CN112284779B - Printer performance identification method and identification device - Google Patents
Printer performance identification method and identification device Download PDFInfo
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- CN112284779B CN112284779B CN202011050017.XA CN202011050017A CN112284779B CN 112284779 B CN112284779 B CN 112284779B CN 202011050017 A CN202011050017 A CN 202011050017A CN 112284779 B CN112284779 B CN 112284779B
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- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
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Abstract
The invention discloses a printer performance identification method and an identification device, wherein the identification method comprises the steps of selecting the type series and the geometric error detection items of a printer; counting geometric errors; calculating the signal-to-noise ratio of each geometric error of each type series of printers; respectively calculating the performance factor of each type series of printers; the performance of each type series of printers was evaluated. According to the technical scheme, the geometric errors are used as the basis for evaluating the performance of the SLM3D printer, the signal-to-noise ratio of each geometric error of each type series printer is calculated according to the value of each geometric error of the printer, the performance factor of one type series printer is calculated by using the obtained signal-to-noise ratio, and the performance factor value is helpful for identifying the performance of each type series printer. According to the technical scheme, the geometric errors are used as the basis for evaluating the performance of the SLM3D printer, and compared with the prior art, the accuracy is high.
Description
Technical Field
The invention relates to the technical field of printers, in particular to a performance identification method of a 3D printer and an identification device for realizing the method.
Background
The performance evaluation of the product refers to the evaluation of the product by carrying out various detections on the product and integrating various detection results, and the purpose of the performance evaluation of the product is to provide a reference for optimizing the performance of the product.
The performance evaluation for the SLM3D printer involved dimensional errors as well as geometric errors. The performance evaluation scheme of the conventional SLM3D printer only takes the dimensional error as the basis of performance evaluation, that is, the performance evaluation scheme of the conventional SLM3D printer takes the dimensional error between the theoretical design value of the workpiece and the actual dimensional value of the workpiece as the basis of performance evaluation. Furthermore, the performance evaluation scheme of the conventional SLM3D printer is only a performance evaluation result for a single device as a final result of performance evaluation of the entire type-series SLM3D printer.
In summary, the performance evaluation scheme of the conventional SLM3D printer is based on a single parameter, which results in a poor accuracy of the performance evaluation result of the SLM3D printer and does not have the value of a comprehensive consideration of the performance evaluation of certain type series of SLM3D printers.
Disclosure of Invention
The invention aims to provide a performance identification method of a 3D printer and an identification device for realizing the method, so as to solve one or more technical problems in the prior art and provide at least one beneficial selection or creation condition.
The technical scheme adopted for solving the technical problems is as follows:
a printer performance identification method includes the following steps:
step 100, selecting a type series of a printer, and selecting a geometric error detection item of the printer;
step 200, counting various geometric errors of various products printed by printers of different types and series aiming at various products printed by printers of various types and series;
step 300, calculating the signal-to-noise ratio of each geometric error of each type series of printers;
step 400, respectively calculating the performance factor of each type series of printers according to the signal-to-noise ratio of each geometric error of the printers of the same type series;
step 500, evaluating the performance of each type series of printers according to the performance factor of each type series of printers;
the geometric error is a geometric mapping representing relative and real image relationship error;
in the step 300, the expected large characteristic signal-to-noise ratio of the geometric error of each type series of printers is calculated through formula 1, the expected large characteristic signal-to-noise ratio of the geometric error of each type series of printers is calculated through formula 2, and the expected small characteristic signal-to-noise ratio of the geometric error of each type series of printers is calculated through formula 3:
wherein
The desired characteristic signal-to-noise ratio representing the geometric error,
the signal-to-noise ratio of the desired characteristic representing the geometric error,
signal-to-noise ratio representing the desired small characteristic of the geometric error, n representing the number of geometric errors of the printer, yiA value representing a geometric error of the printer,
an average value representing a geometric error of the printer, z a target value of the quality characteristic, SnRepresents the standard deviation of a geometric error of the printer,
in step 400, the performance factor of each type series of printers is calculated by the following formula:
where r represents a performance factor of a printer of one type series, m represents the number of geometric error detection items of a printer of one type series,
a signal-to-noise ratio representing a geometric error of a series of types of printers, the signal-to-noise ratio being either a desired characteristic signal-to-noise ratio or a desired characteristic signal-to-noise ratio.
As a further improvement of the above technical solution, in the step 100, the geometric error detection items of the printer include at least one of straightness, flatness, roundness, cylindricity, curve profile, surface profile, position, concentricity, symmetry, circular deflection, total deflection, parallelism, perpendicularity and inclination.
The invention also discloses a printer performance identification device, which comprises:
setting means for selecting a type series of the printer, and selecting a geometric error detection item of the printer;
the input device is used for counting various geometric errors of various products printed by the printers of different types and series aiming at various products printed by the printers of various types and series;
first calculating means for calculating the signal-to-noise ratio of each geometric error of each type series of printers;
the second calculating device is used for respectively calculating the performance factor of each type series of printers according to the signal-to-noise ratio of each geometric error of the same type series of printers;
identifying means for evaluating the performance of each type series of printers based on the performance factor of each type series of printers;
the geometric error is a geometric mapping representing relative and real image relationship error;
the first calculation means calculates a desired characteristic signal-to-noise ratio of the geometric error of the printer of each type series by formula 1, a desired characteristic signal-to-noise ratio of the geometric error of the printer of each type series by formula 2, and a desired characteristic signal-to-noise ratio of the geometric error of the printer of each type series by formula 3:
wherein
The signal-to-noise ratio of the desired characteristic representing the geometric error,
the signal-to-noise ratio of the desired characteristic representing the geometric error,
signal-to-noise ratio representing the desired small characteristic of the geometric error, n representing the number of geometric errors of the printer, yiA value representing a geometric error of the printer,
representing an average value of a geometric error of the printer, z representing a target value of the quality characteristic, SnRepresenting the standard deviation of a geometric error of the printer,
the second calculation means calculates a performance factor of each type series of printers by the following formula:
where r represents a performance factor of a printer of one type series, m represents the number of geometric error detection items of a printer of one type series,
a signal-to-noise ratio representing a geometric error of a series of types of printers, the signal-to-noise ratio being either a desired characteristic signal-to-noise ratio or a desired characteristic signal-to-noise ratio.
As a further improvement of the above technical solution, in the setting device, the geometric error detection items of the printer include at least one of straightness, flatness, roundness, cylindricity, curved section, surface profile, position, concentricity, symmetry, circular deflection, total deflection, parallelism, perpendicularity, and inclination.
The invention has the beneficial effects that: according to the technical scheme, the geometric errors are used as the basis for evaluating the performance of the SLM3D printer, the signal-to-noise ratio of each geometric error of each type series printer is calculated according to the value of each geometric error of the printer, the performance factor of one type series printer is calculated by using the obtained signal-to-noise ratio, and the performance factor value is helpful for identifying the performance of each type series printer. According to the technical scheme, the geometric errors are used as the basis for evaluating the performance of the SLM3D printer, and compared with the prior art, the accuracy is high.
Drawings
The invention is further described with reference to the accompanying drawings and examples;
FIG. 1 is a flow chart illustrating a printer performance identification method according to the present invention.
Detailed Description
Reference will now be made in detail to the present preferred embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to like elements throughout.
In the description of the present invention, it should be understood that the orientation or positional relationship referred to in the description of the orientation, such as the upper, lower, front, rear, left, right, etc., is based on the orientation or positional relationship shown in the drawings, and is only for convenience of description and simplification of description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus, should not be construed as limiting the present invention.
In the description of the present invention, if words such as "a plurality" are described, the meaning is one or more, the meaning of a plurality is two or more, more than, less than, more than, etc. are understood as excluding the present number, and more than, less than, etc. are understood as including the present number.
In the description of the present invention, unless otherwise specifically limited, terms such as set, installation, connection and the like should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above terms in the present invention by combining the specific contents of the technical solutions.
Referring to fig. 1, the present application discloses a printer performance identification method, a first embodiment of which includes the steps of:
step 100, selecting a type series of a printer, and selecting a geometric error detection item of the printer;
step 200, counting various geometric errors of various products printed by printers of different types and series aiming at various products printed by printers of various types and series, wherein a plurality of printers of different types and series are configured;
step 300, calculating the signal-to-noise ratio of each geometric error of each type series of printers;
step 400, respectively calculating the performance factor of each type series of printers according to the signal-to-noise ratio of each geometric error of the printers of the same type series;
the performance of each type series of printers is evaluated according to the performance factor of each type series of printers, step 500.
The geometric error in this embodiment is not just a concept of a range error, but a geometric mapping representing relative and true image relationship errors.
In step 100 of this embodiment, for each selected printer type series, the geometric error detection items selected by the printers of each type series may be the same or different.
In this embodiment, the step 500 is specifically to evaluate the performance of each type series of printers according to the performance factor, and the larger the value of the performance factor is, the higher the performance of the type series but the print is.
The embodiment uses the geometric error as the basis of the SLM3D printer performance evaluation, calculates the signal-to-noise ratio of each geometric error of each type series printer according to the value of each geometric error of the printer, and then calculates the performance factor of one type series printer by using the obtained signal-to-noise ratio, wherein the performance factor value is helpful for identifying the performance of each type series printer. In the embodiment, the geometric errors are used as the basis for evaluating the performance of the SLM3D printer, and compared with the prior art, the accuracy is high, and for printers of the same type series, the geometric errors of a plurality of printers are used as the basis for evaluating the performance of the printers of one type series, so that the evaluation result of the performance of the printers of each type series has the value of the comprehensive consideration.
Further preferably, in the present embodiment, in the step 100, the geometric error detection items of the printer include at least one of straightness, flatness, roundness, cylindricity, curve section, surface profile, position, concentricity, symmetry, circular deflection, total deflection, parallelism, perpendicularity and inclination.
Further as a preferred implementation manner, in the present embodiment, in the step 300, the expected characteristic signal-to-noise ratio of the geometric error of each type series of printer is calculated by formula 1, the expected characteristic signal-to-noise ratio of the geometric error of each type series of printer is calculated by formula 2, and the expected characteristic signal-to-noise ratio of the geometric error of each type series of printer is calculated by formula 3:
wherein
The desired characteristic signal-to-noise ratio representing the geometric error,
the signal-to-noise ratio of the desired characteristic representing the geometric error,
signal-to-noise ratio representing the desired small characteristic of the geometric error, n representing the number of geometric errors of the printer, yiA value representing a geometric error of the printer,
representing an average value of a geometric error of the printer, z representing a target value of the quality characteristic, SnRepresenting the standard deviation of a geometric error of the printer,
further as a preferred implementation manner, in the present embodiment, in the step 400, the performance factor of each type series of printers is calculated by the following formula:
where r represents a performance factor of a printer of one type series, m represents the number of geometric error detection items of a printer of one type series,
a signal-to-noise ratio representing a geometric error of a series of types of printers, the signal-to-noise ratio being either a desired characteristic signal-to-noise ratio or a desired characteristic signal-to-noise ratio.
Specifically, in this embodiment, the signal-to-noise ratio of the geometric error used when calculating the performance factor of the printer of one type series needs to be specifically selected to be an expected large characteristic signal-to-noise ratio, an expected target characteristic signal-to-noise ratio, or an expected small characteristic signal-to-noise ratio according to an actual application situation, that is, when calculating the performance factor of the printer of one type series, the signal-to-noise ratios of the geometric error used may be the same kind of signal-to-noise ratio, or may be different kinds of signal-to-noise ratios.
The application also discloses printer performance recognition device simultaneously, its first embodiment includes:
setting means for selecting a type series of the printer, and selecting a geometric error detection item of the printer;
the input device is used for counting various geometric errors of various products printed by printers of different types and series aiming at various products printed by printers of various types and series;
first computing means for computing the signal-to-noise ratio of each geometric error for each series of types of printer;
the second calculating device is used for respectively calculating the performance factor of each type series of printers according to the signal-to-noise ratio of each geometric error of the same type series of printers;
and identification means for evaluating the performance of the printer of each type series based on the performance factor of the printer of each type series.
Further preferably, in this embodiment, the geometric error detection items of the printer in the setting device include at least one of straightness, flatness, roundness, cylindricity, curve profile, surface profile, position, concentricity, symmetry, circular deflection, total deflection, parallelism, perpendicularity, and inclination.
Further preferably, in this embodiment, the first calculating means calculates the expected characteristic signal-to-noise ratio of the geometric error for each type series of printers by using formula 1, calculates the expected characteristic signal-to-noise ratio of the geometric error for each type series of printers by using formula 2, and calculates the expected characteristic signal-to-noise ratio of the geometric error for each type series of printers by using formula 3:
wherein
The desired characteristic signal-to-noise ratio representing the geometric error,
the signal-to-noise ratio of the desired characteristic representing the geometric error,
signal-to-noise ratio of desired characteristic representing geometric error, n representing number of geometric errors of printer, yiA value representing a geometric error of the printer,
representing an average value of a geometric error of the printer, z representing a target value of the quality characteristic, SnRepresenting the standard deviation of a geometric error of the printer,
further as a preferable embodiment, in the present embodiment, the second calculation means calculates the performance factor of each type series of printers by the following formula:
where r represents a performance factor of the printer of one type family, m represents the number of geometric error detection items of the printer of one type family,
a signal-to-noise ratio representing a geometric error of a series of types of printers, the signal-to-noise ratio being either a desired characteristic signal-to-noise ratio or a desired characteristic signal-to-noise ratio.
While the preferred embodiments of the present invention have been illustrated and described, it will be understood by those skilled in the art that the present invention is not limited to the details of the embodiments shown and described, but is capable of numerous equivalents and substitutions without departing from the spirit of the invention as set forth in the claims appended hereto.
Claims (4)
1. A printer performance identification method is characterized in that: the method comprises the following steps:
step 100, selecting a type series of a printer, and selecting a geometric error detection item of the printer;
step 200, counting various geometric errors of various products printed by printers of different types and series aiming at various products printed by printers of various types and series;
step 300, calculating the signal-to-noise ratio of each geometric error of each type series of printers;
step 400, respectively calculating the performance factor of each type series of printers according to the signal-to-noise ratio of each geometric error of the printers of the same type series;
step 500, evaluating the performance of each type series of printers according to the performance factor of each type series of printers;
the geometric error is a geometric mapping representing relative and real image relationship error;
in the step 300, the expected large characteristic signal-to-noise ratio of the geometric error of each type series of printers is calculated through formula 1, the expected large characteristic signal-to-noise ratio of the geometric error of each type series of printers is calculated through formula 2, and the expected small characteristic signal-to-noise ratio of the geometric error of each type series of printers is calculated through formula 3:
wherein
The desired characteristic signal-to-noise ratio representing the geometric error,
the signal-to-noise ratio of the desired characteristic representing the geometric error,
signal-to-noise ratio representing the desired small characteristic of the geometric error, n representing the number of geometric errors of the printer, yiA value representing a geometric error of the printer,
representing an average value of a geometric error of the printer, z representing a target value of the quality characteristic, SnRepresents the standard deviation of a geometric error of the printer,
in step 400, the performance factor of each type series of printers is calculated by the following formula:
where r represents a performance factor of a printer of one type series, m represents the number of geometric error detection items of a printer of one type series,
a signal-to-noise ratio representing a geometric error of a series of types of printers, the signal-to-noise ratio being either a desired characteristic signal-to-noise ratio or a desired characteristic signal-to-noise ratio.
2. The printer capability identifying method according to claim 1, characterized in that: in the step 100, the geometric error detection items of the printer include at least one of straightness, flatness, roundness, cylindricity, curve profile, surface profile, position, concentricity, symmetry, circular deflection, total deflection, parallelism, perpendicularity and inclination.
3. A printer performance recognition apparatus characterized by: the method comprises the following steps:
setting means for selecting a type series of the printer, and selecting a geometric error detection item of the printer;
the input device is used for counting various geometric errors of various products printed by the printers of different types and series aiming at various products printed by the printers of various types and series;
first calculating means for calculating the signal-to-noise ratio of each geometric error of each type series of printers;
the second calculating device is used for respectively calculating the performance factor of each type series of printers according to the signal-to-noise ratio of each geometric error of the same type series of printers;
identifying means for evaluating the performance of each type series of printers based on a performance factor of each type series of printers;
the geometric error is a geometric mapping representing relative and real image relationship error;
the first calculation means calculates a desired characteristic signal-to-noise ratio of the geometric error of the printer of each type series by formula 1, a desired characteristic signal-to-noise ratio of the geometric error of the printer of each type series by formula 2, and a desired characteristic signal-to-noise ratio of the geometric error of the printer of each type series by formula 3:
wherein
The desired characteristic signal-to-noise ratio representing the geometric error,
the signal-to-noise ratio of the desired characteristic representing the geometric error,
signal-to-noise ratio of desired characteristic representing geometric error, n representing number of geometric errors of printer, yiA value representing a geometric error of the printer,
representing an average value of a geometric error of the printer, z representing a target value of the quality characteristic, SnRepresenting the standard deviation of a geometric error of the printer,
the second calculation means calculates a performance factor of each type series of printers by the following formula:
where r represents a performance factor of a printer of one type series, m represents the number of geometric error detection items of a printer of one type series,
signal-to-noise ratio representing a geometric error of a series of types of printer, said signal-to-noise ratio being either a desired characteristic signal-to-noise ratio or a desired characteristic signal-to-noise ratioAnd (4) a signal-to-noise ratio.
4. A printer capability identifying device according to claim 3, characterized in that: in the setting device, the geometric error detection items of the printer comprise at least one of straightness, planeness, roundness, cylindricity, curve section, surface profile, position, concentricity, symmetry, circular deflection, total deflection, parallelism, perpendicularity and inclination.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101055560A (en) * | 2006-04-12 | 2007-10-17 | 株式会社理光 | Printing quality evaluation method and system |
| CN104597125A (en) * | 2014-12-26 | 2015-05-06 | 奥瑞视（北京）科技有限公司 | Ultrasonic detection control method and ultrasonic detection control device for 3D printed piece |
| US9813591B1 (en) * | 2016-07-14 | 2017-11-07 | Global Graphics Software Limited | Systems and methods for managing printing using multiple colorant levels |
| CN109130191A (en) * | 2018-07-27 | 2019-01-04 | 北京鉴衡认证中心有限公司 | Test method, device and the computer equipment of 3D printer performance |
| CN110378011A (en) * | 2019-07-16 | 2019-10-25 | 西安石油大学 | A kind of metal bellows hydraulic bulging process robust design method |
| CN111274720A (en) * | 2019-10-15 | 2020-06-12 | 长沙理工大学 | Inversion identification method for pile foundation model parameters |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100901075B1 (en) * | 2006-11-13 | 2009-06-03 | 주식회사 엘지화학 | Apparatus and Method for inspecting of droplet discharge characteristics of ink-jet printer head |
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Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101055560A (en) * | 2006-04-12 | 2007-10-17 | 株式会社理光 | Printing quality evaluation method and system |
| CN104597125A (en) * | 2014-12-26 | 2015-05-06 | 奥瑞视（北京）科技有限公司 | Ultrasonic detection control method and ultrasonic detection control device for 3D printed piece |
| US9813591B1 (en) * | 2016-07-14 | 2017-11-07 | Global Graphics Software Limited | Systems and methods for managing printing using multiple colorant levels |
| CN109130191A (en) * | 2018-07-27 | 2019-01-04 | 北京鉴衡认证中心有限公司 | Test method, device and the computer equipment of 3D printer performance |
| CN110378011A (en) * | 2019-07-16 | 2019-10-25 | 西安石油大学 | A kind of metal bellows hydraulic bulging process robust design method |
| CN111274720A (en) * | 2019-10-15 | 2020-06-12 | 长沙理工大学 | Inversion identification method for pile foundation model parameters |
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