JP2006259406A - Image forming apparatus, image forming method, program to make computer execute the method, and recording medium - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image forming apparatus predicting an image quality correction or a failure by carrying out the comprehensive analysis of an evaluation value which is correlated with an image quality factor regarding the cause of an image deterioration. <P>SOLUTION: The image forming apparatus 201 makes an image measuring part 220 measure at least the shape for an image pattern formed at least on one of a photoreceptor or an intermediate transfer body by an image forming part 210, and also makes an image quality calculation part 230 predict the quality of an outputted image on the basis of the measurement of the image pattern by the image measuring part 220. History information of the image quality prediction by the image calculating part 230 is stored by a history storing part 250 and the failure is predicted by a failure predicting part 240 using the history information stored by the history storing part 250. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to an image forming apparatus, an image forming method, a program for causing a computer to execute the method, and a recording medium, and in particular, an image for predicting a failure by predicting an image quality output from the image forming apparatus from an image pattern measurement result. The present invention relates to a forming apparatus, an image forming method, a program for causing a computer to execute the method, and a recording medium.

  Conventionally, image quality is maintained by periodically executing a calibration cycle that includes test pattern output evaluation and feedback to process parameters based on the results, and predicts process degradation limits by taking into account process parameter correction history. And there was technology to issue an alarm. The test pattern evaluation performed by this technology is related to line reproduction performance, that is, sharpness by outputting a line pattern and detecting luminance fluctuation due to interference between this pattern and a grid-like slit pattern provided in the apparatus. Evaluation is performed (Patent Document 1).

  Further, there are the following techniques for measuring the image quality and adjusting the process. A reference image is formed on the image carrier, the density of the reference image is detected by detection means such as a P sensor, and upper and lower limit values are set for the reference value to be compared with the output value, and the process conditions are changed from these relationships Thus, the image is prevented from being crushed or blurred due to deterioration of the developing material (Patent Document 2).

  Further, there is a technique in which a toner adhesion amount with respect to a reference pattern formed on a photosensitive drum is detected by a P sensor, and a control value of a transfer current is corrected based on a detection result. At this time, when the output value of the P sensor is lower than 3.6V, the charging is increased by 50V and the current is reduced by 2 μA. When the output of the P sensor is higher than 3.8V, the charging is adjusted by 50V and the current is increased by 2 μA. (Patent Document 3).

  Further, the output state of the image output device is detected, the detection result is transmitted to the control device of the image output device via the communication means, the correction value is calculated in the control device, and the output device is set using the calculated correction value. There is also a technology to control. In this technique, for example, color misregistration, line width, line density, and the like are measured, and correction is performed so that a target value is obtained (Patent Document 4).

  Also, a technology that prevents dot crushing and line crushing by forming patterns with different area ratios by dots and lines, detecting the density with a P sensor, and changing the process conditions based on the detection results. (Patent Document 5).

JP 2002-351166 A JP 2002-040725 A JP 2001-215761 A JP 2002-214865 A JP-A-5-313453

  However, in addition to the sharpness that is substantially evaluated as shown in Patent Document 1, the image quality factor includes graininess that represents roughness of the image and gradation that corresponds to smoothness of gradation. is there. In particular, in order to output a pictorial image such as a natural image with a quality that satisfies the user, the above-mentioned image quality factors need to be adjusted in a well-balanced manner. Adjustment is not described. Of course, sharpness is the most important factor when only character images are targeted, but there are few devices that only target character output in current output devices, and even if character output is mainly used as an application. The quality of pictorial images is also required to be high.

  In general, in the case of electrophotography, the relationship between various parameters and image quality factors is complicated, and correction of parameters does not necessarily improve all image quality factors. In other words, correction of a certain parameter value often leads to conflicting results, for example, improved graininess but reduced sharpness. Therefore, when determining the correction value of the process parameter or setting the limit value of image quality degradation to determine or predict the presence or absence of failure, comprehensively analyze the evaluation amount that has a correlation with the image quality factor, and correct the correction value. It is necessary to make decisions and predict failures.

  However, in the technique of Patent Document 1, since the failure is determined only from the correction parameter value determined from the evaluation amount related to the sharpness and the history information thereof, even if it is normal with respect to the sharpness, The state of the image quality factor cannot be grasped. For this reason, there is a high possibility that the determination will be erroneous, and there may be a case where it is not possible to determine a substantial failure until the result is an extreme value at which an image cannot be formed. Therefore, it is difficult to predict a failure at an early stage where image quality can still be tolerated and to feed back to the process.

  When a failure occurs in the output device and the image quality is not satisfactory, a service person visits in response to a call from the user, grasps the failure status, and performs repairs. However, since the parts necessary for repair are generally unknown until a visit is made and the failure status is grasped, if replacement parts are not at hand, procedures such as revisiting after repair and taking repairs are taken. As described above, the failure details cannot be grasped until the failure occurs and the user visits the user. As a result, the number of visits to the user increases, and in some cases, the timing of parts ordering is delayed, so that a quick response cannot be made. There was a problem that the cost for the repair service increased.

  In the techniques disclosed in Patent Documents 2 to 4, the average reflectance or density of an image formed on a photoconductor or an intermediate transfer body is measured by an image forming process using a detection unit such as a P sensor, By adjusting the process conditions from this measurement result, it is intended to prevent the occurrence of an abnormal image or the like. However, since the reflectance and density are easily affected by the characteristics of the photoconductor and intermediate transfer body, if the material is changed, it may be necessary for the service person to change the set value, or the correction accuracy may vary due to lot variations. It had the problem of decreasing. It is well known that granularity, sharpness, and gradation are important factors that determine image quality, but with the technique shown here, gradation characteristics (measured density value) Therefore, the image forming conditions of the image forming apparatus are adjusted, and measurement relating to one-dimensional or two-dimensional fluctuation is not performed. Therefore, it has not been possible to perform adjustment for correcting deterioration of graininess and sharpness highly correlated with the fluctuation characteristics.

  In the technique of Patent Document 4, the quality of the image actually output from the image forming apparatus to a recording medium such as paper is measured and fed back to the image processing using the measurement result. The medium has to be consumed, and the running cost has been increased.

  Further, in the techniques of Patent Documents 2, 3, and 5, the detection result such as density performed by the image forming apparatus is based on subjective image quality such as graininess, sharpness, and gradation output from the image forming apparatus. Therefore, it is impossible to judge the superiority or inferiority of the image quality obtained by the output. Therefore, it is difficult for the image processing apparatus to use the detection result to know the state of the image quality of the image forming apparatus on the network. Even if the state of the output apparatus is measured, it can be used for other than internal adjustment. I could not.

  The present invention has been made in view of such problems, and the object thereof is to comprehensively analyze an evaluation amount that correlates with an image quality factor for the cause of image degradation, and to perform image quality correction and failure prediction. When a failure occurs, the user can grasp the details of the failure so that the maintenance cost can be reduced, and the image forming device that can transmit information on image quality degradation and failure prediction to the image processing device on the network, A forming method, a program for causing a computer to execute the method, and a recording medium are provided.

  In order to solve the above-described problems and achieve the object, the invention according to claim 1 is an image forming apparatus, in which an electrostatic latent image formed on a photoreceptor is image-formed by an electrophotographic process. The image pattern measuring means for measuring at least the shape of the image pattern formed on at least one of the photosensitive member and the intermediate transfer member, and the quality of the output image based on the measurement of the image pattern by the image pattern measuring means. Image quality prediction means for prediction, history information storage means for storing history information of image quality prediction by the image quality prediction means, and failure prediction means for predicting a failure using history information by the history information storage means It is characterized by.

  According to a second aspect of the present invention, in the image forming apparatus according to the first aspect of the present invention, the image forming apparatus further includes a state information acquisition unit that acquires state information of the image forming apparatus, and the history information storage unit includes the state information acquisition unit. The failure prediction means predicts a failure based on the history information of the state information stored by the history information storage means.

  According to a third aspect of the present invention, in the image forming apparatus according to the second aspect, the image forming apparatus further includes an image forming condition adjusting unit that adjusts an image forming process condition based on the image quality prediction by the image quality predicting unit, The information acquisition means acquires state information of the image forming apparatus based on the image forming process conditions adjusted by the image forming condition adjustment means, and the history information storage means is based on the state information acquisition means. History information of state information is stored, and the failure prediction means predicts a failure based on history information of the state information stored by the history information storage means.

  According to a fourth aspect of the present invention, in the image forming apparatus according to the third aspect, the failure predicting unit measures the image pattern by the image pattern measuring unit, predicts the image quality by the image quality predicting unit, and adjusts the image forming condition. After the process condition adjustment by the image pattern measurement unit and the image pattern measurement cycle based on the process condition adjustment by the image pattern measurement unit are repeated at least once, the failure prediction unit stores the history information storage unit A failure is predicted based on history information.

  According to a fifth aspect of the present invention, in the image forming apparatus according to any one of the first to fourth aspects, the image forming apparatus includes image forming units having different colors, and the image pattern measuring unit. Is to measure an image pattern for each of the image forming units having different colors, and the image quality predicting means determines the quality of the output image for each color based on the measurement of the image pattern for each color by the image pattern measuring means. The history information storage means stores the image quality prediction for each color by the image quality prediction means, and the failure prediction means is based on the history information of the image quality prediction for each color stored in the history information storage means. And predicting a failure.

  According to a sixth aspect of the present invention, in the image forming apparatus according to any one of the first to fifth aspects, when the image forming apparatus performs dot output, the image pattern measuring unit is configured to output the image pattern. The average area of the dots constituting the dot, the standard deviation of the average area of the dots, the average equivalent circle diameter of the dots, the standard deviation of the average equivalent circle diameter of the dots, the line width of the lines constituting the image pattern, and the line The image pattern is measured by measuring at least one of the edge widths.

  According to a seventh aspect of the present invention, in the image forming apparatus according to any one of the first to sixth aspects, when the image forming apparatus performs image output with toner, the image pattern measuring means has a predetermined size. The image information corresponding to the toner image formed below is excluded from the measured image information, and the image pattern is measured.

  According to an eighth aspect of the present invention, in the image forming apparatus according to any one of the first to seventh aspects, the image pattern measuring unit illuminates with a light beam substantially parallel to the image pattern. , An imaging means for specularly reflecting the light beam of the illumination means on at least one of the photosensitive member and the intermediate transfer body, a photoelectric conversion element for photoelectrically converting the image formed by the imaging means, and the photoelectric conversion element An image analyzing means for analyzing the image information photoelectrically converted by the step, and measuring at least the shape of the image pattern.

  According to a ninth aspect of the present invention, in the image forming apparatus according to any one of the first to eighth aspects, the image quality predicting unit includes, as the quality of the output image, graininess, gradation, and sharpness. It is characterized by predicting at least one of the following.

  According to a tenth aspect of the present invention, in the image forming apparatus according to any one of the first to ninth aspects, when the image forming apparatus performs dot output, the image quality predicting unit Is characterized by calculating and predicting at least one of the standard deviation of the dot area and the standard deviation of the dot circle equivalent diameter.

  According to an eleventh aspect of the present invention, in the image forming apparatus according to any one of the first to tenth aspects, when the image forming apparatus performs dot output, the image quality predicting means includes the gradation property. Is characterized by calculating and predicting the linearity of the gradation characteristic curve from at least one of the dot area average and the dot circle equivalent diameter average and a predetermined number of lines for generating a gradation image. To do.

  According to a twelfth aspect of the present invention, in the image forming apparatus according to any one of the first to eleventh aspects, the image quality predicting unit is configured to calculate the MTF at a specific spatial frequency, the line width and the line edge for the sharpness. It is calculated from the width and predicted.

  According to a thirteenth aspect of the present invention, in the image forming apparatus according to any one of the first to twelfth aspects, the failure prediction unit determines the Mahalanobis distance of each characteristic value calculated by the image pattern measurement unit as the image. It is calculated based on a reference space of the characteristic value set in advance for an image group in which it is determined that the forming apparatus is in failure, and a failure prediction value is calculated on the basis of the calculated Mahalanobis distance. Features.

  According to a fourteenth aspect of the present invention, in the image forming apparatus according to any one of the first to thirteenth aspects, the measurement of the image pattern, the history information of the measurement of the image pattern, the failure prediction, and the failure prediction The information processing apparatus further includes transmission means for transmitting at least one piece of history information to a terminal connected via a network.

  According to a fifteenth aspect of the present invention, in the image forming apparatus according to the fourteenth aspect, the transmission unit transmits the at least one information to the terminal registered in advance at a predetermined cycle through the network. It is a thing to do.

  According to a sixteenth aspect of the present invention, in the image forming apparatus according to the fifteenth aspect, when it is determined that the failure prediction is greater than or equal to a predetermined value set in advance, a determination is made to notify the failure prediction to the previously registered terminal. The information processing apparatus further includes notification means, wherein the transmission means transmits the failure prediction to the previously registered terminal based on the determination by the notification means.

  According to a seventeenth aspect of the present invention, in the image forming apparatus according to the sixteenth aspect, the notifying unit changes a transmission cycle in accordance with a failure prediction by the failure prediction unit.

  According to an eighteenth aspect of the present invention, in the image forming apparatus according to any one of the first to seventeenth aspects, the failure prediction means also calculates a failure prediction value for each part constituting the image forming apparatus. It is characterized by being.

  The invention according to claim 19 is an image forming method, wherein the electrostatic latent image formed on the photoconductor is image-formed by an electrophotographic process. The image forming method comprises: Based on the image pattern measurement step of measuring at least the shape of the image pattern formed on at least one of the photoreceptor and the intermediate transfer member, and the image pattern measurement in the image pattern measurement step by the image quality prediction unit, the output image Using the history information in the history information storage step by the image quality prediction step for predicting the quality of the image, the history information storage step for storing the history information of the image quality prediction in the image quality prediction step by the history information storage means, and the failure prediction means. And a failure prediction step of predicting a failure.

  The invention according to claim 20 is a program, characterized by causing a computer to execute the image forming method according to claim 19.

  The invention according to claim 21 is a computer-readable storage medium, wherein the program according to claim 20 is stored.

  According to the first aspect of the present invention, the pattern is formed on the photosensitive member or the intermediate transfer member, and the shape of the pattern is measured. Compared to the density measurement by the detection means, it is less affected by noise due to density unevenness of the photosensitive member or the intermediate transfer body, and measurement with high accuracy and stability is possible. Also, the quality related to the granularity, gradation, sharpness, etc. of the image output from the image forming apparatus is predicted from the shape measurement result, and the failure is predicted based on the prediction result and its history information. Therefore, it is possible to predict the failure with higher accuracy than when the failure is determined from the process parameters whose quality of subjective image quality and linearity are not guaranteed.

  According to the invention according to claim 2, since information related to the state of the apparatus, for example, state information such as environmental temperature, humidity, and process parameters is acquired in advance, the failure is predicted using this information as well. Furthermore, it is possible to predict failure with high accuracy.

  According to the third aspect of the present invention, since the image forming process condition adjusting means and the failure predicting means are provided based on the image quality prediction result obtained by the image quality predicting means, the image quality can be stabilized. It can be ensured, and quick response is possible when image quality cannot be ensured.

  According to the invention of claim 4, since the image quality prediction is performed again after adjusting the process conditions, and the failure prediction is performed using the result, the degree of improvement in the image quality by the process adjustment and the image quality in the latest state The failure can be predicted based on the above, and the failure can be predicted with high accuracy.

  According to the fifth aspect of the present invention, since image quality prediction and failure prediction are performed for each color unit forming a color image, the image formation conditions can be optimized for each color, resulting in high quality color. An image can be obtained.

  According to the invention of claim 6, the pattern measuring means includes the average area of the dots constituting the pattern and the standard deviation thereof, the average equivalent circle diameter of the dots and the standard deviation thereof, the line width and the line edge width of the lines constituting the pattern. Since at least one of these is measured, the basic quality of the image can be predicted.

  According to the seventh aspect of the present invention, when measuring the shape characteristics of the image pattern on the intermediate transfer member, the toner image detected from the measured image is removed and the image smaller than the predetermined size is removed. In this case, among the scattered toner generated when the toner image is transferred from the photosensitive member to the intermediate transfer member, the fine particle toner component that is not transferred to the recording medium can be removed, and the image quality can be predicted with higher accuracy.

  According to the invention of claim 8, the detection of the pattern formed on the photosensitive member or the intermediate transfer member is illuminated by the light beam that has been made substantially parallel light, and the specularly reflected light from the photosensitive member or the intermediate transfer member is emitted. Since the image is formed, the photosensitive member and the intermediate transfer member having high reflectivity are detected in white, whereas the toner image is detected in black like a shadow because of low reflectivity. As a result, the contrast is high. Since the toner image can be acquired, the shape of the pattern can be measured with high accuracy.

  According to the ninth aspect of the invention, since the image quality predicting means predicts at least one of graininess, gradation, and sharpness, the image quality output by the image forming apparatus can be grasped efficiently and accurately. be able to.

  According to the invention of claim 10, since the graininess is calculated from the standard deviation of the dot area or the standard deviation of the dot circle equivalent diameter, the graininess can be predicted with high accuracy.

  According to the invention of claim 11, since the linearity of the gradation characteristic curve is calculated from the dot area average or the dot circle equivalent diameter average and the predetermined number of lines used to create the gradation image, the gradation is accurately obtained. Tonality can be predicted.

  According to the twelfth aspect of the invention, since the MTF at the specific spatial frequency is calculated from the line width and the line edge width, the sharpness can be accurately predicted.

  According to the thirteenth aspect of the present invention, the Mahalanobis distance of each characteristic value obtained from the pattern measuring means is calculated based on the reference space constituted by the image group determined as a good image when the apparatus malfunctions. In addition, since the failure probability is quantitatively calculated from the Mahalanobis distance, the occurrence of the failure can be predicted efficiently.

  According to the fourteenth aspect of the present invention, since the measurement result, the failure prediction result, and the history information thereof can be transmitted to the terminal connected via the network, the user on the network who intends to use the image forming apparatus. However, it is possible to know the output image quality by the image forming apparatus and to transmit the failure content to the external terminal of the transmission destination when a failure occurs. Can be reduced.

  According to the fifteenth aspect of the present invention, the measurement result, the failure prediction result, and the history information thereof are periodically transmitted to a predetermined terminal to a terminal connected via the network. It can be monitored by a service person or the like, and it is possible to take measures before a serious failure occurs, and loss due to the failure can be avoided.

  According to the invention of claim 16, when the failure prediction result becomes a predetermined value or more, the notification means for notifying the information is provided, so unnecessary communication can be reduced and the apparatus can be managed efficiently. .

  According to the invention of claim 17, since the calibration timing is changed according to the failure prediction result, the calibration period is automatically adjusted even when the image quality of the apparatus deteriorates and becomes unstable. By doing so, it is possible to suppress a temporal change in image quality and provide a stable image quality.

  According to the eighteenth aspect of the invention, since the probability of failure can be predicted from the text of Ataka or lower, maintenance of each part can be performed efficiently.

  According to the nineteenth aspect of the present invention, the pattern is formed on the photosensitive member or the intermediate transfer member, and the shape of the pattern is measured. Compared to the density measurement by the detection means, it is less affected by noise due to density unevenness of the photosensitive member or the intermediate transfer body, and measurement with high accuracy and stability is possible. Also, the quality related to the granularity, gradation, sharpness, etc. of the image output from the image forming apparatus is predicted from the shape measurement result, and the failure is predicted based on the prediction result and its history information. Therefore, it is possible to predict the failure with higher accuracy than when the failure is determined from the process parameters whose quality of subjective image quality and linearity are not guaranteed.

  According to the twentieth aspect of the present invention, it is possible to cause a computer to execute the image forming method according to the nineteenth aspect.

  According to the invention of claim 21, the program of claim 20 can be stored and read by a computer.

  Referring to the accompanying drawings, the best mode of an image forming apparatus, an image forming method, a program for causing a computer to execute the method, and a recording medium according to the present invention is divided into first to fourth embodiments. This will be described in detail.

(1. Embodiment 1)
(1.1. Main part of image forming apparatus)
FIG. 1 is a functional block diagram of a main part of the image forming apparatus according to the first embodiment. FIG. 2 is a schematic configuration diagram illustrating a tandem type digital color printer as the image forming apparatus according to the first embodiment. The main part of the image forming apparatus according to the first embodiment is incorporated in the tandem type digital color printer 1. The digital color printer 1 includes an image reading device 2 and can perform full-color copy output.

  Inside the digital color printer main body 1, image forming units 13K and 13Y for black (K), yellow (Y), magenta (M), and cyan (C) are provided as image forming units constituting the image output apparatus 100. , 13M, 13C are arranged at regular intervals along the horizontal direction. The black (K), yellow (Y), magenta (M), and cyan (C) toner images formed by the image forming units 13K, 13Y, 13M, and 13C are superimposed on the intermediate transfer belt 25. After the primary transfer in this state, a secondary transfer is performed collectively from the intermediate transfer belt 25 onto the recording paper 34 to form a color image.

  The image forming apparatus 201 according to Embodiment 1 includes an image forming unit 210, an image measuring unit 220, an image quality calculating unit 230, a failure prediction unit 240, a history storage unit 250, a communication unit 260, and an input unit 270.

  Here, the image forming unit 210 uses the image forming units 13K, 13Y, 13M, and 13C to form an image pattern on the intermediate transfer member. However, the image forming unit 210 may be configured to form an image pattern on the photoreceptor and detect the formed image pattern.

  The image measuring unit 220 detects the image quality measurement pattern on the intermediate transfer member created by the image forming unit 210. The image quality calculation unit 230 predicts the output image quality based on the result measured by the image measurement unit 220. The failure prediction unit 240 calculates a failure probability based on the image quality prediction result calculated by the image quality calculation unit 230. The history storage unit 250 stores information necessary for the operation of each unit, results calculated by each unit, and history information thereof. The communication unit 260 communicates with an arbitrary terminal 90 connected via a network via a connector. The input unit 270 accepts input for the user to make various settings via the user interface, and accepts settings for the number of image quality predictions to be described later and the transmission destination of the prediction results.

  In the image forming apparatus according to the first embodiment, the image quality calculation unit 230 calculates the image quality of the image quality measurement image pattern formed by the image forming unit 210, and the failure prediction unit 240 receives the history information from the history storage unit 250. Reads out and predicts failure.

  Hereinafter, the main part of the image forming apparatus, which is a functional part of failure prediction, which is a feature of the present invention, will be described mainly, and the configuration of a general digital color printer 1 is known and will be described later (FIG. 23).

(1.2. Calculation of image quality)
(Image measuring unit 220)
FIG. 3 is a functional block diagram of the image measurement unit. The image measurement unit 220 includes a pattern detection unit 60, an image memory 221, an analysis unit 222, and a CPU 223, which are connected by a bus.

  The pattern detection unit 60 detects an image, and the image memory 221 temporarily stores the detected image. The analysis unit 222 analyzes the read pattern, and calculates measurement values such as the dot area and the standard deviation of the dot area, the line width, and the line edge width. Here, the pattern detection unit 60 reads the measurement pattern formed on the intermediate transfer member.

  FIG. 4 is a schematic diagram illustrating an example of an image pattern for measurement formed by the image forming unit according to the embodiment. FIG. 5 is a diagram for explaining the operation detected by the pattern detection unit. The pattern detection unit 60 includes a light source 61, an imaging lens 62, and a photoelectric conversion element 63.

  The light source 61 irradiates the image pattern generated on the intermediate transfer body 25 and forms an image on the photoelectric transfer element 63 such as a CCD sensor by the imaging lens 62 and forms the reflected light on the intermediate transfer body. Read the toner image. At this time, the photoelectric conversion element 63 may be a one-dimensional line sensor in which the elements are arranged one-dimensionally or an area sensor in which the elements are two-dimensionally arranged. The detection unit 60 detects whether dots and lines are periodically arranged in the measurement patterns 401 and 402 shown in FIG.

  FIG. 6 is a diagram illustrating a light beam that illuminates the measurement image pattern. Here, the illumination light beam is made substantially parallel light, and the regular reflection light from the intermediate transfer body 25 is imaged. The light source 61 is a one-dimensional or two-dimensional LED array, and the light beam from the light source 61 is diffused by the diffuser plate 64, and this is a function called a light control film, which regulates the light distribution direction of the transmitted light beam. The light that has been converted into parallel light using the conductive film 65 is vertically reflected on the intermediate transfer body 25 by the half mirror 66. Then, the reflected light beam from the intermediate transfer body 25 is imaged onto the photoelectric conversion element 63 by the imaging lens 62, and an image of the measurement pattern is obtained.

  Here, the method of making the illumination light substantially parallel is not limited to using a functional film such as a light control film, and a similar effect may be obtained by combining lenses.

  Also, the illumination and the imaging direction are not limited to vertical epi-illumination, but may be in a relative positional relationship for detecting a specularly reflected light beam. However, when a two-dimensional image is obtained from an oblique direction using an area sensor, a correction process for correcting image distortion is required.

(Image quality calculation unit 230)
The image quality calculation unit 230 calculates a predicted value of the image quality when output on a recording medium such as paper based on the measurement amount calculated by the image measurement unit 220. Details of the image quality predicted by the image quality calculation unit 230 and the prediction method are as follows.

  In general, granularity, sharpness, and gradation are important as factors that determine image quality. By obtaining image quality evaluation values for at least the above three factors, most of the image quality that is finally obtained is determined. Can be explained.

  However, the image quality evaluation amount predicted by the present invention from the shape characteristics of the measurement pattern is not limited to these three factors. For example, evaluation amounts such as banding, color shift, and background stains may be added. Hereinafter, a method for predicting graininess, sharpness, and gradation using the shape characteristic value of the measurement pattern will be described.

(Granularity)
A method for predicting graininess will be described. The pattern 401 composed of dots in the pattern of FIG. 4 described above shows a halftone dot pattern of 600 dpi, 150 lines, and 0 degrees, and each point in the figure is composed of 2 × 2 dots. In the electrophotographic method, the reproducibility of 1 × 1 dots is often extremely poor, and even if the area of 1 × 1 dots is measured, the correlation with the graininess at all gradation levels is low. It is known from the experiment conducted, and it is preferable to use a dot pattern of at least 1 × 2 dots or more, preferably 2 × 2 dots.

  FIG. 7 is a graph showing the granularity with respect to the standard deviation of the dot area. FIG. 17 shows the standard deviation calculated by measuring the area of each point of the pattern 401 in FIG. 4 on the photosensitive member or intermediate transfer member, and the average granularity actually measured by outputting several types of gradation patterns. Correlation is shown. As shown in FIG. 7, there is a high correlation between the standard deviation of the dot area and the average granularity. Therefore, by measuring the standard deviation of the dot area, the average graininess of the image can be predicted without actually outputting it on paper. This is the basis for predicting the average graininess.

  FIG. 8 is a schematic diagram showing that the measurement pattern is divided into rectangular areas each including one dot. Here, the area of each point was measured as follows. The image is binarized at a predetermined threshold level using a measurement amount such as reflectance. A value obtained by multiplying the sum of pixels classified on the low reflectance side by binarization by the area per pixel is calculated as a dot area in each region. The relationship between the standard deviation of the area and the granularity of the output image shown in FIG. 7 includes the measurement results with a plurality of lines (106 lines, 150 lines, 212 lines), and as long as the same pattern is used. Does not depend on the number of lines.

  This is a matter clarified by the present inventors through experiments. Therefore, the same pattern can be used as the measurement pattern used for predicting the graininess even when the output model and halftone processing are different. On the contrary, if different measurement patterns are used, the gradient of granularity with respect to the standard deviation of the area is different, so that accurate image quality prediction cannot be performed, and therefore the same pattern must be used.

  Further, instead of the standard deviation of the dot area, for example, from the area calculated for each rectangular area, a radius of a circle that gives an area equal to the area (this is referred to as a circle equivalent diameter) may be calculated. In addition, values such as brightness and density calculated from the area ratio and area ratio in each rectangular area may be used.

The granularity prediction formula using the standard deviation of the dot area is shown in (1).
Granularity = 472.5 × [standard deviation of dot area] −0.1 (1) Equation (1) By the way, assuming that the equivalent circle diameter is r and the total area of toner in each rectangle in FIG.
r = (S / π) ^ 0.5
It is expressed.

  Here, when the pattern formed on the intermediate transfer body 25 is detected and the dot area or the like is measured by the pattern measurement unit, a large amount of toner scatters when the image is transferred from the photoconductor to the intermediate transfer body. Many of these small toner particles are not actually transferred to the paper and do not affect the final image quality.

  Therefore, by removing fine particles from detected image data prior to pattern measurement, toner particles that are not transferred to a recording medium such as paper can be removed, and image quality can be predicted with higher accuracy.

(Gradation)
FIG. 9 is a graph showing gradation with respect to the product of the average dot area and the number of lines used for output. This shows the relationship between the contribution rate when the brightness characteristic is linearly regressed, and the product of the average area of the dots of the pattern used for the granularity prediction and the number of lines used for the output. A tone prediction method will be described with reference to FIG. Here, the gradation is defined as the brightness characteristic of the output image with respect to the input image signal.

Formula (2) shows an example of the prediction formula. However, the present invention is not limited to this prediction formula.
Tonal linearity =
−0.23 × [dot area] × [number of lines] −0.5 Equation (2)

  The higher the contribution rate when the lightness characteristic is linearly regressed (closer to 1), the more linear the lightness characteristic is. Lightness is a psychophysical quantity configured to be linear with human brightness perception. Therefore, the fact that the output characteristics of the output machine are linear in brightness means that the difference between adjacent gradations is uniform in all output gradations, and the gradations are crushed or the gradations skip at a certain level. This means that there is little occurrence of contours, which indicates the most suitable state for engine gradation characteristics.

(Sharpness)
FIG. 10 is a graph showing the result of MTF prediction of MTF at a spatial frequency of 6 c / mm using the line width and the edge width of the line according to equation (3). The formula (3) is as follows.
Sharpness =
-4.6 × | ideal line width−line width | −4.1 [line edge width] +0.76 Equation (3) Modulation Transfer Function (amplitude transfer function) It is an index showing whether it can be reproduced. The sharpness prediction method will be described with reference to FIG. Both show a high correlation, and it can be seen that the MTF can be predicted from the shape characteristics of the line.

  In the present invention, the MTF is predicted using the equation (3). However, the present invention is not limited to this. For example, the MTF is calculated using the number or area of toner particles scattered between lines as a measurement amount instead of the edge width. It may be predicted.

  The line width is calculated as the number of pixels in the line width direction in a binary image obtained by binarizing the detected pattern image with a predetermined threshold level calculated from the maximum and minimum values of the reflectance of the image. be able to. The line width calculation method is defined in JIS X 6930, and may be measured by a method according to this.

  The line edge width can be obtained by measuring the line width at two different threshold levels and multiplying the difference value of the line width at that time by 1/2.

(1.3. Failure prediction)
(Failure prediction unit 240)
A specific example of a failure probability calculation method calculated by the failure prediction unit 240 will be described below. Here, failure prediction can be performed using the Mahalanobis distance (Mahalanobis distance). The Mahalanobis distance is a distance measure between a normal population and a sample. For example, a group of images with various image quality is created in advance by changing the process conditions, subjective evaluation is performed on the image group, an image group determined to be a device failure is extracted, and the extracted image is used. Create a reference space. In this case, it is needless to say that a non-failed state may be used as the reference space.

  The Mahalanobis distance is calculated based on the reference space for each measurement value obtained by actually measuring the measurement pattern on the photoconductor or intermediate transfer member, and failure prediction is performed from the Mahalanobis distance of each measurement value. What is necessary is just to calculate a value. Further, a distance from the reference space may be used as a failure prediction value, or a failure prediction value may be given as a probability calculated according to the distance.

If it is assumed that the failure probability transitions from a normal state to a failure state according to a logistic function as shown in the equation (4), for example, it can be easily obtained.
Failure probability = 1 / (1 + exp (−x)) (4) where x is a distance from the reference space when a normal (no failure) state is set as the reference space.

  By using the Mahalanobis distance, measurement quantities of different dimensions, such as area and width, as well as temporal fluctuation characteristics obtained from historical information, can be handled as the Mahalanobis distance from the reference space. Can be efficiently constructed.

  Also, the failure probability of each part in the device can be calculated in exactly the same way by creating a reference space created for the device for each part.

  The method for calculating the failure probability is not limited to the method using the Mahalanobis distance, and the failure probability may be estimated using Bayesian statistics or may be based on other statistical methods.

  Here, the dot pattern and the line pattern on the intermediate transfer body 25 are created without actually outputting to a recording medium such as paper, the pattern is read, and the graininess, gradation, Predict quality against image quality factors such as sharpness. At this time, parameters and the like necessary for prediction are read from the storage means and used. Further, it is also possible to adopt a configuration in which a pattern in a latent image formed by forming a latent image on the photosensitive member instead of on the intermediate transfer member 25 is read and predicted.

  Next, the failure prediction unit 240 stores the measured image quality prediction result in the history storage unit 250 and includes the past image quality prediction result stored in the history storage unit 250 so that the current state is within a predetermined fluctuation range. Each image quality factor is analyzed using a statistical method to determine whether the image quality factors are balanced and in a stable state or the like, and the probability that the apparatus has failed is calculated.

  The calculated value does not have to be a probability in a strict sense, and may be an evaluation amount that indicates the degree of possibility of failure or the possibility of failure, such as the number of output sheets until failure occurs. It may be anything. Further, the calculated failure probability may be a failure probability at the present time, or may be a failure probability after a predetermined number of outputs.

  FIG. 11 is a flowchart illustrating an image forming procedure according to the first embodiment. The image forming unit 210 controls the image forming units 13K, 13Y, 13M, and 13C to generate the measurement image pattern shown in FIG. 4 (step S101). The image measurement unit 220 reads the generated image pattern by the pattern detection unit shown in FIGS. 5 and 6 (step S102), and measures the shape of the image pattern (step S103). The image quality calculation unit 230 calculates a quality prediction value of the output image including the already described granularity, sharpness, and gradation (step S104), and the failure prediction unit 240 uses the history information stored in the history storage unit 250. Read out and calculate the failure probability (step S105). The procedure of the failure probability calculated by the failure prediction unit 240 will be described below.

  FIG. 12 is a flowchart for explaining a failure prediction procedure. The failure prediction procedure performed by the failure prediction unit 240 is as follows. First, the failure prediction unit 240 reads history information from the history storage unit 250 (step S201), and calculates the Mahalanobis distance (step S202). Then, the failure probability is calculated by equation (4) 1 / (1 + exp (−x)) (step S203).

(1.4. Effect)
As described above, in the image forming apparatus 102 according to the first embodiment, the image measuring unit 220 measures the image quality measurement pattern on the intermediate transfer member created by the image forming unit 210, and the image quality calculating unit 230 includes the image measuring unit. The output image quality is predicted based on the result measured by 220, and the failure prediction unit 240 calculates the failure probability based on the image quality prediction result calculated by the image quality calculation unit 230, so that the image pattern is stored on the recording medium. Therefore, it is possible to predict the failure probability efficiently.

(2. Embodiment 2)
FIG. 13 is a functional block diagram of the image forming apparatus according to the second embodiment. Embodiment 202 differs from Embodiment 1 in that it further includes a state information acquisition unit 280 to acquire information about the state of the apparatus, and failure prediction unit 240 adds to the image quality calculated by image quality calculation unit 230. In other words, the failure is predicted based on the state information.

  The status information acquisition unit 280 acquires status information of the image forming apparatus, and obtains a failure probability based on the acquired status information and history information stored in the history storage unit 250. Here, prior to the calculation of the failure probability, information on the state of the apparatus including the installation environment information (temperature, humidity) is acquired, and this information is further added and used for the failure probability calculation.

  FIG. 14 is a flowchart illustrating an image forming procedure according to the third embodiment. Steps up to step S304 are the same as steps up to step S104 in FIG. The status information acquisition unit 280 acquires device temperature and humidity information, which is environmental information of the device (step S305), and the failure prediction unit 240 determines the output image quality prediction value and the device temperature and humidity information. A failure probability is predicted (step S306).

  Thereby, for example, the prediction accuracy can be improved by performing processing such as correcting the failure determination according to the environmental temperature.

(3. Embodiment 3)
FIG. 15 is a functional block diagram of the image forming apparatus according to the third embodiment. The difference between the image forming apparatus 203 according to the third embodiment and the second embodiment is that the image forming apparatus 203 further includes a process control unit 290 that includes information on the state of the apparatus (for example, process parameter values and installation environment) before calculating the failure probability. Information (temperature, humidity)), and the failure prediction unit 240 adds the above process parameter value and installation environment information (temperature, humidity)) to the image quality and status information calculated by the image quality calculation unit 230. It is a point to predict a failure based on this. As a result, it is possible to improve the prediction accuracy by performing processing such as correcting the failure determination by the process parameter value, for example, the environmental temperature.

  If the obtained image quality prediction result is, for example, poor graininess, this occurs because dot reproduction is unstable, so it is stabilized by increasing the dot size to be reproduced by increasing the exposure amount. Can be achieved. Further, by changing the halftone process, it is possible to cope with selection of an image processing method such that the deterioration of graininess is not noticeable.

  The process control unit 290 determines an image output condition based on the predicted image quality value calculated by the image quality calculation unit 230. At this time, a reference value of image quality may be set in advance, and the output condition may be adjusted according to the magnitude of deviation from the reference value.

  FIG. 16 is a flowchart illustrating an image forming procedure according to the third embodiment. Steps S401 to S404 are the same as steps S101 to S104 in FIG. The process control unit 290 calculates image forming process conditions. Here, for example, the process control unit 290 calculates an increase amount for increasing the exposure amount from the quality prediction value of the output image (step S405), and controls the process condition based on the calculated increase amount of the exposure amount (step S406). The status information acquisition unit 280 acquires the status information of the device (step S407), and the failure prediction unit 240 calculates the failure probability based on the status information of the device under the process conditions controlled by the process control unit 290 ( Step S408).

  In this way, from the predicted value of the image quality calculated by the image quality calculation unit, the process control unit acquires the state information by controlling the image forming process, and the failure prediction unit calculates the failure probability, thereby increasing the higher probability. Accurate failure prediction can be performed while forming a quality image.

(3.1. Modification 1)
The image forming apparatus according to the modification differs from the image forming apparatus according to the third embodiment in that the process control result is fed back. The process control performed prior to failure prediction is different.

  FIG. 17 is a schematic diagram of an operation panel portion of the image forming apparatus. Here, the number N of repetitions that the process control unit calculates and controls the image forming process conditions is received, and the number of times (N) that the input unit 270 is pressed is received by pressing the operation button of the operation panel 330. Set and repeat N times of image quality prediction and process control. At this time, if it is determined that the image quality prediction result provides sufficient image quality even within the set number of times, no process adjustment is performed. Even if the image quality is not sufficient as a result of the adjustment, the adjustment is not repeated for the set number N or more. In any case, failure prediction is performed using the final image quality prediction result.

  After making process adjustments, an evaluation pattern is formed again on the photoconductor or intermediate transfer member, pattern shape measurement and image quality prediction are performed, and failures are predicted from the measured image quality prediction results and history information. The accompanying failure prediction can be performed more finely and accurately.

  In other words, in process control, one adjustment item is rarely independent of a single image quality factor (for example, only graininess), and in many cases there is an interaction. Not all factors are in a satisfactory range.

  For example, if the sharpness and gradation are within the predetermined range and only the granularity is bad, the gradation is reduced and falls outside the predetermined range as a result of adjusting the parameters to improve the granularity. Will occur.

  FIG. 18 is a flowchart illustrating an image forming procedure according to a modification. Steps up to step S504 are the same as step S104 in FIG. The counter of the process control unit 290 determines whether or not the number of times of reception is less than the set N and there is a necessity for process control (step S505). If not necessary (No in step S505), FIG. The process proceeds to step S510 similar to step S407 described in step S407.

  If it is determined that the number of times the process control unit 290 has received is less than N and there is a need for process control (Yes in step S505), the process control unit performs the process control performed in steps S405 and 406 (step S506, 507), it is determined whether or not the count is N (step S508). If it is not N (No in step S508), the count is incremented (step S509), the process returns to step S501, and the same steps are repeated. When it is determined that the count is N (Yes in step S508), the state information is acquired and the failure probability is calculated in the same manner as in steps S407 and 408 (steps S510 and 511).

  Thus, by using the image quality prediction value measured after the process adjustment is performed a plurality of times for the final failure prediction, the accuracy with respect to the failure prediction can be improved.

  Further, it is possible to set the process condition to a more optimal state by repeating the measurement and the adjustment of the process condition a plurality of times.

  Further, since the present invention does not actually output to paper, there is an advantage that even if such a repeated adjustment step is taken, there is little cost loss.

(3.2. Modification 2)
An image forming apparatus according to another modification, when it is determined that the apparatus is out of order, main components constituting the output apparatus based on each image quality prediction result, temperature, humidity, each control parameter, and their history information The difference is that the failure probability is calculated for each.

  As a result, for example, when notifying the service person of the failure, by adding the failure probability calculation result of each part and notifying, it becomes easy to take an appropriate response even if it is not a skilled service person. As a result, it is possible to quickly respond to the user, and it is possible to improve the service and reduce loss due to failure.

  Also, the failure probability of each part can be calculated not only for the apparatus but also for each part by creating the reference space described in the description of the failure prediction for each part for each part.

  In the case of a color printer, the image quality prediction and failure prediction based on the shape characteristics of the measurement pattern are preferably performed for each unit that forms a toner image of each color, but the image quality for a representative color (for example, black) is predicted. The process conditions may be adjusted.

(4. Embodiment 4)
FIG. 19 is a functional block diagram of the image forming apparatus according to the fourth embodiment. The image forming apparatus according to the fourth embodiment is different from the first embodiment in that it includes a notification unit 295, and when it is determined that the failure prediction value is higher than the reference value, the communication unit 260 is connected via the network. The point is that the terminal transmits information related to failure prediction.

  Here, when the failure probability Pf is set as a reference value for determining the presence or absence of a failure and the reference value is not cleared, the communication unit 260 notifies the display device on the printer or the terminal on the network, and other Notification is made to the terminal 60 at the location of the service person or manager.

  When the user determines that a failure has occurred, for example, a transmission destination input and a transmission execution instruction for transmitting the image quality prediction value, the failure prediction value, and the history information thereof to a service person are performed from the input unit 270. When the input unit 270 accepts an operation input, the image quality prediction result, the state information, and the history of the information may be transmitted to a predetermined address, or the information may be read in advance to a predetermined terminal or operator. May be allowed.

  FIG. 20 is a flowchart illustrating an image forming procedure according to the fourth embodiment. FIG. 20 shows only characteristic steps. For example, after the failure prediction unit 240 of FIG. 11 calculates the failure probability (step S105), the calculated failure probability is stored in the history storage unit 250, and notification is made. The unit 295 reads the stored predicted failure value (step S601) and compares it with the reference value Pf (step S602). When higher than the reference value (Yes in step S602), the communication unit 260 transmits a failure prediction value to the management terminal 60 or the like (step S603). If it is equal to or less than the reference value (No in step S602), the process ends.

  As a result, the user is usually released from the work of checking the status of the printer, and improvement measures can be taken promptly.

  In addition, when notifying service personnel and managers, the service personnel can know the failure status in detail by transmitting not only the failure probability but also the history information or the history information upon request. Therefore, quick and efficient response measures such as visiting the user after preliminarily preparing alternatives etc. by narrowing down the cause of the failure to some extent, omitting unnecessary work such as visiting the user only for grasping the failure status Can be taken. Therefore, the user can reduce the loss due to the failure of the apparatus. Furthermore, the cost for repair service can be reduced.

  In particular, in the case of the present invention, information to be transmitted to the service person includes not only a process parameter but an evaluation amount having a correlation with human perception, so that the degree of failure can be easily grasped and the service person is also appropriate. There is merit that it is easy to take action.

  Furthermore, even if the failure probability of the apparatus of the present invention clears the reference value, if the user determines that it is a failure, or if a failure occurs due to an unexpected reason, the user can be an administrator or a service. An operation unit may be provided for transmitting the image quality prediction result and the apparatus status information to the man through a network line connected to the apparatus.

  In any case, the manager or the service person can easily acquire the information as necessary, so that a quick response can be taken.

  Here, it is desirable that the transmission destination is configured to transmit only to registered terminals.

(4.1. Modification 3)
The image forming apparatus according to the modification has a configuration in which the calibration cycle is made different according to the failure probability even if the failure probability is equal to or less than the failure determination probability Pf.

  FIG. 21 is a graph showing an increase in failure probability with respect to the number of output sheets. From this graph, it can be seen that the failure probability of the apparatus increases as the number of output sheets increases.

  As a result, the higher failure probability indicates that the state of the apparatus becomes unstable or unstable. In such a case, it is possible to keep the state of the apparatus stable by shortening the calibration cycle.

  Until now, when the failure probability is Pc or less, calibration is performed every N sheets, and when the failure probability is Pc or more, calibration is performed so that calibration is performed every M sheets. Change the set value. Here, M <N. That is, in this case, if the reference value is lower than the first reference value, the calibration cycle is N times as it is, and if it is between the lower reference value and the first reference value, the calibration cycle is shortened. That is, calibration is performed more frequently.

  Here, only one reference value for changing the calibration cycle is used. However, the present invention is not limited to this, and there may be a plurality of reference values for switching the calibration cycle, and the calibration cycle is a continuous function as a function of the failure probability. It may be set as a value.

  FIG. 22 is a flowchart illustrating an image forming procedure according to a modification. Steps S701 to 703 are the same as steps S601 to 603 in FIG.

  When the notification unit 295 determines that the failure prediction value is not higher than the reference value Pf (No in step S702), the notification unit 295 further determines whether or not the failure prediction value is higher than the reference value Pc (step S704). In step S704 No), the process is terminated.

  On the other hand, when the notification unit 295 determines that the value is higher than the reference value Pc (Yes in Step S704), the calibration cycle is changed to M times (Step S705).

  As a result, as the number of outputs increases, that is, the more the device is used, the higher the probability of failure, and the shorter the calibration cycle, the more likely the device state becomes unstable or unstable. This makes it possible to maintain a more stable state.

(5. Overall configuration)
FIG. 23 is a configuration diagram of a tandem digital color printer as the image forming apparatus according to the first embodiment. Here, the configuration of the present invention will be described using a tandem type digital color printer, but the present invention is also effective in a color copying machine / facsimile. A general image forming operation by the digital color printer 1 will be described with reference to FIGS.

  The digital color printer main body 1 includes an image reading device (IIT: Image Input Terminal) 4 that reads an image of the document 2 at an upper portion on one end side. Further, inside the digital color printer main body 1, predetermined image processing is performed on image data output from the image reading device 4, a personal computer (not shown) or the like, or image data sent via a telephone line or a LAN. An image processing apparatus (IPS: Image Processing System) 12 that performs image processing and an image output apparatus (IOT: Image Output Terminal) 100 that outputs an image based on image data subjected to predetermined image processing by the image processing apparatus 12. It is arranged.

  Inside the digital color printer main body 1, image forming units 13K and 13Y for black (K), yellow (Y), magenta (M), and cyan (C) are provided as image forming units constituting the image output apparatus 100. , 13M, 13C are arranged at regular intervals along the horizontal direction. Below the four image forming units 13K, 13Y, 13M, and 13C, an intermediate transfer belt 25 that transfers toner images of respective colors sequentially formed by these image forming units in a state of being superimposed on each other is indicated in the direction of the arrow. It is arrange | positioned so that rotation is possible. The toner images of each color transferred onto the intermediate transfer belt 25 in a multiple manner are collectively transferred onto a recording paper 34 as a recording material fed from a paper feed tray 39 or the like, and then recorded on the recording paper by a fixing device 37. 34 is fixed and discharged to the outside.

  In the embodiment shown in FIG. 23, the image output apparatus 100 has black (K), yellow (Y), magenta (M), cyan (C) formed by the image forming units 13K, 13Y, 13M, and 13C. ) Are first transferred in a state where they are superimposed on the intermediate transfer belt 25 and then secondarily transferred from the intermediate transfer belt 25 onto the recording paper 34 to form a color image. However, the present invention is not limited to this example, and the color of each color of black (K), yellow (Y), magenta (M), and cyan (C) formed by each image forming unit is described. The present invention can also be applied to a configuration in which a color image is formed by transferring a toner image on a recording sheet conveyed by a sheet conveying belt while being superimposed on each other. The order of colors of the image forming units is not limited to the order of black (K), yellow (Y), magenta (M), and cyan (C), but yellow (Y), magenta (M), Any order such as cyan (C) and black (K) may be used.

  A platen cover 3 that presses the document 2 against the platen glass 5 and an image reading device that reads an image of the document 2 placed on the platen glass 5 are disposed on the upper end of the main body of the tandem digital color printer 1. 4 is arranged. The image reading device 4 illuminates a document 2 placed on a platen glass 5 with a light source 6, and reflects a reflected light image from the document 2 from a full-rate mirror 7, half-rate mirrors 8 and 9, and an imaging lens 10. The image reading element 11 composed of a CCD or the like is scanned and exposed through a reduction optical system, and the color material reflected light image of the document 2 is formed at a predetermined dot density (for example, 16 dots / mm) by the image reading element 11. It is configured to read.

  The color material reflected light image of the document 2 read by the image reading device 4 is, for example, an image processing device as document reflectivity data of three colors of red (R), green (G), and blue (B) (8 bits each). 12 (Image Processing System), and the image processing apparatus 12 performs shading correction, position shift correction, brightness / color space conversion, gamma correction, frame deletion, color / movement for the reflectance data of the document 2. Predetermined image processing such as editing is performed.

  Image data that has been subjected to predetermined image processing by the image processing apparatus 12 is document color material gradation data of four colors of yellow (Y), magenta (M), cyan (C), and black (K) (each 8 bits). ROS 14K and 14Y of image forming units 13K, 13Y, 13M, and 13C for each color of black (K), yellow (Y), magenta (M), and cyan (C) as described below. , 14M, 14C (Raster Output Scanner). These ROSs 14K, 14Y, 14M, and 14C perform image exposure with laser light in accordance with original color material gradation data of a predetermined color.

  Incidentally, inside the tandem type digital color printer main body 1, as described above, four image forming units 13K, 13Y, 13M of black (K), yellow (Y), magenta (M), and cyan (C) are provided. , 13C are arranged in parallel with a certain interval in the horizontal direction. These four image forming units 13K, 13Y, 13M, and 13C are all configured in the same manner, and are roughly divided into a photosensitive drum 15 that rotates at a predetermined rotational speed in the direction of the arrow, and the photosensitive drum 15. Primary charging scorotron 16 for uniformly charging the surface of the photosensitive drum 15, ROS 14 as an image exposure device for forming an electrostatic latent image by exposing an image corresponding to each color on the surface of the photosensitive drum 15, and a photosensitive member The developing unit 17 for developing the electrostatic latent image formed on the drum 15 and a cleaning device 18 are configured.

  As shown in FIG. 23, the ROS 14 modulates the semiconductor laser 19 according to the original color material gradation data, and emits a laser beam LB from the semiconductor laser 19 according to the gradation data. The laser beam LB emitted from the semiconductor laser 19 is deflected and scanned by the rotary polygon mirror 22 via the reflection mirrors 20 and 21, and again carries an image via the reflection mirrors 20 and 21 and the plurality of reflection mirrors 23 and 24. Scanning exposure is performed on the photosensitive drum 15 as a body.

  From the image processing device 12, black (K), yellow (Y), magenta (M), and cyan (C) image forming units 13K, 13Y, 13M, and 13C have ROSs 14K, 14Y, 14M, and 14C. Image data (raster data) is sequentially output, and laser beams LB emitted according to the image data from these ROSs 14K, 14Y, 14M, and 14C are scanned on the surfaces of the respective photosensitive drums 15K, 15Y, 15M, and 15C. Exposure is performed to form an electrostatic latent image. The electrostatic latent images formed on the photoconductor drums 15K, 15Y, 15M, and 15C are respectively developed by the developing units 17K, 17Y, 17M, and 17C, so that black (K), yellow (Y), magenta (M), and cyan ( C) is developed as a toner image of each color.

  Each color of black (K), yellow (Y), magenta (M), and cyan (C) sequentially formed on the photosensitive drums 15K, 15Y, 15M, and 15C of the image forming units 13K, 13Y, 13M, and 13C. The toner images are transferred in multiple by primary transfer rolls 26K, 26Y, 26M, and 26C onto an intermediate transfer belt 25 as an intermediate transfer member disposed below each of the image forming units 13K, 13Y, 13M, and 13C. . The intermediate transfer belt 25 is wound around the drive roll 27, the stripping roll 28, the steering roll 29, the idle roll 30, the backup roll 31, and the idle roll 32 with a constant tension. A drive roll 27 that is rotationally driven by a dedicated drive motor with excellent constant speed (not shown) is circulated at a predetermined speed in the direction of the arrow. As the transfer belt 25, for example, a flexible synthetic resin film such as polyimide is formed in a band shape, and both ends of the synthetic resin film formed in a band shape are connected by means such as welding, thereby forming an endless belt shape. What was formed in is used.

  The black (K), yellow (Y), magenta (M), and cyan (C) toner images transferred onto the transfer belt 25 in multiple layers are pressed against each other by the secondary transfer roll 33 that is pressed against the backup roll 31. The recording paper 34 is secondarily transferred onto the recording paper 34 by force and electrostatic force, and the toner image of each color is transferred to the fixing device 37 by the two transport belts 35 and 36. The recording paper 34 onto which the toner images of the respective colors have been transferred undergoes a fixing process with heat and pressure by a fixing device 37 and is discharged onto a discharge tray 38 provided outside the copying machine main body 1.

  As shown in FIG. 2, the recording paper 34 has a predetermined size from any of a plurality of paper feed trays 39, 40, 41, and a pair of paper feed rollers 42 and a pair of paper transport rollers 43, 44, The paper is once transported to a registration roll 47 through a paper transport path 46 composed of 45. The recording paper 34 supplied from any of the paper feed trays 39, 40, 41 is sent onto the intermediate transfer belt 25 by a registration roll 47 that is rotationally driven at a predetermined timing. Then, in the four image forming units 13K, 13Y, 13M, and 13C of black, yellow, magenta, and cyan, as described above, the black, yellow, magenta, and cyan toner images respectively have predetermined timings. Are formed in order.

  The photosensitive drums 15K, 15Y, 15M, and 15C are subjected to the next image forming process after the toner image transfer process is completed and the residual toner and paper dust are removed by the cleaning devices 18K, 18Y, 18M, and 18C. Prepare for. Further, residual toner is removed from the intermediate transfer belt 25 by a belt cleaner 48.

(6. Hardware configuration etc.)
FIG. 24 is a block diagram illustrating a hardware configuration of the image forming apparatus. As shown in the figure, this image forming apparatus has a configuration in which a controller 910 and an engine unit 960 are connected via a PCI (Peripheral Component Interconnect) bus. A controller 910 is a controller that controls the entire image forming apparatus, image reading, image processing, and input from an operation unit (not shown). The engine unit 960 is an image processing engine that can be connected to a PCI bus, and includes, for example, an image processing part such as error diffusion and gamma conversion for acquired image data.

  The controller 910 includes a CPU 911, a north bridge (NB) 913, a system memory (MEM-P) 912, a south bridge (SB) 914, a local memory (MEM-C) 917, and an ASIC (Application Specific Integrated Circuit). 916 and a hard disk drive 918, and the North Bridge 913 and the ASIC 916 are connected by an AGP (Accelerated Graphics Port) bus 915. The MEM-P 912 further includes a ROM (Read Only Memory) 912a and a RAM (Random Access Memory) 912b.

  The CPU 911 performs image formation control of the image forming apparatus and overall control of the image forming apparatus. The CPU 911 includes a chip set including the NB 913, the MEM-P 912, and the SB 914, and is connected to other devices via the chip set. Is done.

  The NB 913 is a bridge for connecting the CPU 911 and the MEM-P 912, SB 914, and AGP 915, and includes a memory controller that controls reading and writing to the MEM-P 912, a PCI master, and an AGP target.

  The MEM-P 912 is a system memory used as a memory for storing programs and data, a memory for developing programs and data, and the like, and includes a ROM 912a and a RAM 912b. The ROM 912a is a read-only memory used as a memory for storing programs and data. The RAM 912b is a writable and readable memory used as a memory for developing programs and data, an image drawing memory during image processing, and the like.

  The SB 914 is a bridge for connecting the NB 913 to a PCI device and peripheral devices. The SB 914 is connected to the NB 913 via a PCI bus, and a network interface (I / F) unit (not shown) and the like are also connected to the PCI bus.

  The ASIC 916 is an integrated circuit (IC) for multimedia information processing having hardware elements for multimedia information processing, and has a role of a bridge for connecting the AGP 915, the PCI bus, the HDD 918, and the MEM-C 917, respectively.

  The ASIC 916 includes a PCI target and an AGP master, an arbiter (ARB) that forms the core of the ASIC 916, a memory controller that controls the MEM-C 917, and a plurality of DMACs (Direct Memory) that perform image data rotation by hardware logic or the like. A Universal Serial Bus (USB) 940 and an IEEE (The Institute of Electrical and Engineering Engineers 1394) interface 950 are connected between the Access Controller and the engine unit 960 via a PCI bus.

  The MEM-C 917 is a local memory used as an image buffer for transmission and a code buffer, and the HDD 918 is a storage for storing image data, programs, font data, and forms.

  The AGP 915 is a bus interface for a graphics accelerator card that has been proposed to speed up graphics processing. The AGP 915 speeds up the graphics accelerator card by directly accessing the MEM-P 912 with high throughput.

  The keyboard 920 connected to the ASIC 916 receives an operation input from the operator, and transmits the operation input information received by the ASIC 916.

  An image forming program executed by the image forming apparatus of the present embodiment is a file in an installable or executable format, such as a CD-ROM, a flexible disk (FD), a CD-R, a DVD (Digital Versatile Disk), or the like. You may comprise so that it may record and provide on a computer-readable recording medium.

  Furthermore, the image forming program executed by the image forming apparatus of the present embodiment may be stored on a computer connected to a network such as the Internet and provided by being downloaded via the network. Alternatively, it may be configured to be provided or distributed via a network such as the Internet.

  The image forming program executed by the image forming apparatus according to the present embodiment includes the above-described units (image forming unit, image measuring unit, image quality calculating unit, failure predicting unit, state information acquiring unit, communication unit, history storage unit, input) Module, and a process control unit). As actual hardware, the CPU (processor) reads the image forming program from the ROM and executes it to load each unit onto the main storage device. Then, an image forming unit, an image measuring unit, an image quality calculating unit, a failure predicting unit, a state information acquiring unit, a communication unit, a history storage unit, an input unit, a process control unit, and the like are generated on the main storage device. ing.

  The embodiment of the present invention and the examples thereof described above are examples for description, and the present invention is not limited to these examples described here.

  As described above, the image forming apparatus, the image forming method, the program for causing the computer to execute the method, and the recording medium according to the present invention are useful for the image forming technology, and particularly useful for the image forming technology for printing out on recording paper. It is.

2 is a functional block diagram of a main part of the image forming apparatus according to Embodiment 1. FIG. 1 is a schematic configuration diagram illustrating a tandem type digital color printer as an image forming apparatus according to Embodiment 1. FIG. It is a functional block diagram of an image measurement part. It is a schematic diagram which shows an example of the image pattern for a measurement which the image formation part by embodiment forms. It is a figure explaining the operation | movement which a pattern detection part detects. It is a figure explaining the light beam which illuminates the image pattern for a measurement. It is a graph which shows the granularity with respect to the standard deviation of a dot area. It is a schematic diagram which shows having divided | segmented the measurement pattern into the rectangular area | region which contains 1 dot in each area | region. It is the graph which showed the gradation property with respect to the product of the average area of a dot, and the number of lines used for the output. It is the graph which showed the result of having performed MTF prediction using the line width and the edge width of a line by (3) Formula by MTF in the spatial frequency of 6c / mm. 3 is a flowchart illustrating an image forming procedure according to the first embodiment. It is a flowchart explaining the procedure of failure prediction. 6 is a functional block diagram of an image forming apparatus according to Embodiment 2. FIG. 10 is a flowchart illustrating an image forming procedure according to the third embodiment. 6 is a functional block diagram of an image forming apparatus according to Embodiment 3. FIG. 10 is a flowchart illustrating an image forming procedure according to the third embodiment. 3 is a schematic diagram of an operation panel portion of the image forming apparatus. FIG. It is a flowchart explaining the image formation procedure by a modification. FIG. 10 is a functional block diagram of an image forming apparatus according to a fourth embodiment. 10 is a flowchart illustrating an image forming procedure according to the fourth embodiment. It is a graph showing the increase in the failure probability with respect to the number of output sheets. It is a flowchart explaining the image formation procedure by a modification. 1 is a configuration diagram of a tandem type digital color printer as an image forming apparatus according to a first embodiment; FIG. 2 is a block diagram illustrating a hardware configuration of such an image forming apparatus.

Explanation of symbols

210 Image formation unit 220 Image measurement unit 230 Image quality calculation unit 240 Failure prediction unit 250 History storage unit 260 Communication unit 270 Input unit 280 Status information acquisition unit 290 Process control unit 295 Notification unit

Claims (21)

In an image forming apparatus for forming an image of an electrostatic latent image formed on a photoreceptor by an electrophotographic process,
Image pattern measuring means for measuring at least the shape of an image pattern formed on at least one of the photosensitive member and the intermediate transfer member;
An image quality prediction means for predicting the quality of the output image based on the measurement of the image pattern by the image pattern measurement means;
History information storage means for storing history information of image quality prediction by the image quality prediction means;
Failure prediction means for predicting failure using history information by the history information storage means;
An image forming apparatus comprising: A status information acquisition unit configured to acquire status information of the image forming apparatus;
The history information storage means stores history information of state information by the state information acquisition means,
The image forming apparatus according to claim 1, wherein the failure prediction unit predicts a failure based on history information of the state information stored by the history information storage unit. An image forming condition adjusting unit that adjusts an image forming process condition based on the image quality prediction by the image quality predicting unit;
The status information acquisition unit acquires status information of the image forming apparatus based on an image formation process condition adjusted by the image formation condition adjustment unit,
The history information storage means stores history information of state information by the state information acquisition means,
The image forming apparatus according to claim 2, wherein the failure prediction unit predicts a failure based on history information of the state information stored in the history information storage unit. The failure prediction means includes
Measurement of an image pattern by the image pattern measuring means,
Image quality prediction by the image quality prediction means;
After repeating the adjustment of the process conditions by the image forming condition adjusting unit and the measurement of the image pattern based on the adjustment of the process conditions by the image pattern measuring unit at least once,
The image forming apparatus according to claim 3, wherein the failure prediction unit predicts a failure based on the history information stored in the history information storage unit. The image forming apparatus includes image forming units having different colors.
The image pattern measuring unit measures an image pattern for each of the image forming units having different colors.
The image quality prediction means predicts the quality of the output image for each color based on the measurement of the image pattern for each color by the image pattern measurement means,
The history information storage means stores an image quality prediction for each color by the image quality prediction means,
The failure prediction means predicts a failure based on history information of image quality prediction for each color stored in the history information storage means, according to any one of claims 1 to 4. The image forming apparatus described. When the image forming apparatus performs dot output,
The image pattern measuring means comprises the average area of the dots constituting the image pattern, the standard deviation of the average area of the dots, the average circle equivalent diameter of the dots, the standard deviation of the average circle equivalent diameter of the dots, and the image pattern The image formation according to claim 1, wherein at least one of a line width of a line to be performed and an edge width of the line is measured to measure an image pattern. apparatus. When the image forming apparatus performs image output with toner,
7. The image pattern measuring unit measures image patterns by excluding image information corresponding to toner images formed with a predetermined size or less from the measured image information. The image forming apparatus according to any one of the above. The image pattern measuring means is
Illumination means for illuminating with a light beam substantially parallel to the image pattern,
An imaging unit that forms an image by specularly reflecting the light flux of the illumination unit on at least one of the photosensitive member and the intermediate transfer member;
A photoelectric conversion element that photoelectrically converts an image formed by the imaging means; and an image analysis means that analyzes image information photoelectrically converted by the photoelectric conversion element, and measures at least a shape of the image pattern. The image forming apparatus according to claim 1, wherein the image forming apparatus is an image forming apparatus.   9. The image quality predicting means predicts at least one of graininess, gradation, and sharpness as the quality of an output image. The image forming apparatus described. When the image forming apparatus performs dot output,
The image quality predicting means predicts the granularity by calculating at least one of a standard deviation of a dot area and a standard deviation of a dot circle equivalent diameter. The image forming apparatus according to claim 1. When the image forming apparatus performs dot output,
The image quality predicting means calculates the linearity of the gradation characteristic curve from at least one of the dot area average and the dot circle equivalent diameter average and a predetermined number of lines for generating a gradation image for the gradation property. The image forming apparatus according to claim 1, wherein the image forming apparatus predicts the image.   The image quality prediction means predicts the sharpness by calculating an MTF at a specific spatial frequency from a line width and a line edge width. The image forming apparatus described.   The failure prediction means sets the Mahalanobis distance of each characteristic value calculated by the image pattern measurement means to a reference space of the characteristic value set in advance for an image group in which the image forming apparatus is determined to be in failure. The image forming apparatus according to claim 1, wherein a failure prediction value is calculated based on the calculated Mahalanobis distance. Transmitting means for transmitting at least one of the measurement of the image pattern, the history information of the measurement of the image pattern, the failure prediction, and the history information of the failure prediction to a terminal connected via a network;
The image forming apparatus according to claim 1, further comprising:   The image forming apparatus according to claim 14, wherein the transmission unit transmits the at least one information to the terminal registered in advance at a predetermined cycle through the network. If it is determined that the failure prediction is greater than or equal to a predetermined value set in advance, further comprising notification means for making a decision to notify the failure prediction to the pre-registered terminal,
The image forming apparatus according to claim 15, wherein the transmission unit is configured to transmit the failure prediction to the previously registered terminal based on the determination of the notification unit.   The image forming apparatus according to claim 16, wherein the notification unit changes a transmission cycle in accordance with failure prediction by the failure prediction unit.   The image forming apparatus according to claim 1, wherein the failure predicting unit also calculates a predicted failure value for each part constituting the image forming apparatus. An image forming method in an image forming apparatus for forming an image of an electrostatic latent image formed on a photoreceptor by an electrophotographic process,
An image pattern measuring step for measuring at least the shape of the image pattern formed on at least one of the photosensitive member and the intermediate transfer member by an image pattern measuring unit;
An image quality prediction step of predicting the quality of the output image based on the measurement of the image pattern in the image pattern measurement step by the image quality prediction means;
A history information storage step of storing history information of image quality prediction in the image quality prediction step by history information storage means;
A failure prediction step of predicting a failure using the history information in the history information storage step by a failure prediction means;
An image forming method comprising:   A program for causing a computer to execute the image forming method according to claim 19.   A computer-readable storage medium storing the program according to claim 20.

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