in the nozzle direction of ink ejected from a specific nozzle of the inkjet head in the imaging data; The defective nozzle estimation device according to claim 1 or 2.

4. the nozzle mapping correction information includes information about the thickness of the print medium; The defective nozzle estimation device according to claim 1 .

5. The at least one processor When there are a plurality of estimated defective nozzle candidates, a first correction process is performed to suppress image defects caused by a first defective nozzle candidate, which is at least one of the plurality of defective nozzle candidates, and a first corrected printout is printed, and first corrected captured data is acquired based on a first corrected captured image captured by the scanner; determining whether the first defective nozzle candidate is a defective nozzle based on the first corrected imaging data; The defective nozzle estimation device according to claim 1 .

6. The at least one processor If it is determined that the first faulty nozzle candidate is not a faulty nozzle, a second faulty nozzle candidate that is at least one of the plurality of faulty nozzle candidates, and that is different from the first faulty nozzle candidate, is subjected to a second correction process to suppress image defects caused by the second faulty nozzle candidate, and a second corrected printed product is printed, and second corrected captured data is acquired based on a second corrected captured image captured by the scanner; determining whether the second defective nozzle candidate is a defective nozzle based on the second corrected imaging data; The defective nozzle estimation device according to claim 5 .

7. When there are a plurality of the estimated defective nozzle candidates, the at least one processor a correction process for suppressing image defects caused by a faulty nozzle candidate selected from the plurality of faulty nozzle candidates is performed a plurality of times so that each of the plurality of faulty nozzle candidates is selected at least once; a plurality of corrected prints printed using the plurality of corrected print data obtained by the plurality of correction processes are printed using the plurality of corrected print data, and a plurality of corrected captured images are acquired by the scanner, and a plurality of corrected captured data is acquired based on the plurality of corrected captured images. determining whether or not each of the plurality of defective nozzle candidates is a defective nozzle based on the plurality of corrected imaging data; The defective nozzle estimation device according to claim 1 .

8. the printing device includes a plurality of inkjet heads; the at least one processor obtains nozzle mapping information for each of the plurality of inkjet heads. The defective nozzle estimation device according to claim 1 .

9. The defective nozzle estimation device according to any one of claims 1 to 8, an inkjet head having a plurality of nozzles arranged in the nozzle direction; a scanner in which a plurality of reading pixels are arranged in the nozzle direction; a relative movement mechanism that moves the inkjet head and the scanner relative to the print medium in the relative movement direction; Equipped with A printing device that prints a printed material on the printing medium by ejecting ink from the nozzles of the inkjet head based on original printing data onto the printing medium that is moved relatively in the relative movement direction, and reads the printed material with the reading pixels of the scanner.

10. a single-pass printing device that includes an inkjet head having a plurality of nozzles arranged in a nozzle direction, a scanner having a plurality of reading pixels arranged in the nozzle direction, and a relative movement mechanism that moves the inkjet head, the scanner, and a printing medium relative to each other in a relative movement direction that intersects with the nozzle direction, and that prints a printed material on the printing medium by ejecting ink from the nozzles of the inkjet head based on original print data, and that reads the printed material with the reading pixels of the scanner, the single-pass printing device comprising: an imaging data acquisition step of acquiring imaging data based on an image of the printed matter captured by the scanner; a reference data acquisition step of acquiring reference image data based on the original print data or a reference image of a reference print captured by the scanner as reference data; an image defect position acquisition step of acquiring a position in the nozzle direction of an image defect in the image data of the printed matter caused by the faulty nozzle by comparing the image data with the reference data; a nozzle mapping information acquisition step of acquiring nozzle mapping information, which is a correspondence relationship between the positions of the plurality of nozzles and pixel positions in the nozzle direction of the imaging data, the nozzle mapping information being stored in advance in at least one memory; a nozzle mapping correction information acquisition step of acquiring nozzle mapping correction information for correcting a positional relationship in the nozzle direction between at least two of the print medium, the inkjet head, and the scanner; a nozzle mapping information correcting step of correcting the nozzle mapping information using the nozzle mapping correction information; a defective nozzle candidate estimating step of estimating at least one defective nozzle candidate that is the cause of the image defect in the printed product using the corrected nozzle mapping information; A defective nozzle estimation method comprising:

11. a printing process in which a single-pass printing device includes an inkjet head having a plurality of nozzles arranged in a nozzle direction, a scanner having a plurality of reading pixels arranged in the nozzle direction, and a relative movement mechanism that moves the inkjet head, the scanner, and a printing medium relative to each other in a relative movement direction that intersects with the nozzle direction, and ejects ink from the nozzles of the inkjet head based on original print data onto the printing medium that has been moved relatively in the relative movement direction; an image defect detection step of detecting image defects in the printed matter by comparing the captured image data with reference data; a defective nozzle estimation method according to claim 10; a correction processing step of performing a correction process on the original print data to suppress image defects caused by the at least one defective nozzle candidate; A method for manufacturing a printed matter comprising the steps of:

12. A program for causing a computer to execute the defective nozzle estimation method according to claim 10.

13. A non-transitory computer-readable recording medium on which the program according to claim 12 is recorded.

Images