CN118377447A - Printer abnormality judgment method and device based on cloud edge cooperation - Google Patents
Printer abnormality judgment method and device based on cloud edge cooperation Download PDFInfo
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Abstract
The application particularly relates to a method and a device for judging printer abnormality based on Yun Bian cooperation. Comprising the following steps: acquiring a target print job of a target printer; acquiring task execution conditions and fault analysis conditions of other printers existing in the working environment of the target printer; if the task execution condition is in task execution and the fault analysis condition indicates that other printers are in a state without potential faults, acquiring current working sound information of the target printer in a working time period; if the fault analysis condition indicates that other printers are in a potential fault state, acquiring current working sound information of the target printer in a working time period under the condition that the task execution condition is that the task execution is completed; determining standard working sound information of a target printer when executing a printing task; and comparing the standard working sound information with the current working sound information, and determining whether the target printer has potential abnormal faults according to the comparison result.
Description
Technical Field
The application relates to the technical field of target printers, in particular to a printer abnormality judgment method and device based on cloud edge cooperation.
Background
A thermal printer is a printer that performs printing using a thermal technique. The principle of operation is that a transparent film is applied to a light-colored material (typically paper) and the film is heated for a period of time to become dark (typically black, also blue). Such printers produce corresponding graphics by selectively heating at certain locations on the thermal paper. Heating is provided by a small electronic heater on the printhead that contacts the thermal material, the heater being logically controlled by the printer in the form of square dots or stripes that when actuated produce a pattern on the thermal paper corresponding to the heating elements. The thermal printer chemical reaction is carried out at a certain temperature, and the high temperature accelerates the chemical reaction. When the temperature is below 60 ℃, the paper needs to go through a considerable length of time, even up to several years, before becoming dark; and when the temperature is 200 c, the reaction is completed in a few microseconds.
In the conventional technology, the conventional abnormality judgment and processing method of the thermal printer has the problems of low efficiency and long time consumption, and the maintenance cost of some printers exceeding the quality protection period becomes high. These problems not only bring inconvenience to the customer, but also may have serious influence on the business of the customer, such as poor printing quality, sudden downtime, etc., thereby affecting the order taking of the customer.
There is still a lack of methods for timely fault detection of printers.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a method and apparatus for determining printer abnormality based on cloud edge cooperation, which can predict a failure of a target printer.
In a first aspect, the present application provides a method for determining printer abnormality based on cloud edge collaboration, including:
acquiring current working sound information and a target printing task of a target printer in a working time period from a working environment of the target printer; the target printing task comprises type information, thickness information, material information, hardness information of printing paper and printing content information in the target printing task;
determining standard working sound information of a target printer when executing a printing task;
and comparing the standard working sound information with the current working sound information, and determining whether the target printer has potential abnormal faults according to the comparison result.
In one embodiment, determining standard working sound information of a target printer when executing a print job includes:
The method comprises the steps that standard working sound information is obtained, wherein the standard working sound information comprises first standard sound information corresponding to a first target component associated with type information in a target printer, second standard sound information corresponding to a second target component associated with thickness information in the target printer, third standard sound information corresponding to a third target component associated with material information in the target printer, fourth standard sound information corresponding to a fourth target component associated with hardness information in the target printer, and fifth standard sound information corresponding to a fifth target component associated with printing content information in the target printer;
And fusing the first standard sound information, the second standard sound information, the third standard sound information, the fourth standard sound information and the fifth standard sound information to obtain standard working sound information of the target printer when executing the printing task.
In one embodiment, the first target component includes at least a print head and a print initiator in the target printer; the second target part comprises at least a paper feeding mechanism, a printing head and a paper conveying roller in the target printer; the third target component comprises at least a paper transport system, a printhead, and a paper sensor in the target printer; the fourth target part comprises at least a paper conveying roller and a conveyor belt, a printing head or a printing roller and a paper sensor or a detector in the target printer; the fifth target component includes at least a paper transport roller and belt, a printhead or print roller, and a paper sensor or detector in the target printer.
In one embodiment, the method further comprises:
and under the condition that the target printer has potential abnormal faults, determining abnormal components in the target printer according to the comparison result.
In one embodiment, fusing the first standard sound information, the second standard sound information, the third standard sound information, the fourth standard sound information and the fifth standard sound information to obtain standard working sound information of the target printer when executing the print task includes:
Determining a first weight corresponding to the first standard sound information, a second weight corresponding to the second standard sound information, a third weight corresponding to the third standard sound information, a fourth weight corresponding to the fourth standard sound information and a fifth weight corresponding to the fifth standard sound information according to interaction conditions among the first standard sound information, the second standard sound information, the third standard sound information, the fourth standard sound information and the fifth standard sound information;
and according to the first weight, the second weight, the third weight, the fourth weight and the fifth weight, fusing the first standard sound information, the second standard sound information, the third standard sound information, the fourth standard sound information and the fifth standard sound information to obtain standard working sound information of the target printer when executing the printing task.
In one embodiment, according to the first weight, the second weight, the third weight, the fourth weight and the fifth weight, the first standard sound information, the second standard sound information, the third standard sound information, the fourth standard sound information and the fifth standard sound information are fused to obtain standard working sound information of the target printer when executing the print task, including:
According to the first weight, the second weight, the third weight, the fourth weight and the fifth weight, fusing the sound characteristics in the first standard sound information, the sound characteristics in the second standard sound information, the sound characteristics in the third standard sound information, the sound characteristics in the fourth standard sound information and the sound characteristics in the fifth standard sound information to obtain standard working sound information of the target printer when executing a printing task;
the sound characteristic information comprises at least one of volume characteristics, frequency characteristics, tone characteristics, maximum volume characteristics, average volume characteristics and energy characteristics of specific frequency components.
In one embodiment, comparing the standard working sound information with the current working sound information to determine an abnormal component in the target printer includes:
Comparing each sound characteristic in the current working sound information with each sound characteristic in the standard sound information to determine an abnormal dimension;
According to the abnormal dimension, determining an abnormal part in the target printer from the first target part, the second target part, the third target part, the fourth target part and the fifth target part.
In one embodiment, if the task execution condition is task execution and the fault analysis condition indicates that other printers are in a state without potential fault, acquiring current working sound information of the target printer in a working time period includes:
If the task execution condition is in task execution and the fault analysis condition indicates that other printers are in a state without potential faults, determining whether sound information generated by other printers during working can cause interference to sound information generated by the target printing working according to relative position information between the other printers and the target printer, sound print information of the other printers and sound print information of the target printer;
And if no interference exists, acquiring current working sound information of the target printer in the working time period. .
In one embodiment, the relative position information between the other printer and the target printer includes distance information between the other printer and the target printer and obstacle information between the other printer and the target printer; determining whether sound information generated by other printers during operation will cause interference to sound information generated by the target printer during operation according to relative position information between the other printers and the target printer, voiceprint information of the other printers and voiceprint information of the target printer, including:
According to the sound propagation model, analyzing distance information between other printers and the target printer and barrier information between other printers and the target printer to obtain propagation conditions of sound information generated by other printers in working environments;
predicting the intensity and sound characteristics of sound information generated by other printers at the target printer position according to the propagation condition of sound information generated by other printers in the working environment;
and if the degree of the disturbance is smaller than the disturbance threshold, and the voiceprint similarity between the voiceprint information of the other printers and the voiceprint information of the target printer is smaller than the similarity threshold, determining that the voice information generated by the other printers in operation cannot cause disturbance to the voice information generated by the target printer in operation. .
The embodiment provides a target printer abnormality judgment device based on cloud edge cooperation, the device comprises:
The sound collection module is used for obtaining current working sound information and a target printing task of the target printer in a working time period from the working environment of the target printer; the target printing task comprises type information, thickness information, material information, hardness information of printing paper and printing content information in the target printing task;
the sound comparison module is used for determining standard working sound information of the target printer when the target printer executes the printing task;
And the abnormal fault identification module is used for comparing the standard working sound information with the current working sound information and determining whether the target printer has potential abnormal faults according to the comparison result.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the related art, the drawings that are needed in the description of the embodiments of the present application or the related technologies will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and other related drawings may be obtained according to these drawings without inventive effort to those of ordinary skill in the art.
FIG. 1 is a flow chart of a method for determining printer anomalies based on Yun Bian cooperation in one embodiment;
FIG. 2 is an internal block diagram of a computer device in one embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
In an exemplary embodiment, as shown in fig. 1, a method for determining printer abnormality based on cloud edge collaboration is provided, including:
Step 101, obtaining a target print job of a target printer.
The target printing task comprises type information, thickness information, material information, hardness information of printing paper and printing content information in the target printing task;
Step 102, acquiring task execution conditions and fault analysis conditions of other printers existing in the working environment of the target printer.
Specifically, before the collection of the sound information of the target printer is started, the task execution condition and the fault analysis condition of other printers in the same working environment are acquired. This may be accomplished by interfacing with an interface of the target printer management system, or by directly querying the status of each target printer.
Step 103, if the task execution condition is that the task is in execution and the fault analysis condition indicates that other printers are in a state without potential faults, acquiring current working sound information of the target printer in a working time period.
If the task execution status of other printers is displayed as "in task execution", and the failure analysis status indicates that these target printers are in a state of no potential failure, the current operation sound information of the target printers can be acquired at this time. Because in this case, sounds generated by other printers operating normally are unlikely to cause significant interference with sound information collection of the target printer.
If the fault analysis condition indicates that other printers are in a potential fault state, acquiring current working sound information of the target printer in a working time period under the condition that the task execution condition is that the task execution is completed.
And 104, if the fault analysis condition indicates that other printers are in a potential fault state, acquiring current working sound information of the target printer in a working time period under the condition that the task execution condition is that the task execution is completed.
If the fault analysis condition shows that the other printers have potential abnormal faults, waiting for the task execution of the target printers to be finished and then collecting sound information. This is to avoid that the abnormal sound generated by the faulty target printer affects the accuracy of the sound information collection of the target printer.
Specifically, a sound recording device (such as a microphone) is used to capture the sound of the target printer when in operation.
Step 105, determining standard working sound information of the target printer when executing the print job.
In particular, manufacturer provided data or standard sound samples may be looked up. By comparing the sounds of the same model of target printer. Historical data or previously collected normal operating sounds are used as references.
And 106, comparing the standard working sound information with the current working sound information, and determining whether the target printer has potential abnormal faults according to the comparison result.
Specifically, the current working sound information collected in step 103 and step 104 is compared with the standard sound information determined in step 105. This may involve comparison of sound waveforms, frequency analysis or comparison of other sound characteristics. Based on the difference in the sound comparison, it can be judged whether or not there is an abnormality in the target printer. For example, if the device sound contains abnormal noise, rub or other non-standard sounds, this may indicate that the target printer is malfunctioning or is about to malfunction.
By adopting the flow, the state of the target printer can be monitored more effectively, and potential problems can be found and processed in time, so that the reliability and the service life of the target printer are improved. The fault detection method based on sound can be used as a non-invasive and real-time monitoring means, and is particularly suitable for detecting internal faults of equipment which are not easy to directly observe or contact.
In an exemplary embodiment, if the task execution condition is task execution and the fault analysis condition indicates that other printers are in a state without potential fault, acquiring current working sound information of the target printer in a working time period includes:
If the task execution condition is in task execution and the fault analysis condition indicates that other printers are in a state without potential faults, determining whether sound information generated by other printers during working can cause interference to sound information generated by the target printing working according to relative position information between the other printers and the target printer, sound print information of the other printers and sound print information of the target printer; and if no interference exists, acquiring current working sound information of the target printer in the working time period.
Alternatively, first, the task execution condition of the other printer is confirmed as "in task execution".
Next, it is confirmed by the fault analysis module that these printers are currently free of potential faults, i.e., they are in a normal operating state. And collecting relative position information between other printers and the target printer. This may involve using sensors, positioning, or a pre-set map to determine the relative distance and orientation between printers. And simultaneously, voiceprint information of other printers and the target printer is acquired. Voiceprint information can be obtained by recording and analyzing voice samples of printers during operation, and can reflect data of unique voice characteristics of each printer. And performing interference assessment by using the collected position information and voiceprint information. This includes analyzing whether sounds generated by other printers operating may overlap or mask the operating sound of the target printer due to too close a distance, similar sound characteristics, or a sound propagation path.
The evaluation can be performed by methods such as an acoustic propagation model, acoustic feature comparison, signal to noise ratio calculation and the like to determine whether interference exists. If it is confirmed through the evaluation that the sound generated when the other printers work does not generate significant interference to the working sound of the target printer, a judgment is made that no interference exists. If there is a risk of interference, it may be necessary to take isolation measures, adjust the printer position, or select other suitable time for sound information collection. And under the condition that no interference is confirmed, starting a sound collection device (such as a microphone) to collect sound information aiming at the target printer. The acquisition process should ensure that the equipment is set correctly and that all relevant sounds of the target printer during the working period can be recorded clearly. The collected sound information is saved as an audio file for subsequent data analysis and processing. These data can be analyzed in detail by specialized voice analysis software to monitor the printer's operating status, identify anomalies, or predict maintenance needs.
In one implementation, the relative position information between the other printers and the target printer includes distance information between the other printers and the target printer and obstacle information between the other printers and the target printer; determining whether sound information generated by other printers during operation will cause interference to sound information generated by the target printer during operation according to relative position information between the other printers and the target printer, voiceprint information of the other printers and voiceprint information of the target printer, including:
01 According to the sound propagation model, analyzing distance information between other printers and the target printer and barrier information between other printers and the target printer to obtain propagation conditions of sound information generated during the work of other printers in the working environment.
In particular, distance information between other printers and the target printer is determined, which may be achieved by physical measurement or using positioning techniques. Obstacle information between other printers and the target printer is identified and recorded, including the type, size, and location of the obstacle, etc. These obstructions may affect the transmission of sound. The sound propagation model is used to analyze the relative position information, in particular the distance and the influence of obstacles on the sound propagation. This model may take into account attenuation, reflection, diffraction of sound and blocking of sound by obstacles.
Specifically, when analyzing the relative position information using the sound propagation model and simulating the sound propagation situation, the following specific algorithm may be adopted:
Step a 1) initializing parameters: the distance (D) between the other printer and the target printer is input. Obstacle information is entered including the position, size, and material characteristics of the obstacle. The propagation speed of sound in air (c, typically 343 m/s) is set. The frequency (f) and source intensity (I0), typically in decibels, of the sound are set.
Step a 2) calculating the sound attenuation: from the distance D, the sound attenuation is calculated using the point sound source attenuation formula. In the absence of an obstacle, the relationship of sound intensity as a function of distance attenuation can be expressed as: i=i0-20×log10 (D/D0), where I0 is the sound intensity at the sound source, D0 is the reference distance (typically 1 meter), and D is the actual distance.
Step a 3) considers the obstacle effect: for each obstacle, its blocking, absorbing and reflecting effects on sound are estimated based on its position, dimensions and material properties. Diffraction theory is used to calculate the attenuation of sound as it bypasses an obstacle. The diffraction attenuation depends on the wavelength of sound (λ=c/f) and the size of the obstacle. If there are multiple obstacles, the interaction between them and the effects of multiple reflections and diffractions need to be considered.
Step a 4) simulates sound propagation: in combination with the effects of sound attenuation and obstructions, the process of sound propagation from the sound source (other printer) to the receiving point (target printer location) is simulated. Wave equation or ray tracing techniques are used to simulate the reflection, diffraction and propagation paths of sound.
Step a 5) calculating the sound intensity and characteristics of reaching the target location: from the simulation result, the intensity (i_target) of the sound when it reaches the target printer position is calculated. Sound features such as frequency distribution, sound pressure level, etc. are extracted, which may vary due to the influence of obstacles and distances.
Step a 6) outputting the result: the simulated sound propagation path, the sound intensity reaching the target location, and the sound characteristics are output. These outputs can be used to evaluate the potential interference of sounds produced by other printers in operation with the target printer sounds.
02 Predicting the intensity and sound characteristics of sound information generated by other printers at the target printer location based on the propagation of sound information generated by other printers in the work environment.
First, it is necessary to acquire sound information including the intensity, frequency distribution, tone, and the like of sound when other printers are operated. This can be achieved by making in-situ measurements using a professional sound recording device or sound level meter while the printer is in operation. The information of the obstacles in the working environment, including their position, size, material and their reflection, absorption and diffraction properties for sound, is recorded in detail. Environmental factors such as temperature, humidity, etc. in the working environment are considered because they may affect the propagation speed of sound. The propagation of sound in the working environment is simulated using a suitable sound propagation model, such as a ray tracing model, wave equation model or statistical model. Sound source data (data collected in step 1) and propagation environment information (data analyzed in step 2) are input. The process of sound propagation from other printers to the target printer location is simulated by the model. Predicting sound intensity at a target printer location typically involves calculation of sound attenuation, taking into account distance attenuation, obstruction, etc. While predicting changes in sound characteristics, such as changes in frequency distribution, changes in tone color, etc., which may occur due to reflection, diffraction, and absorption of sound during propagation. The accuracy of the model is verified by making actual measurements at the target printer location, if possible. And according to the comparison between the actual measurement result and the model prediction result, adjusting the model parameters to improve the prediction accuracy. Predicted sound intensity and sound characteristic data are collated and output. This data may be used to further analyze the potential acoustic interference of other printers to the target printer.
03 Based on the intensity and sound characteristics, determining the degree of interference of sound information generated by other printers with sound information generated by the target printer.
Sound intensity data generated by other printers at the target printer location is acquired, which may be measured in the field by a sound level meter or other sound measurement device. At the same time, sound characteristics of other printers, such as dominant frequency, tone, duration, etc., are recorded. These features may be extracted by audio analysis tools or software. And comparing the sound intensity of other printers with the sound intensity of the target printer in normal operation. If the sound intensity of the other printers is significantly higher than the target printer, the possibility of interference is greater. Comparing the sound characteristics of the two, especially whether the main frequency bands are overlapped. If the dominant frequencies are similar, sound confusion may result, adding to the complexity of the disturbance. One or more interference indicators such as a sound intensity ratio (ratio of other printer sound intensities to target printer sound intensity), a dominant frequency overlap, etc. are set. Based on these metrics, a scoring criterion or algorithm is formulated for quantifying the degree of interference. For example, different thresholds may be set, classifying the interference level into "no interference", "slight interference", "moderate interference" and "severe interference" levels. And (5) carrying out comprehensive evaluation by combining the comparison analysis result of the sound intensity and the sound characteristics and the quantized interference degree index. Other factors are considered, such as the mode of operation of the printer (continuous printing, intermittent printing, etc.), the background noise level of the operating environment, etc., which may also affect the final disturbance evaluation result.
04 If the degree of the disturbance is smaller than the disturbance threshold, and the voiceprint similarity between the voiceprint information of the other printers and the voiceprint information of the target printer is smaller than the similarity threshold, the voice information generated during the operation of the other printers is determined not to cause disturbance to the voice information generated during the operation of the target printer.
If it is determined that there is no interference, current operation sound information of the target printer in the operation period can be collected safely. If there is a risk of interference, measures need to be taken to reduce the interference, such as adjusting the position of the printer, adding sound insulation, or collecting sound information when other printers are not operating.
In one exemplary embodiment, determining standard working sound information of a target printer when executing a print job includes:
11 The acquired standard work sound information includes first standard sound information corresponding to a first target component associated with the type information in the target printer, second standard sound information corresponding to a second target component associated with the thickness information in the target printer, third standard sound information corresponding to a third target component associated with the material information in the target printer, fourth standard sound information corresponding to a fourth target component associated with the hardness information in the target printer, and fifth standard sound information corresponding to a fifth target component associated with the print content information in the target printer.
The first target part at least comprises a spray head and a printing paper guide in the target printer; the second target part comprises at least a paper feeding mechanism, a printing head and a paper conveying roller in the target printer; the third target component comprises at least a paper transport system, a printhead, and a paper sensor in the target printer; the fourth target part comprises at least a paper conveying roller and a conveyor belt, a printing head or a printing roller and a paper sensor or a detector in the target printer; the fifth target component includes at least a paper transport roller and belt, a printhead or print roller, and a paper sensor or detector in the target printer.
It will be appreciated that the first target component mainly includes the nozzle of the target printer and the print initiator. These components are in direct contact with the paper during printing and their operating sound is affected by the paper type. Spray head: the nozzle is a key component in the target printer responsible for ejecting ink or carbon powder to form text and images. Different types of paper have different ink absorption capacities, which can affect the working sound of the nozzle. For example, some coated papers may cause the nozzle to produce a different sound when ejecting ink because the ink diffuses and absorbs at a different rate on the papers than on plain paper. Printing paper guiding device: the print guide is responsible for guiding the paper into the print zone and ensuring that the paper remains in the correct position during printing. Different types of paper may produce different friction sounds and paper movement sounds as they pass through the paper guides, depending on the surface smoothness, thickness and texture of the paper. In order to acquire the first standard sound information associated with the paper type, the following steps may be performed: a series of different types of paper are selected, such as plain paper, photo paper, card paper, etc. And (3) respectively performing printing tests aiming at each paper type, and recording sounds emitted by the spray head and the printing paper guide during operation. These sound data are analyzed, and characteristic sounds corresponding to each paper type are extracted. And establishing a sound database, and matching each paper type with the corresponding standard sound information.
It will be appreciated that the thickness of the sheet directly affects the sound of the feeding mechanism when pushing the sheet, and thicker sheets may produce greater friction and mechanical movement sounds. The sound of contact and movement of the print head will also vary when printing sheets of different thickness. The sound of the paper transport rollers rolling and contacting the paper may also vary as the paper transport rollers transport different thicknesses of paper. A range of different thickness sheets, ranging from tissue to cardboard, are selected to ensure coverage of the various sheet thicknesses that may be encountered by the target printer. Testing was performed in a quiet, well controlled environment to reduce interference from external noise. Ensuring that the recording device (e.g., a high-fidelity microphone) can clearly capture the sound of the target printer when in operation. Printing tests were performed using different thicknesses of paper, respectively. In the testing process, the target printer is ensured to be in a normal working state, and other operations are prevented from interfering with the testing result. During printing, sound emitted by the paper feeding mechanism, the printing head, the paper conveying roller and other parts is captured by using a recording device. Ensures high recording quality for subsequent analysis. And carrying out detailed analysis on the recorded sound data, and extracting characteristic sounds related to the thickness of the paper. These features may include friction sounds during sheet feeding, sounds of the print head contacting the sheet, sounds of the sheet transport rollers rolling, and the like. Classifying and arranging characteristic sounds corresponding to the paper with different thicknesses, and establishing a standard sound information base related to the thickness of the paper. This information base will serve as a reference for future target printer status monitoring and fault diagnosis. And verifying and updating the standard sound information base regularly to ensure the accuracy and timeliness of the standard sound information base. As the target printer ages and parts wear, certain sound characteristics may change, and thus the standard sound information base needs to be updated in time to reflect these changes.
It will be appreciated that different materials of the paper may produce different sounds during transport, for example smooth paper may produce less friction sound, while rough paper may produce more friction sound. When the printing head is contacted with paper made of different materials, the printing sound is different. When detecting paper of different materials, the paper sensor may generate different signal sounds due to different reflection or absorption properties. Collecting paper samples of different materials, such as plain paper, glossy paper, rough paper, coated paper and the like, so as to ensure the diversity of the test samples. The test area is set in an environment with good sound insulation effect and low background noise. Using professional sound recording equipment, it is ensured that subtle sound differences can be captured. For each material sheet, a standardized print job is executed. This may include printing text, images, or specific test patterns. During printing, sound generated when the paper conveying system, the printing head, the paper sensor and other parts work is captured through the recording device. Note that sound data corresponding to each paper material is recorded separately. And processing and analyzing the collected sound data, and extracting the characteristics related to the paper material. This may include sounds of the paper contacting the printhead, friction sounds of the paper during transport, feedback sounds of the paper sensor, and so forth. And (3) filing the characteristic voice arrangement corresponding to each paper material, and establishing a standard voice information database associated with the paper material. In order to ensure the accuracy of the database, multiple tests and verifications of the sound information of different paper materials are required. If the data is found to be abnormal or inconsistent with the reality, timely calibration and adjustment are needed. Once a reliable third standard sound information database is established, it can be applied to daily monitoring and maintenance of the target printer. By comparing the real-time sound data with the standard sound information in the database, the problems possibly encountered by the target printer when processing paper with different materials can be found in time.
It will be appreciated that the stiffness of the paper may affect its contact sound with the conveyor rollers and belt, and that a stiffer paper may produce a clearer, louder impact sound. The print head or print roller also produces different print sounds when in contact with sheets of different hardness. The paper sensor or detector may also have different acoustic characteristics of its feedback signal when detecting paper of different stiffness. The fourth target component mainly includes a sheet transport roller, a conveyor belt, a printhead or a print roller, and a sheet sensor or detector. These components produce unique sounds when handling paper of different hardness. A series of papers of varying hardness were selected for testing, ensuring coverage ranging from softer papers to hard cards. Thus, the sound characteristics of the target printer when processing paper sheets with different hardness can be comprehensively captured. In a quiet test environment to reduce interference from external noise. The use of high quality recording equipment ensures accurate capture and recording of sound when the target printer is in operation. Printing operations are performed using paper sheets of different hardness, respectively, and sound is recorded at the same time. The focus is on the paper transport roller rolling sound, the belt running sound, the sound of the print head or print roller contacting the paper, and the feedback sound of the paper sensor. And carrying out detailed analysis on the recorded sound data, and extracting sound characteristics related to the hardness of the paper. For example, hard paper may produce a more brittle impact sound, while soft paper may produce a more clumsy sound. And correlating the extracted sound characteristics with the corresponding paper hardness, and establishing a comprehensive fourth standard sound information base. This information base will provide an important reference for future target printer status monitoring and fault diagnosis. And through multiple tests and verification, the accuracy and the reliability of the fourth standard sound information base are ensured. In practical application, whether the target printer is in a normal working state or not can be judged by comparing the real-time sound data with the standard sound information, and potential problems can be found in time.
It will be appreciated that differences in print content (e.g., text density, image complexity, etc.) can result in changes in the movement pattern of the printhead and the frequency of printing, resulting in different sound cadences and intensities. For example, when printing large black areas, the print head may continue to operate and produce continuous sound, while when printing sparse text, intermittent sound may occur. In addition, the transmission rollers, conveyor belts, and sensors or detectors may also have different sounds when processing different print content. To fully capture sound features associated with print content, a series of test print content of varying complexity and type needs to be designed. For example, plain text, images, graphics, mixed content, and the like may be included. In addition, the density and distribution of the printed content should be considered to simulate various conditions that may be encountered in actual use. For each test print, a print job is executed and sound is recorded at the same time. During the recording process, the distance and angle between the recording device and the target printer should be ensured to be consistent so as to accurately reflect the sound characteristics. The recorded sound data is analyzed in detail to extract sound features associated with the print content. These features may include the movement sound of the print head, the operating sound of the ink/toner cartridge, the sound variations of the paper transport system when handling different content, etc. By analyzing these features, the performance of the target printer in processing different types and complexity of content can be understood. And associating the extracted sound characteristics with the corresponding printing content, and establishing a comprehensive fifth standard sound information base. This information base will provide an important reference for future target printer status monitoring, fault diagnosis and performance optimization. In order to ensure the accuracy and reliability of the fifth standard sound information base, a plurality of tests and verifications are required. In practical application, whether the state of the target printer is normal when processing the specific printing content can be judged by comparing the real-time sound data with the standard sound information, so that the problem can be found and solved in time. At the same time, this information base can also provide valuable feedback for the design and optimization of the target printer.
12 The first standard sound information, the second standard sound information, the third standard sound information, the fourth standard sound information and the fifth standard sound information are fused to obtain standard working sound information of the target printer when the printing task is executed.
All collected standard sound information is ensured to be subjected to the same preprocessing steps, such as denoising, standardization and the like, so as to ensure the consistency and comparability of the data. And extracting characteristics of the sound information, such as extracting frequency, amplitude, time domain and frequency domain characteristics of the sound, so as to facilitate subsequent data analysis and fusion. The sound features collected from different test conditions are fused. This may be achieved by feature stitching, feature weighting, or other feature fusion techniques. And the relevance among different sound characteristics is considered, the introduction of redundant information is avoided, and the representativeness and the degree of distinction of the fused characteristic set are ensured. A unified data structure is established to store the fused standard sound information. This data structure should be able to accommodate multiple types of sound features and facilitate subsequent data retrieval and analysis. And carrying out normalization processing on the fused data to eliminate dimensional differences among different features and ensure that the fused data have the same weight in subsequent analysis. And taking the fused sound characteristics as the basis of a standard working sound information base. This library will contain sound characteristics associated with various factors such as paper thickness, material, stiffness, print, etc. The information base is indexed and optimized to facilitate quick retrieval and matching of real-time collected target printer sound data. And comparing the standard sound information with sound data of an actual target printer in operation, and verifying the accuracy and the validity of the fused standard sound information. And adjusting the fusion method and parameters according to the verification result to optimize the representation capability of the standard sound information. The fused standard working sound information is applied to state monitoring, fault diagnosis and preventive maintenance of the target printer. With the increase of the service time of the target printer and the abrasion of the components, the standard sound information base is updated periodically to ensure the matching degree of the standard sound information base and the actual target printer state.
In an exemplary embodiment, the method further comprises: and under the condition that the target printer has potential abnormal faults, determining abnormal components in the target printer according to the comparison result.
Correspondingly, the first standard sound information, the second standard sound information, the third standard sound information, the fourth standard sound information and the fifth standard sound information are fused to obtain standard working sound information of the target printer when the printing task is executed, and the method comprises the following steps:
21 According to the interaction condition among the first standard sound information, the second standard sound information, the third standard sound information, the fourth standard sound information and the fifth standard sound information, determining a first weight corresponding to the first standard sound information, a second weight corresponding to the second standard sound information, a third weight corresponding to the third standard sound information, a fourth weight corresponding to the fourth standard sound information and a fifth weight corresponding to the fifth standard sound information.
22 According to the first weight, the second weight, the third weight, the fourth weight and the fifth weight, the first standard sound information, the second standard sound information, the third standard sound information, the fourth standard sound information and the fifth standard sound information are fused, and standard working sound information of the target printer when the printing task is executed is obtained.
Specifically, according to the first weight, the second weight, the third weight, the fourth weight and the fifth weight, the first standard sound information, the second standard sound information, the third standard sound information, the fourth standard sound information and the fifth standard sound information are fused to obtain standard working sound information of the target printer when the printing task is executed, and the method comprises the following steps: according to the first weight, the second weight, the third weight, the fourth weight and the fifth weight, fusing the sound characteristics in the first standard sound information, the sound characteristics in the second standard sound information, the sound characteristics in the third standard sound information, the sound characteristics in the fourth standard sound information and the sound characteristics in the fifth standard sound information to obtain standard working sound information of the target printer when executing a printing task; standard working sound information of the target printer when executing the print job is obtained.
The sound characteristic information comprises at least one of volume characteristics, frequency characteristics, tone characteristics, maximum volume characteristics, average volume characteristics and energy characteristics of specific frequency components.
Specifically, the interaction condition among the first standard sound information, the second standard sound information, the third standard sound information, the fourth standard sound information and the fifth standard sound information is analyzed.
First, key sound features such as volume, frequency, tone, duration, etc. are extracted from each standard sound information. These features need to be quantified as specific values or parameters for subsequent mathematical analysis and comparison. In time domain analysis, waveform changes of a sound signal are observed, and periodic components, transient events, and the like are identified. In the frequency domain analysis, the frequency spectrum distribution of sound is checked by fourier transform or the like to understand the energy and intensity of different frequency components. Statistical methods (e.g., correlation coefficient calculations) are used to analyze the correlation of sound features between different standard sound information. This helps to identify which sound features are interrelated and the degree of association between them. The interaction between different acoustic information is identified by comparing their characteristic changes under the same or similar operating conditions. For example, when the printer performs a specific task, a certain feature in the first standard sound information may change simultaneously with a certain feature in the second standard sound information. The sound information is classified and cluster analyzed using machine learning or pattern recognition techniques.
This helps to identify which sound features are dominant under different operating conditions and how they interact with other sound features. Based on the analysis, a model is constructed to describe the interaction relationship between the different acoustic information. This model may be a statistical model, a physical model, or a machine learning model for predicting changes in acoustic characteristics under given operating conditions.
And respectively determining the corresponding weights, namely a first weight, a second weight, a third weight, a fourth weight and a fifth weight according to the contribution degree of the sound information to the overall sound characteristics of the target printer. Each standard sound information is weighted and fused by using the determined weights (first weight, second weight, third weight, fourth weight, and fifth weight). In the fusion process, the sound features (such as volume features, frequency features, tone features, etc.) may be weighted averaged or other mathematical operations according to weights to obtain a comprehensive sound feature set, i.e., standard working sound information.
It is understood that the volume characteristic refers to the loudness or intensity of sound. The frequency characteristic refers to the distribution of different frequency components in the sound. Timbre characteristics refer to the specific quality of sound produced by overtones and resonances of sound. The maximum volume feature refers to the maximum loudness value in sound. The average volume characteristic refers to the average value of the loudness of sound. The energy profile of a specific frequency component refers to the energy distribution of sound within a specific frequency or frequency band.
In practice, these sound features may be extracted from the recorded sound data by signal processing techniques (e.g., fourier transforms, wavelet transforms, etc.) and used in subsequent fusion and analysis processes.
Further, comparing the standard working sound information with the current working sound information to determine an abnormal component in the target printer, including:
31 Comparing each sound characteristic in the current working sound information with each sound characteristic in the standard sound information to determine an abnormal dimension.
First, various sound features, such as volume, frequency, tone, etc., are extracted from current working sound information collected in real time. These sound features are then compared one by one with the corresponding sound features in the standard working sound information. The purpose of the comparison is to find out in which feature dimensions the current working sound information and the standard sound information have significant differences, and the dimensions of the differences are regarded as abnormal dimensions.
32 According to the abnormal dimension, determining an abnormal part in the target printer from the first target part, the second target part, the third target part, the fourth target part and the fifth target part.
Once the anomaly dimensions are determined, the potential anomaly components can be analyzed based on their association with the particular component's working sound. For example, if the volume characteristics are abnormally high, it may be associated with a roller or motor of the paper transport system; if the frequency signature is abnormal, it may be related to the operating status of the printhead or the inkjet/toner cartridge. In combination with the previously established knowledge of the association of the first, second, third, fourth and fifth target components with the sound features, it is possible to accurately locate the particular component in which the anomaly has occurred.
It should be understood that, although the steps in the flowcharts related to the above embodiments are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides a target printer abnormality judgment device based on cloud edge cooperation, which is used for realizing the printer abnormality judgment method based on cloud edge cooperation. The implementation scheme of the device for solving the problem is similar to the implementation scheme described in the above method, so the specific limitation in the embodiments of the one or more target printer abnormality determination devices based on cloud edge cooperation provided below can be referred to the limitation of the printer abnormality determination method based on cloud edge cooperation hereinabove, and will not be described herein.
In an exemplary embodiment, as shown in fig. 2, there is provided a target printer abnormality determination device based on cloud edge cooperation, including:
a task acquisition module 11 for acquiring a target print task of a target printer; the target printing task comprises type information, thickness information, material information, hardness information of printing paper and printing content information in the target printing task;
The other obtaining module 12 is configured to obtain task execution conditions and fault analysis conditions of other printers existing in the working environment where the target printer is located;
The first sound obtaining module 13 is configured to obtain current working sound information of the target printer in a working time period if the task execution condition is in task execution and the fault analysis condition indicates that other printers are in a state without potential faults;
the second sound obtaining module 14 is configured to obtain current working sound information of the target printer in a working time period when the task execution condition is that the task execution is completed if the fault analysis condition indicates that the other printers are in a latent fault state; a sound comparison module 15 for determining standard work sound information of the target printer when executing the print job;
the abnormal fault recognition module 16 is configured to compare the standard working sound information with the current working sound information, and determine whether the target printer has a potential abnormal fault according to the comparison result.
All or part of the modules in the target printer abnormality judgment device based on cloud edge cooperation can be realized by software, hardware and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one exemplary embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of:
acquiring a target print job of a target printer; the target printing task comprises type information, thickness information, material information, hardness information of printing paper and printing content information in the target printing task;
Acquiring task execution conditions and fault analysis conditions of other printers existing in the working environment of the target printer;
If the task execution condition is in task execution and the fault analysis condition indicates that other printers are in a state without potential faults, acquiring current working sound information of the target printer in a working time period;
If the fault analysis condition indicates that other printers are in a potential fault state, acquiring current working sound information of the target printer in a working time period under the condition that the task execution condition is that the task execution is completed; determining standard working sound information of a target printer when executing a printing task;
and comparing the standard working sound information with the current working sound information, and determining whether the target printer has potential abnormal faults according to the comparison result.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring a target print job of a target printer; the target printing task comprises type information, thickness information, material information, hardness information of printing paper and printing content information in the target printing task;
Acquiring task execution conditions and fault analysis conditions of other printers existing in the working environment of the target printer;
If the task execution condition is in task execution and the fault analysis condition indicates that other printers are in a state without potential faults, acquiring current working sound information of the target printer in a working time period;
If the fault analysis condition indicates that other printers are in a potential fault state, acquiring current working sound information of the target printer in a working time period under the condition that the task execution condition is that the task execution is completed; determining standard working sound information of a target printer when executing a printing task;
and comparing the standard working sound information with the current working sound information, and determining whether the target printer has potential abnormal faults according to the comparison result.
In one embodiment, a computer program product is provided comprising a computer program which, when executed by a processor, performs the steps of:
acquiring a target print job of a target printer; the target printing task comprises type information, thickness information, material information, hardness information of printing paper and printing content information in the target printing task;
Acquiring task execution conditions and fault analysis conditions of other printers existing in the working environment of the target printer;
If the task execution condition is in task execution and the fault analysis condition indicates that other printers are in a state without potential faults, acquiring current working sound information of the target printer in a working time period;
If the fault analysis condition indicates that other printers are in a potential fault state, acquiring current working sound information of the target printer in a working time period under the condition that the task execution condition is that the task execution is completed; determining standard working sound information of a target printer when executing a printing task;
and comparing the standard working sound information with the current working sound information, and determining whether the target printer has potential abnormal faults according to the comparison result.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in embodiments provided herein may include at least one of non-volatile memory and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (RESISTIVE RANDOM ACCESS MEMORY, reRAM), magneto-resistive Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (PHASE CHANGE Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in various forms such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), etc. The databases referred to in the embodiments provided herein may include at least one of a relational database and a non-relational database. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processor referred to in the embodiments provided in the present application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computation, an artificial intelligence (ARTIFICIAL INTELLIGENCE, AI) processor, or the like, but is not limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the present application.
The foregoing examples illustrate only a few embodiments of the application and are described in detail herein without thereby limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of the application should be assessed as that of the appended claims.
Claims (10)
1. A printer abnormality judgment method based on cloud edge cooperation is characterized by comprising the following steps:
Acquiring a target printing task of the target printer; the target printing task comprises type information, thickness information, material information, hardness information of printing paper and printing content information in the target printing task;
acquiring task execution conditions and fault analysis conditions of other printers existing in the working environment of the target printer;
If the task execution condition is in task execution and the fault analysis condition indicates that the other printers are in a state without potential faults, acquiring current working sound information of the target printer in a working time period;
If the fault analysis condition indicates that the other printers are in a potential fault state, acquiring current working sound information of the target printer in a working time period under the condition that the task execution condition is that the task execution is completed;
determining standard working sound information of the target printer when the target print task is executed;
and comparing the standard working sound information with the current working sound information, and determining whether the target printer has potential abnormal faults according to a comparison result.
2. The method of claim 1, wherein said determining standard operating sound information for the target printer when executing the print job comprises:
Acquiring first standard sound information corresponding to a first target component associated with the type information in the target printer, second standard sound information corresponding to a second target component associated with the thickness information in the target printer, third standard sound information corresponding to a third target component associated with the material information in the target printer, fourth standard sound information corresponding to a fourth target component associated with the hardness information in the target printer, and fifth standard sound information corresponding to a fifth target component associated with print content information in the target printer;
And fusing the first standard sound information, the second standard sound information, the third standard sound information, the fourth standard sound information and the fifth standard sound information to obtain standard working sound information of the target printer when the printing task is executed.
3. The method of claim 2, wherein the first target component comprises at least a print head and a print initiator in the target printer; the second target part at least comprises a paper feeding mechanism, a printing head and a paper conveying roller in the target printer; the third target component includes at least a paper transport system, a printhead, and a paper sensor in the target printer; the fourth target part comprises at least a paper conveying roller and a conveyor belt, a printing head or a printing roller and a paper sensor or a detector in the target printer; the fifth target component includes at least a paper transport roller and belt, a printhead or print roller, and a paper sensor or detector in the target printer.
4. The method according to claim 2, wherein the method further comprises:
and under the condition that the target printer has potential abnormal faults, determining abnormal components in the target printer according to the comparison result.
5. The method of claim 4, wherein the fusing the first standard sound information, the second standard sound information, the third standard sound information, the fourth standard sound information, and the fifth standard sound information to obtain standard working sound information of the target printer when executing the print job comprises:
Determining a first weight corresponding to the first standard sound information, a second weight corresponding to the second standard sound information, a third weight corresponding to the third standard sound information, a fourth weight corresponding to the fourth standard sound information and a fifth weight corresponding to the fifth standard sound information according to the interaction condition among the first standard sound information, the second standard sound information, the third standard sound information, the fourth standard sound information and the fifth standard sound information;
and according to the first weight, the second weight, the third weight, the fourth weight and the fifth weight, fusing the first standard sound information, the second standard sound information, the third standard sound information, the fourth standard sound information and the fifth standard sound information to obtain standard working sound information of the target printer when executing the printing task.
6. The method according to claim 5, wherein the fusing the first standard sound information, the second standard sound information, the third standard sound information, the fourth standard sound information, and the fifth standard sound information according to the first weight, the second weight, the third weight, the fourth weight, and the fifth weight to obtain standard working sound information of the target printer when executing the print job includes:
According to the first weight, the second weight, the third weight, the fourth weight and the fifth weight, fusing the sound characteristics in the first standard sound information, the sound characteristics in the second standard sound information, the sound characteristics in the third standard sound information, the sound characteristics in the fourth standard sound information and the sound characteristics in the fifth standard sound information to obtain standard working sound information of the target printer when executing the printing task;
wherein the sound characteristic information includes at least one of a volume characteristic, a frequency characteristic, a tone characteristic, a maximum volume characteristic, an average volume characteristic, and an energy characteristic of a specific frequency component.
7. The method of claim 6, wherein the comparing the standard working sound information with the current working sound information to determine an abnormal component in the target printer comprises:
comparing each sound characteristic in the current working sound information with each sound characteristic in the standard sound information to determine an abnormal dimension;
And determining an abnormal component in the target printer from the first target component, the second target component, the third target component, the fourth target component and the fifth target component according to the abnormal dimension.
8. The method according to claim 1, wherein if the task execution condition is in task execution and the fault analysis condition indicates that the other printers are in a state without potential fault, acquiring current working sound information of the target printer in a working period includes:
If the task execution condition is in task execution and the fault analysis condition indicates that the other printers are in a state without potential faults, determining whether sound information generated when the other printers work can cause interference to sound information generated when the target printing work according to relative position information between the other printers and the target printer, sound print information of the other printers and sound print information of the target printer;
And if no interference exists, acquiring current working sound information of the target printer in a working time period.
9. The method according to claim 8, wherein the relative position information between the other printer and the target printer includes distance information between the other printer and the target printer and obstacle information between the other printer and the target printer; the determining whether the sound information generated by the other printers during the operation of the target printer will cause interference to the sound information generated during the operation of the target printer according to the relative position information between the other printers and the target printer, the voiceprint information of the other printers and the voiceprint information of the target printer includes:
According to the sound propagation model, analyzing distance information between the other printers and the target printer and barrier information between the other printers and the target printer to obtain propagation conditions of sound information generated when the other printers work in the working environment;
Predicting the intensity and sound characteristics of sound information generated by other printers at the target printer position according to the propagation condition of the sound information generated by the other printers in the working environment;
and if the degrees of the disturbance are smaller than the disturbance threshold, and the voiceprint similarity between the voiceprint information of the other printers and the voiceprint information of the target printer is smaller than the similarity threshold, determining that the voice information generated by the other printers during the work does not cause disturbance to the voice information generated by the target print work.
10. Target printer anomaly judgment device based on cloud limit cooperation, characterized in that, the device includes:
The task acquisition module is used for acquiring a target printing task of the target printer; the target printing task comprises type information, thickness information, material information, hardness information of printing paper and printing content information in the target printing task;
The other acquisition module is used for acquiring task execution conditions and fault analysis conditions of other printers existing in the working environment of the target printer;
The first sound acquisition module is used for acquiring current working sound information of the target printer in a working time period if the task execution condition is in task execution and the fault analysis condition indicates that the other printers are in a potential fault-free state;
The second sound acquisition module is used for acquiring current working sound information of the target printer in a working time period under the condition that the task execution condition is that the task execution is completed if the fault analysis condition indicates that the other printers are in a potential fault state;
The sound comparison module is used for determining standard working sound information of the target printer when the printing task is executed;
And the abnormal fault identification module is used for comparing the standard working sound information with the current working sound information and determining whether the target printer has potential abnormal faults according to the comparison result.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2014142498A (en) * | 2013-01-24 | 2014-08-07 | Canon Inc | Image forming system |
| JP2019181796A (en) * | 2018-04-10 | 2019-10-24 | 富士通コンポーネント株式会社 | Evaluation device and program |
| CN116728783A (en) * | 2023-08-09 | 2023-09-12 | 深圳市金石三维打印科技有限公司 | Simulation method and system based on 3D printer |
| CN116895286A (en) * | 2023-09-11 | 2023-10-17 | 珠海芯烨电子科技有限公司 | Printer fault monitoring method and related device |
-
2024
- 2024-06-21 CN CN202410808917.8A patent/CN118377447B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2014142498A (en) * | 2013-01-24 | 2014-08-07 | Canon Inc | Image forming system |
| JP2019181796A (en) * | 2018-04-10 | 2019-10-24 | 富士通コンポーネント株式会社 | Evaluation device and program |
| CN116728783A (en) * | 2023-08-09 | 2023-09-12 | 深圳市金石三维打印科技有限公司 | Simulation method and system based on 3D printer |
| CN116895286A (en) * | 2023-09-11 | 2023-10-17 | 珠海芯烨电子科技有限公司 | Printer fault monitoring method and related device |
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