A glass slide marking machine and a material jam prediction method thereof

Abstract

The application relates to the technical field of medical equipment, and provides a card jam pre-judgment method of a slide marking machine and the slide marking machine, which comprises the following steps: collecting a load parameter of a driving motor driving a feeding device in real time, and generating a measured load curve; comparing the measured load curve with a standard load curve, and extracting a difference feature; when the difference feature meets a card jam precursor condition, determining that there is a card jam risk, and outputting a warning or performing an intervention action. According to the application, subtle changes of the load curve are monitored in real time, risks can be identified and active intervention can be performed before a card jam fault occurs, the equipment maintenance mode is upgraded from "passive maintenance" to "active pre-judgment", and the operation reliability of the slide marking machine is remarkably improved.

Description

Technical Field

[0001] This application relates to the field of medical device technology, and in particular to a method for predicting jamming in a slide marking machine and the slide marking machine itself. Background Technology

[0002] In the pathology testing process, glass slides, as carriers of pathological tissue samples, need to be labeled with patient information (such as name, pathology number, and testing date) before testing to enable sample traceability. A slide labeling machine is an automated device that performs this function, using a slide pushing mechanism to push slides one by one from the hopper to the printing station to complete the information labeling.

[0003] However, existing slide marking machines frequently face the following technical problems during the slide pushing process: First, slide adhesion leads to abnormal slide pushing. Due to the smooth surface of the slides, when multiple slides are stacked in the hopper, adjacent slides are easily adhered due to static electricity or moisture. During slide pushing, the pushing component may push multiple slides simultaneously, or jam at the discharge port, preventing the equipment from picking up slides normally. Second, slide breakage is difficult to detect in a timely manner. The slides are only about 1 mm thick and are brittle. When the pushing mechanism has abnormal resistance or the slide itself has microcracks, the slide is prone to breakage during the pushing process. The fragments may damage the equipment or contaminate the samples, and manual cleaning is often required to restore operation after breakage, affecting testing efficiency. Third, existing fault detection solutions are all "post-hoc". Some researchers have attempted to detect slide pushing abnormalities through motor parameters. For example, by detecting the motor running distance through an encoder, when the number of pulses (i.e., the running distance) is less than a preset threshold, it is determined that the motor is stalled, thus identifying slide adhesion and taking measures such as increasing the current to attempt separation or stopping the motor for manual intervention. However, this approach has significant limitations. Its judgment is based on "the number of pulses being less than a preset threshold," meaning that an anomaly can only be detected when the pushing action is obstructed and the motor can no longer complete the predetermined stroke. By this time, the fault has already occurred, and the equipment is already stopped, representing a typical post-fault detection method.

[0004] In summary, existing slide marking machines lack the ability to identify and proactively intervene in issues such as slide adhesion and abnormal pushing resistance before material jamming actually occurs during the slide pushing process. Therefore, how to predict and intervene in material jamming risks during slide pushing has become a pressing technical problem to be solved in this field.

[0005] Application content The main purpose of this application is to provide a method for predicting material jamming in a glass slide marking machine and the glass slide marking machine itself. By collecting the load parameters (current and / or torque) of the drive motor in real time, a measured load curve is generated and compared with a standard load curve to extract the difference features. Thus, when the difference features meet the preset warning conditions for material jamming, the risk can be judged in advance and proactive intervention can be carried out, upgrading the equipment maintenance mode from "passive maintenance" to "proactive prediction".

[0006] In a first aspect, embodiments of this application provide a method for predicting material jamming in a glass slide marking machine, comprising the following steps: During the slide pushing operation of the feeding device of the glass slide marking machine, the load parameters of the drive motor are collected in real time to generate a measured load curve. The measured load curve is compared with the pre-stored standard load curve, and the difference features are extracted; When the difference characteristics meet the preset warning conditions for material jamming, it is determined that there is a risk of material jamming. Based on the judgment result, output a warning signal and / or control the feeding device to perform intervention actions; The load parameters include the drive current value and / or drive torque value of the drive motor.

[0007] In one embodiment, the difference features include at least one of the following: The measured load curve shows the fluctuation amplitude and frequency in the early section of the pusher stroke; The ratio of the mean deviation between the measured load curve and the standard load curve over the entire stroke; The measured load curve shows an instantaneous decrease in amplitude during the pusher stroke; The aforementioned warning conditions for material jamming include: When the fluctuation amplitude exceeds the first threshold and the fluctuation frequency exceeds the second threshold, it is determined to be a precursor to material jamming caused by adhesion between glass slides or debris. When the mean deviation ratio exceeds the third threshold, it is determined that the pushing mechanism has abnormal resistance. When the instantaneous amplitude drops below the no-load current value, it is determined that the glass slide has been damaged.

[0008] In one embodiment, the step of performing the intervention action includes: When the material jamming is detected as a sign of adhesion or debris between glass slides, the feeding device is controlled to retract a preset distance and then push the slide again at a reduced speed, and / or a micro-vibration pushing strategy of slow push-pause-slow push is implemented. When the resistance of the pushing mechanism is determined to be abnormal, a cleaning or maintenance prompt is output, and the pushing speed is automatically reduced; When it is determined that the glass slide has been damaged, the slide pushing action is stopped immediately, an alarm signal is output, and the current glass slide and the corresponding glass slide hopper are marked as abnormal.

[0009] In one embodiment, the standard load curve is generated in the following manner: During the equipment factory calibration phase, at least one successful slide pushing operation is performed using a standard glass slide to collect the load parameters of the drive motor and form a factory standard curve. And / or, during equipment use, the measured load curves of multiple successful wafer pushes are screened and averaged to update the standard load curve and achieve adaptive calibration; The screening process includes removing abnormal curves that deviate from the current standard curve by more than a preset multiple.

[0010] In one embodiment, it further includes: Record each predicted event indicating a risk of material jamming. The recorded information for each predicted event includes the time of occurrence, the type of judgment, the differential characteristic data, and the actual result after intervention. When the number of times the same type of material jamming risk occurs within a preset time window exceeds the fourth threshold, a device health warning is generated, prompting the corresponding mechanical components to be inspected or maintained.

[0011] In one embodiment, the slide marking machine further includes: a first slide hopper, a second slide hopper, and corresponding first and second feeding devices; The method further includes: when it is determined that there is a risk of material jamming based on the measured load curve of the first feeding device, the pushing task is switched to the second feeding device, the second feeding device is controlled to perform a pushing operation, and an abnormal handling operation is performed on the first feeding device.

[0012] In one embodiment, switching the current push task to the second feeding device includes: When it is determined that the risk of material jamming is of the type that will cause equipment failure or glass slide damage, the current pushing action of the first feeding device is immediately interrupted and the unfinished pushing task is switched to the second feeding device. When it is determined that the material jamming risk belongs to the abnormal resistance type of the pushing mechanism and has not yet reached the emergency fault threshold, the total number of current tasks to be printed is obtained, and the remaining number of pusher times is estimated based on the historical trend of the average current deviation ratio of the first feeding device. When the remaining number of pusher times is less than the total number of tasks to be printed, the subsequent pusher tasks are switched to the second feeding device after the first feeding device completes the current pusher task.

[0013] In one embodiment, it further includes: During the push-piece operation of the second feeding device, the result of the abnormal handling operation performed on the first feeding device is recorded; The first feeding device is managed based on the results.

[0014] In one embodiment, it further includes: During the slide pushing process, auxiliary sensing signals are collected simultaneously. The auxiliary sensing signals include at least one of the slide pushing vibration signal, the glass slide friction sound signal, and the slide pushing position signal. The measured load curve is fused with the auxiliary sensing signal and input into the trained classification model to output the probability value of material jamming risk. When the probability value of the material jamming risk exceeds the fifth threshold, it is determined that there is a risk of material jamming. The classification model uses a support vector machine or random forest model, and its training data includes signal data from the historical push process and the corresponding push result labels.

[0015] Secondly, embodiments of this application provide a slide marking machine, comprising: An outer casing; at least one slide hopper disposed on the outer casing for holding slides; A feeding device, located inside the outer casing, is used to push glass slides from the glass slide hopper to the printing station; A drive motor is used to drive the feeding device; A sensing module, coupled to the drive motor, is used to collect the load curve of the drive motor in real time during the feeding device's push-piece operation. Storage module, used to store standard load curves; The processing module, connected to the sensing module and the storage module respectively, is used to compare the measured load curve with the standard load curve and extract the difference features; when the difference features meet the preset material jamming warning conditions, it is determined that there is a risk of material jamming; based on the judgment result, an early warning signal is output and / or the feeding device is controlled to perform an intervention action; wherein, the load parameters include the drive current value and / or drive torque value of the drive motor.

[0016] Beneficial effects: By collecting the load parameters of the drive motor of the feeding device in real time during the slide pushing operation of the glass slide marking machine, a measured load curve is generated. The measured load curve is compared with the pre-stored standard load curve to extract the difference features. Based on the difference features and the preset jamming warning conditions, the risk of jamming can be judged in advance, and the warning or intervention can be carried out proactively based on the judgment results, upgrading the equipment maintenance mode from "passive maintenance" to "proactive prediction". Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of the structure of a slide marking machine provided in one embodiment of this application; Figure 2 This is a flowchart illustrating a method for predicting material jamming in a glass slide marking machine according to an embodiment of this application. Figure 3 This is a schematic diagram of the structure of a slide marking machine provided in another embodiment of this application; Figure 4 This is a flowchart illustrating a method for predicting material jamming in a glass slide marking machine, as provided in another embodiment of this application.

[0019] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0021] It should be noted that all directional indicators (such as up, down, left, right, front, back, etc.) in the embodiments of this application are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicator will also change accordingly.

[0022] Furthermore, the use of terms such as "first" and "second" in this application is for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the term "and / or" throughout the text includes three solutions; taking A and / or B as an example, it includes technical solution A, technical solution B, and a technical solution that simultaneously satisfies A and B. Furthermore, the technical solutions of various embodiments can be combined with each other, but this must be based on the ability of a person skilled in the art to implement them. When the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0023] A slide numbering machine is an automated device specifically designed for hospital pathology departments. It is primarily used to quickly and accurately print patient information (such as name, pathology number, and test date) onto glass slides (carriers of pathological tissue samples). It is a key piece of equipment in the pathology workflow, typically including thermal ribbon printers and slide numbering machines. This application aims to provide a method for predicting slide jamming in a slide numbering machine and the slide numbering machine itself. By identifying and proactively intervening in risks before slide jamming occurs, the equipment maintenance mode is upgraded from "passive maintenance" to "proactive prediction," significantly improving the operational reliability of the slide numbering machine.

[0024] The method for predicting material jamming in the slide marking machine is implemented by the slide marking machine itself.

[0025] Please see Figure 1 , Figure 1 This is a schematic diagram of a slide marking machine provided in one embodiment of this application. Figure 1 As can be seen, the slide marking machine 10 provided in this application includes a housing 11, a slide hopper 50 disposed on the housing 11 for accommodating slides, a feeding device 20 disposed inside the housing 11, and a printing station 40. The feeding device 20 is used to push the slides from the slide hopper 50 to the printing station 40. The drive motor 30 is integrated into the drive assembly of the feeding device 20 and is used to drive the feeding device 20 to perform the pushing action.

[0026] The sensing module 60 is coupled to the drive motor 30 and is used to collect the load parameters of the drive motor of the feeding device 20 in real time during the pushing operation of the feeding device 20, generating a measured load curve. The storage module 70 is used to store the standard load curve. The processing module 80 is connected to both the sensing module 60 and the storage module 70, and is used to compare the measured load curve with the standard load curve, extract the difference features, and determine that there is a risk of jamming when the difference features meet the preset jamming precursor conditions. The processing module 80 outputs a warning signal and / or controls the feeding device 20 to perform intervention actions based on the determination result. The load parameters include the drive current value and / or drive torque value of the drive motor.

[0027] The glass slide marking machine 10 provided in this application, through the sensing module 60 coupled to the drive motor 30, collects the load curve of the drive motor 30 in real time during the slide pushing operation of the feeding device 20, generates the measured load curve, and compares it with the pre-stored standard load curve, thereby realizing the prediction of risks and proactive intervention before the occurrence of material jamming failure.

[0028] Based on the aforementioned slide marking machine 10, this application embodiment provides a method for predicting material jamming in the slide marking machine. This method comprises... Figure 1 The slide marking machine 10 shown is used for this operation. The method will be described in detail below with reference to specific embodiments.

[0029] Please see Figure 2 , Figure 2 This application provides a method for predicting material jamming in a slide marking machine, as an embodiment of the present application. Figure 2 It can be seen that the method includes the following steps: S210: During the slide pushing operation of the feeding device of the glass slide marking machine, the load parameters of the drive motor are collected in real time to generate a measured load curve.

[0030] The feeding device is activated to push the slides. During the slide pushing operation of the glass slide marking machine, the load parameters of the drive motor are collected in real time at a preset frequency by a sensing module, generating a measured load curve that changes over time. The load parameters include the drive motor's drive current value (unit: A) and / or drive torque value (unit: N·m). The sampling frequency is preferably 100Hz-1000Hz to capture subtle changes during the slide pushing process.

[0031] S220: Compare the measured load curve with the pre-stored standard load curve and extract the difference features.

[0032] The processing module reads the standard load curve from the storage module, compares the measured load curve with the standard load curve, and extracts the differences.

[0033] In this embodiment, the difference features include at least one of the following: (1) the fluctuation amplitude and fluctuation frequency of the measured load curve in the first section of the pusher stroke; (2) the average deviation ratio between the measured load curve and the standard load curve over the entire stroke; (3) the instantaneous amplitude decrease of the measured load curve during the pusher stroke.

[0034] S230: When the difference characteristics meet the preset warning conditions for material jamming, it is determined that there is a risk of material jamming.

[0035] The processing module determines the risk of different card materials based on the extracted differential features.

[0036] Specifically, if the fluctuation amplitude exceeds a first threshold (e.g., the first threshold is 3 times the normal fluctuation amplitude) and the fluctuation frequency exceeds a second threshold (e.g., the second threshold is 10Hz), then it is determined that there is a precursor to material jamming caused by adhesion or debris between glass slides. The principle is that adhesion or debris will cause periodic jerking during the movement of the glass slide, which is reflected as periodic and violent fluctuations in the driving current or driving torque value of the drive motor.

[0037] If the difference characteristic is that the proportion of mean deviation exceeds the third threshold (for example, the third threshold is 20%), then it is determined that there is a precursor to material jamming due to abnormal resistance in the pushing mechanism. The principle is that track wear, foreign object intrusion, etc., will continuously increase the overall friction, resulting in a significant increase in the average load.

[0038] If the difference is characterized by a sudden drop in amplitude that falls below the no-load current, it is determined to be a precursor to glass slide breakage and jamming. The principle is that at the moment the glass slide breaks, the load on the drive motor is suddenly released, and the drive current or drive torque value of the drive motor drops to near the no-load value.

[0039] By extracting three different characteristics of the measured load curve in the early section of the slide pushing stroke—the fluctuation amplitude and frequency, the deviation ratio from the mean of the standard curve, and the instantaneous amplitude decrease—it is possible to predict different types of jamming risks, such as slide adhesion or debris, abnormal resistance of the pushing mechanism, and slide breakage, thus achieving full coverage prediction of multiple failure modes.

[0040] It should be noted that the first threshold, the second threshold, and the third threshold mentioned above are all preset empirical values ​​or experimental calibration values. The specific values ​​can be adjusted according to factors such as the mechanical structure, drive motor parameters, and slide specifications of different models of slide marking machines. This application does not impose any restrictions on these values.

[0041] S240: Output a warning signal and / or control the feeding device to perform an intervention action based on the judgment result; wherein, the load parameters include the drive current value and / or drive torque value of the drive motor.

[0042] The processing module executes differentiated response strategies based on different judgment results.

[0043] For example, when the determination result is that the material jamming is caused by the adhesion between glass slides or debris, the pusher of the feeding device is controlled to retract a preset distance (e.g., 5mm-10mm), and then pushed again at a reduced speed to try to gently separate the adhered glass slides.

[0044] Alternatively, the feeding device can be controlled to execute a micro-vibration pushing strategy of "slow push-pause-slow push again" (e.g., advance 2-3mm, pause for 0.1-0.3s, repeat).

[0045] If the above strategy fails to push normally after a preset number of attempts (e.g., 3 times), it is determined to be a serious sticking, an alarm signal is output, and the use of the hopper is suspended.

[0046] When the abnormal resistance of the pushing mechanism is detected, a cleaning or maintenance prompt is output (such as "Please clean the pushing track" or "Please check if there are foreign objects in the clearance part"), and the pushing speed is automatically reduced, such as to 60%-80% of the normal speed, in order to reduce impact and wear and prevent the fault from worsening.

[0047] When a glass slide is determined to be broken, the slide pushing action is immediately stopped, an alarm signal is output, and the current glass slide and its corresponding slide hopper are marked as abnormal to prevent contamination or damage to subsequent glass slides. The breakage event is recorded for later analysis. This application designs differentiated intervention strategies for different types of material jamming risks: for signs of adhesion, a retraction and re-pushing strategy or a micro-vibration strategy is used to attempt gentle separation; for abnormal resistance, a maintenance prompt is output and the speed is reduced; for glass slide breakage, the machine is immediately stopped and marked as abnormal. This tiered intervention strategy ensures the continuous operation of the equipment while preventing the malfunction from worsening or causing secondary damage.

[0048] As can be seen from the above analysis, the slide marking machine jam prediction method provided in this application includes: real-time acquisition of the load parameters of the drive motor of the drive feeding device to generate a measured load curve; comparison of the measured load curve with a standard load curve to extract the difference features; and determination of jam risk when the difference features meet the jam precursor conditions, and output of warning or execution of intervention actions. This application, by real-time monitoring of subtle changes in the load curve, can identify risks and proactively intervene before a jam failure occurs, upgrading the equipment maintenance mode from "passive maintenance" to "proactive prediction," significantly improving the operational reliability of the slide marking machine.

[0049] To make the comparison benchmark more accurate, this application also provides a mechanism for generating and adaptively updating standard load curves.

[0050] Specifically, the standard load curve is generated by performing at least one, preferably 3-5, successful slide pushing operations using a standard glass slide during the equipment factory calibration phase, collecting the load parameters of the drive motor, taking the average value as the factory standard curve, and storing it in the storage module.

[0051] The adaptive update method for the standard load curve includes: during equipment use, after each successful slide push (i.e., without triggering any material jamming risk judgment and with normal slide printing), the measured curve of that slide push is included in the adaptive calibration data pool. When the data pool accumulates multiple consecutive (e.g., 3 or more) measured load curves of successful slide pushes, the mean curve and standard deviation curve of N (N≥3, preferably 10) curves are calculated, and abnormal curves that deviate from the mean by more than a preset multiple (e.g., 2 times the standard deviation) are removed (these abnormal curves may be caused by occasional factors); the average value of the remaining curves is used as the updated standard load curve, replacing the original curve in the storage module.

[0052] For example, during three months of continuous operation of a certain device (approximately 15,000 pushes), adaptive calibration was triggered 12 times. After calibration, the average current of the standard curve gradually adjusted from the initial 285mA to 268mA, reflecting the true state of the device after break-in. The false alarm rate (misjudging normal pushes as abnormal) decreased from 5.2% before calibration to 1.8% after calibration.

[0053] This application uses an adaptive calibration mechanism to dynamically update the standard load curve using data from continuous successful wafer pushing. This allows it to adapt to changes in equipment conditions such as break-in and wear, significantly reducing the false alarm rate (experimental data shows it can be reduced from 5.2% to 1.8%).

[0054] Please see Figure 3 , Figure 3 This is a schematic diagram of a slide marking machine provided in another embodiment of this application. The slide marking machine 10 and... Figure 1 Compared to the slide marking machine 10 shown, its main difference lies in the inclusion of dual material bins and dual feeding devices. Specifically, as shown... Figure 3 As shown, the dual-bin glass slide marking machine 20 includes: a first glass slide bin 12, a second glass slide bin 13, and a first feeding device 14 and a second feeding device 15 corresponding to each of them.

[0055] Based on this dual-hopper slide marking machine, this application also provides a method for predicting slide jamming in the slide marking machine. Please refer to [link to relevant documentation]. Figure 4 This method is in Figure 2 Based on the method shown, the task scheduling and state management between the two material warehouses are further explained. Details are as follows: S410: During the slide pushing operation of the first feeding device of the slide marking machine, the load parameters of the drive motor are collected in real time to generate a measured load curve.

[0056] The specific implementation method of this step and Figure 2 The steps S210 shown are the same, and will not be repeated here.

[0057] S420: Compare the measured load curve with the pre-stored standard load curve and extract the difference features.

[0058] The specific implementation method of this step and Figure 2 The steps S220 shown are the same, and will not be repeated here.

[0059] S430: When the difference characteristics meet the preset material jamming precursor conditions, it is determined that there is a risk of material jamming in the first hopper.

[0060] The specific implementation method of this step and Figure 2 Step S230 is the same as shown, and will not be repeated here. It should be noted that the "material jamming risk" determined in this step includes, but is not limited to, glass slide adhesion or fragmentation, abnormal resistance of the pushing mechanism, glass slide breakage, etc.

[0061] S440: When it is determined that there is a risk of material jamming in the first hopper based on the measured load curve of the first feeding device, the pushing task is switched to the second feeding device, the second feeding device is controlled to perform the pushing operation, and the first feeding device is subjected to an abnormal handling operation.

[0062] In this embodiment, task switching is divided into the following two scenarios: Scenario 1: When it is determined that the risk of material jamming is of the type that will cause equipment failure or glass slide damage (e.g., the glass slide is broken, the current drops suddenly to below the no-load value, etc.), the processing module immediately interrupts the current pushing action of the first feeding device and seamlessly switches the unfinished pushing task to the second feeding device, which continues to perform the pushing operation. At the same time, the first feeding device is subjected to abnormal handling operations (e.g., controlling the pusher to return to the initial position and outputting an emergency fault prompt for the first hopper).

[0063] Scenario 2: When the risk of material jamming is determined to be of the abnormal resistance type of the pushing mechanism, and has not yet reached the preset emergency fault threshold, the processing module obtains the total number of tasks to be printed; based on the historical trend of the average current deviation ratio of the first feeding device, it estimates the remaining number of pushes; when the remaining number of pushes is less than the total number of tasks to be printed, after the first feeding device completes the current push task, the subsequent push tasks are switched to the second feeding device, and a prompt message indicating that the first hopper needs preventive maintenance is output; if the remaining number of pushes is greater than or equal to the total number of tasks to be printed, no switching is performed, and the first feeding device continues to perform the task, but its pushing speed is reduced and continuous monitoring is carried out.

[0064] S450: During the push-piece operation of the second feeding device, the result of the abnormal handling operation performed on the first feeding device is recorded, and the first feeding device is managed according to the result.

[0065] Specifically, when the abnormal handling operation of the first feeding device is successful (e.g., the device returns to normal after executing a rollback-repush strategy, or the fault is eliminated after manual cleaning), the first feeding device is marked as "standby available". At this time, the hopper can be reinstated into the task scheduling queue for use by subsequent tasks. By recording and analyzing the trends of predicted events, equipment health warnings can be generated when similar material jam risks occur frequently, prompting users to inspect or maintain the corresponding mechanical components, thus achieving an upgrade from single-time prediction to long-term health management.

[0066] If the abnormal handling operation of the first feeding device fails and the cumulative number of failures of the same type exceeds the preset threshold (for example, the same fault type cannot be recovered after 3 consecutive abnormal handling operations, or 5 failures in 24 hours), the first feeding device will be marked as "fault disabled" and a targeted maintenance prompt message will be output (for example, "Please check whether there are foreign objects or mechanical wear on the first hopper push track").

[0067] A hopper marked as "fault disabled" can only be marked as "standby available" after the user performs maintenance operations and manually confirms the recovery.

[0068] This embodiment, through its dual-bin structure and task switching mechanism, allows for seamless task switching to the second bin when a jam occurs in the first bin. This ensures that the overall printing task is not affected during the handling of the anomaly, significantly improving the task continuity and throughput efficiency of the equipment.

[0069] Furthermore, as another preferred embodiment of this application, the material jamming risk determination in steps S410 to S430 above can also be achieved using a multi-sensor fusion approach to further improve the accuracy of the determination. Specifically, this includes: synchronously acquiring auxiliary sensing signals during the slide pushing process, wherein the auxiliary sensing signals include at least one of the slide pushing vibration signal, the glass slide friction sound signal, and the slide pushing position signal; performing feature fusion between the measured load curve and the auxiliary sensing signals, and inputting the fused feature vector into a pre-trained classification model, which outputs a material jamming risk probability value; when the material jamming risk probability value exceeds a fifth threshold (e.g., 0.7 or 0.8, the specific value can be set according to the equipment model and actual needs), a material jamming risk is determined to exist.

[0070] The classification model can be a support vector machine (SVM) or a random forest model. Its training data comes from the load curves, auxiliary sensor signals and corresponding final slide label (e.g., success, jam, broken slide) collected during the historical slide pushing process.

[0071] By using multi-sensor fusion to determine the load curve and combining it with auxiliary signals such as vibration, sound, and position, and inputting them into the classification model, the accuracy of material jamming risk assessment is further improved.

[0072] The above description is merely a preferred embodiment of this application and does not limit the patent scope of this application. Any equivalent structural transformations made based on the concept of this application and the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included within the patent protection scope of this application.

Claims

1. A method for predicting material jamming in a glass slide marking machine, characterized in that, Includes the following steps: During the slide pushing operation of the feeding device of the glass slide marking machine, the load parameters of the drive motor are collected in real time to generate a measured load curve. The measured load curve is compared with the pre-stored standard load curve, and the difference features are extracted; When the difference characteristics meet the preset warning conditions for material jamming, it is determined that there is a risk of material jamming. Based on the judgment result, output a warning signal and / or control the feeding device to perform intervention actions; The load parameters include the drive current value and / or drive torque value of the drive motor.

2. The method according to claim 1, characterized in that, The difference features include at least one of the following: The measured load curve shows the fluctuation amplitude and frequency in the early section of the pusher stroke; The ratio of the mean deviation between the measured load curve and the standard load curve over the entire stroke; The measured load curve shows an instantaneous decrease in amplitude during the pusher stroke; The aforementioned warning conditions for material jamming include: When the fluctuation amplitude exceeds the first threshold and the fluctuation frequency exceeds the second threshold, it is determined to be a precursor to material jamming caused by adhesion between glass slides or debris. When the mean deviation ratio exceeds the third threshold, it is determined that the pushing mechanism has abnormal resistance. When the instantaneous amplitude drops below the no-load current value, it is determined that the glass slide has been damaged.

3. The method according to claim 2, characterized in that, The steps for performing the intervention include: When the material jamming is detected as a sign of adhesion or debris between glass slides, the feeding device is controlled to retract a preset distance and then push the slide again at a reduced speed, and / or a micro-vibration pushing strategy of slow push-pause-slow push is implemented. When the resistance of the pushing mechanism is determined to be abnormal, a cleaning or maintenance prompt is output, and the pushing speed is automatically reduced; When it is determined that the glass slide has been damaged, the slide pushing action is stopped immediately, an alarm signal is output, and the current glass slide and the corresponding glass slide hopper are marked as abnormal.

4. The method according to claim 1, characterized in that, The standard load curve is generated in the following manner: During the equipment factory calibration phase, at least one successful slide pushing operation is performed using a standard glass slide to collect the load parameters of the drive motor and form a factory standard curve. And / or, during equipment use, the measured load curves of multiple successful wafer pushes are screened and averaged to update the standard load curve and achieve adaptive calibration; The screening process includes removing abnormal curves that deviate from the current standard curve by more than a preset multiple.

5. The method according to claim 1, characterized in that, Also includes: Record each predicted event indicating a risk of material jamming. The recorded information for each predicted event includes the time of occurrence, the type of judgment, the differential characteristic data, and the actual result after intervention. When the number of times the same type of material jamming risk occurs within a preset time window exceeds the fourth threshold, a device health warning is generated, prompting the corresponding mechanical components to be inspected or maintained.

6. The method according to claim 1, characterized in that, The glass slide marking machine also includes: a first glass slide hopper, a second glass slide hopper, and corresponding first and second feeding devices; The method further includes: when it is determined that there is a risk of material jamming based on the measured load curve of the first feeding device, the pushing task is switched to the second feeding device, the second feeding device is controlled to perform a pushing operation, and an abnormal handling operation is performed on the first feeding device.

7. The method according to claim 6, characterized in that, The step of switching the current push task to the second feeding device includes: When it is determined that the risk of material jamming is of the type that will cause equipment failure or glass slide damage, the current pushing action of the first feeding device is immediately interrupted and the unfinished pushing task is switched to the second feeding device. When it is determined that the material jamming risk is of the abnormal resistance type of the pushing mechanism and has not yet reached the preset emergency fault threshold, the total number of current tasks to be printed is obtained, and the remaining number of pushes is estimated based on the historical trend of the average current deviation ratio of the first feeding device. When the remaining number of pushes is less than the total number of tasks to be printed, the subsequent pushes are switched to the second feeding device after the first feeding device completes the current push task.

8. The method according to claim 6, characterized in that, Also includes: During the pusher operation of the second feeding device, the result of the abnormal handling operation performed on the first feeding device is recorded, and the first feeding device is managed according to the result.

9. The method according to claim 1, characterized in that, Also includes: During the slide pushing process, auxiliary sensing signals are collected simultaneously. The auxiliary sensing signals include at least one of the slide pushing vibration signal, the glass slide friction sound signal, and the slide pushing position signal. The measured load curve is fused with the auxiliary sensing signal and input into the trained classification model to output the probability value of material jamming risk. When the probability value of the material jamming risk exceeds the fifth threshold, it is determined that there is a risk of material jamming. The classification model uses a support vector machine or random forest model, and its training data includes signal data from the historical push process and the corresponding push result labels.

10. A glass slide marking machine, characterized in that, include: outer shell; At least one slide hopper is provided on the outer casing for holding glass slides; A feeding device, located inside the outer casing, is used to push glass slides from the glass slide hopper to the printing station; A drive motor is used to drive the feeding device; A sensing module, coupled to the drive motor, is used to collect the load curve of the drive motor in real time during the feeding device's push-piece operation. Storage module, used to store standard load curves; The processing module is connected to the sensing module and the storage module respectively, and is used to compare the measured load curve with the standard load curve and extract the difference features. When the difference characteristics meet the preset warning conditions for material jamming, it is determined that there is a risk of material jamming; based on the determination result, an early warning signal is output and / or the feeding device is controlled to perform an intervention action; wherein, the load parameters include the drive current value and / or drive torque value of the drive motor.

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