A multi-dimensional operation parameter intelligent analysis and optimization control system of a digital printing machine

Abstract

The present application relates to the field of digital printing machine, mainly aims at the problem that the detection index of the optimization control system of the digital printing machine is too isolated and lacks joint analysis capability, and specifically relates to a kind of digital printing machine multi-dimensional running parameter intelligent analysis and optimization control system, including front-end detection module, fusion detection module, abnormality identification module, maintenance positioning module and deviation control healing module;The present application introduces the acoustic emission signal monitoring of the nozzle part while collecting the nozzle temperature, ink dot precision and nozzle interference vibration amplitude, and generates settlement data package by fusion, realizes the multi-source heterogeneous data fusion of multiple parameters, judges the correlation coupling relationship between multiple parameters, accurately locates the root cause of the decline of printing quality, also judges the growth speed of nozzle blockage according to the acoustic emission signal related parameters, quantitatively evaluates the growth stage and growth speed of blockage, realizes early warning and growth trend prediction of nozzle blockage.

Description

Technical Field

[0001] This invention relates to the field of digital printing presses, specifically to a multi-dimensional intelligent analysis and optimization control system for operating parameters of digital printing presses. Background Technology

[0002] Digital printing technology, as an advanced production method that eliminates the need for plate making and enables variable data printing, has been widely used in the packaging, publishing, and commercial printing industries. During the operation of digital printing presses, especially inkjet digital printing presses, the quality of printed products is closely related to the operating parameters of the equipment. In existing technologies, the monitoring and control of the operating status of digital printing presses mainly relies on two types of methods: one is to use front-end detection devices such as temperature sensors and vibration sensors to monitor single parameters such as printhead temperature and printhead vibration amplitude at thresholds. When the parameters exceed the set thresholds, an alarm is triggered and the machine is stopped for adjustment. The other is to use image acquisition equipment to obtain the deviation between the actual printed ink dots and the preset digital template, calculate the ink dot accuracy, and make feedback compensation accordingly.

[0003] However, the aforementioned existing technologies have obvious limitations in practical applications. They often treat parameters such as printhead temperature, ink droplet accuracy, and vibration amplitude as independent indicators for isolated monitoring, lacking the ability to jointly analyze the inherent coupling relationship between multi-dimensional parameters. For example, printhead interference vibration may cause ink droplet offset, while temperature changes will change the viscosity of the ink, thus affecting the formation and accuracy of ink droplets. Therefore, printer malfunctions are a multi-factor chain effect, which is difficult to effectively identify and trace in traditional isolated monitoring systems. Secondly, traditional technologies are relatively lagging in detecting key malfunctions such as printhead clogging, and they are usually only discovered after obvious visual defects such as streaks or ink shortages appear on the printed matter.

[0004] In summary, how to achieve multi-dimensional fusion analysis of the operating parameters of digital printing presses is a technical problem that urgently needs to be solved in this field. To address this, a solution is proposed. Summary of the Invention

[0005] To address the problem that the detection indicators of the optimization and control system for digital printing presses are too isolated and lack joint analysis capabilities, a multi-dimensional intelligent analysis and optimization control system for the operating parameters of digital printing presses is proposed.

[0006] The objective of this invention can be achieved through the following technical solution: a multi-dimensional intelligent analysis and optimization control system for operating parameters of a digital printing press, including a front-end detection module, wherein the front-end detection module is used to collect the operating parameters of the digital printing press, and to summarize the operating parameters of the digital printing press to generate a master data package; The fusion detection module monitors the printhead of the digital printing press, obtains the acoustic emission signal monitoring results of the printhead, and fuses them with the main data packet generated by the front-end detection module to generate a settlement data packet. An anomaly identification module performs operation mode verification based on the settlement data packet, obtains and marks abnormal data in the settlement data packet, and synchronizes the marked data to the maintenance and positioning module. The maintenance and positioning module analyzes abnormal data, identifies the corresponding equipment components, and performs joint analysis based on the equipment components to generate a digital printing press fault warning. The deviation control and healing module acquires digital printing press fault warnings and abnormal data, identifies the digital printing press fault warnings, classifies them into recoverable faults and unrecoverable faults, performs correction actions for recoverable faults, and dynamically tracks abnormal data, identifies the recovery range of abnormal data, and outputs a correction normal signal and a correction warning signal based on the recovery range of abnormal data.

[0007] In a preferred embodiment of the present invention, the operating parameters of the digital printing press collected by the front-end detection module include: Printhead temperature, ink droplet accuracy, and printhead vibration amplitude; The front-end detection module synchronizes and aligns the printhead temperature, ink droplet accuracy, and printhead interference vibration amplitude in time to obtain a set of data. The front-end detection module sorts the data sequence according to time order, generates a data sequence, and summarizes the data sequence into a main data packet.

[0008] In a preferred embodiment of the present invention, when the front-end detection module acquires the nozzle temperature, it collects the nozzle temperatures of different colored nozzles separately, and records the collected nozzle temperatures separately after marking them. The method by which the front-end detection module collects ink dot accuracy is as follows: obtain a preset digital template of printed image, obtain the actual landing point of printed ink dot through image acquisition, compare the landing point of printed ink dot with the standard landing point in the set digital template of printed image, calculate the straight-line distance between the center points of the two ink dots, and calculate the ratio of the set threshold to the straight-line distance to obtain the ink dot accuracy. The method by which the front-end detection module collects the printhead interference vibration amplitude is as follows: the printhead vibration amplitude is collected, and minute vibrations are filtered out by a preset threshold. The retained vibrations are taken as valid vibrations. The front-end detection module compares the occurrence time of the valid vibrations with the ink ejection time of the printhead. The valid vibrations in which the two times overlap are recorded as interference vibrations, thereby obtaining the printhead interference vibration amplitude.

[0009] In a preferred embodiment of the present invention, the method by which the fusion detection module obtains the acoustic emission signal monitoring results is as follows: A preset background noise threshold is obtained, and recording begins when the acoustic emission signal intensity first exceeds the background noise threshold. Recording then stops when the acoustic emission signal intensity falls below the background noise threshold. The recording time is used as the period step. The peak amplitude of the acoustic emission signal within one period step is selected for recording. After one period step is completed, a set step length of filtering time is set. After the set step length of filtering time has elapsed, the acoustic emission signal is recorded again to obtain the monitoring results of the acoustic emission signal.

[0010] In a preferred embodiment of the present invention, the method for the anomaly identification module to perform operation mode verification is as follows: The anomaly identification module compares the printhead temperature, ink droplet accuracy, and printhead interference vibration amplitude with the control parameters set under the standard operating conditions, and marks the printhead temperature, ink droplet accuracy, and printhead interference vibration amplitude that exceed the control parameters under the standard conditions.

[0011] In a preferred embodiment of the present invention, after acquiring the monitoring results of the acoustic emission signal, the anomaly identification module calculates the vibration energy and vibration frequency of the acoustic emission signal based on the monitoring results, generates a vibration energy variation curve and vibration trigger frequency, and compares the vibration energy variation curve with the set blockage growth curve to obtain the blockage overlap. The anomaly identification module then performs a comprehensive calculation based on the overlap of blockages and the vibration frequency to generate the blockage growth rate.

[0012] In a preferred embodiment of the present invention, the maintenance positioning module makes a threshold judgment based on the blockage growth rate to determine whether the nozzle is blocked, a blockage growth warning is issued, or the nozzle is normal. The maintenance positioning module performs time overlap analysis based on the marked printhead temperature, ink drop accuracy, and printhead interference vibration amplitude. If there is a high temporal correlation between the marked printhead temperature and ink drop accuracy, it is determined that the temperature affects the ink drop accuracy, and a printhead temperature warning is generated. If there is a high temporal correlation between the marked printhead interference vibration amplitude and ink drop accuracy, it is determined that the vibration affects the ink drop accuracy, and a printhead vibration warning is generated. The maintenance positioning module generates corresponding fault warnings based on the judgment results.

[0013] In a preferred embodiment of the present invention, when the nozzle is clogged, the deviation control and healing module records it as an unrecoverable fault and issues a signal alarm. After the deviation control and healing module obtains the nozzle growth warning, nozzle temperature warning, and nozzle vibration warning, it records them as recoverable faults and performs periodic timing. At the end of each cycle, the existence status of the warning is recorded. If the warning signal disappears, a normal correction signal is generated. If the warning signal still exists, an abnormal correction signal is generated.

[0014] Compared with the prior art, the beneficial effects of the present invention are: This invention, while collecting printhead temperature, ink droplet accuracy, and printhead interference vibration amplitude, also incorporates acoustic emission signal monitoring of the printhead area and integrates these signals to generate a settlement data package. This achieves multi-source heterogeneous data fusion of vibration energy, trigger frequency, and conventional operating parameters. By analyzing the temporal overlap of the multi-source heterogeneous data, the correlation and coupling relationships between multiple parameters are determined. The causal relationship between previously isolated temperature anomalies, vibration anomalies, and decreased ink droplet accuracy is quantified and correlated, accurately pinpointing whether the root cause of the print quality degradation is temperature drift or vibration interference, providing a clear decision-making basis for subsequent targeted adjustments. In this invention, when monitoring acoustic emission signals, the vibration energy variation curve and vibration trigger frequency are further calculated based on the vibration energy and vibration frequency of the acoustic emission signals. The vibration energy variation curve is compared with the set blockage growth curve to obtain the blockage overlap. Then, the blockage growth rate is calculated in combination with the vibration frequency. This avoids the limitations of judging solely by the acoustic emission intensity threshold. It can quantitatively assess the growth stage and growth rate of the blockage before the printhead blockage produces visual defects on the printed material, thus achieving early warning and prediction of printhead blockage growth trends. This invention also identifies fault warnings for digital printing presses and performs corrective actions for recoverable faults. Simultaneously, it dynamically tracks abnormal data, identifies the recovery range of abnormal data, and records the existence status of the warning at the end of each cycle. This enables proactive correction and closed-loop tracking of recoverable faults. It can dynamically judge the correction effect based on the real-time recovery range of abnormal data, output a normal signal after the fault is automatically cleared, and output an abnormal signal when the fault persists. This minimizes unnecessary downtime intervention while ensuring printing quality. Attached Figure Description

[0015] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0016] Figure 1 This is a system block diagram of the present invention; Figure 2 This is a system flowchart of the present invention. Detailed Implementation

[0017] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0018] Example 1: Please refer to Figure 1 - Figure 2 As shown, a multi-dimensional intelligent analysis and optimization control system for operating parameters of a digital printing press includes a front-end detection module, a fusion detection module, an anomaly identification module, a maintenance positioning module, and a deviation control and healing module. Overview of the front-end detection module: The front-end detection module is used to collect the operating parameters of the digital printing press and summarize the operating parameters to generate the main data package. Specifically, the operating parameters of the digital printing press collected by the front-end detection module include: printhead temperature, ink droplet accuracy, and printhead interference vibration amplitude. The front-end detection module synchronizes and aligns the printhead temperature, ink droplet accuracy, and printhead interference vibration amplitude in time to obtain a set of data. The specific time synchronization method is as follows: the front-end detection module has a built-in high-precision real-time clock, and all sensor data are marked with the timestamp of this clock, with a time synchronization accuracy of ±1ms. The specific method of data alignment is as follows: taking the data sampling period T=10ms of the front-end detection module as the benchmark, the various types of data collected in each sampling period are matched according to the timestamp. For data whose timestamps cannot be strictly aligned, a linear interpolation method is used to complete them. The front-end detection module sorts the data sequence according to the time order, generates a data sequence, and summarizes the data sequence into the main data packet.

[0019] The specific method for collecting nozzle temperature is as follows: When the front-end detection module acquires the nozzle temperature, it collects the nozzle temperature of different colored nozzles separately, marks the collected nozzle temperatures, and records them separately.

[0020] For example, a printing press is equipped with four printhead groups: cyan (C), magenta (M), yellow (Y), and black (K). Each printhead group has a temperature sensor installed at its printhead. The front-end detection module collects the temperature values ​​of the four printheads (C, M, Y, and K) and labels them as T. C T M T Y T K And record them in timestamp order; The specific method for collecting ink dot accuracy is as follows: Obtain a preset digital template of the printed image, and acquire the actual landing point of the printed ink dot through image acquisition. Compare the landing point of the printed ink dot with the standard landing point in the set digital template of the printed image, calculate the straight-line distance between the center points of the two ink dots, and calculate the ratio of the set threshold to the straight-line distance to obtain the ink dot accuracy.

[0021] For example, the preset digital template for the printed image is a regular grid dot matrix image. For instance, at a resolution of 1200 dpi, the spacing between adjacent standard ink dots is 21.2 μm. When the printing press prints this grid dot matrix image, it uses a high-speed industrial camera to capture real-time images of the actual ink dots on the printing medium. After image acquisition, the front-end detection module performs binarization processing and a center-of-circle extraction algorithm on the image, and calculates the distance d between the center point of each actual ink dot and its corresponding standard ink dot center point. Let the preset allowable deviation threshold be Dmax, then the formula for calculating the ink dot accuracy P is: P = Dmax / d. When d > Dmax, P < 1, indicating insufficient ink dot accuracy. When d ≤ Dmax, P ≥ 1, indicating qualified ink dot accuracy. The front-end detection module records the P value as a dimensionless accuracy coefficient. The front-end detection module collects the printhead interference vibration amplitude as follows: it collects the printhead vibration amplitude, filters out minor vibrations through a preset threshold, and retains the vibrations as valid vibrations. The front-end detection module compares the occurrence time of the valid vibrations with the ink ejection time of the printhead, and records the valid vibrations in which the two times overlap as interference vibrations, thereby obtaining the printhead interference vibration amplitude. Specifically, each nozzle assembly is equipped with a triaxial accelerometer. The front-end detection module collects the vibration acceleration values ​​of the nozzle in the X, Y, and Z axes in real time and calculates the composite vibration amplitude A = x² + y² + z², where x, y, and z are the vibration acceleration values ​​on the X, Y, and Z axes, respectively. When the composite vibration amplitude A is less than a preset threshold, it is considered as ambient background noise and is not recorded. When A is greater than or equal to the preset threshold, it is recorded as a valid vibration, and the start time and duration of the valid vibration are also recorded. Simultaneously, the front-end detection module acquires the inkjet timing signal of the printhead. The inkjet timing signal records the start and end times of inkjet printing for each printhead in each inkjet cycle. When the time interval of an effective vibration overlaps with the time interval of any inkjet cycle, the effective vibration is identified as an interference vibration, and the peak amplitude A of the interference vibration is recorded. s Within a sampling period, the front-end detection module counts the peak amplitudes of all interfering vibrations and takes the maximum value as the nozzle interfering vibration amplitude V for that sampling period. The fusion detection module monitors the printhead of the digital printing press, obtains the acoustic emission signal monitoring results of the printhead, and fuses them with the main data packet generated by the front-end detection module to generate a settlement data packet. The method for the fusion detection module to obtain the acoustic emission signal monitoring results is as follows: a preset background noise threshold is obtained, and recording begins when the acoustic emission signal intensity is first greater than the background noise threshold. Subsequently, recording stops when the acoustic emission signal intensity is less than the background noise threshold. The recording time is used as the period step. The peak amplitude of the acoustic emission signal within one period step is selected for recording. After the recording of one period step is completed, a set step length of filtering time is set. After the set step length of filtering time has elapsed, the acoustic emission signal is recorded again, thereby obtaining the acoustic emission signal monitoring results.

[0022] Specifically, a broadband acoustic emission sensor is installed near each printhead group. First, when the printing press is running normally and the printheads are in brand new and good condition, the ambient background acoustic emission signal is collected for 30 seconds. The root mean square value of the background noise is calculated and multiplied by a safety factor of 1.5 to obtain the background noise threshold.

[0023] The fusion detection module continuously monitors the acoustic emission signal intensity. When the acoustic emission signal intensity is greater than the background noise threshold for the first time, it is determined that a potential nozzle abnormality event has started and timing is started. Subsequently, when the acoustic emission signal intensity is less than the background noise threshold for 5 ms for a continuous period, it is determined that the event has ended and timing is stopped, thus obtaining the duration period step L of this event.

[0024] Within the cycle step L, the fusion detection module finds the maximum instantaneous amplitude of the acoustic emission signal and records it as AE. After completing this recording, a filtering time is set. During this period, the fusion detection module continues to receive acoustic emission signals but does not perform new cycle recordings to avoid the same physical event being split into multiple cycles. After a filtering time, the fusion detection module resets and begins the next cycle detection.

[0025] After the fusion detection module acquires the acoustic emission signal monitoring results, it associates and fuses them with the main data packet output by the front-end detection module according to the timestamp. Specifically, based on the time axis in the main data packet, acoustic emission monitoring events with similar landing times are merged with the corresponding temperature, ink dot accuracy, and interference vibration amplitude data into the same data frame to generate a settlement data packet. Each settlement data packet contains the printhead temperature, ink dot accuracy, printhead interference vibration amplitude, and acoustic emission event parameters (cycle step size, peak amplitude) associated with a timestamp.

[0026] Using the above method, the fusion detection module obtains a series of continuous acoustic emission monitoring records. Each record includes: event start time, period step L, and peak amplitude AE.

[0027] The anomaly identification module verifies the operating mode based on the settlement data packet, marks any abnormal data in the settlement data packet, and synchronizes the marked data to the maintenance and positioning module.

[0028] The method for the anomaly identification module to verify the operating mode is as follows: compare the printhead temperature, ink droplet accuracy, and printhead interference vibration amplitude with the control parameters set under the standard working state, and mark the printhead temperature, ink droplet accuracy, and printhead interference vibration amplitude that exceed the control parameters under the standard state. Specifically, the range of control parameters under standard operating conditions: The standard range for printhead temperature is Tmin to Tmax, the standard range for ink droplet accuracy is P > Pmax, and the standard range for printhead interference vibration amplitude is V < Vmax. For each settlement data packet, the anomaly detection module checks the T, P, and V values ​​one by one: If the nozzle temperature T < Tmin or T > Tmax, then the temperature data of the nozzle is marked as an abnormal temperature. If the ink dot accuracy P < Pmax, then the ink dot accuracy data is marked as an abnormal ink dot. If the vibration amplitude V of the nozzle interference is greater than Vmax, the vibration data is marked as abnormal vibration, and all marked data, along with their timestamps, are synchronized to the maintenance positioning module.

[0029] After acquiring the monitoring results of the acoustic emission signal, the anomaly identification module calculates the vibration energy and frequency of the acoustic emission signal based on the monitoring results, generating a vibration energy variation curve and vibration trigger frequency. It then compares the vibration energy variation curve with a preset blockage growth curve to obtain the blockage overlap degree. Finally, it performs a comprehensive calculation based on the blockage overlap degree and vibration frequency to generate the blockage growth rate. Specifically, the anomaly identification module collects all acoustic emission monitoring events over a certain period of time, and calculates the vibration energy for each event. The integration interval is the period step L of the event. The vibration energy E of each event is arranged in time order to obtain the vibration energy variation curve E(t). At the same time, the number of acoustic emission events occurring per unit time is counted and recorded as the vibration trigger frequency F(AE).

[0030] Subsequently, the vibration energy variation curves of the nozzle under different degrees of blockage during the process from an intact state to complete blockage were obtained, and a standard blockage growth curve Eb(t) was fitted to obtain a standard blockage growth curve. This curve describes the exponential increase of acoustic emission vibration energy as the degree of nozzle blockage increases. The anomaly identification module performs dynamic time warping matching between the actual vibration energy variation curve E(t) and the standard blockage growth curve Eb(t), calculates the similarity between the two curves, and generates the blockage overlap degree S. The range of S is 0-1. The closer S is to 1, the more it matches the acoustic emission variation characteristics of the current nozzle with the standard blockage growth mode. Furthermore, the anomaly identification module calculates the blockage growth rate G based on the formula:

[0031] Where α and β are preset weighting coefficients, F(AE)max is the maximum trigger frequency in the history of the nozzle under normal conditions, and the value of G is in the range of [0,1]. The larger the value, the faster the blockage grows and the more obvious the trend.

[0032] The maintenance and positioning module analyzes abnormal data, identifies the corresponding equipment components, and performs joint analysis based on these components to generate a digital printing press fault warning. The maintenance and positioning module uses threshold judgment based on the blockage growth rate to determine whether the nozzle is blocked, triggering a blockage growth warning, or indicating that the nozzle is normal. Specifically, two thresholds are set: Gl and Gh, where Gl is less than Gh.

[0033] If G≥Gh, it is determined that the printhead is blocked, indicating that the printhead has entered a state of severe blockage, and streaking defects will soon or have already occurred on the printed matter. If Gl≤G_block<Gh, it is judged as a blockage growth warning, indicating that the printhead is in the early or middle stage of blockage growth, and has not yet had a significant impact on printing quality, but it needs to be monitored. If G < Gl, then the nozzle is considered to be normal.

[0034] The maintenance and positioning module performs time overlap analysis based on the marked printhead temperature, ink droplet accuracy, and printhead interference vibration amplitude. If there is a high temporal correlation between the marked printhead temperature and ink droplet accuracy, it is determined that the temperature affects the ink droplet accuracy and a printhead temperature warning is generated. If there is a high temporal correlation between the amplitude of the marked printhead interference vibration and the accuracy of ink droplets, it is determined that the vibration affects the accuracy of ink droplets, and a printhead vibration warning is generated.

[0035] Specifically, the maintenance and positioning module extracts all data points marked as abnormal temperature and data points marked as abnormal ink dots within a certain period of time, and creates abnormal temperature data set and abnormal ink dot data set. It calculates the overlap between the two sets on the time axis: for each abnormal ink dot event in the abnormal ink dot data set, it checks whether there are abnormal temperature events in the abnormal temperature data set before and after its timestamp. If so, it marks this pair of events as a temperature ink dot related event. The proportion of the number of related events to the total number of abnormal ink drop events is counted. If the counted proportion is greater than or equal to the set threshold, it is determined that there is a high degree of temporal correlation, and a printhead temperature warning is generated. The warning information includes which specific color printhead has an abnormal temperature and the time period in which the abnormality occurred. Similarly, an abnormal vibration data set is created for data points marked as abnormal vibrations. For each abnormal ink dot event in the abnormal ink dot data set, it is checked whether there are abnormal vibration events in the abnormal vibration data set before and after its timestamp. If there are abnormal vibration events, this pair of events is marked as a vibration ink dot associated event. The proportion of the number of associated events to the total number of abnormal ink dot events is counted. If the counted proportion is greater than or equal to a set threshold, it is determined that there is a high degree of temporal correlation, and a printhead vibration warning is generated. The warning information includes the axial direction and amplitude range of the vibration source. The maintenance and positioning module summarizes the above judgment results and generates a digital printing press fault warning.

[0036] Example 2: Please refer to Figure 1 - Figure 2 As shown, the deviation control and healing module acquires digital printing press fault warnings and abnormal data, identifies the digital printing press fault warnings, classifies them into recoverable faults and non-recoverable faults, performs correction actions for recoverable faults, and dynamically tracks abnormal data to identify the recovery range of abnormal data. Based on the recovery range of abnormal data, it outputs a correction normal signal and a correction warning signal. Specifically, it includes the following steps: Step 1: Fault type classification: When the deviation control healing module detects nozzle blockage, it records it as an unrecoverable fault and proceeds to Step 2; After obtaining the nozzle growth warning, nozzle temperature warning, and nozzle vibration warning, record them as recoverable faults, start periodic timing, and proceed to step three; Step 2: The deviation control healing module immediately triggers an audible and visual alarm and displays "nozzle blockage" on the host computer interface, while pausing the printing task. Step 3: The deviation control and healing module executes the corresponding correction actions and dynamically tracks abnormal data, recording the existence status of the warning at the end of each cycle; Specifically, the corrective actions in step three include: For nozzle growth warning: The deviation control and healing module initiates a mild cleaning procedure, increases the suction negative pressure of the nozzle maintenance station, and performs 10 gentle suction cycles. Simultaneously, the value of the blockage growth rate G is recalculated at regular intervals to dynamically track the changing trend of the blockage growth rate. At the end of each periodic timing, it checks whether the current blockage growth rate G has fallen below Gl. If it has, a normal correction signal is generated, indicating that the blockage growth trend has been suppressed. If the blockage growth rate G is still greater than Gl after n consecutive cycles, an abnormal correction signal is generated, and an early warning is issued.

[0037] For printhead temperature warnings: The deviation control and healing module performs graded correction based on the degree of temperature exceeding the limit. If the temperature exceeds the upper limit by less than the set value (i.e., slightly exceeds the upper limit), the printhead cooling fan is activated to increase the fan duty cycle. If the temperature exceeds the upper limit by more than the set value (i.e., significantly exceeds the upper limit), the printing speed is reduced to decrease the printhead workload. At the end of each periodic timing, it is checked whether the printhead temperature has returned to the standard range. If it has returned, a normal correction signal is generated; if it continues to exceed the limit, an abnormal correction signal is generated. For nozzle vibration warning: The deviation control and healing module analyzes the vibration spectrum characteristics to determine the source of vibration. If the vibration mainly comes from the paper feeding mechanism, the clamping force of the paper feeding roller is adjusted; if the vibration mainly comes from the drying fan, the fan speed is reduced. At the end of each periodic timing, it checks whether the interference vibration amplitude V has dropped below the set threshold. If it drops below the threshold, a normal correction signal is generated; if it still exceeds the standard, an abnormal correction signal is generated.

[0038] Thresholds, preset values, or preset ranges are set for result comparison and analysis to determine whether they are good or bad. The magnitude of these values ​​is determined by a combination of large-scale model analysis of the sample data and human experience. They can also be adjusted appropriately based on seasonal or common-sense influence conditions. Similarly, the weighting ratio coefficients and influence factors are set based on the magnitude of each parameter's influence on the results. These values ​​are assigned to reflect the overall impact on the results. They are also determined by a combination of large-scale model analysis of the sample data and human experience. They can also be adjusted appropriately based on seasonal or common-sense influence conditions.

[0039] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A multi-dimensional intelligent analysis and optimization control system for operating parameters of a digital printing press, characterized in that, It includes a front-end detection module, which is used to collect the operating parameters of the digital printing press, and summarize the operating parameters of the digital printing press to generate a master data packet; The fusion detection module monitors the printhead of the digital printing press, obtains the acoustic emission signal monitoring results of the printhead, and fuses them with the main data packet generated by the front-end detection module to generate a settlement data packet. An anomaly identification module performs operation mode verification based on the settlement data packet, obtains and marks abnormal data in the settlement data packet, and synchronizes the marked data to the maintenance and positioning module. The maintenance and positioning module analyzes abnormal data, identifies the corresponding equipment components, and performs joint analysis based on the equipment components to generate a digital printing press fault warning. The deviation control and healing module acquires digital printing press fault warnings and abnormal data, identifies the digital printing press fault warnings, classifies them into recoverable faults and unrecoverable faults, performs correction actions for recoverable faults, and dynamically tracks abnormal data, identifies the recovery range of abnormal data, and outputs a correction normal signal and a correction warning signal based on the recovery range of abnormal data.

2. The intelligent analysis and optimization control system for multi-dimensional operating parameters of a digital printing press according to claim 1, characterized in that, The operating parameters of the digital printing press collected by the front-end detection module include: Printhead temperature, ink droplet accuracy, and printhead vibration amplitude; The front-end detection module synchronizes and aligns the printhead temperature, ink droplet accuracy, and printhead interference vibration amplitude in time to obtain a set of data. The front-end detection module sorts the data sequence according to time order, generates a data sequence, and summarizes the data sequence into a main data packet.

3. The intelligent analysis and optimization control system for multi-dimensional operating parameters of a digital printing press according to claim 1, characterized in that, When the front-end detection module acquires the nozzle temperature, it collects the nozzle temperature of different colored nozzles separately, marks the collected nozzle temperatures, and records them separately. The method by which the front-end detection module collects ink dot accuracy is as follows: obtain a preset digital template of printed image, obtain the actual landing point of printed ink dot through image acquisition, compare the landing point of printed ink dot with the standard landing point in the set digital template of printed image, calculate the straight-line distance between the center points of the two ink dots, and calculate the ratio of the set threshold to the straight-line distance to obtain the ink dot accuracy. The method by which the front-end detection module collects the printhead interference vibration amplitude is as follows: the printhead vibration amplitude is collected, and minute vibrations are filtered out by a preset threshold. The retained vibrations are taken as valid vibrations. The front-end detection module compares the occurrence time of the valid vibrations with the ink ejection time of the printhead. The valid vibrations in which the two times overlap are recorded as interference vibrations, thereby obtaining the printhead interference vibration amplitude.

4. The intelligent analysis and optimization control system for multi-dimensional operating parameters of a digital printing press according to claim 1, characterized in that, The method by which the fusion detection module obtains the acoustic emission signal monitoring results is as follows: A preset background noise threshold is obtained, and recording begins when the acoustic emission signal intensity first exceeds the background noise threshold. Recording then stops when the acoustic emission signal intensity falls below the background noise threshold. The recording time is used as the period step. The peak amplitude of the acoustic emission signal within one period step is selected for recording. After one period step is completed, a set step length of filtering time is set. After the set step length of filtering time has elapsed, the acoustic emission signal is recorded again to obtain the monitoring results of the acoustic emission signal.

5. The intelligent analysis and optimization control system for multi-dimensional operating parameters of a digital printing press according to claim 1, characterized in that, The method for the anomaly detection module to perform operational mode verification is as follows: The anomaly identification module compares the printhead temperature, ink droplet accuracy, and printhead interference vibration amplitude with the control parameters set under the standard operating conditions, and marks the printhead temperature, ink droplet accuracy, and printhead interference vibration amplitude that exceed the control parameters under the standard conditions.

6. The intelligent analysis and optimization control system for multi-dimensional operating parameters of a digital printing press according to claim 1, characterized in that, After acquiring the monitoring results of the acoustic emission signal, the anomaly identification module calculates the vibration energy and vibration frequency of the acoustic emission signal based on the monitoring results, generates a vibration energy variation curve and vibration trigger frequency, and compares the vibration energy variation curve with the set blockage growth curve to obtain the blockage overlap. The anomaly identification module then performs a comprehensive calculation based on the overlap of blockages and the vibration frequency to generate the blockage growth rate.

7. The intelligent analysis and optimization control system for multi-dimensional operating parameters of a digital printing press according to claim 1, characterized in that, The maintenance and positioning module makes a threshold judgment based on the blockage growth rate to determine whether the nozzle is blocked, a blockage growth warning is issued, or the nozzle is normal. The maintenance positioning module performs time overlap analysis based on the marked printhead temperature, ink drop accuracy, and printhead interference vibration amplitude. If there is a high temporal correlation between the marked printhead temperature and ink drop accuracy, it is determined that the temperature affects the ink drop accuracy, and a printhead temperature warning is generated. If there is a high temporal correlation between the marked printhead interference vibration amplitude and ink drop accuracy, it is determined that the vibration affects the ink drop accuracy, and a printhead vibration warning is generated. The maintenance positioning module generates corresponding fault warnings based on the judgment results.

8. The intelligent analysis and optimization control system for multi-dimensional operating parameters of a digital printing press according to claim 1, characterized in that, When the deviation control and healing module detects nozzle blockage, it records it as an unrecoverable fault and issues a signal alarm. After the deviation control and healing module detects nozzle growth warning, nozzle temperature warning, and nozzle vibration warning, it records them as recoverable faults and performs periodic timing. At the end of each cycle, it records the existence status of the warning. If the warning signal disappears, a normal correction signal is generated. If the warning signal still exists, an abnormal correction signal is generated.

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