US-12617202-B2 - Drive waveform creation method, information processing apparatus, and program

US12617202B2US 12617202 B2US12617202 B2US 12617202B2US-12617202-B2

Abstract

A drive waveform creation method, an information processing apparatus, and a program that enable even a technician not having professional knowledge to efficiently create a drive waveform suitable for ejecting liquid to be used. A method of creating a drive waveform to be used for driving a piezoelectric element of a liquid ejection head including the piezoelectric element includes, via one or more processors, predicting flight of liquid to be ejected by the liquid ejection head in a case of inputting an unknown drive waveform using a machine learning model that is trained through machine learning using data related to an actual flight shape of the liquid in a case where each of a plurality of drive waveforms is applied to the piezoelectric element using the liquid and the liquid ejection head, and determining a drive waveform suitable for ejecting the liquid based on the prediction of the flight.

Inventors

Baku Nishikawa
Yuta MIZOUCHI
Yusuke WATADA

Assignees

FUJIFILM CORPORATION

Dates

Publication Date: 20260505
Application Date: 20231129
Priority Date: 20221214

Claims (20)

1 . A drive waveform creation method of creating a drive waveform to be used for driving a piezoelectric element of a liquid ejection head including the piezoelectric element, the drive waveform creation method comprising: via one or more processors, predicting flight of liquid to be ejected by the liquid ejection head in a case of inputting an unknown drive waveform using a machine learning model that is trained through machine learning using data related to an actual flight shape of the liquid in a case where each of a plurality of drive waveforms is applied to the piezoelectric element using the liquid and the liquid ejection head; calculating a waveform feature represented by coordinates in a latent space in smaller dimensions than dimensions of the unknown drive waveform from the unknown drive waveform; causing the trained machine learning model to output a predicted characteristic indicating a flight characteristic of the liquid predicted in a case where the unknown drive waveform is applied by inputting the waveform feature into the trained machine learning model; and determining a drive waveform suitable for ejecting the liquid based on the prediction of the flight including the predicted characteristic.
2 . The drive waveform creation method according to claim 1 , wherein a parameter of the drive waveform includes at least one of a pulse width, a slope, a pulse height, or a pulse interval.
3 . The drive waveform creation method according to claim 1 , wherein a learning phase of the machine learning model includes a step of compressing each of the plurality of drive waveforms into the latent space in smaller dimensions than dimensions of the drive waveform.
4 . The drive waveform creation method according to claim 3 , wherein the drive waveform is converted into coordinates in the latent space by inputting the drive waveform into an autoencoder.
5 . The drive waveform creation method according to claim 3 , wherein in the learning phase, the machine learning model is trained to predict an evaluation value based on the actual flight shape in a case of applying the drive waveform using a correspondence relationship between the coordinates of each of the plurality of drive waveforms in the latent space and the evaluation value.
6 . The drive waveform creation method according to claim 5 , wherein the data related to the actual flight shape includes the evaluation value indicating a characteristic extracted from an image in which the actual flight shape is imaged.
7 . The drive waveform creation method according to claim 5 , wherein the evaluation value includes at least one value indicating a droplet speed, a droplet amount, or whether or not a satellite droplet is present for the liquid ejected from the liquid ejection head.
8 . The drive waveform creation method according to claim 5 , wherein the prediction of the flight includes prediction of the evaluation value, and the one or more processors are configured to: generate one or more of the unknown drive waveforms different from the plurality of drive waveforms; calculate coordinates in the latent space from the unknown drive waveform; calculate the evaluation value predicted from the coordinates of the unknown drive waveform in the latent space using the machine learning model; and determine a drive waveform satisfying a target value by comparing the evaluation value calculated using the machine learning model and the target value with each other.
9 . The drive waveform creation method according to claim 8 , wherein the one or more processors are configured to calculate the coordinates in the latent space from the unknown drive waveform using an autoencoder.
10 . The drive waveform creation method according to claim 1 , wherein the one or more processors are configured to generate a plurality of the unknown drive waveforms different from the plurality of drive waveforms by randomly extracting a value of a parameter of the drive waveform based on a uniform distribution and predict the flight using the machine learning model with respect to each drive waveform.
11 . An information processing apparatus that executes the drive waveform creation method according to claim 1 , the information processing apparatus comprising: the one or more processors; and one or more storage devices in which the machine learning model is stored.
12 . A non-transitory, computer-readable tangible recording medium which records thereon a program for causing, when read by a computer, the computer to execute the drive waveform creation method according to claim 1 .
13 . A drive waveform creation method of creating a drive waveform to be used for driving a piezoelectric element of a liquid ejection head including the piezoelectric element, the drive waveform creation method comprising: via one or more processors, predicting flight of liquid to be ejected by the liquid ejection head in a case of inputting an unknown drive waveform using a machine learning model that is trained through machine learning using data related to an actual flight shape of the liquid in a case where each of a plurality of drive waveforms is applied to the piezoelectric element using the liquid and the liquid ejection head, wherein a learning phase of the machine learning model includes a step of compressing each of the plurality of drive waveforms into a latent space in smaller dimensions than dimensions of the drive waveform, wherein in the learning phase, the machine learning model is trained to predict an evaluation value based on the actual flight shape in a case of applying the drive waveform using a correspondence relationship between coordinates of each of the plurality of drive waveforms in the latent space and the evaluation value, and wherein the machine learning model is a model that outputs an average value and a standard deviation of the evaluation value predicted from the coordinates in the latent space; and determining a drive waveform suitable for ejecting the liquid based on the prediction of the flight.
14 . The drive waveform creation method according to claim 13 , wherein the one or more processors are configured to: generate one or more of the unknown drive waveforms different from the plurality of drive waveforms; calculate coordinates in the latent space from the unknown drive waveform; calculate the average value and the standard deviation of the evaluation value predicted from the coordinates in the latent space using the machine learning model; calculate a probability of the evaluation value exceeding a target value from the average value and the standard deviation of the evaluation value calculated using the machine learning model; and determine a drive waveform of which the probability of exceeding the target value is high as a proper drive waveform.
15 . An information processing apparatus that executes the drive waveform creation method according to claim 13 , the information processing apparatus comprising: the one or more processors; and one or more storage devices in which the machine learning model is stored.
16 . A non-transitory, computer-readable tangible recording medium which records thereon a program for causing, when read by a computer, the computer to execute the drive waveform creation method according to claim 13 .
17 . A drive waveform creation method of creating a drive waveform to be used for driving a piezoelectric element of a liquid ejection head including the piezoelectric element, the drive waveform creation method comprising: via one or more processors, predicting flight of liquid to be ejected by the liquid ejection head in a case of inputting an unknown drive waveform using a machine learning model that is trained through machine learning using data related to an actual flight shape of the liquid in a case where each of a plurality of drive waveforms is applied to the piezoelectric element using the liquid and the liquid ejection head, wherein a learning phase of the machine learning model includes a step of compressing each of the plurality of drive waveforms into a latent space in smaller dimensions than dimensions of the drive waveform, wherein in the learning phase, the machine learning model is trained to predict an evaluation value based on the actual flight shape in a case of applying the drive waveform using a correspondence relationship between coordinates of each of the plurality of drive waveforms in the latent space and the evaluation value, and wherein the one or more processors are configured to, in a case of generating a plurality of the unknown drive waveforms different from the plurality of drive waveforms by randomly extracting a value of a parameter of the drive waveform based on a uniform distribution, clarify a relationship between a distance on the latent space and a variance of the evaluation value in advance through variogram analysis and set a search interval of the drive waveform based on the variogram analysis; and determining a drive waveform suitable for ejecting the liquid based on the prediction of the flight.
18 . The drive waveform creation method according to claim 17 , wherein the search interval is set to be greater than or equal to a distance in which the distance on the latent space and the variance of the evaluation value become uncorrelated with each other based on the variogram analysis.
19 . An information processing apparatus that executes the drive waveform creation method according to claim 17 , the information processing apparatus comprising: the one or more processors; and one or more storage devices in which the machine learning model is stored.
20 . A non-transitory, computer-readable tangible recording medium which records thereon a program for causing, when read by a computer, the computer to execute the drive waveform creation method according to claim 17 .

Description

CROSS-REFERENCE TO RELATED APPLICATION The present application claims priority under 35 U.S.C. § 119(a) to Japanese Patent Application No. 2022-199620 filed on Dec. 14, 2022, which is hereby expressly incorporated by reference, in its entirety, into the present application. BACKGROUND OF THE INVENTION 1. Field of the Invention The present disclosure relates to a drive waveform creation method, an information processing apparatus, and a program, and particularly to a technology for creating a drive waveform to be applied to a liquid ejection head that ejects liquid by driving a piezoelectric element, and to an information processing technology for executing processing thereof. 2. Description of the Related Art In ink jet printing, in a case where ink to be used varies, a flight shape of ink ejected from an ink jet head changes even with a slight change in a physical property value. Thus, it has been a major object to acquire a favorable ejection characteristic. The ejection characteristic may include, for example, landing position accuracy, whether or not a satellite droplet is present, a droplet speed, a droplet amount, and stability. Since the ink jet head that ejects ink by driving a piezoelectric element has a degree of freedom in a drive waveform, a developer generally executes optimization of the drive waveform for each ink to be used. JP2021-160314A discloses a system including an apparatus that ejects a liquid material via an ink jet head, in which the ejecting apparatus includes a unit that acquires identification information of the ink jet head, a unit that supplies a drive pulse for ejecting the liquid material to an actuator of the ink jet head, and a test unit that detects a state of a liquid droplet ejected from the ink jet head. The system further includes a database in which ejection characteristics of individual ink jet heads and identification information of individual ink jet heads are associated with each other, and an optimization unit that provides first optimization information for generating an optimized drive pulse with respect to a tentative attribute assumed with respect to the liquid material to be ejected by the ejecting apparatus based on the ejection characteristic of the ink jet head acquired using the identification information. The optimization unit includes a dynamic optimization unit that detects the state of the liquid droplet ejected using the drive pulse generated based on the first optimization information via the test unit, assumes an actual attribute related to ejection of the liquid material to be ejected based on the ejection characteristic of the ink jet head obtained using the identification information, and provides second optimization information for dynamically optimizing the drive pulse with respect to the assumed actual attribute. SUMMARY OF THE INVENTION In order to optimize the drive waveform with respect to ink to be used, a method of predicting a flight shape of the ink with respect to input of the drive waveform using a physical simulation technique such as an equivalent circuit model or computational fluid dynamics (CFD) has been generally used in the related art. However, in such a method, it is difficult to construct a model used in prediction without high-level knowledge and experience related to fluid dynamics and computation. In addition, a method of determining an optimal drive waveform satisfying a condition of a desired characteristic by selecting a drive waveform from a drive waveform group prepared in advance and evaluating a characteristic of the drive waveform is generally used as a technique of optimizing the drive waveform. However, optimization that accompanies trial and error requires an enormous amount of time. Attempts to shorten a time required for optimizing the drive waveform have been made so far. However, in the general method of the related art, the prepared drive waveform group is limited, and it is impossible to search for a completely unknown drive waveform. The above object is not limited to an ink jet apparatus for printing application and is a common object for apparatuses using a liquid ejection head that ejects various types of functional liquid. The present disclosure is conceived in view of such circumstances, and an object thereof is to provide a drive waveform creation method, an information processing apparatus, and a program that enable a technician not having high-level knowledge and experience related to creating a drive waveform to efficiently create a drive waveform suitable for ejecting ink to be used. A drive waveform creation method according to a first aspect of the present disclosure is a method of creating a drive waveform to be used for driving a piezoelectric element of a liquid ejection head including the piezoelectric element, the drive waveform creation method comprising, via one or more processors, predicting flight of liquid to be ejected by the liquid ejection head in a case of inputting an unknow