Defoaming control method, system and equipment based on multiple sensors and medium

Abstract

The invention relates to the field of ink path control, and provides a defoaming control method, system and equipment based on multiple sensors and a medium. The defoaming control method comprises the steps that multi-source monitoring data related to the bubble state in an ink path system is collected through the multiple sensors; establishing a bubble risk quantification model based on the multi-source monitoring data; calculating a current bubble risk index according to the bubble risk quantification model; judging a current risk level according to the bubble risk index and a preset risk level threshold value; a defoaming control instruction is generated according to the judged risk level, early quantitative evaluation of bubble risks is realized by fusing multi-source sensing information and constructing a bubble risk quantitative model, and a differentiated control instruction is triggered based on an evaluation result, so that differentiated prevention and defoaming measures are conveniently implemented; therefore, the conversion from passive response to active prevention and adaptive control is realized, and the stability and yield of the OLED printing process are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of ink path control, in particular to a multi-sensor-based defoaming control method, system, device and medium. BACKGROUND

[0002] As a non-contact, high-precision and high-efficiency patterning process, inkjet printing technology has shown great application potential in the fields of OLED display panels, flexible electronics, micro-nano device manufacturing, etc. However, the printing quality of inkjet printing technology is highly dependent on the running stability of the ink supply system, which is particularly sensitive to OLED printing applications. Because the ink used for OLED printing is a precise formula solvent system that dissolves organic functional materials, the ink is easily affected by factors such as solvent evaporation, temperature fluctuations, mechanical pumping disturbances, and micro-leakage of pipe interfaces during flow in the circulating pipeline, resulting in micron-level or even millimeter-level bubbles. In order to eliminate the adverse effects of bubbles on printing, it is often necessary to use a circulating flushing method to remove bubbles in actual production, which inevitably causes some loss of ink. Since OLED functional materials are expensive, such ink loss will directly lead to a significant increase in production costs. SUMMARY

[0003] The present application aims to improve at least one technical problem in the background art.

[0004] The present application provides a multi-sensor bubble monitoring and defoaming control method, which comprises: being applied to a multi-sensor-based defoaming control system, the defoaming control system comprising: a control device and a plurality of sensors electrically connected to the control device; the defoaming control method comprising: collecting, by the plurality of sensors, multi-source monitoring data related to the bubble state in the ink path system; establishing a bubble risk quantification model based on the multi-source monitoring data; calculating a current bubble risk index according to the bubble risk quantification model; determining a current risk level according to the bubble risk index and a preset risk level threshold; generating a defoaming control instruction according to the determined risk level.

[0005] According to some technical solutions of the present application, the sensors include ultrasonic sensors for detecting acoustic characteristics of bubbles, viscosity-temperature compound sensors for monitoring the physical state of ink, and optical sensors for detecting contaminants, and the collecting, by the plurality of sensors, multi-source monitoring data related to the bubble state in the ink path system specifically comprises: acquiring acoustic characteristic values corresponding to the existence, size and number of bubbles by the ultrasonic sensors; A viscosity-temperature composite sensor is used to collect the viscosity and temperature of the ink, and the viscosity change rate is calculated based on the viscosity and temperature. An optical particle sensor is used to collect signals of tiny particulate contaminants in the ink. Acoustic characteristic values, viscosity change rate, and particulate pollutant signals are integrated to obtain multi-source monitoring data.

[0006] According to some technical solutions of this application, the establishment of a bubble risk quantification model based on multi-source monitoring data specifically includes: Based on the multi-source monitoring data, several characteristic parameters for quantifying bubble risk were determined; Multiple feature parameters are normalized to obtain multiple normalized parameter values; Each normalized parameter value is assigned a weight to obtain the corresponding weight parameter; A bubble risk quantification model is established based on multiple normalized parameter values ​​and corresponding weighting coefficients.

[0007] According to some technical solutions of this application, the determination of multiple characteristic parameters for quantifying bubble risk based on the multi-source monitoring data specifically includes: Extract data from multi-source monitoring data to obtain extracted data; Several intermediate parameters were calculated based on the extracted data, including mechanical index, cavitation threshold, bubble radius change rate and ultrasonic energy density. Based on the mechanical index, cavitation threshold, bubble radius change rate, and ultrasonic energy density, several characteristic parameters for quantifying bubble risk were determined.

[0008] According to some technical solutions of this application, the risk level threshold includes a first risk threshold and a second risk threshold. The step of determining the current risk level based on the bubble risk index and the preset risk level threshold specifically includes: Obtain the preset first risk threshold and second risk threshold; If the bubble risk index is lower than the first risk threshold, it is judged as low risk; If the bubble risk index is between the first risk threshold and the second risk threshold, it is judged as medium risk; If the bubble risk index is greater than the second risk threshold, it is judged as high risk.

[0009] According to some technical solutions of this application, the step of generating defoaming control instructions based on the determined risk level specifically includes: When the risk level is determined to be low, a command to maintain the current operating state is generated. When the risk level is determined to be medium, a temperature adjustment command and a pumping parameter adjustment command are generated. When a high-risk condition is identified, an activation command for the defoaming device is generated.

[0010] According to some technical solutions of this application, after generating the defoaming control instruction based on the determined risk level, the method further includes: The bubble monitoring data after defoaming was collected again using multiple sensors; Based on bubble monitoring data and bubble risk quantification model, the adjusted risk index is calculated; Compare the adjusted risk index and the bubble risk index; If the adjusted risk index is lower than the bubble risk index, then record the actual parameters of the bubble risk quantification model and the corresponding defoaming control strategy.

[0011] This application also provides a multi-sensor-based defoaming control system, which includes: a control device and a plurality of sensors electrically connected to the control device; the control device is used to execute the defoaming control method described in the above technical solution.

[0012] This application also provides a defoaming control device based on multiple sensors, the defoaming control device comprising: a memory and at least one processor, wherein the memory stores instructions; At least one of the processors invokes the instructions in the memory to cause the defoaming control device to perform the various steps of the defoaming control method as described in the above technical solution.

[0013] This application also provides a computer-readable storage medium storing instructions that, when executed by a processor, implement the various steps of the defoaming control method described above.

[0014] The defoaming control method based on multiple sensors provided in this application has at least the following beneficial effects: by fusing multi-source sensor information and constructing a bubble risk quantification model, early quantitative assessment of bubble risk is achieved, and differentiated control commands are triggered based on the assessment results, which facilitates the implementation of differentiated prevention and defoaming measures. This realizes the transformation from passive response to active prevention and adaptive control, which is conducive to improving the stability and yield of OLED printing process. Attached Figure Description

[0015] Figure 1 One of the flowcharts of the defoaming control method provided in the embodiments of this application; Figure 2 A second schematic flowchart of the defoaming control system provided in the embodiments of this application; Figure 3 The third schematic diagram of the defoaming control system provided in the embodiments of this application; Figure 4The fourth schematic diagram of the defoaming control system provided in the embodiments of this application; Figure 5 Fifth schematic diagram of the defoaming control system provided in the embodiments of this application; Figure 6 A schematic diagram of the defoaming control system provided in the embodiments of this application, number six; Figure 7 The seventh schematic diagram of the defoaming control system provided in the embodiments of this application; Figure 8 This is a schematic diagram of the structure of the defoaming control system provided in the embodiments of this application; Figure 9 This is a schematic diagram of the structure of the defoaming control device provided in the embodiments of this application. Detailed Implementation

[0016] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0017] In the description of this application, it should be understood that the orientation descriptions, such as up, down, front, back, left, right, etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation or be constructed or operated in a specific orientation. Therefore, they should not be construed as limiting the present invention.

[0018] In the description of this application, unless otherwise expressly defined, terms such as "setup," "installation," and "connection" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this application in conjunction with the specific content of the technical solution.

[0019] The following is combined Figures 1 to 9 Embodiments of the present invention will be described.

[0020] The presence and movement of air bubbles can cause a series of problems. First, air bubbles traveling with the ink to the printhead nozzles can lead to unstable droplet volume, erratic flight paths, and even complete ink loss. On OLED panels, this manifests as pixel defects and uneven brightness (Mura effect), severely reducing product yield. Second, air bubble accumulation in precision nozzles or narrow flow channels can cause blockages, requiring frequent shutdowns for flushing and maintenance, reducing overall equipment efficiency. Prolonged cavitation effects can also damage critical components such as pumps and valves. Eliminating the effects of air bubbles often requires sacrificing some ink for recycling and flushing, which translates to considerable cost losses for expensive OLED functional materials.

[0021] Based on the above, this application provides a multi-sensor bubble monitoring and defoaming control method, comprising: an application to a multi-sensor-based defoaming control system, the defoaming control system comprising: a control device and a plurality of sensors electrically connected to the control device; the defoaming control method comprising: S100 collects multi-source monitoring data related to the bubble state in the ink path system through multiple sensors; for example, it monitors the ink using sensors such as ultrasonic sensors, viscosity-temperature composite sensors, and optical particle sensors. For instance, an ultrasonic sensor is installed at a critical location in the ink path, such as the main pipeline near the printhead. This sensor emits ultrasonic pulses of a specific frequency into the flowing ink and receives signals that penetrate the ink or are reflected back. By analyzing the received signals, a series of acoustic characteristic values ​​can be extracted. A viscosity-temperature composite sensor is installed in the ink circulation loop, enabling direct and synchronous measurement of the ink's real-time viscosity and temperature. An optical particle sensor is installed upstream of the ink path or in the ink supply tank. This sensor utilizes the principle of laser scattering or light blocking to monitor the number and size of tiny particulate contaminants in the ink in real time.

[0022] S200 establishes a bubble risk quantification model based on multi-source monitoring data. Since the parameters of the multi-source monitoring data have different dimensions and numerical ranges, each parameter needs to be normalized to enable weighted comparisons within a unified framework. For example, a minimum-maximum normalization method is used to map the value of each parameter to the [0,1] interval.

[0023] S300 calculates the current bubble risk index based on the bubble risk quantification model. Its magnitude directly and comprehensively reflects the probability and severity of the presence or generation of bubbles in the ink system at this moment.

[0024] S400, determine the current risk level based on the bubble risk index and the preset risk level threshold; for example, the system presets two risk thresholds, a first risk threshold and a second risk threshold, and the second risk threshold is greater than the first risk threshold.

[0025] S500 generates defoaming control instructions based on the determined risk level. For example, if the risk level is "low," a "maintenance instruction" is generated. The system maintains all current parameters and does not initiate any defoaming action. If the risk level is "medium," a "level one adjustment instruction" is generated. This instruction eliminates the causes of bubble formation by fine-tuning environmental parameters. If the risk level is "high," a "level two intervention instruction" is generated. This instruction aims to directly eliminate existing bubbles, such as activating a dedicated ultrasonic defoamer to actively break up bubbles with ultrasonic pulses of specific parameters; or opening the bypass valve of the bubble trap / degassing membrane assembly to guide the ink for efficient degassing.

[0026] Therefore, by integrating multi-source sensor information and constructing a bubble risk quantification model, early quantitative assessment of bubble risk is achieved. Based on this assessment result, differentiated control commands are triggered, facilitating the implementation of differentiated prevention and defoaming measures. This realizes a shift from passive response to proactive prevention and adaptive control. It is beneficial for improving production yield, equipment utilization, and material utilization in OLED inkjet printing and other high-precision fluid applications.

[0027] In some embodiments, the sensor includes an ultrasonic sensor for detecting the acoustic properties of bubbles, a viscosity-temperature composite sensor for monitoring the physical state of the ink, and an optical sensor for detecting contaminants. The ultrasonic sensor detects bubbles by detecting changes in the propagation characteristics of sound waves in the ink; the viscosity-temperature composite sensor directly monitors key physical state parameters of the ink; and the optical sensor is used to detect particulate contaminants that may induce bubbles. In S100, multiple sensors are used to collect multi-source monitoring data related to the bubble state in the ink path system, specifically including: S110 uses an ultrasonic sensor to collect acoustic characteristic values ​​corresponding to the presence, size, and number of bubbles; such as the degree of ultrasonic attenuation at a specific frequency and changes in propagation speed.

[0028] S120 employs a viscosity-temperature composite sensor to acquire the viscosity and temperature of the ink, and calculates the viscosity change rate based on the viscosity and temperature. Since abnormal viscosity fluctuations often precede the formation of obvious bubbles, the viscosity change rate is calculated by directly acquiring the real-time viscosity and temperature of the ink. For example, the calculation is performed with a fixed sampling period, such as acquiring the viscosity-temperature composite sensor reading once per second. The viscosity change rate is obtained by calculating the difference between the viscosity value at the current sampling moment and the viscosity value at the previous sampling moment, and then dividing by the sampling time interval.

[0029] S130 uses an optical particle sensor to collect signals of tiny particulate contaminants in ink; it monitors signals of tiny particulate contaminants that may lead to bubble nucleation.

[0030] S140 integrates acoustic characteristic values, viscosity change rate, and particulate contaminant signals to obtain multi-source monitoring data that comprehensively reflects the potential risks of bubbles.

[0031] Therefore, by integrating acoustics, rheology, and optics, the limitations of single sensor technology are reduced, enabling comprehensive monitoring of the causes and states of bubble formation, such as cavitation, changes in physical properties, and contamination.

[0032] In some embodiments, step S200 involves determining feature parameters from multi-source monitoring data, normalizing the parameters, assigning weights to the normalized parameters, and finally establishing a model based on the weighted parameters. Specifically, this includes: S210, Based on the multi-source monitoring data, determine multiple characteristic parameters for quantifying bubble risk; S220, normalizes multiple feature parameters to obtain multiple normalized parameter values; S230, assign weights to each normalized parameter value to obtain the corresponding weight parameters; S240, a bubble risk quantification model is established based on multiple normalized parameter values ​​and corresponding weight coefficients.

[0033] For example, the core of the bubble risk quantification model is a multi-parameter fusion weighted evaluation equation used to integrate data from different sensors into an intuitive risk indicator: in R This represents the bubble risk index, which comprehensively reflects the degree of risk of bubbles being generated in the current system. The higher the value, the greater the risk. This indicates that a parameter is normalized. The purpose of normalization is to convert sensor data with different dimensions and ranges into a similar range, i.e., between 0 and 1, so that they can be compared with each other by weight. The weighting parameters represent the mechanical index. The weighting parameter represents the cavitation threshold. The weighting parameter represents the static pressure of the environment. The weighted parameter represents the rate of change of the bubble radius, and satisfies... These weights can be adjusted based on different ink properties or the importance of different printing stages.

[0034] Specifically, The mechanical index, used to assess cavitation risk, is directly proportional to the negative pressure at the ultrasonic peak and inversely proportional to the square root of the ultrasonic frequency. The formula for the mechanical index is as follows: in This indicates negative pressure at the ultrasonic peak. The mechanical index indicates the ultrasonic frequency. Its physical significance lies in the fact that in ink systems where ultrasonic defoaming or cleaning is used, an excessively high index may induce localized cavitation and generate new bubbles.

[0035] This represents the cavitation threshold, which is the minimum energy or pressure required to generate cavitation bubbles in a liquid. This threshold is affected by ink formulation, temperature, and dissolved gas content. Real-time monitoring... The change in the value reflects the change in ink stability. The formula for the cavitation threshold is as follows: in, Indicates the static pressure of the environment. Indicates the surface tension of tissue fluid. This represents the initial radius of the bubble.

[0036] This represents the rate of change of bubble radius, that is... The velocity of change of a bubble under the action of ultrasound is described by the Rayleigh-Plasset equation, which simulates the dynamic process of a bubble “breathing” (oscillating) or collapsing. Drastic changes are a direct indicator of bubble instability. The formula for the rate of change of bubble radius is as follows: in Indicates the instantaneous radius of the bubble. Indicates the density of the liquid. Indicates the dynamic viscosity of a liquid. This represents the change in sound pressure over time. This represents the vapor pressure inside the bubble. This is the existing standard formula.

[0037] Ultrasonic energy density is a measure of the ultrasonic energy deposited per unit volume of medium, reflecting the intensity of cavitation. The formula for ultrasonic energy density is as follows: in This represents the ultrasonic sound pressure amplitude. This indicates the speed at which ultrasound waves propagate through the medium. In using an active ultrasonic defoaming strategy, it is necessary to... Control the level to a level sufficient to break up harmful bubbles, but not high enough to damage the ink or device.

[0038] Therefore, in some embodiments, step S210, based on the multi-source monitoring data, determines multiple characteristic parameters for quantifying bubble risk, specifically including: S231, Extract the multi-source monitoring data to obtain the extracted data; S232, based on the extracted data, several intermediate parameters are calculated, including mechanical index, cavitation threshold, bubble radius change rate and ultrasonic energy density; the intermediate parameters are directly related to the dynamic processes such as bubble generation, growth and collapse, and are thus determined as the core characteristic parameters for quantifying risk.

[0039] S233 determines multiple characteristic parameters for quantifying bubble risk based on mechanical index, cavitation threshold, bubble radius change rate, and ultrasonic energy density.

[0040] Therefore, transforming multi-dimensional monitoring data into a standardized and calculable risk index is crucial. Normalization eliminates the influence of dimensions, allowing parameters of different properties to be compared and calculated. Weight allocation reflects the differences in the contribution of different parameters to bubble risk, increasing the model's flexibility and adjustability, enabling it to adapt to the needs of different ink formulations or process stages.

[0041] In some embodiments, a risk level threshold is preset, which includes a first risk threshold and a second risk threshold. In step S400, the current risk level is determined based on the bubble risk index and the preset risk level threshold, specifically including: S410: Obtain a preset first risk threshold and a second risk threshold; based on the determined risk level, take corresponding action. For example, the risk level is divided into the following three states: S420, if the bubble risk index is lower than the first risk threshold, it is judged as low risk; at this time, all parameters fluctuate within the ideal range.

[0042] S430, if the bubble risk index is between the first risk threshold and the second risk threshold, it is determined to be medium risk; that is, when the bubble risk index is greater than or equal to the first risk threshold and less than or equal to the second risk threshold, it is determined to be medium risk, and at this time one or more parameters show observable deviation.

[0043] S440, if the bubble risk index is greater than the second risk threshold, it is judged as high risk, and the parameter deviation is obvious at this time.

[0044] Therefore, by using the first and second risk thresholds, frequent false alarms or missed alarms caused by a single threshold are avoided; the three-level early warning system makes the control strategy more hierarchical and targeted, enabling mild adjustment measures to be taken to intervene in the early stage of risk, preventing it from evolving into a high-risk event, and optimizing the stability of the control process.

[0045] In some embodiments, step S500 generates defoaming control instructions based on the determined risk level; that is, it generates control instructions of different intensities and directions based on different risk levels. Specifically, this includes: S510: When the risk is determined to be low, since all parameters fluctuate within the ideal range, the system does not take any action and generates a command to maintain the current running state and continue to maintain the existing running state. S520, when judged as medium risk, indicates that the system has a tendency to produce bubbles, and preventive measures need to be initiated, such as the system initiating a level one response, generating temperature adjustment commands and pumping parameter adjustment commands, and fine-tuning the ambient temperature and pump frequency. S530 When a high risk is determined, it indicates that bubbles have been detected or bubbles are about to be generated, and strong measures need to be taken immediately, such as initiating a secondary response and generating an activation command for the defoaming device. For example, the defoaming device includes an ultrasonic pulse defoamer or a mechanical bubble trap, so that defoaming can be carried out by means of pulse defoaming, activation of the trap, etc.

[0046] Therefore, by setting up a three-level control strategy that matches the three-level risk warning, unnecessary equipment actions and energy consumption are avoided under low-risk conditions, while ensuring that defoaming can be implemented quickly and effectively under high-risk conditions, thereby improving the overall control efficiency and reliability.

[0047] In some embodiments, after generating the defoaming control instruction based on the determined risk level, step S500 further includes: S610 re-collects bubble monitoring data after defoaming through multiple sensors; S620, based on bubble monitoring data and bubble risk quantification model, calculates the adjusted risk index; S630 will compare the adjusted risk index and the bubble risk index; S640, if the adjusted risk index is lower than the bubble risk index, then record the actual parameters of the bubble risk quantification model and the corresponding defoaming control strategy.

[0048] Specifically, after the system performs the defoaming action, it continues to monitor changes in sensor data. If the risk index decreases accordingly, it indicates that the model's judgment is accurate and the measures are effective. This successful case data is recorded to provide feedback for optimizing quantitative model parameters and strengthening the current decision-making logic. For new ink formulations or environmental conditions, the system can run under initial settings and record the results. By accumulating this new data, feature weights or risk thresholds can be dynamically adjusted, allowing the model to continuously adapt to new operating conditions.

[0049] Therefore, by accumulating operational data, the system can dynamically adjust the risk model or enrich the control strategy library, enabling it to better adapt to new ink materials, environmental conditions, or equipment status, which is conducive to continuously improving the accuracy of monitoring and control.

[0050] This application also provides a multi-sensor-based defoaming control system, which includes: a control device and a plurality of sensors electrically connected to the control device; the control device is used to execute the defoaming control method as described in the above embodiments.

[0051] In some embodiments, the control system includes an acquisition module 100, an establishment module 200, a calculation module 300, a judgment module 400, and a generation module 500.

[0052] Specifically, the acquisition module 100 is used to acquire multi-source monitoring data related to the bubble state in the ink system through multiple sensors; the establishment module 200 is used to establish a bubble risk quantification model based on the multi-source monitoring data; the calculation module 300 is used to calculate the current bubble risk index according to the bubble risk quantification model; the judgment module 400 is used to determine the current risk level according to the bubble risk index and the preset risk level threshold; and the generation module 500 is used to generate defoaming control instructions according to the determined risk level.

[0053] This application also provides a defoaming control device based on multiple sensors, the defoaming control device comprising: a memory and at least one processor, wherein the memory stores instructions; At least one of the processors invokes the instructions in the memory to cause the defoaming control device to perform the various steps of the defoaming control method as described in the above embodiments.

[0054] Figure 3 This is a schematic diagram of a defoaming control device 600 provided in an embodiment of the present invention. The defoaming control device 600 can vary significantly due to different configurations or performance characteristics. It may include one or more central processing units (CPUs) 610 (e.g., one or more processors) and a memory 620, and one or more storage media 630 (e.g., one or more mass storage devices) storing application programs 633 or data 632. The memory 620 and storage media 630 can be temporary or persistent storage. The program stored in the storage media 630 may include one or more modules (not shown in the diagram), each module including a series of instruction operations on the defoaming control device 600. Furthermore, the processor 610 may be configured to communicate with the storage media 630 and execute the series of instruction operations in the storage media 630 on the defoaming control device 600 to implement the steps of the methods provided in the above-described method embodiments.

[0055] The defoaming control device 600 may also include one or more power supplies 640, one or more wired or wireless network interfaces 650, one or more input / output interfaces 660, and / or one or more operating systems 631, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, etc. Those skilled in the art will understand that... Figure 6 The illustrated electronic device structure does not constitute a limitation on the electronic device and may include more or fewer components than illustrated, or combine certain components, or have different component arrangements.

[0056] This application also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. The computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to perform the steps of the above-described defoaming control method.

[0057] The preferred embodiments of the present invention have been described in detail above, but the present disclosure is not limited to the embodiments described. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention, and these equivalent modifications or substitutions are all included within the scope defined by the claims of the present disclosure.

Claims

1. A defoaming control method based on multiple sensors, characterized in that: An application is made to a multi-sensor-based defoaming control system, the defoaming control system comprising: a control device and multiple sensors electrically connected to the control device; the defoaming control method comprising: Multi-source monitoring data related to the bubble state in the ink system are collected using multiple sensors. A bubble risk quantification model was established based on multi-source monitoring data. The current bubble risk index is calculated based on the bubble risk quantification model. The current risk level is determined based on the bubble risk index and the preset risk level threshold; Defoaming control instructions are generated based on the determined risk level.

2. The defoaming control method based on multiple sensors according to claim 1, characterized in that: The sensors include an ultrasonic sensor for detecting the acoustic properties of air bubbles, a viscosity-temperature composite sensor for monitoring the physical state of the ink, and an optical sensor for detecting contaminants. The acquisition of multi-source monitoring data related to the air bubble state in the ink path system through multiple sensors specifically includes: An ultrasonic sensor was used to collect acoustic characteristic values ​​corresponding to the presence, size, and number of bubbles. A viscosity-temperature composite sensor is used to collect the viscosity and temperature of the ink, and the viscosity change rate is calculated based on the viscosity and temperature. An optical particle sensor is used to collect signals of tiny particulate contaminants in the ink. Acoustic characteristic values, viscosity change rate, and particulate pollutant signals are integrated to obtain multi-source monitoring data.

3. The defoaming control method based on multiple sensors according to claim 1, characterized in that: The bubble risk quantification model established based on multi-source monitoring data specifically includes: Based on the multi-source monitoring data, several characteristic parameters for quantifying bubble risk were determined; Multiple feature parameters are normalized to obtain multiple normalized parameter values; Each normalized parameter value is assigned a weight to obtain the corresponding weight parameter; A bubble risk quantification model is established based on multiple normalized parameter values ​​and corresponding weighting coefficients.

4. The defoaming control method based on multiple sensors according to claim 3, characterized in that: Based on the multi-source monitoring data, several characteristic parameters for quantifying bubble risk are determined, specifically including: Extract data from multi-source monitoring data to obtain extracted data; Several intermediate parameters were calculated based on the extracted data, including mechanical index, cavitation threshold, bubble radius change rate and ultrasonic energy density. Based on the mechanical index, cavitation threshold, bubble radius change rate, and ultrasonic energy density, several characteristic parameters for quantifying bubble risk were determined.

5. The defoaming control method based on multiple sensors according to claim 1, characterized in that: The determination of the current risk level based on the bubble risk index and a preset risk level threshold specifically includes: The preset risk level thresholds include a first risk threshold and a second risk threshold; If the bubble risk index is lower than the first risk threshold, it is judged as low risk; If the bubble risk index is between the first risk threshold and the second risk threshold, it is judged as medium risk; If the bubble risk index is greater than the second risk threshold, it is judged as high risk.

6. The defoaming control method based on multiple sensors according to claim 5, characterized in that: The process of generating defoaming control instructions based on the determined risk level specifically includes: When the risk level is determined to be low, a command to maintain the current operating state is generated. When the risk level is determined to be medium, a temperature adjustment command and a pumping parameter adjustment command are generated. When a high-risk condition is identified, an activation command for the defoaming device is generated.

7. The defoaming control method based on multiple sensors according to claim 1, characterized in that: After generating the defoaming control instruction based on the determined risk level, the process also includes: The bubble monitoring data after defoaming was collected again using multiple sensors; Based on bubble monitoring data and bubble risk quantification model, the adjusted risk index is calculated; Compare the adjusted risk index and the bubble risk index; If the adjusted risk index is lower than the bubble risk index, then record the actual parameters of the bubble risk quantification model and the corresponding defoaming control strategy.

8. A defoaming control system based on multiple sensors, characterized in that, include: A control device and a plurality of sensors electrically connected to the control device; the control device is used to perform the defoaming control method as described in any one of claims 1-7.

9. A defoaming control device based on multiple sensors, characterized in that, The defoaming control device includes: a memory and at least one processor, wherein the memory stores instructions; At least one of the processors invokes the instructions in the memory to cause the defoaming control device to perform the steps of the defoaming control method as described in any one of claims 1-7.

10. A computer-readable storage medium having instructions stored thereon, characterized in that, When the instructions are executed by the processor, they implement the steps of the defoaming control method as described in any one of claims 1-7.

Images