A printer ink cartridge and its intelligent ink consumption prediction method

Abstract

This invention relates to the field of data processing technology, specifically to a printer ink cartridge and its intelligent ink consumption prediction method, comprising: acquiring ink volume data, printed image data, and drive current data for each printing period; determining the cleaning effectiveness for each printing period based on the differences between ink volume data and printed image data in each printing period, combined with the degree of current distortion; filtering the end times of all printing periods based on the distribution of current distortion in each printing period, combined with the cleaning effectiveness, to determine each clogging cutoff time; filtering the printing periods to obtain standard periods based on the difference distribution of current distortion in printing periods before each clogging cutoff time, wherein the ink volume data of the standard periods is used for ink consumption prediction. This invention ensures the credibility of the input samples of the prediction model, and the higher the reference value of the obtained prediction results, the better.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, specifically to a printer ink cartridge and a method for intelligent prediction of ink consumption. Background Technology

[0002] Water-based ink printer cartridges are consumables specifically designed for inkjet printers. They contain dye-based or pigment-based inks with water as the primary solvent, and are characterized by being environmentally friendly, odorless, and fast-drying. During printing, water-based ink is sprayed from the printhead onto the paper surface, producing vibrant colors and natural transitions, making it suitable for high-precision output scenarios such as photos and documents.

[0003] Intelligent ink consumption prediction for water-based ink printers uses comprehensive analysis of print job characteristics, historical ink consumption data, and printhead status to estimate the amount of ink needed for each print job in advance. This effectively avoids print interruptions, image quality degradation, or printhead damage caused by insufficient ink. Furthermore, intelligent prediction helps users plan ink cartridge replacement times more efficiently, reducing consumable waste and operating costs, thus improving printing efficiency and ensuring print quality.

[0004] In existing technologies, machine learning methods are often used to build predictive models. Input features such as paper size, dot percentage, and ink type, and output ink volume estimates. However, printheads may become clogged during long-term use. Changes in the clogging state directly affect the actual ink consumption, resulting in the actual ink consumption of the samples used for machine learning being too low. This leads to low reliability of the training samples and low reference value of the ink volume prediction results. Summary of the Invention

[0005] To address the technical problem that existing methods fail to consider abnormal ink consumption due to clogging in their training samples, resulting in low reliability of the training samples, this invention aims to provide an intelligent prediction method for printer ink cartridges and their ink consumption. The specific technical solution adopted is as follows:

[0006] In a first aspect, the present invention provides a method for intelligent prediction of ink consumption of a printer ink cartridge, comprising:

[0007] Acquire ink volume data, printed image data, and drive current data for each printing period when executing a printing task. Between two adjacent printing periods, there is one ink cartridge cleaning operation.

[0008] Based on the differences in ink volume data and printed image data between each printing period, the cleaning effectiveness for each printing period is obtained by combining the degree of current distortion; the degree of current distortion is used to characterize the changes in driving current data within a local time interval in each printing period.

[0009] Based on the distribution of current distortion in each printing period and the effectiveness of the cleaning, the end times of all printing periods are screened to determine the cutoff time for each blockage.

[0010] Based on the difference distribution of current distortion during the printing period before each blockage cutoff time, standard printing periods are obtained by filtering the printing periods. The ink volume data of the standard printing periods are used for ink consumption prediction.

[0011] Preferably, the step of determining the cleaning effectiveness for each printing period based on the differences in ink volume data and printed image data during each printing period, combined with the degree of current distortion, specifically includes:

[0012] Based on the differences in ink volume data between each printing period and other printing periods, as well as the differences in printed image data, the degree of ink loss in each printing period is obtained;

[0013] Based on the difference in drive current data between adjacent moments within each local time interval in each printing period, and the drive current data at each moment, the degree of current distortion in each local time interval in each printing period is obtained.

[0014] The local time interval is obtained by uniformly dividing a printing period.

[0015] Based on the degree of current distortion in the first and last local time intervals of each printing period, and in conjunction with the degree of ink loss, the initial clogging degree and the final clogging degree of each printing period are obtained respectively.

[0016] The difference between the final clogging level of each printing period and the initial clogging level of the adjacent previous printing period is normalized to obtain the cleaning effectiveness of each printing period.

[0017] Preferably, the step of determining the degree of ink loss for each printing period based on the differences in ink volume data between each printing period and other printing periods, as well as the differences in printed image data, specifically includes:

[0018] Based on the difference in ink volume data between each reference printing period and the target printing period, the loss index corresponding to each reference printing period is determined;

[0019] Print image data refers to the rasterized image of each printing period; based on the grayscale value of each pixel in each channel of the print image data of each printing period, a color vector for each printing period is constructed.

[0020] The similarity index of ink demand for each reference printing period is obtained by negatively correlating the magnitudes of the difference vectors between the color vectors of each reference printing period and the target printing period.

[0021] The ink consumption loss level for the target printing period is obtained by weighting and summing the loss indices corresponding to each reference printing period using the ink demand similarity index; where the target printing period refers to any printing period, and the reference printing period refers to other printing periods besides the target printing period.

[0022] Preferably, the step of obtaining the current distortion degree of each local time interval in each printing period based on the difference in drive current data between adjacent moments within each local time interval in each printing period, and the drive current data at each moment, specifically includes:

[0023] For any local time interval in any printing period, obtain the difference between the drive current data at each moment and the minimum value of all drive current data to obtain the first difference coefficient; obtain the absolute value of the difference between the drive current data at each moment and the adjacent previous moment to obtain the second difference coefficient.

[0024] The degree of current distortion in the local time interval is determined based on the product of the first difference coefficient and the second difference coefficient within the local time interval.

[0025] Preferably, the step of obtaining the initial clogging degree and the final clogging degree for each printing period based on the current distortion degree of the first and last local time intervals in each printing period, combined with the ink loss degree, specifically includes:

[0026] The initial clogging level of each printing period is determined by multiplying the current distortion level of the first local time interval in each printing period with the ink loss level of that printing period.

[0027] The product of the current distortion level in the last local time interval of each printing period and the ink loss level in that printing period is determined as the termination clogging level of that printing period.

[0028] Preferably, the step of filtering the end times of all printing periods based on the distribution of current distortion during each printing period and the effectiveness of cleaning, to determine the cutoff time for each blockage, specifically includes:

[0029] The degree of blockage degradation for each printing period is obtained based on the difference in the degree of current distortion between adjacent local time intervals in each printing period, and the difference in the degree of current distortion between the last local time interval and the first local time interval.

[0030] The degree of blockage cessation for each printing period is determined by multiplying the negative correlation coefficient between the degree of blockage deterioration and the degree of cleaning effectiveness for each printing period.

[0031] The last moment of the printing period corresponding to a blockage cutoff level greater than or equal to the preset cutoff threshold is taken as the blockage cutoff time.

[0032] Preferably, the step of obtaining the degree of blockage degradation for each printing period based on the difference in current distortion between adjacent local time intervals within each printing period, and the difference in current distortion between the last local time interval and the first local time interval, specifically includes:

[0033] For any given printing period, the difference in current distortion between the last local time interval and the first local time interval is used to determine the increase in congestion.

[0034] When the increase in congestion is less than or equal to the preset congestion threshold, the degree of congestion degradation during the printing period is set to the preset value;

[0035] When the increase in congestion exceeds a preset congestion threshold, the sum of the absolute values ​​of the differences in current distortion between adjacent local time intervals is used to obtain the congestion change magnitude; the product of the ratio of the increase in congestion magnitude to the congestion change magnitude and the increase in congestion magnitude is used as the congestion degradation degree during the printing period; the preset value is less than the congestion degradation degree at this time.

[0036] Preferably, the step of filtering the printing time periods to obtain standard time periods based on the difference distribution of current distortion levels during the printing period before each blockage cutoff time specifically includes:

[0037] Each suspected congestion cycle is obtained by dividing all printing periods into segments based on the congestion cutoff time.

[0038] Based on the difference in the degree of congestion deterioration between each printing period and other printing periods within each suspected congestion cycle, the degree of congestion onset for each printing period within each suspected congestion cycle is obtained;

[0039] For each suspected congestion cycle, the printing period between the printing time corresponding to the maximum degree of congestion onset and the printing time at the end of the congestion constitutes the actual congestion cycle; other printing periods besides the actual congestion cycle are used as standard periods.

[0040] Preferably, the step of determining the degree of blockage initiation for each printing period within each suspected blockage cycle based on the difference in the degree of blockage deterioration between each printing period and other printing periods within each suspected blockage cycle specifically includes:

[0041] For any suspected congestion period, the selected printing period and all subsequent printing periods are obtained as the first printing period, and all printing periods before the selected printing period are obtained as the second printing period; wherein, the selected printing period is any one of the suspected congestion periods;

[0042] The difference between the fluctuation coefficient of the degree of clogging degradation in all printing periods of the first printing cycle and the fluctuation coefficient of the degree of clogging degradation in all printing periods of the second printing cycle is used as the degree of clogging initiation in the selected printing period.

[0043] In a second aspect, the present invention provides a printer ink cartridge, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the computer program is executed by the processor, it implements the steps of an intelligent prediction method for ink consumption of a printer ink cartridge.

[0044] The embodiments of the present invention have at least the following beneficial effects:

[0045] This invention first acquires various data points during printing periods between cleaning operations. Then, it analyzes the differences in ink consumption data for each printing period, and simultaneously analyzes the changes in drive current data within local time intervals of each printing period, comprehensively evaluating the cleaning effectiveness of the cleaning operations preceding each printing period. Furthermore, it analyzes the distortion degree of current pulse changes and quantifies the aggravation characteristics of distortion degree within printing periods, thereby achieving detailed quantification of the clogging degree to screen out the clogging termination time point. Finally, based on the continuous difference distribution of current distortion degree before the clogging termination time, it accurately locates the clogging start time point to screen out standard periods without clogging. Standard periods represent periods unaffected by clogging, and their data parameters are realistic. Using the various parameter data under standard periods for ink consumption prediction ensures the credibility of the input samples of the prediction model. Higher reference value of the obtained prediction results improves the accuracy of ink consumption prediction. Attached Figure Description

[0046] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 This is a flowchart of the steps of an intelligent prediction method for ink consumption of printer ink cartridges provided by the present invention.

[0048] Figure 2This is a flowchart of the steps in the method for obtaining the cleaning effectiveness provided by the present invention;

[0049] Figure 3 This is a schematic diagram of the distribution of drive current data under normal conditions provided by the present invention;

[0050] Figure 4 This is a schematic diagram of the distribution of drive current data under blocked conditions provided by the present invention;

[0051] Figure 5 This is a flowchart of the steps for obtaining the blockage cutoff time provided by the present invention. Detailed Implementation

[0052] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a printer ink cartridge and its intelligent ink consumption prediction method according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0053] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0054] The following description, in conjunction with the accompanying drawings, details the specific scheme of a printer ink cartridge and its intelligent ink consumption prediction method provided by the present invention.

[0055] Please see Figure 1 The diagram illustrates a flowchart of a method for intelligently predicting ink consumption of a printer cartridge according to an embodiment of the present invention. The method includes the following steps:

[0056] Step S100: Obtain ink volume data, printed image data, and drive current data for each printing period when executing the printing task. Among them, there is a cartridge cleaning operation between two adjacent printing periods.

[0057] During printing, prolonged exposure of the nozzles to air can lead to ink evaporation, dust ingress, or ink deposition, resulting in issues such as missing prints or uneven ink ejection, causing problems like broken lines and color deviations. In some embodiments, cleaning operations can be performed periodically or after detecting blockages. Methods such as suction, ejection, and scraping remove residual impurities and dried ink while keeping the nozzles moist, ensuring stable ink droplet ejection, consistent print quality, and extended printhead life.

[0058] One possible approach is to schedule automatic cleaning operations for each print job. For example, in high-frequency printing scenarios, such as continuously printing high-resolution photos where ink deposition is rapid, the printer can schedule an automatic cleaning operation (e.g., every 20 pages). In other embodiments, where a single print job has a short printing duration or uses little ink, and ink deposition is not a concern, automatic cleaning can be scheduled after multiple print jobs. It should be noted that the specific method for performing the cleaning operation needs to be tailored to the specific implementation scenario. This embodiment only collects data from a historical database based on recorded cleaning operation periods. Furthermore, it should be understood that automatic ink cartridge cleaning is a well-known technology and will not be discussed in detail here.

[0059] In this embodiment, parameter data from multiple dimensions within a historical time period are obtained from the printer's historical database. Then, the historical time period is divided into multiple sub-time periods based on the cleaning operation period. The time range within each sub-time period for executing printing tasks is defined as the printing time period. The cleaning operation period refers to the time range within which the printer performs automatic cleaning operations. It should be understood that there is an automatic cartridge cleaning operation between each printing time period and the next adjacent printing time period.

[0060] Then, in each printing period, the drive current data of the printer at each moment when the printing task is performed is obtained in chronological order, the ink volume data at the last moment of the printing task in the printing period is obtained, and the printed image data after the single page is printed is obtained.

[0061] More specifically, drive current data reflects the actual current state of the printhead during operation. As a concrete example, a Hall effect current sensor can be used to collect the current data of the connection line between the output of the drive chip and the input of the printhead coil. The printer driver converts the print job into a rasterized image that the printer can recognize, recorded as print image data. This image is in pixels, with each pixel containing ink volume information for the four CMYK color channels, typically represented by grayscale values ​​from 0-255. Higher values ​​correspond to greater ink volume requirements for that color. Ink volume data refers to the total ink consumption within a printing period after the print job is completed, and this data can be collected from the printer's cloud database.

[0062] Therefore, it should be understood that a printing period may correspond to one or more print jobs, or a partial stage of a print job. A printing period corresponds to ink volume data, drive current data, and one or more printed image data.

[0063] Step S200: Based on the differences between ink volume data and printed image data in each printing period, and combined with the degree of current distortion, the cleaning effectiveness corresponding to each printing period is obtained; the degree of current distortion is used to characterize the change of driving current data in a local time interval in each printing period.

[0064] The main purpose of this step is to determine the printhead clogging status by quantifying ink usage anomalies and drive current changes during the printing period, and ultimately evaluate the actual effect of the ink cartridge cleaning operation, providing key evidence for subsequent screening of reliable sample intervals.

[0065] Firstly, printhead clogging directly leads to a lower actual ink volume than required, resulting in abnormal ink volume data and loss of print quality. However, relying solely on ink volume data from a single printing period is insufficient to distinguish whether the difference in ink volume is due to clogging or a difference in ink volume requirements inherent in the printing task itself. Therefore, it is necessary to combine data analysis results from both ink usage requirements and printing needs to jointly determine the true ink loss in each printing period.

[0066] Secondly, the ink consumption data changes slowly, and the quantification method based on printing time periods cannot capture the process of clogging worsening within a single printing time period. For example, if the clogging gradually worsens during printing, the real-time change of the drive current can directly reflect the nozzle ejection state. Therefore, it is necessary to quantify the degree of current distortion within a printing time period by detecting changes in the drive current data.

[0067] Finally, by combining the results of feature analysis from both aspects, the effectiveness of the cleaning operations preceding each printing period is accurately assessed, thus providing a data foundation for subsequently evaluating the reference value of ink volume data within the printing period. For example... Figure 2 As shown, the method for obtaining the cleaning effectiveness can be implemented by steps S201 to S204.

[0068] Step S201: Based on the differences in ink volume data between each printing period and other printing periods, as well as the differences in printed image data, the degree of ink loss in each printing period is obtained.

[0069] If two printing sessions have highly similar ink volume requirements but significantly different actual ink usage, it's highly likely that one of the printing sessions experienced printhead clogging, resulting in ink loss. Relying solely on ink volume data might mistakenly classify a high-ink-volume-demand task as unclogging, or a low-ink-volume-demand task as clogged. Therefore, it's necessary to couple the ink volume difference with the similarity of ink volume requirements by assessing the degree of ink loss, achieving a preliminary quantification of the clogging status and laying the foundation for subsequent accurate judgment. Based on this, the steps for obtaining the degree of ink loss are as follows:

[0070] The first step is to determine the loss index for each reference printing period based on the difference in ink volume data between each reference printing period and the target printing period.

[0071] The target printing period refers to any printing period, while the reference printing period refers to other printing periods besides the target printing period.

[0072] Specifically, the difference in ink volume data between each reference printing period and the target printing period is calculated. When the difference is greater than 0, it indicates that the ink consumption of each reference printing period is greater than that of the target printing period. In this case, further analysis can be conducted to determine whether the ink consumption requirements of the printing tasks between the two periods are the same or similar. If so, it indicates that a blockage occurred in the target printing period, resulting in less ink consumption than the reference printing period. When the difference is less than 0, it indicates that the reference printing period itself may have experienced blockage, leading to even less ink consumption, or that the ink consumption of the target printing period may be relatively normal. Therefore, using this type of data to assess the ink consumption loss of the target printing period has little reference value, and no data analysis is performed on it.

[0073] Therefore, for the target printing period, when the difference in ink volume data corresponding to each reference printing period is less than 0, the ink consumption loss index of the reference printing period for the target printing period is 0. When the difference in ink volume data corresponding to each reference printing period is greater than 0, this difference is used as the ink consumption loss index of the corresponding reference printing period for the target printing period.

[0074] As a concrete example, taking the i-th printing period as the target printing period and the n-th reference printing period of the i-th printing period as an example, the method for obtaining the loss index of the n-th reference printing period relative to the target printing period can be expressed by the formula: ;in, Let i represent the loss index of the nth reference printing time period relative to the target printing time period, where i represents the i-th printing time period, which is also the target printing time period. This represents the ink volume data for the nth reference printing period within the target printing period. Indicates ink volume data for the target printing period; This represents the function that takes the maximum value.

[0075] Finally, each reference printing period represents the difference in the amount of ink ejected from the printhead during printing compared to the target printing period. In other words, it uses each reference printing period as a reference to analyze the degree of difference in the actual ink consumption between the two printing periods, and also reflects the amount of ink that the target printing period may consume less of due to clogging compared to each reference printing period.

[0076] The second step is to construct a color vector for each printing period based on the grayscale value of each pixel in each channel of the printed image data for each printing period.

[0077] It should be understood that printed image data refers to the rasterized image of each printing period. Each pixel contains color information in four channels, usually represented by grayscale values ​​of 0-255. The higher the value, the greater the color ink requirement of the corresponding printing task. Therefore, the color vector of a single printing period can be constructed by combining the grayscale values ​​of all pixels in each channel of all printed image data in a single printing period.

[0078] As a concrete example, the sum of grayscale values ​​of all pixels in each channel is calculated for each printing period. For example, the sum of the four channels is C=5000, M=3200, Y=2800, and K=4500 respectively. Then, the color vector for each printing period is constructed in the form of [C value, M value, Y value, K value].

[0079] The only factor that determines the amount of ink used is the color distribution and intensity of the printed image data, and thus the color vector represents the actual ink usage requirement for each printing period.

[0080] The third step is to perform negative correlation processing on the magnitude of the difference vector between the color vectors of each reference printing period and the target printing period to obtain the ink volume demand similarity index corresponding to each reference printing period.

[0081] As a concrete example, the ink demand similarity index corresponding to the nth reference printing period of the i-th printing period can be expressed as: ;in, This represents the ink demand similarity index corresponding to the nth reference printing time period for the i-th printing time period, where i represents the i-th printing time period, which is also the target printing time period. The modulus of the difference vector between the color vector of the nth reference printing time period and the color vector of the target printing time period; and the normalization function, which can be the minimization normalization method, without restriction.

[0082] The ink volume demand similarity index characterizes the degree of similarity between the theoretical ink volume demand of the reference printing period and the target printing period. The larger the value, the closer the theoretical ink volume demand between the two, and the smaller the value, the greater the difference in theoretical ink volume demand between the two.

[0083] The fourth step is to use the ink demand similarity index to perform a weighted summation of the loss index corresponding to each reference printing period to obtain the ink loss level of the target printing period.

[0084] When the theoretical ink requirements of the reference printing period and the target printing period are closer, the greater the actual ink usage in the reference printing period compared to the target printing period, the more severe the clogging may occur in the target printing period, resulting in ink loss. Therefore, for the target printing period, the ink requirement similarity index of each reference printing period can be used as a weight, and the weighted sum of the loss indices corresponding to each reference printing period can be used to obtain the degree of ink loss in the target printing period.

[0085] In other embodiments, considering the high similarity between the theoretical ink requirements of the reference printing period and the target printing period, the reference value of the actual ink usage difference between the corresponding reference printing period and the target printing period is higher. Therefore, the reference printing period corresponding to an ink requirement similarity index greater than or equal to a preset similarity threshold can be used as a high-value reference period. Then, the loss index corresponding to each high-value reference period is weighted and summed using the ink requirement similarity index of each high-value reference time to obtain the ink usage loss degree of the target printing period. As a specific example, the similarity threshold can be 0.6, and the implementer can set it according to the specific implementation scenario. The main purpose is to select printing periods with relatively close theoretical ink requirements from other printing periods to evaluate ink usage loss.

[0086] Thus, this step quantifies the ink loss caused by clogging in a single printing period by combining the differences in ink volume across all similar printing periods based on the degree of ink loss. The higher the degree of ink loss, the greater the probability of clogging in that period and the more significant the impact of clogging.

[0087] Step S202: Based on the difference in drive current data between adjacent moments within each local time interval in each printing period, and the drive current data at each moment, the degree of current distortion in each local time interval in each printing period is obtained.

[0088] The local time interval is obtained by uniformly dividing a printing period. Specifically, each printing period is uniformly divided to obtain each local time interval. More specifically, each printing period is divided into 10 local time intervals. In other embodiments, the implementer can divide the intervals according to the actual situation. The purpose is to perform feature analysis on the distribution of changes in drive current data within the local time range of each printing period.

[0089] like Figure 3 As shown, under normal conditions, the drive current presents as regular rectangular pulses, meaning the pulse top is stable and the edges transition smoothly. Figure 4As shown, when the nozzle experiences slight clogging, the heat dissipation environment of the ink chamber changes, and the local temperature rises more rapidly. This leads to a rapid increase in the temperature of the resistive region, making it difficult for the current to maintain a stable rectangular state. This manifests as an early drop in the current waveform or distortion, reflecting a decrease in ejection efficiency and unstable droplet volume. Therefore, the calculation logic for the degree of current distortion essentially focuses on the stability of the pulse core region, achieving distortion quantification through the coupling of two dimensions. It should be noted that the above describes the current variation characteristics of thermally induced inkjet printheads; this embodiment of the invention only analyzes the current variation characteristics of thermally induced inkjet printheads.

[0090] Based on this, for any local time interval in any printing period, the difference between the driving current data at each moment and the minimum value of all driving current data is obtained to obtain the first difference coefficient; the absolute value of the difference between the driving current data at each moment and the adjacent previous moment is obtained to obtain the second difference coefficient; based on the product of the first difference coefficient and the second difference coefficient in the local time interval, the degree of current distortion in the local time interval is determined.

[0091] As a concrete example, taking the m-th local time interval within the i-th printing period as an illustration, the method for obtaining the current distortion degree within the m-th local time interval of the i-th printing period can be expressed by the formula:

[0092]

[0093] in, This represents the degree of current distortion in the m-th local time interval within the i-th printing period. This represents the drive current data at time x within the m-th local time interval of the i-th printing period. This represents the minimum value of all drive current data. This represents the absolute value of the difference between the drive current data at time x and time x-1. This represents the total number of moments contained within the m-th local time interval; Represents the normalized activation function. This represents the normalization function, which can be achieved using the minimax normalization method; no restrictions are imposed here.

[0094] This reflects the lower and more stable portions on both sides of a normal nozzle pulse, which is the basic stable range of the current. Firstly, the first difference coefficient is used to distinguish whether the current monitoring time point is located in the pulse core region. A large value indicates that the current is in the core region of the pulse peak at that moment. Under normal conditions, the current in this region should be highly stable. This is a sensitive area for distortion caused by blockage, and it is necessary to pay closer attention to whether there are large fluctuations in the current changes at adjacent moments. When When the value is small or 0, it indicates that the current is in the pulse edge transition region or the basic stable region at that moment. Under normal conditions, the current in this region itself changes and is not the main area where blockage distortion occurs. Therefore, the attention to the current change at adjacent moments is relatively small.

[0095] The first difference coefficient essentially characterizes the deviation of the current from the relatively stable baseline at each moment, giving higher weight to current fluctuations in the pulse core region and lower weight to fluctuations in the stable baseline region.

[0096] Second difference coefficient The main function is to quantify the fluctuation range of the current between adjacent moments, which is the direct basis for judging whether the current is stable. In the normal pulse core region, the second difference coefficient should be close to 0, that is, the current is stable and there is no fluctuation; in the pulse core region when blocked, the second difference coefficient increases significantly, that is, the current fluctuates violently and the waveform is distorted; in the basic stable region / edge region, even if there are small fluctuations in the second difference coefficient, it is mostly a normal transition and not caused by blockage.

[0097] The degree of current distortion in each local time interval is weighted by the difference in current relative to the stable base region at each moment within the local time interval. The current difference fluctuations at adjacent moments are weighted and averaged to focus the distortion judgment on the current fluctuations in a short period of time.

[0098] Step S203: Based on the degree of current distortion in the first and last local time intervals of each printing period, and in conjunction with the degree of ink loss, obtain the initial clogging degree and the final clogging degree for each printing period.

[0099] The degree of ink loss characterizes the macroscopic impact of clogging, while the degree of current distortion characterizes the microscopic clogging state. The main purpose of this step is to accurately quantify the clogging start and end states for each printing period by coupling ink loss and current distortion.

[0100] The degree of ink loss reflects the macroscopic clogging effect throughout the printing period, while the degree of current distortion in a local current range reflects the microscopic clogging state at a specific time.

[0101] Specifically, the product of the current distortion level in the first local time interval of each printing period and the ink loss level of that printing period is determined as the initial clogging level of that printing period; the product of the current distortion level in the last local time interval of each printing period and the ink loss level of that printing period is determined as the final clogging level of that printing period.

[0102] More specifically, for any printing period, the initial clogging level = ink loss level × current distortion level of the first local time interval, which describes the clogging state at the beginning of the printing period; the final clogging level = ink loss level × current distortion level of the last local interval, which describes the clogging state at the end of the printing period.

[0103] Step S204: Normalize the difference between the final clogging level of each printing period and the initial clogging level of the adjacent previous printing period to obtain the cleaning effectiveness of each printing period.

[0104] At any given moment, printhead cleaning essentially involves removing dried ink, air bubbles, or impurities from the nozzle orifice through methods such as suction. Therefore, the degree of clogging after cleaning is generally less than before. If the observed ink loss before and after cleaning is significantly reduced and the jet current distortion is noticeably lessened, it indicates that cleaning has effectively restored nozzle patency. In this case, it can be considered that the cleaning has most likely resolved the printhead clogging problem, and the printhead's jetting performance has been restored.

[0105] For any given cleaning operation, if the cleaning is effective, the initial level of clogging during the printing session after cleaning should be significantly lower than the level of clogging at the end of the printing session before cleaning. A larger value for the cleaning effectiveness indicates a significant reduction in clogging after cleaning, demonstrating a significant cleaning effect. A smaller value indicates that cleaning may not have resolved the clogging problem (e.g., clogging impurities were not removed), providing a direct basis for subsequent judgment on whether cleaning can restore normal operation.

[0106] In this embodiment, the normalization process can adopt the minimax normalization method, and there is no restriction. The implementer can choose according to the specific implementation scenario.

[0107] Step S300: Based on the distribution of current distortion in each printing period and the effectiveness of cleaning, the end times of all printing periods are screened to determine the blockage cutoff time.

[0108] The main purpose of this step is to accurately pinpoint the moment when the blockage is completely relieved and there is no further deterioration (i.e., the blockage cutoff moment) from the printing period where blockage fluctuations occur. This process relies on two key pieces of information: firstly, the distribution trend of the current distortion degree reflects whether the blockage continues to worsen; secondly, the effectiveness of the cleaning reflects whether the cleaning has truly resolved the blockage. Only by coupling these two pieces of information can we avoid misjudging temporary blockage relief as complete cutoff, or missing the situation where blockage remains after cleaning.

[0109] Based on the above logic, such as Figure 5 As shown, the calculation needs to be broken down step by step through steps S301 to S303 to achieve accurate screening of the blockage cutoff time.

[0110] Step S301: Based on the difference in current distortion between adjacent local time intervals in each printing period, and the difference in current distortion between the last local time interval and the first local time interval, the degree of blockage degradation for each printing period is obtained.

[0111] The main purpose of this step is to quantify the worsening trend of congestion within a single printing period. The degree of current distortion can only reflect the congestion status in a local time interval. It is necessary to determine whether the congestion is continuously worsening, fluctuating and easing, or remaining stable by analyzing the distortion differences between adjacent local intervals.

[0112] If some nozzles on the printhead become clogged during a printing session, the condition tends to gradually worsen as printing continues. This is because clogging leads to incomplete nozzle ejection, localized ink deposits, or air bubble accumulation, preventing ink droplets from forming and being ejected properly. Simultaneously, prolonged operation with clogged nozzles accelerates ink drying or impurity buildup, further reducing ejection stability. As a result, the clogging condition during that printing session gradually worsens, progressing from minor ink breaks to noticeable ink gaps, eventually affecting overall ink consumption and print quality.

[0113] Based on this, taking any printing period as an example, the first step is to obtain the difference in the degree of current distortion between the last local time interval and the first local time interval in the printing period to obtain the blockage increase.

[0114] The increase in congestion during each printing period reflects the overall severity of the congestion. When the increase in congestion is less than or equal to a preset congestion threshold, the degree of congestion deterioration during the printing period is set to a preset value.

[0115] In this embodiment, the congestion threshold is set to 0, and the preset value is also set to 0. In other embodiments, the implementer may set the preset value to a very small positive number, such as 0.01, depending on the specific implementation situation. That is, when the increase in congestion during the printing period is less than or equal to 0, it indicates that the congestion during the printing period has been alleviated. Setting the deterioration level directly to 0 indicates that there is no continuous worsening of the congestion during the printing period, or the possibility of continuous worsening of the congestion is extremely small.

[0116] More specifically, if the initial blockage during the printing period is very minor (such as only the attachment of tiny dust particles), and the ink flow rate occasionally disperses the impurities during the printing process (without cleaning operation), the degree of blockage may be reduced. In this case, the total increment is negative, and its distortion and deterioration degree is directly set to 0, that is, there is currently no blockage or deterioration.

[0117] Furthermore, when the increase in congestion exceeds a preset congestion threshold, the sum of the absolute values ​​of the differences in current distortion between adjacent local time intervals is obtained to determine the magnitude of the congestion change. The product of the ratio of the increase in congestion to the magnitude of the congestion change and the increase in congestion is taken as the degree of congestion degradation during the printing period. The preset value is less than the degree of congestion degradation at this time.

[0118] When the increase in congestion during the printing period exceeds the congestion threshold, it indicates that there is a high probability that the congestion will continue to worsen during the printing period. Further characteristic analysis is needed, taking into account the differences in the degree of current distortion.

[0119] As a concrete example, the method for obtaining the distortion and degradation level of the i-th printing time period can be expressed by the formula:

[0120]

[0121] in, This indicates the degree of distortion and degradation in the i-th printing time period. This represents the degree of current distortion in the Mth local time interval of the i-th printing period, where M represents the number of local time intervals within the i-th printing period. This indicates the degree of current distortion in the first local time interval of the i-th printing period. This represents the degree of current distortion in the d-th local time interval of the i-th printing period. This indicates the degree of current distortion in the (d-1)th local time interval of the i-th printing period. This is a normalization function, which implementers can set according to specific implementation scenarios, such as the max-min normalization method.

[0122] Increase in congestion This represents the total weight indicating the degree of congestion during the current i-th printing period. A larger value indicates more severe distortion. (The magnitude of the congestion change is also mentioned.) It represents the sum of the absolute values ​​of the differences in the degree of current distortion among all adjacent local current intervals, and essentially characterizes the total fluctuation of the degree of blockage among adjacent local current intervals.

[0123] The monotonically increasing characteristic reflecting the severity of blockage indicates whether the degree of blockage represented by current distortion is increasing, serving as a reliability indicator. If the degree of blockage continues to worsen without fluctuation (ideally a monotonically increasing trend), then the change in the degree of blockage between adjacent local current intervals... All values ​​are positive, and the sum of their absolute values ​​equals the total increment. At this point, the ratio reaches its maximum, indicating the highest confidence in the continued worsening of the blockage. If the degree of blockage fluctuates (e.g., it first worsens and then eases), the change in the degree of blockage between adjacent local current intervals is also significant. The values ​​may alternate between positive and negative, and the sum of the absolute values ​​is greater than the total increment. If the ratio is less than 1, it indicates that the credibility of the congestion continuing to worsen is low.

[0124] The degree of increase in the overall current distortion during the i-th printing period is used to describe the degree of degradation and characterize the magnitude of the overall increase in blockage. The degree of distortion degradation during the current printing period is comprehensively characterized by combining the confidence level with the magnitude of the overall increase in blockage, indicating the severity of blockage degradation during the current printing period.

[0125] Step S302: Determine the degree of blockage cutoff for each printing period based on the product of the negative correlation coefficient between the degree of blockage deterioration and the degree of cleaning effectiveness.

[0126] The main purpose of this step is to couple the trend of continuous worsening of clogging within a single printing period with the cleaning effect, quantify the reliability of clogging cessation during the printing period, and reflect whether the cleaning before that printing period was effective.

[0127] As a concrete example, calculate the degree of congestion degradation during the i-th printing period. negative correlation coefficient The product of the negative correlation coefficient and the cleaning effectiveness in the i-th printing period is normalized to obtain the blockage closure level in the i-th printing period. This represents an exponential function with the natural constant e as its base. The normalization method can be the minimax normalization method, and the implementer can choose according to the specific implementation scenario.

[0128] A higher value for the degree of clogging degradation during a printing period indicates that the clogging persists after cleaning, and the reliability of clogging cessation for that printing period is lower. Conversely, a lower value indicates that the clogging does not worsen after cleaning, the clogging is alleviated, and the reliability of clogging cessation for that printing period is higher.

[0129] A lower value for the cleaning effectiveness during the printing period indicates that the cleaning before the printing period was ineffective or had a poor effect, the blockage persisted, and the reliability of the blockage termination during the corresponding printing period was low. Conversely, a higher value for the cleaning effectiveness during the printing period indicates that the cleaning before the printing period was effective, the blockage was alleviated, and the reliability of the blockage termination during the corresponding printing period was high.

[0130] Step S303: The last moment of the printing period corresponding to the blockage cutoff degree being greater than or equal to the preset cutoff threshold is taken as the blockage cutoff time.

[0131] The higher the value of the blockage cutoff level during a printing period, the higher the reliability of the blockage cutoff during that printing period; the lower the value of the blockage cutoff level during a printing period, the lower the reliability of the blockage cutoff during that printing period.

[0132] In this embodiment, the cutoff threshold is set to 0.8. In other embodiments, the implementer can set this threshold according to the specific implementation scenario. By using the preset cutoff threshold for judgment, low-confidence cases of incomplete blocking can be excluded.

[0133] Step S400: Based on the difference distribution of current distortion degree during the printing period before each blockage cutoff time, the printing period is filtered to obtain a standard period. The ink volume data of the standard period is used for ink consumption prediction.

[0134] The congestion cutoff time only marks the endpoint of complete congestion relief. However, the time sequence between two congestion cutoff times (i.e., the suspected congestion period) is not entirely congested. Each period includes three stages: a non-congested period before congestion, a period of congestion occurrence and worsening, and a non-congested period after cleaning. Directly excluding all periods between two congestion cutoff times would waste a large amount of reliable, non-congested data; failing to locate the congestion start point would mix invalid data from the congested period into the sample. Therefore, it is necessary to accurately filter standard time periods by using the logic of dividing suspected congestion periods → locating the congestion start point → distinguishing between actual congested and non-congested periods, thus balancing data reliability and data utilization.

[0135] Based on this, the first step is to divide all printing periods into each suspected congestion cycle by the congestion cutoff time.

[0136] Specifically, the blockage cutoff time can divide all printing periods into multiple suspected blockage cycles, meaning there is one suspected blockage cycle between two adjacent blockage cutoff times. It should be understood that the period from the first blockage cutoff time to the first printing period constitutes one suspected blockage cycle. Each blockage cutoff time represents a complete resolution of a blockage after cleaning.

[0137] The second step is to determine the degree of blockage initiation for each printing period within each suspected blockage cycle based on the differences in the degree of blockage deterioration between each printing period and other printing periods within each suspected blockage cycle.

[0138] Before the blockage occurs, the degree of blockage degradation fluctuates little during each printing period (the degree of degradation is close to 0 when there is no blockage, and the fluctuation is stable); after the blockage begins, the degree of degradation fluctuates significantly (the degree of degradation increases due to the worsening of the blockage, and the fluctuation increases). Therefore, the degree of blockage initiation can be quantified by the variance of the degree of degradation.

[0139] As a specific example, taking any suspected congestion cycle as an example, the selected printing time period is obtained, which is any printing time period in the suspected congestion cycle.

[0140] Specifically, for any suspected congestion period, the selected printing period and all subsequent printing periods are obtained as the first printing period, and all printing periods before the selected printing period are obtained as the second printing period; the difference between the fluctuation coefficient of the congestion deterioration degree of all printing periods in the first printing period and the fluctuation coefficient of the congestion deterioration degree of all printing periods in the second printing period is taken as the degree of congestion onset of the selected printing period.

[0141] In this embodiment, variance is used to represent the fluctuation coefficient. That is, the variance of the degree of blockage deterioration in all printing periods in the first printing cycle and the variance of the degree of blockage deterioration in all printing periods in the second printing cycle are calculated respectively, and then the difference is calculated to obtain the degree of blockage initiation in the selected printing period.

[0142] If the selected printing period is the starting point of the blockage, then in subsequent printing periods, due to the blockage at home, the degree of blockage deterioration will change from stable to more volatile, resulting in a larger variance for the first printing cycle and a smaller variance for the second printing cycle. At this time, the value of the degree of blockage initiation will be larger.

[0143] If the selected printing period does not have a blockage start point, the fluctuation of the degree of blockage deterioration before and after the selected printing period is relatively small, and the value of the degree of blockage start is smaller.

[0144] The third step is to define the actual congestion cycle as the printing period between the printing period corresponding to the maximum degree of congestion onset and the printing period between the printing period at the end of the congestion; and to define the printing periods other than the actual congestion cycle as the standard periods.

[0145] The printing period corresponding to the maximum degree of blockage in each suspected blockage cycle is the blockage initiation period. The blockage initiation period is the key node for the start of blockage. All printing periods from the first moment of the blockage initiation period to the blockage end time of the suspected blockage cycle are defined as the actual blockage cycle. Blockage exists in all printing periods within this interval. Ink volume data is unreliable due to ink volume loss and must be excluded to avoid using it as a training sample, which would result in low reference value for the prediction results.

[0146] Furthermore, printing periods outside the actual clogging cycle are set as standard periods. During these standard periods, there is no clogging interference, the drive current is stable, and the ink volume data can truly reflect the actual ink consumption requirements of the printing task, which can be used for predictive operations of ink consumption.

[0147] It should be noted that predicting ink consumption based on data from various dimensions during the printing process is a well-known technology, such as using neural network models for prediction. This is not the focus of this embodiment and will not be elaborated upon here. This embodiment focuses on the fact that the standard time period represents the period without interference from clogging, and its data parameters are realistic. Using the parameter data under the standard time period to predict ink consumption ensures the credibility of the input sample of the prediction model. The higher the reference value of the obtained prediction results, the more accurate the ink consumption prediction results can be.

[0148] This invention also provides a printer ink cartridge, including a memory, a processor, and a computer program stored in the memory and running on the processor. When executed by the processor, the computer program implements the steps of an intelligent prediction method for ink consumption of a printer ink cartridge. Since an intelligent prediction method for ink consumption of a printer ink cartridge has already been described in detail, it will not be repeated here.

[0149] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for intelligently predicting ink consumption of a printer cartridge, characterized in that, The method includes the following steps: Acquire ink volume data, printed image data, and drive current data for each printing period when executing a printing task. Between two adjacent printing periods, there is one ink cartridge cleaning operation. Based on the differences in ink volume data and printed image data between each printing period, the cleaning effectiveness for each printing period is obtained by combining the degree of current distortion; the degree of current distortion is used to characterize the changes in driving current data within a local time interval in each printing period. Based on the distribution of current distortion levels during each printing period and the effectiveness of cleaning, the end times of all printing periods are screened to determine the blockage cutoff time for each period. Specifically, this includes: obtaining the blockage degradation level for each printing period based on the differences in current distortion levels between adjacent local time intervals within each printing period, and the differences in current distortion levels between the last local time interval and the first local time interval; determining the blockage cutoff level for each printing period based on the product of the negative correlation coefficient between the blockage degradation level and the effectiveness of cleaning; and taking the last moment of the printing period corresponding to a blockage cutoff level greater than or equal to a preset cutoff threshold as the blockage cutoff time. Based on the difference in the distribution of current distortion during the printing period before each blockage cutoff time, standard periods are obtained by filtering the printing periods. Specifically, this includes: dividing all printing periods into each suspected blockage cycle based on the blockage cutoff time; obtaining the blockage initiation degree of each printing period within each suspected blockage cycle based on the difference in the fluctuation of the blockage deterioration degree between each printing period and other printing periods within each suspected blockage cycle; for each suspected blockage cycle, the printing period between the printing period corresponding to the maximum blockage initiation degree and the blockage cutoff time constitutes the actual blockage cycle; and other printing periods besides the actual blockage cycle are used as standard periods, and the ink volume data of the standard periods are used for ink consumption prediction.

2. The intelligent prediction method for ink consumption of a printer cartridge according to claim 1, characterized in that, The method of determining the cleaning effectiveness for each printing period based on the differences in ink volume data and printed image data during each printing period, combined with the degree of current distortion, specifically includes: Based on the differences in ink volume data between each printing period and other printing periods, as well as the differences in printed image data, the degree of ink loss in each printing period is obtained; Based on the difference in drive current data between adjacent moments within each local time interval in each printing period, and the drive current data at each moment, the degree of current distortion in each local time interval in each printing period is obtained. The local time interval is obtained by uniformly dividing a printing period. Based on the degree of current distortion in the first and last local time intervals of each printing period, and in conjunction with the degree of ink loss, the initial clogging degree and the final clogging degree of each printing period are obtained respectively. The difference between the final clogging level of each printing period and the initial clogging level of the adjacent previous printing period is normalized to obtain the cleaning effectiveness of each printing period.

3. The intelligent prediction method for ink consumption of a printer cartridge according to claim 2, characterized in that, The process of determining the degree of ink loss in each printing period based on the differences in ink volume data between each printing period and other printing periods, as well as the differences in printed image data, specifically includes: Based on the difference in ink volume data between each reference printing period and the target printing period, the loss index corresponding to each reference printing period is determined; Print image data refers to the rasterized image of each printing period; based on the grayscale value of each pixel in each channel of the print image data of each printing period, a color vector for each printing period is constructed. The similarity index of ink demand for each reference printing period is obtained by negatively correlating the magnitudes of the difference vectors between the color vectors of each reference printing period and the target printing period. The ink consumption loss level for the target printing period is obtained by weighting and summing the loss indices corresponding to each reference printing period using the ink demand similarity index; where the target printing period refers to any printing period, and the reference printing period refers to other printing periods besides the target printing period.

4. The intelligent prediction method for ink consumption of a printer cartridge according to claim 2, characterized in that, The process of obtaining the current distortion degree of each local time interval in each printing period based on the difference in drive current data between adjacent moments within each local time interval in each printing period, and the drive current data at each moment, specifically includes: For any local time interval in any printing period, obtain the difference between the drive current data at each moment and the minimum value of all drive current data to obtain the first difference coefficient; obtain the absolute value of the difference between the drive current data at each moment and the adjacent previous moment to obtain the second difference coefficient. The degree of current distortion in the local time interval is determined based on the product of the first difference coefficient and the second difference coefficient within the local time interval.

5. The intelligent prediction method for ink consumption of a printer cartridge according to claim 2, characterized in that, The method of obtaining the initial clogging degree and the final clogging degree for each printing period based on the current distortion degree of the first and last local time intervals in each printing period, combined with the ink loss degree, specifically includes: The initial clogging level of each printing period is determined by multiplying the current distortion level of the first local time interval in each printing period with the ink loss level of that printing period. The product of the current distortion level in the last local time interval of each printing period and the ink loss level of that printing period is determined as the termination clogging level of that printing period.

6. The intelligent prediction method for ink consumption of a printer cartridge according to claim 2, characterized in that, The degree of congestion degradation for each printing period is determined based on the differences in current distortion between adjacent local time intervals within each printing period, and the differences in current distortion between the last local time interval and the first local time interval. Specifically, this includes: For any given printing period, the difference in current distortion between the last local time interval and the first local time interval is used to determine the increase in congestion. When the increase in congestion is less than or equal to the preset congestion threshold, the degree of congestion degradation during the printing period is set to the preset value; When the increase in congestion exceeds a preset congestion threshold, the sum of the absolute values ​​of the differences in current distortion between adjacent local time intervals is used to obtain the congestion change magnitude; the product of the ratio of the increase in congestion magnitude to the congestion change magnitude and the increase in congestion magnitude is used as the congestion degradation degree during the printing period; the preset value is less than the congestion degradation degree at this time.

7. The intelligent prediction method for ink consumption of a printer cartridge according to claim 2, characterized in that, The degree of blockage initiation within each printing period is determined by analyzing the differences in the degree of blockage deterioration between different printing periods within each suspected blockage cycle. This specifically includes: For any suspected congestion period, the selected printing period and all subsequent printing periods are obtained as the first printing period, and all printing periods before the selected printing period are obtained as the second printing period; wherein, the selected printing period is any one of the suspected congestion periods; The difference between the fluctuation coefficient of the degree of clogging degradation in all printing periods of the first printing cycle and the fluctuation coefficient of the degree of clogging degradation in all printing periods of the second printing cycle is used as the degree of clogging initiation in the selected printing period.

8. A printer ink cartridge, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the computer program is executed by the processor, it implements the steps of the intelligent prediction method for ink consumption of a printer cartridge as described in any one of claims 1-7.

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