Nanometer microcrystalline glass calendaring forming equipment and control method thereof

Abstract

The invention discloses nanocrystalline glass calendaring equipment and a control method thereof, and relates to the technical field of microcrystalline glass processing, the end point of the maximum allowable continuous operation speed interval is used as a safe operation boundary point in a process regulation strategy, a speed-risk coupling model is constructed, and a comprehensive risk evaluation value at a corresponding calendaring speed is output. And in the process control stages from the speed intervention point to the end point of the maximum allowable operation interval, for each process control stage, on the basis of the comprehensive risk evaluation value output in real time in the process control stage, the allowable rolling speed upper limit value of the stage is calculated, and a speed safety boundary curve dynamically adjusted along with the process progress is formed. According to the control method, through a technical path of risk identification-boundary quantification-dynamic regulation and control, the intelligent level of the production process is remarkably improved while the forming quality of the nanocrystalline glass and the reliability of equipment are guaranteed.

Description

Technical Field

[0001] This invention relates to the field of microcrystalline glass processing technology, specifically to nanocrystalline glass calendering equipment and its control method. Background Technology

[0002] In the industrial rolling process of nanocrystalline glass, in order to pursue production efficiency and capacity, a higher rolling speed is usually adopted to increase the output of glass strip per unit time. However, as the rolling speed increases, the frictional heat generated between the rolling roll and the glass strip intensifies, causing the surface and internal temperature of the rolling roll to rise rapidly. At the same time, the mechanical vibration of the equipment is enhanced under high-speed operation, the load on key components (such as bearings and transmission systems) increases, and the equipment performance is prone to progressive deterioration. In addition, problems such as uneven heating and unbalanced stress distribution of glass during high-speed flow will also significantly increase the probability of forming quality defects such as thickness deviation, surface ripples, and edge breakage. To control the aforementioned risks, the industry currently employs fixed speed thresholds or empirical speed reduction strategies. These strategies maintain production within a preset speed range or directly reduce the operating speed when a local anomaly is detected (such as excessive roller temperature). However, these methods have significant limitations: Firstly, fixed thresholds do not consider the dynamic evolution of equipment status (such as cumulative roller temperature rise and vibration energy changes) and glass properties (such as viscosity migration and flow response) during the process, which can easily lead to "overly conservative speed limiting" (sacrificing efficiency but with manageable actual risks) or "lagging control" (reducing speed only after the risk has occurred). Secondly, empirical strategies lack systematic correlation analysis of multi-dimensional risk indicators (such as roller temperature gradient, vibration spectrum, and glass thickness deviation rate), making it difficult to accurately quantify the comprehensive risk of process degradation at different speeds and failing to achieve multi-objective synergistic optimization of "efficiency-quality-equipment lifespan".

[0003] Given the aforementioned needs, for applications requiring continuous control of equipment performance degradation and product quality deterioration risks during high-speed calendering, a sophisticated control method is urgently needed. This method can dynamically sense multi-dimensional operating states, accurately quantify the nonlinear correlation between speed and risk, and adaptively adjust the calendering speed accordingly. Therefore, achieving dynamic adaptation of the safety boundary of calendering speed through real-time monitoring, risk modeling, and dynamic regulation has become a pressing technical problem to be solved in this field. Summary of the Invention

[0004] The purpose of this invention is to provide a nanocrystalline glass calendering equipment and its control method to solve the problems in the prior art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for controlling the rolling and forming of nanocrystalline glass, the method comprising the following steps: S1: Collect multi-dimensional operating status data during the rolling process of nanocrystalline glass, analyze it using a process degradation model, identify risk indicators that will lead to equipment performance degradation or product quality degradation in the current process stage, and calculate the maximum allowable continuous operating speed range within the safe threshold range for all risk indicators. The endpoint of this maximum allowable continuous operating speed range is taken as the safe operating boundary point in the process control strategy, and further defined as the speed intervention point. S2: Construct a speed-risk coupling model to quantitatively describe the nonlinear relationship between rolling speed and various process degradation risks. The output is the comprehensive risk assessment value under the corresponding rolling speed. In the process control stage from the speed intervention point to the end of the maximum allowable operating range, for each process control stage, based on the comprehensive risk assessment value output in real time within the process control stage, calculate the upper limit of the allowable rolling speed for that stage, forming a speed safety boundary curve that is dynamically adjusted with the process progress. S3: Based on each process control stage and the corresponding calculated upper limit of the rolling speed, a process speed control strategy that dynamically evolves with the rolling process is constructed.

[0006] Preferably, in step S2: the speed-risk coupling model comprehensively reflects the impact of increasing the rolling speed on the temperature rise rate of the rolling roll, thermal stress distribution, and vibration energy, as well as the mechanism by which increasing the rolling speed affects the glass strip's fluidity, thickness uniformity, and edge forming quality.

[0007] Preferably, in step S2: the speed-risk coupling model comprehensively reflects a mechanism-driven analytical expression, that is, it is based on the theories of heat conduction, rheology and mechanical vibration. The input parameters include the current equipment status, glass physical property parameters and process settings, and the output is the comprehensive risk assessment value at the corresponding rolling speed.

[0008] Preferably, in step S2: constructing a speed-risk coupling model to quantitatively describe the nonlinear correlation between rolling speed and various process degradation risks, and outputting a comprehensive risk assessment value at the corresponding rolling speed, includes the following steps: The input parameters of the speed-risk coupling model include current equipment status parameters, glass physical property parameters, and process settings. The input parameters are mapped to a comprehensive risk assessment value. The comprehensive risk assessment value is a multi-dimensional comprehensive indicator of equipment performance degradation risk and product quality degradation risk. The magnitude of the comprehensive risk assessment value represents the overall risk level of the process system at the current speed. Based on the constructed speed-risk coupling model, the process is divided into time slices, roll positions, or production stages during the process control phase from the speed intervention point to the end of the maximum allowable operating range. The upper limit of the allowable calendering speed is calculated in real time for each process control stage. Based on the real-time operating status data and glass property parameters of the current stage, the speed-risk coupling model is input and the comprehensive risk assessment value corresponding to different speeds at this stage is output.

[0009] Preferably, S2: In the process control phase from the speed intervention point to the end of the maximum allowable operating range, for each process control phase, based on the comprehensive risk assessment value output in real time within that process control phase, the upper limit of the allowable rolling speed for that phase is calculated, forming a speed safety boundary curve that is dynamically adjusted with the process progress, including the following steps: By filtering through reverse constraint logic, and using the safety threshold of all risk indicators as a benchmark, the speed parameters are gradually adjusted until the highest speed value corresponding to the condition that all risk indicators do not exceed the threshold is found. The highest speed value is the upper limit of the rolling speed allowed in the current process control stage. As the process progresses, the risk characteristics of different process control stages will dynamically evolve due to the heat accumulation effect of the equipment, slight fluctuations in glass composition, or changes in the state of the roll surface, causing the upper limit of the allowable rolling speed to show a gradual decreasing trend.

[0010] Preferably, S1: Identify risk indicators that will lead to equipment performance degradation or product quality deterioration in the current process stage, and calculate the maximum permissible continuous operating speed range within which all risk indicators are within the safe threshold range. The endpoint of this maximum permissible continuous operating speed range is taken as the safe operating boundary point in the process control strategy, and further defined as the speed intervention point, including the following steps: A thermal fatigue accumulation model is constructed based on the theory of heat conduction and thermal stress to assess the risk of thermodynamic degradation of equipment. The temperature gradient and number of thermal cycles in the roller part are calculated by real-time temperature field data, and the degree of damage accumulation of material microstructure is evaluated. Vibration signal spectrum analysis technology is used to assess the risk of mechanical vibration degradation, extracting the characteristic frequency energy proportions corresponding to typical faults such as bearing wear and gear damage, and combining the vibration amplitude time series to determine the degree of abnormality of mechanical components. To address the risk of deterioration in glass forming quality, statistical process control methods are used to analyze the real-time fluctuation trends of thickness consistency standard deviation and surface waviness amplitude, and to identify the risk level of process stability deviating from the threshold. Identify risk indicators that could lead to a decline in equipment performance or a deterioration in product quality at the current stage of the process, including but not limited to excessive roller temperature, abnormal vibration, and an increase in glass defect rate. Based on the identified risk indicators, the maximum permissible continuous operating speed range is calculated so that all risk indicators remain within the safe threshold range during the current process task cycle or planned production interval.

[0011] Preferably, in step S3: a process speed control strategy that dynamically evolves with the rolling process is constructed, and the logic of the control strategy is as follows: Starting from the speed intervention point, as the process progresses, the allowable upper limit of the rolling speed is gradually lowered, so that the actual rolling speed does not exceed the safe upper limit allowed for that stage at each process control stage.

[0012] Preferably, multi-dimensional operational status data are collected during the calendering process of nanocrystalline glass. This multi-dimensional operational status data is related to equipment performance degradation and process stability. The multi-dimensional operational status data includes the surface temperature distribution of the calendering roll, local temperature difference, thermal deformation, vibration amplitude and spectrum characteristics; roll bearing load, drive motor current fluctuation, abnormal signals of the transmission system; glass strip thickness consistency, surface waviness, edge integrity, flow uniformity; actual calendering speed, deviation between set pressure and actual pressing force, and roll gap control stability.

[0013] This application also provides a nanocrystalline glass calendering equipment. The equipment includes a main body and a circulating liquid cooling calendering mechanism. The circulating liquid cooling calendering mechanism includes a frame and a set of two calendering rollers on the top of the frame. The calendering rollers are rotatably connected to the frame via bearings. A motor is also fixedly installed on one side of the top of the frame. The motor drives the two calendering rollers to rotate in opposite directions via a reducer.

[0014] Preferably, the calender roll has an S-shaped channel inside, and the outlet and inlet of the S-shaped channel are located on the side away from the motor. The calender roll also has multiple small impeller generators inside, which are electrically connected to a thermometer mounted on the frame.

[0015] The technical effects and advantages provided by the present invention in the above technical solution are as follows: 1. This invention enables early warning and quantitative definition of potential process degradation risks, avoiding the problems of "overly conservative speed limiting" (limiting capacity but actual risks are controllable) or "lagging control" (intervening only after risks have occurred) caused by the traditional fixed threshold speed limiting method, which ignores the dynamic evolution of equipment status. It reduces the risk of thermal fatigue, mechanical damage and sudden failure caused by long-term high temperature, high vibration and high load operation of equipment from the source, significantly extends the service life of core components such as calendering rolls and transmission systems, and improves the long-term operational stability of production equipment.

[0016] 2. This invention dynamically determines the upper limit of the allowable rolling speed for each stage based on a comprehensive risk assessment value calculated in real time, ultimately forming a speed safety boundary curve that adjusts in real time according to the process progress (such as roll temperature accumulation, glass composition changes, and equipment load shifts). This technology overcomes the limitations of traditional static speed management methods, achieving dynamic matching between speed control and process status—when equipment heat accumulation intensifies or glass fluidity changes, the system automatically identifies the increased risk and lowers the upper limit of the speed for the corresponding stage; conversely, if the status is stable, the speed is maintained or finely adjusted, ensuring that each process stage operates under controllable risk, solving the efficiency loss problem caused by "one-size-fits-all" speed limits, and accurately avoiding the risk of process degradation caused by improper speed.

[0017] 3. This invention maximizes production efficiency and increases the output of glass strip per unit time by avoiding unnecessary speed limitations (such as maintaining a high speed during the stable phase of equipment operation). By strictly limiting the rolling speed during high-risk phases (such as when the roll temperature approaches the threshold or the glass thickness deviation increases), it effectively reduces quality problems such as uneven thickness, surface ripples, and edge damage caused by excessive speed, thereby improving the forming accuracy and yield of nanocrystalline glass. At the same time, by reducing the probability of the equipment being in extreme conditions such as high temperature and high vibration for a long time, it slows down the thermal fatigue, mechanical wear, and aging process of the rolling rolls and transmission system, reduces the number of unplanned downtime maintenance and maintenance costs, and achieves multi-objective synergistic optimization of production efficiency, product quality, and equipment life. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0019] Figure 1 This is a flowchart of the control method of the present invention.

[0020] Figure 2 This is a schematic diagram of the overall structure of the molding system of the present invention.

[0021] In the diagram: 1 - Equipment body; 2 - Circulating liquid cooling calendering mechanism; 3 - Frame; 4 - Calendering roll; 5 - Motor; 6 - Reducer. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] Example: This example provides a method for controlling the calendering and forming of nanocrystalline glass. Please refer to [link / reference]. Figure 1 As shown, the control method includes the following steps: S1: Identify potential degradation risks in the calendering process and determine the safe operating window and control start point for the process speed. Collect multi-dimensional operational status data related to equipment performance degradation and process stability during the rolling process of nanocrystalline glass, including: Temperature distribution, local temperature difference, thermal deformation, vibration amplitude and spectral characteristics of calender roll surface; Roller bearing load, drive motor current fluctuation, and abnormal signals in the transmission system; Forming quality indicators include glass ribbon thickness consistency, surface waviness, edge integrity, and flow uniformity; Process parameters such as actual calendering speed, deviation between set pressure and actual pressing force, and roll gap control stability.

[0024] Based on multi-dimensional operational status data, analysis is conducted using process degradation models (such as thermal fatigue accumulation models) to identify key risk indicators that may lead to equipment performance degradation or product quality deterioration in the current process stage, and calculations are performed. Within the current process task cycle or planned production range, the maximum permissible continuous operating speed range that can ensure all key risk indicators (such as excessive roller temperature, abnormal vibration, and increased glass defect rate) remain within the safety threshold range. The endpoint of the maximum permissible continuous operating speed range (i.e., the highest control point at which the rolling speed can be safely maintained without causing significant process degradation risk) is taken as the safe operating boundary point in the process control strategy, and further defined as the speed intervention point. This point marks the transition of the calendering process from a "high-efficiency and stable operation period" to a "risk prevention and control period requiring active speed reduction," and is a key starting point for implementing subsequent adaptive speed control strategies.

[0025] S2: Establish a coupling relationship model between speed and process risk, and calculate the allowable upper limit of process speed stage by stage. A speed-risk coupling model is constructed to quantitatively describe the nonlinear correlation between rolling speed and the risk of various process degradations. This speed-risk coupling model comprehensively reflects: The effects of increasing calendering speed on the temperature rise rate, thermal stress distribution, and vibration energy of calendering rolls; The mechanism by which it affects the fluidity, thickness uniformity, and edge forming quality of glass ribbon; The speed-risk coupling model is a mechanism-driven analytical expression (such as based on heat conduction, rheology and mechanical vibration theory). The input parameters include the current equipment status, glass physical properties and process settings, and the output is the comprehensive risk assessment value at the corresponding rolling speed.

[0026] In the process control phase from the speed intervention point to the end of the maximum allowable operating range (i.e., the transitional range where there is still potential for speed increase but requires gradual adjustment), for each process control phase (e.g., control nodes divided by time slice, by roll position segment, or by production stage), based on the comprehensive risk assessment value output in real time within that phase, calculate the upper limit of the allowable calendering speed for that phase: The upper limit of the rolling speed indicates that, in order to ensure the stability of equipment operation and the quality of glass forming, the rolling speed should not exceed this limit at the current stage. As the process progresses, due to heat accumulation in the equipment, changes in glass composition, or changes in the condition of the roller surface, the upper limit of the speed allowed in different control stages will gradually decrease, forming a speed safety boundary curve that is dynamically adjusted with the process.

[0027] S3: Construct a dynamic speed control strategy to achieve adaptive speed reduction and multi-objective collaborative optimization in the rolling process. Based on each process control stage and its corresponding calculated upper limit value for rolling speed, a process speed control strategy that dynamically evolves with the rolling process is constructed. Its core control logic is as follows: Starting from the speed intervention point, as the process progresses, the allowable upper limit of the rolling speed is gradually reduced to ensure that the actual rolling speed does not exceed the safe upper limit allowed for that stage at each process control stage. This strategy does not involve a fixed speed reduction, but rather dynamically calculates and adapts the upper limit of the rolling speed for each stage based on the actual conditions of the equipment and glass at each stage (such as roll temperature distribution, vibration level, glass thickness deviation, etc.) to achieve precise and flexible speed control.

[0028] This dynamic control strategy plays the following multi-objective optimization role during process execution: While ensuring the safety and quality of equipment and products, maintain a high calendering speed as much as possible to improve output per unit time and overall production efficiency; prevent problems such as abnormal roll temperature, glass flow instability, and surface defects caused by excessive speed to ensure the uniformity of thickness, surface smoothness, and consistency of internal microstructure of nanocrystalline glass; and reduce thermal fatigue, mechanical wear, and system aging by avoiding calendering rolls from being in extreme working conditions such as high temperature, high vibration, and high load for a long time, thereby extending the service life of equipment and reducing unplanned downtime and maintenance frequency.

[0029] This strategy is deeply integrated with the online monitoring system of the rolling equipment, the glass quality sensing module, and the intelligent decision-making unit to form a closed-loop control system of "state perception - risk prediction - speed regulation - effect feedback". This achieves truly adaptive and intelligent rolling speed management, effectively supporting the stable production of high-precision, high-quality nanocrystalline glass.

[0030] This embodiment provides a nanocrystalline glass calendering and forming equipment. Please refer to [link / reference]. Figure 2 As shown, the molding equipment includes a main body 1, on which a circulating liquid cooling calendering mechanism 2 is provided. The circulating liquid cooling calendering mechanism 2 includes a frame 3, and a set of calendering rollers 4 is provided on the top of the frame 3. There are two calendering rollers 4. The calendering rollers are rotatably connected to the frame 3 through bearings. A motor 5 is also fixedly provided on one side of the top of the frame 3. The motor 5 drives the two calendering rollers 4 to rotate in opposite directions through a reducer 6. An S-shaped channel is opened inside the calendering roller 4. The outlet and inlet of the S-shaped channel are both located on the side away from the motor 5. Multiple small impeller generators are also provided inside the calendering roller 4. The impeller generators are electrically connected to a thermometer installed on the frame 3. During the calendering process, the motor 5 is controlled to run according to the calendering speed output by the controller. The motor 5 drives the two calendering rollers 4 to rotate in opposite directions through the reducer 6 to calender the microcrystalline glass. The glass is heated by the electric heating element embedded in the inner wall of the calendering roller 4. During the cooling process, the outlet and inlet of the S-shaped channel are connected to the external coolant circulation system through a seal. The external coolant circulation system injects coolant into the S-shaped channel through the inlet. When the coolant flows, the impeller generator generates electricity and supplies power to the thermometer. The thermometer displays the temperature of the calendering roller 4 in real time. After cooling is completed, the external coolant circulation system draws the coolant back from the S-shaped channel 7 through the outlet, completing the coolant recovery.

[0031] The implementation details of this application are described below: In the description disclosed in this embodiment: a multi-type high-precision sensor network deployed in key parts of the calendering equipment is used to collect multi-dimensional operating status data closely related to equipment performance degradation and process stability in real time, specifically covering the following four types of core parameters: The thermodynamic and mechanical state parameters of calender rolls include the three-dimensional temperature distribution on the calender roll surface (continuous temperature field data along the axial and circumferential directions of the roll body), the temperature difference in local high-temperature areas (hot spots and their temperature gradients are identified through gridded temperature monitoring), the thermal deformation of the roll body (radial / axial deformation of the roll surface measured by a laser displacement sensor), and the vibration amplitude and spectral characteristics (vibration signals are acquired through an accelerometer, and characteristic frequencies and energy distribution are extracted through fast Fourier transform). The mechanical transmission status parameters of calendering equipment include the roller bearing load (bearing radial / axial load measured by strain gauges or force sensors), drive motor current fluctuations (real-time change curve of motor input current collected by current sensors), and abnormal signals of the transmission system (such as abnormal gear meshing frequency and specific frequency noise caused by insufficient bearing lubrication). The quality parameters of glass ribbon forming involve the consistency of glass ribbon thickness (multi-point thickness measurement data and standard deviation along the longitudinal and transverse directions of the ribbon surface), surface waviness (the amplitude and wavelength distribution of surface micro-undulations detected by optical interferometer or laser profilometer), edge integrity (visual identification results of defects such as cracks and missing corners in the edge area), and flow uniformity (simulation results of the flow pattern of glass melt in the roll gap area or the actual edge flow symmetry index). Process control parameters include actual rolling speed (real-time linear speed measured by the encoder), deviation between set pressure and actual pressing force (the degree of deviation between the inter-roll contact pressure measured by the pressure sensor and the process set value), and roll gap control stability (real-time fluctuation range of the gap between the upper and lower rolls and its mean deviation).

[0032] In the description disclosed in this embodiment: In view of the risk of thermodynamic deterioration of equipment, a thermal fatigue accumulation model is constructed based on the theory of heat conduction and thermal stress. The temperature gradient and number of thermal cycles of key parts of the roller (such as the bearing support area and the transmission connection part) are calculated by real-time temperature field data to assess the degree of accumulation of material microstructure damage. During continuous calendering production, frictional heat generated between the calendering rolls and the glass belt causes the roll temperature to rise continuously. In particular, the bearing support area (such as near the bearing seats at both ends of the roll) is prone to forming localized high-temperature hotspots due to poor heat dissipation and radial load. If the temperature in this area exceeds the allowable temperature threshold of the material (such as alloy steel) (e.g., 800℃), or if it undergoes multiple "heating-cooling" thermal cycles in a short period of time (such as natural cooling after each batch of calendering and reheating for the next batch), it will cause damage to the microstructure of the material (such as grain boundary oxidation and the initiation of thermal fatigue cracks).

[0033] A thermocouple array (5mm spacing, covering both axial and circumferential directions) is deployed in the bearing support area of ​​the roller to acquire real-time temperature distribution data (e.g., the highest temperature currently measured is 780℃, and the temperature of the adjacent area is 520℃, forming a local temperature difference of 260℃). Based on heat conduction theory, the temperature gradient between the bearing support area and the center area of ​​the roller is calculated (ΔT=780℃-520℃=260℃). Simultaneously, by recording the cooling time after each batch of calendering and the heating rate of the next batch, the number of thermal cycles experienced by this area in the current process stage (e.g., continuous production for 5 hours) is counted (e.g., each batch is cooled to 300℃ and then reheated to above 750℃, accumulating 12 thermal cycles). If the temperature gradient exceeds the safety threshold (e.g., 200℃), or the number of thermal cycles approaches the material fatigue life limit (e.g., the design allows for maintenance after 20 thermal cycles), the model determines that there is a risk of thermodynamic degradation in this area.

[0034] Examples of key risk indicators: Roll temperature exceeding limits: The real-time temperature of the bearing support area reaches 810℃ (exceeding the material's allowable threshold of 800℃), triggering a "high temperature warning"; Thermal stress concentration: A local temperature difference of 260℃ causes thermal stress to exceed the material's yield strength, which may lead to the propagation of micro-cracks; If the speed and temperature are not reduced in time, it may further develop into thermal fatigue cracking (such as visible network cracks on the roll surface), eventually leading to roll breakage or bearing seizure.

[0035] In the description disclosed in this embodiment: In response to the risk of mechanical vibration deterioration, vibration signal spectrum analysis technology is used to extract the characteristic frequency energy ratio corresponding to typical faults such as bearing wear and gear damage, and the degree of abnormality of mechanical components is judged by combining the vibration amplitude time series. Under high-speed operation of calendering equipment (e.g., linear speed ≥ 15 m / min), bearings, as key components supporting the rollers, will generate vibration signals at specific frequencies if they wear due to long-term load or insufficient lubrication (e.g., raceway surface peeling, rolling element damage). (For example, the characteristic frequency of inner ring failure is 120 Hz, and the characteristic frequency of outer ring failure is 80 Hz). When the proportion of such vibration energy increases abnormally, it indicates bearing performance degradation, which may further deteriorate into severe vibration or even equipment shutdown.

[0036] Vibration signals are acquired in real time using an accelerometer (sampling frequency 10kHz) installed near the calender roll bearing housing (e.g., the current vibration amplitude is 0.5g, and the energy proportion of the 120Hz frequency component in the spectrum is 15%). The vibration signal is then decomposed using Fast Fourier Transform (FFT) to extract the energy proportion of characteristic frequencies corresponding to typical faults (e.g., 120Hz for inner ring faults, 80Hz for outer ring faults, and 200Hz for gear meshing). Simultaneously, the time-series changes in vibration amplitude are monitored (e.g., the vibration amplitude has continuously increased from 0.3g to 0.5g within the last 10 minutes). If the energy proportion of characteristic frequencies exceeds a preset warning value (e.g., the normal threshold for bearing fault characteristic frequency energy proportion is ≤10%, currently 15%), or the vibration amplitude exceeds the safe range (e.g., normal ≤0.4g, currently 0.5g), the model determines that there is a risk of mechanical vibration deterioration.

[0037] Examples of key risk indicators: Abnormal vibration: 15% of the energy at the characteristic frequency of 120Hz (exceeding the threshold of 10%) indicates that the inner ring of the bearing may be worn; Accumulated vibration energy: An increase in the proportion of high-frequency vibration (>1kHz) energy may cause micro-vibration wear on the roller surface or ripples on the glass belt surface; If the speed is not reduced and repaired in time, the bearing wear may be aggravated, which may cause axial movement of the roller (e.g., runout ≥0.1mm), resulting in excessive thickness deviation of the glass belt (e.g., local thickness deviation ≥0.3mm) or edge damage.

[0038] In the description disclosed in this embodiment: In response to the risk of deterioration in glass forming quality, the real-time fluctuation trend of parameters such as thickness consistency standard deviation and surface waviness amplitude is analyzed by statistical process control methods to identify the risk level of process stability deviating from the threshold.

[0039] The forming quality of nanocrystalline glass is highly dependent on the stability of the rolling speed and roll gap control. If the rolling speed is too fast (e.g., increasing from 12m / min to 18m / min), the flow time of the glass melt in the roll gap area is shortened, which may lead to uneven flow speed between the edge and the center (e.g., edge flow lag), resulting in thickness deviation (e.g., the edge thickness is 0.2mm thinner than the center). If the thickness uniformity exceeds the process allowable range (e.g., standard deviation ≥ 0.1mm), it will lead to a decrease in the optical performance of the finished product (e.g., uneven light transmittance) or a reduction in mechanical strength.

[0040] Using laser thickness gauges (accuracy ±0.01mm, measurement frequency 100Hz) positioned on the upper and lower surfaces of the glass strip, the thickness data of the strip surface in the longitudinal (along the rolling direction) and transverse (width direction) directions are acquired in real time (e.g., the current transverse thickness standard deviation is 0.08mm, the minimum thickness in the edge area is 2.95mm, and the thickness in the center is 3.10mm). Based on the statistical process control (SPC) method, the real-time trends of parameters such as the thickness consistency standard deviation (σ) and surface waviness amplitude (e.g., the height of fluctuation within a 10mm wavelength) are calculated (e.g., σ gradually increases from 0.06mm to 0.08mm in the past 5 minutes, and the minimum edge thickness decreases from 3.00mm to 2.95mm). If the thickness consistency standard deviation exceeds the process allowable value (e.g., ≤0.07mm), or the surface waviness amplitude exceeds the design limit (e.g., ≤0.05mm, currently 0.06mm), the model determines that there is a risk of deterioration in the glass forming quality.

[0041] Examples of key risk indicators: Thickness deviation exceeding tolerance: Edge area thickness 2.95mm (below the lower limit of the target value of 3.00mm ± 0.05mm), and lateral standard deviation 0.08mm (exceeding the threshold of 0.07mm); Surface ripple exceeding tolerance: Ripple amplitude within 50mm wavelength reaches 0.1mm (exceeding the allowable value of 0.08mm), affecting the surface smoothness of the glass strip; If the rolling speed or roll gap is not adjusted in time, it may lead to an increase in edge breakage rate (e.g., ≥3 corner defects per kilometer of glass strip) and unqualified optical uniformity of finished products (e.g., light transmittance deviation ≥ 5%).

[0042] Based on the above analysis results, the model identifies key risk indicators that may lead to a decline in equipment performance (such as thermal fatigue cracking of the roller, premature wear of bearings, and reduced efficiency of the transmission system) or a deterioration in product quality (such as excessive thickness deviation, excessive surface ripples, and increased edge breakage rate) in the current process stage (such as single-batch production cycle, continuous production time window, or specific process parameter setting range). These indicators include, but are not limited to, excessive roller temperature (such as exceeding the allowable temperature threshold of the material), abnormal vibration (such as the proportion of specific fault frequency energy exceeding the preset warning value), and increased glass defect rate (such as the proportion of thickness deviation area or the proportion of surface ripple length exceeding the process allowable value).

[0043] During a specific continuous production phase (e.g., a single batch production cycle of 2 hours), the model integrates the above analysis results and outputs key risk indicators: The bearing support area temperature is 810℃ (exceeding the allowable threshold of 800℃), and the thermal gradient is 260℃ (exceeding the safe value of 200℃). The bearing's 120Hz characteristic frequency energy accounts for 15% (exceeding the threshold of 10%), and the vibration amplitude is 0.5g (exceeding 0.4g). The thickness consistency standard deviation is 0.08mm (exceeding 0.07mm), and the edge breakage rate has increased by 2 locations / km compared to the previous batch.

[0044] Based on this, the system determines that the current process stage has a combined risk of "equipment thermodynamic deterioration (high temperature of the roller), mechanical vibration deterioration (bearing wear), and glass forming quality deterioration (uneven thickness)". It is necessary to suppress the further development of the risk through a dynamic speed reduction strategy (such as reducing the rolling speed from 16m / min to 14m / min).

[0045] In the description disclosed in this embodiment: Based on the identified key risk indicators, the process degradation model further calculates the maximum permissible continuous operating speed range that can ensure all key risk indicators remain within the safety threshold range during the current process task cycle (such as the duration of a single continuous rolling operation, or the total rolling volume corresponding to a planned production order) or planned production interval. This calculation process uses reverse constraint logic: Using the safety thresholds of each risk indicator as constraints (such as roller temperature ≤ 800℃, vibration characteristic frequency energy ≤ 5% of total energy, and glass thickness deviation rate ≤ ±0.5%), the set of highest speeds that meet all constraints is selected by iteratively adjusting the speed parameters. The upper limit of this set is the endpoint of the maximum allowable continuous operating speed range.

[0046] This endpoint is defined as the safe operating boundary point in the process control strategy (i.e., the highest control point at which the rolling speed can be safely maintained without triggering a significant risk of process degradation), and is further named the speed intervention point. This point has a clear process significance—it marks the transition of the rolling process from the "high-efficiency and stable operation period" (the equipment and process are in good condition, allowing for the maintenance of a higher speed to increase capacity) to the "risk prevention and control period that requires active speed control" (the equipment or process condition shows a potential trend of degradation, and speed control is needed to suppress the further development of risks). It is the key starting point for triggering the implementation of subsequent adaptive speed control strategies.

[0047] In the description disclosed in this embodiment: a speed-risk coupling model is constructed. This model uses mechanism-driven analytical expression processing logic to comprehensively reflect the nonlinear influence mechanism of rolling speed changes on equipment and process status, specifically covering the following core relationships: Firstly, increasing the calendering speed directly exacerbates the rate of frictional heat generation between the calendering roll and the glass strip. This leads to an increase in the temperature gradient on the surface and inside of the roll through the heat conduction path, thereby accelerating the accumulation of local thermal stress (such as thermal deformation stress in the bearing support area of ​​the roll due to excessive temperature difference). At the same time, the mechanical vibration energy caused by high-speed friction (such as an increase in the proportion of energy in the high-frequency vibration band) is also enhanced. Secondly, increased speed affects the flow behavior of the glass melt in the roll gap area, resulting in decreased uniformity of glass strip thickness (such as increased difference in flow speed between the edge and the center during high-speed flow, leading to thickness deviation), increased surface waviness (such as micro-undulations caused by flow instability), and deterioration of edge forming quality (such as an increased probability of edge cracks or missing corners).

[0048] The model's input parameters include three key types of information: first, current equipment status parameters (such as real-time temperature distribution of the calendering rolls, vibration spectrum characteristics, and bearing load values); second, glass physical property parameters (such as the viscosity-temperature curve, surface tension coefficient, and melt flow index of the current batch of glass); and third, process settings (such as target thickness, set pressing force, and roll gap). Through mechanistic analysis, the model maps these parameters to a comprehensive risk assessment value—a multi-dimensional comprehensive indicator of equipment performance degradation risk (such as thermal fatigue accumulation index and vibration anomaly index) and product quality degradation risk (such as thickness deviation index and surface ripple index). Its magnitude directly represents the overall risk level of the process system at the current speed.

[0049] In the description disclosed in this embodiment: Based on the constructed speed-risk coupling model, in the process control stage from the speed intervention point to the end of the maximum allowable operating range (in this stage, the equipment and process status have not yet deteriorated significantly, but active adjustment is still needed to prevent risk accumulation), the system further refines the control granularity, dividing the process into time slices (e.g., every 5 minutes is a control node), roll position segments (e.g., every 10° rotation of the calendering roll is a control node), or production stages (e.g., every 100 meters of glass ribbon produced is a control node), and calculates the upper limit of the allowable calendering speed in real time for each process control stage; Based on the real-time operating status data of the current stage (such as the roller temperature distribution, vibration signal, and glass thickness measurement within this time slice) and glass physical property parameters, input the speed-risk coupling model and output the comprehensive risk assessment value under different assumed speeds for this stage. By using reverse constraint logic for screening—based on the safety thresholds of all key risk indicators (e.g., thermal stress index ≤ safety threshold A, vibration anomaly index ≤ safety threshold B, thickness deviation index ≤ safety threshold C)—the assumed speed parameters are gradually adjusted until the highest speed value corresponding to the condition that all risk indicators do not exceed the threshold is found. This value is the upper limit of the rolling speed allowed in the current process control stage. This upper limit clearly defines the critical point that the rolling speed cannot be exceeded in the current stage to ensure the stability of equipment operation (e.g., avoiding thermal fatigue crack propagation and vibration-induced mechanical damage) and the quality of glass forming (e.g., maintaining thickness uniformity and controlling surface defect rate).

[0050] As the process progresses, the risk characteristics of different process control stages will dynamically evolve due to equipment heat accumulation effects (such as the continuous increase in calender roll temperature due to sustained high-speed operation), slight fluctuations in glass composition (such as viscosity changes caused by deviations in raw material mixing ratios), or roll surface condition migration (such as wear on the roll surface microstructure altering thermal conductivity). This will lead to a gradual decrease in the allowable speed limit. The system dynamically plots a speed safety boundary curve that adjusts with the process progress (such as time, roll rotation, and production accumulation) by updating the comprehensive risk assessment value of each stage in real time. This curve, with speed on the vertical axis and process progress on the horizontal axis, shows the current maximum allowable speed value for each control node, intuitively reflecting the control requirement that "speed should decrease as risk increases." The dynamic nature of this curve ensures that the control strategy always matches the actual process state, avoiding the control lag or overly conservative problems caused by ignoring state evolution in traditional fixed speed thresholds. This provides a precise, staged speed constraint basis for subsequent adaptive speed control strategies.

[0051] The input parameters involved in this embodiment are divided into three categories of key information, and their specific data comes from the online monitoring system and process setting parameter table in actual production: Data collected using a thermocouple array positioned on the roller surface (every 10cm axially and every 5cm circumferentially) showed that the highest temperature in the roller bearing support area (near the drive end) during the current time slice (first 5 minutes) was 760℃ (close to the material's allowable threshold of 800℃), with a local temperature difference (between the hot spot and the roller's center area) of 240℃. Vibration spectrum characteristics were obtained from an accelerometer (sampling frequency 10kHz). Spectrum analysis showed that the energy percentage at 120Hz (the bearing inner ring fault characteristic frequency) was 8% (normal threshold ≤10%), but the vibration amplitude was 0.42g (close to the safe upper limit of 0.45g). The radial load on the bearing, measured by strain gauges, was 75% of the rated value (not overloaded, but continuous high-speed operation may lead to load accumulation).

[0052] Viscosity-temperature profile: The current glass melt temperature is 1450℃, corresponding to a viscosity of 1.2×10⁻⁶. 6 Pa·s (in the viscosity range suitable for calendering, but the viscosity decreases by about 5% for every 10°C increase in temperature); Surface tension coefficient: 0.35 N / m (affects the flow stability at the edge of the glass ribbon); Melt flowability index: 0.85 (medium flowability, requires high pressure to ensure uniform filling of the roll gap).

[0053] Target thickness: 3.00±0.05mm (allowable thickness deviation range is 2.95~3.05mm); Set the pressing force to 500kN (corresponding to a theoretical value of 0.8mm for the roll gap). Roll gap: The actual measured value is 0.78mm (slightly smaller than the set value, and the filling uniformity needs to be balanced by adjusting the speed).

[0054] In this embodiment, the system divides the process into time slices (each 5 minutes is a control node). The current analysis is of the first 5 minutes (that is, the initial stage after the speed intervention point, when the equipment and process status have not deteriorated significantly, but risk accumulation needs to be prevented).

[0055] The equipment status parameters (roller temperature 760℃, vibration amplitude 0.42g, 120Hz energy percentage 8%) and glass physical properties (viscosity 1.2×10⁻⁶) within the first 5 minutes were recorded. 8 The input speed-risk coupling model uses the parameters (Pa·s, flowability index 0.85) and process settings (target thickness 3.00 mm, pressing force 500 kN, roll gap 0.78 mm) as inputs. The model maps these parameters to a comprehensive risk assessment value through mechanistic analysis—a multi-dimensional comprehensive indicator of equipment performance degradation risk (such as thermal fatigue accumulation index, vibration anomaly index) and product quality degradation risk (such as thickness deviation index, surface ripple index).

[0056] Based on the current process setting speed (15m / min), a series of incremental speed values ​​(such as 14m / min, 15m / min, 16m / min, 17m / min) are assumed. For each assumed speed, the model calculates the roller temperature gradient (the higher the speed, the faster the frictional heat generation, and the larger the temperature gradient), vibration spectrum energy (increased speed may aggravate mechanical vibration), and glass thickness fluctuation (excessive speed may lead to uneven flow and increased thickness deviation) based on the heat conduction theory, and outputs the comprehensive risk assessment value at that speed.

[0057] Screening is conducted based on the safety thresholds of all key risk indicators: Thermal stress index ≤ safety threshold A (e.g., 200MPa, corresponding to roll temperature ≤ 800℃ and local temperature difference ≤ 250℃). Vibration anomaly index ≤ safety threshold B (e.g., 10% of 120Hz energy percentage, vibration amplitude ≤ 0.45g). Thickness deviation index ≤ safety threshold C (e.g., thickness standard deviation ≤ 0.07 mm, ensuring a pass rate of ≥ 99% for target thickness 3.00 ± 0.05 mm).

[0058] By gradually adjusting the assumed velocity parameters (trying from high to low), it was found that: When the assumed speed is 16 m / min, the model calculation shows that the temperature in the roller bearing support area rises to 785℃ (close to the 800℃ threshold), the local temperature difference is 255℃ (exceeding 250℃), and the thermal stress index is 210 MPa (exceeding the safety threshold A); at the same time, the vibration amplitude rises to 0.46g (exceeding 0.45g), the energy proportion of 120Hz rises to 11% (exceeding 10%), and the comprehensive risk assessment value exceeds the standard. When the speed is assumed to drop to 15 m / min, the roller temperature stabilizes at 760℃ (not exceeding 800℃), the local temperature difference is 240℃ (not exceeding 250℃), the thermal stress index is 190 MPa (≤200 MPa), the vibration amplitude is 0.42g (≤0.45g), the energy proportion of 120Hz is 8% (≤10%), the standard deviation of glass thickness is 0.06mm (≤0.07mm), and all comprehensive risk assessment values ​​meet the standards. If the speed is further reduced to 14 m / min, although the risk is lower, it would be an overly conservative speed limit (resulting in efficiency loss).

[0059] Therefore, the maximum allowable rolling speed in the current process control phase (the first 5 minutes) is 15 m / min—that is, at this speed, the real-time status of the equipment and the glass meets the safety thresholds of all key risk indicators, and it is the maximum efficiency speed achievable under current conditions.

[0060] As the process progresses (e.g. from the first 5 minutes to the sixth 5 minutes), the equipment and process conditions change dynamically due to heat accumulation, glass composition fluctuations, or roller surface condition migration, causing the allowable speed limit to gradually decrease at each stage. The system plots a speed safety boundary curve in real time (with speed as the vertical axis, process progress as the horizontal axis, and the horizontal axis marked with time slice number or cumulative output value).

[0061] 1) The first 5 minutes to the third 5 minutes (initial stabilization phase) The first 5 minutes: Speed ​​limit 15m / min (as calculated above); In the second 5-minute period: due to the continuous high-speed operation of the calendering rolls, the temperature in the bearing support area accumulated to 775℃ (an increase of 15℃ from the initial temperature), with a local temperature difference of 245℃, and the thermal stress index rose to 195MPa (close to the threshold); at the same time, due to a slight decrease in the feed inlet temperature (from 1450℃ to 1445℃), the viscosity of the glass melt increased to 1.25×10⁻⁶. 6 Pa·s, fluidity decreased slightly, and the standard deviation of thickness increased to 0.065 mm. The upper limit of the speed allowed by the model calculation was fine-tuned to 14.5 m / min (0.5 m / min lower than in stage 1).

[0062] 2) From the 4th to the 6th 5-minute period (mid-term risk accumulation phase) In the fourth 5-minute period: the calender roll temperature further increased to 790℃ (approaching the 800℃ threshold), the local temperature difference was 250℃, and the thermal stress index was 200MPa (reaching the edge of the safety threshold); the vibration amplitude increased to 0.44g (approaching 0.45g) due to the cumulative bearing load, and the energy proportion of 120Hz was 9% (approaching 10%); the standard deviation of glass thickness was 0.07mm (reaching the upper limit of the threshold). The upper limit of the model calculation speed decreased to 14m / min (a further decrease of 0.5m / min compared to the second stage).

[0063] The sixth 5-minute interval: The roller temperature reached 805℃ (exceeding the permissible threshold), with a local temperature difference of 260℃, significantly increasing the risk of thermal fatigue cracking; due to a slight adjustment in the raw material mixing ratio (a shift in the viscosity-temperature curve), the actual viscosity of the glass increased to 1.3×10⁻⁶. 6 Pa·s, thickness deviation rate out of tolerance (edge ​​thickness 2.93mm, below the target lower limit of 2.95mm). The system forcibly reduces the upper speed limit to 13m / min (a decrease of 2m / min from the initial 15m / min) to avoid equipment damage and quality accidents.

[0064] The speed safety boundary curve uses time slices (1 to 12 5-minute intervals) as the horizontal axis and speed as the vertical axis. Each time slice corresponds to a maximum permissible speed value (e.g., 1st 5-minute interval → 15 m / min, 3rd 5-minute interval → 14.5 m / min, 6th 5-minute interval → 14 m / min). Its dynamic nature intuitively reflects the control requirement that "speed must be reduced as risk increases"—for example, when the curve shows a clear inflection point in the 6th 5-minute interval (speed drops sharply from 14 m / min to 13 m / min), the operator or intelligent decision-making unit can clearly know that "the current process risk has significantly escalated, and the speed must be further reduced."

[0065] This curve avoids the problems of traditional fixed speed thresholds (such as always allowing 15m / min) that cause control lag due to ignoring state evolution (such as waiting until the roll temperature exceeds 800℃ before reducing the speed) or excessive conservatism (such as limiting the speed to 12m / min throughout the process, resulting in wasted production capacity). It provides a precise staged speed constraint basis for subsequent adaptive speed control strategies, ensuring that the nanocrystalline glass rolling process continues to operate in a safe, efficient, and high-quality state.

[0066] In the description disclosed in this embodiment: under the premise of ensuring the safety of equipment and product quality, a higher calendering speed is maintained as much as possible to improve the output per unit time and the overall production efficiency; by preventing problems such as abnormal roller temperature, glass flow instability, and surface defects caused by excessive speed, the thickness uniformity, surface smoothness, and internal microstructure consistency of the nanocrystalline glass are guaranteed; by avoiding the calendering roller being in the working limit state of high temperature, high vibration, and high load for a long time, thermal fatigue, mechanical wear and system aging are reduced, the service life of the equipment is extended, and the frequency of unplanned downtime and maintenance is reduced.

[0067] This strategy is deeply integrated with the online monitoring system of the rolling equipment, the glass quality sensing module, and the intelligent decision-making unit to form a closed-loop control system of "state perception - risk prediction - speed regulation - effect feedback". This achieves truly adaptive and intelligent rolling speed management, effectively supporting the stable production of high-precision, high-quality nanocrystalline glass.

[0068] In the description disclosed in this embodiment: based on the upper limit value of the calendering speed calculated in step S2 for each process control stage (such as divided by time slice, roll position segment, or production stage), a dynamically evolving process speed control strategy is constructed, and its core control logic follows the principle of "risk-driven and precise adaptation": Starting from the speed intervention point (i.e. the critical point where process risks begin to require active control), as the calendering process continues to advance, the system dynamically tracks the actual operating status of each process control stage by monitoring the equipment status and glass forming quality parameters in real time, and strictly ensures that the actual calendering speed of each stage does not exceed the corresponding allowable safety upper limit value—this upper limit value is calculated by step S2 based on the current thermodynamic state of the equipment, glass physical property parameters and process settings, and is a key threshold for ensuring the stability of the equipment and process.

[0069] The essence of this control strategy is not to use a fixed gradient or single-mode deceleration logic (such as a constant reduction of a fixed speed value per minute), but to rely on real-time sensing data and dynamic risk assessment to achieve precise and flexible speed control with "one stage and one threshold". In the description disclosed in this embodiment: at the beginning of each process control stage, the system first obtains the upper limit value of the rolling speed corresponding to that stage (this value has been calculated by the speed-risk coupling model of step S2, and takes into account dynamic factors such as current equipment heat accumulation, glass composition changes and roll surface state migration). During the process execution, the actual process status at the current stage is dynamically evaluated through the deep collaboration of the online monitoring system of the rolling equipment (which collects parameters such as roll temperature distribution, vibration spectrum, and bearing load in real time), the glass quality sensing module (which synchronously acquires data such as thickness uniformity, surface waviness, and edge integrity), and the intelligent decision-making unit (which integrates multi-source information and executes control logic). If a parameter (such as an abnormal increase in local roll temperature or an increase in glass thickness deviation rate) is detected, causing the comprehensive risk assessment value to approach the safety threshold, the system will immediately adjust the actual allowable speed limit for that stage (by recalculating the highest speed that meets the risk constraints through reverse constraint logic). This ensures that the actual rolling speed always matches the most precise risk boundary, rather than mechanically following a preset fixed speed reduction curve. This dynamic adaptation mechanism effectively solves the problems of "excessive speed reduction" (limiting capacity but with controllable actual risk) or "delayed regulation" (intervention only after risk has occurred) caused by traditional control strategies ignoring real-time fluctuations in process conditions, achieving the intelligent control goal of "precisely matching risk and flexibly adjusting speed".

[0070] During continuous calendering production, the system, based on the speed-risk coupling model of step S2, has calculated an initial allowable upper limit for calendering speed of 14 m / min for the current process control stage (e.g., the third 5-minute time interval, corresponding to the roll position segment where the calendering roll rotates approximately 60°, or the production stage where 50 meters of glass ribbon are produced). This value comprehensively considers the current equipment status (e.g., calendering roll bearing support area temperature 780℃, local temperature difference 248℃, vibration amplitude 0.43g, 120Hz characteristic frequency energy percentage 9%) and glass physical properties (e.g., viscosity 1.28×10⁻⁶). 6 Pa·s, flowability index 0.82) and process settings (such as target thickness 3.00±0.05mm, roll gap 0.78mm).

[0071] Once the process control phase begins, the online monitoring system for the rolling mill, the glass quality sensing module, and the intelligent decision-making unit immediately initiate in-depth collaborative monitoring: The online monitoring system collects the roller temperature distribution in real time through a thermocouple array and finds that the temperature in the bearing support area is slowly rising at a rate of 0.5℃ / min (from 780℃ to 783℃); vibration spectrum analysis shows that the energy proportion of the 120Hz characteristic frequency has increased slightly from 9% to 9.2% (still below the threshold of 10%), but the vibration amplitude has increased slightly from 0.43g to 0.44g (close to the safe upper limit of 0.45g); the bearing load value is stable at 75% of the rated value.

[0072] The glass quality sensing module synchronously acquires the surface thickness data through a laser thickness gauge and finds that the standard deviation of thickness uniformity has increased slightly from 0.068mm to 0.070mm (close to the threshold of 0.07mm), the surface waviness amplitude remains at 0.05mm (not exceeding the limit), and no abnormalities are found in edge integrity.

[0073] The intelligent decision-making unit inputs the above real-time parameters into the velocity-risk coupling model to calculate the comprehensive risk assessment value under the current state. The results show that the thermal stress index is 192MPa (close to the safety threshold of 200MPa), the vibration anomaly index is 9.2% (close to the threshold of 10%), and the thickness deviation index is 0.070mm (close to the threshold of 0.07mm). Although the overall risk level has not exceeded the limit, it is close to the safety boundary.

[0074] When an abnormal increase in local roller temperature is detected (783℃→785℃, an increase of 2℃ within 5 minutes) and an increase in glass thickness deviation rate (standard deviation 0.070mm→0.072mm, exceeding the threshold of 0.07mm), the system immediately adjusts the actual allowable speed limit for that stage through reverse constraint logic. The intelligent decision-making unit identified that the thickness deviation index (0.072 mm) had exceeded the safety threshold (0.07 mm), while the thermal stress index (195 MPa) was close to the safety threshold (200 MPa), and the vibration abnormality index (9.3%) was also close to the threshold (10%). The comprehensive risk assessment value increased significantly, indicating that the current speed of 14 m / min may lead to the process deterioration risk (such as thickness deviation, accumulation of thermal fatigue of the roller, and mechanical damage caused by vibration) entering an uncontrollable range.

[0075] Based on the latest parameters (roller temperature 785℃, local temperature difference 250℃, vibration amplitude 0.44g, 120Hz energy percentage 9.3%, glass thickness standard deviation 0.072mm, viscosity 1.28×10⁻⁶),... 6 The assumed speed value was gradually reduced through reverse constraint logic. When the assumed speed was 13.5 m / min, the model calculation showed that the roller temperature dropped to 780℃ (≤800℃), the local temperature difference was 245℃ (≤250℃), the thermal stress index was 190MPa (≤200MPa), the vibration amplitude was 0.43g (≤0.45g), the energy ratio of 120Hz was 9% (≤10%), and the thickness standard deviation was 0.068mm (≤0.07mm). All key risk indicators returned to the safe range.

[0076] The actual allowable speed limit for the current process control stage is immediately reduced from 14 m / min to 13.5 m / min, and the calendering roll speed is controlled by an actuator (such as a frequency converter) to ensure that the actual calendering speed does not exceed the new limit.

[0077] In the description disclosed in this embodiment: the dynamic control strategy plays multiple optimization roles throughout the entire process: In terms of safety, by strictly limiting the calendering speed of each stage to no more than the dynamically calculated safety limit, the risks of equipment thermal fatigue (such as local overheating of the calendering roll leading to damage to the microstructure of the material), mechanical wear (such as high-frequency vibration aggravating the wear of bearings and transmission components) and glass forming defects (such as uneven thickness and excessive surface ripples under high-speed flow) caused by excessive speed are fundamentally avoided, ensuring long-term stable operation of the equipment and consistency of product quality. In terms of efficiency, the strategy is not to blindly reduce the speed, but to maintain a higher rolling speed as much as possible while ensuring that the risks are controllable. For example, when the equipment is in good condition (such as the roll temperature is stable at the lower limit of the safety threshold and the vibration energy is within the normal range) and the glass flow is stable, the system allows the actual speed to be close to the upper limit of the current stage, maximizing the output of glass strip per unit time and improving the overall production efficiency. At the quality level, by precisely controlling the matching relationship between speed and process parameters, problems such as glass strip thickness deviation (e.g., the difference in thickness between the edge and the center exceeds the allowable value of the process), decreased surface smoothness (e.g., increased amplitude of micro-undulations), and uneven internal microstructure (e.g., disordered crystal orientation) caused by improper speed are effectively suppressed, ensuring the high-precision forming quality of nanocrystalline glass. In terms of equipment lifespan, by avoiding prolonged exposure of calender rolls to extreme working conditions such as high temperature (e.g., close to the material's allowable temperature limit), high vibration (e.g., continuous exceedance of energy at specific fault frequencies), and high load (e.g., exceeding the design value of the pressing force), the propagation of thermal fatigue cracks, wear of mechanical components, and system aging rate can be significantly slowed down. This reduces the frequency of unplanned downtime for maintenance and maintenance costs, and extends the reliable operating time throughout the entire equipment lifespan.

[0078] Ultimately, this dynamic control strategy is deeply integrated with the online monitoring system of the rolling mill (which collects multi-dimensional operating status data in real time), the glass quality sensing module (which detects forming quality parameters with high precision), and the intelligent decision-making unit (which integrates mechanism models and data-driven algorithms to execute control logic), constructing a closed-loop control system of "status perception - risk prediction - speed control - effect feedback": The online monitoring system and quality perception module provide real-time data input. The intelligent decision-making unit calculates the upper limit of the allowable speed at the current stage based on the speed-risk coupling model of the S2 step, and generates control instructions by comparing the deviation between the actual speed and the upper limit value. Finally, the rolling speed is adjusted through the actuator (such as the frequency converter).

[0079] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0080] 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 method for controlling the rolling and forming of nanocrystalline glass, characterized in that: The control method includes the following steps: S1: Collect multi-dimensional operating status data during the rolling process of nanocrystalline glass, analyze it using a process degradation model, identify risk indicators that will lead to equipment performance degradation or product quality degradation in the current process stage, and calculate the maximum allowable continuous operating speed range within the safe threshold range for all risk indicators. The endpoint of this maximum allowable continuous operating speed range is taken as the safe operating boundary point in the process control strategy, and further defined as the speed intervention point. S2: Construct a speed-risk coupling model to quantitatively describe the nonlinear relationship between rolling speed and various process degradation risks. The output is the comprehensive risk assessment value under the corresponding rolling speed. In the process control stage from the speed intervention point to the end of the maximum allowable operating range, for each process control stage, based on the comprehensive risk assessment value output in real time within the process control stage, calculate the upper limit of the allowable rolling speed for that stage, forming a speed safety boundary curve that is dynamically adjusted with the process progress. S3: Based on each process control stage and the corresponding calculated upper limit of the rolling speed, a process speed control strategy that dynamically evolves with the rolling process is constructed.

2. The method for controlling the rolling and forming of nanocrystalline glass according to claim 1, characterized in that: In step S2: the speed-risk coupling model comprehensively reflects the impact of increasing the rolling speed on the temperature rise rate of the rolling roll, thermal stress distribution, and vibration energy, as well as the mechanism by which increasing the rolling speed affects the glass strip's fluidity, thickness uniformity, and edge forming quality.

3. The method for controlling the rolling and forming of nanocrystalline glass according to claim 2, characterized in that: In step S2: The speed-risk coupling model is a mechanism-driven analytical expression, that is, it is based on the theories of heat conduction, rheology and mechanical vibration. The input parameters include the current equipment status, glass physical property parameters and process settings, and the output is the comprehensive risk assessment value at the corresponding rolling speed.

4. The method for controlling the rolling and forming of nanocrystalline glass according to claim 3, characterized in that: In step S2: a speed-risk coupling model is constructed to quantitatively describe the nonlinear correlation between rolling speed and the risk of various process degradations. The output is a comprehensive risk assessment value at the corresponding rolling speed, including the following steps: The input parameters of the speed-risk coupling model include current equipment status parameters, glass physical property parameters, and process settings. The input parameters are mapped to a comprehensive risk assessment value. The comprehensive risk assessment value is a multi-dimensional comprehensive indicator of equipment performance degradation risk and product quality degradation risk. The magnitude of the comprehensive risk assessment value represents the overall risk level of the process system at the current speed. Based on the constructed speed-risk coupling model, the process is divided into time slices, roll positions, or production stages during the process control phase from the speed intervention point to the end of the maximum allowable operating range. The upper limit of the allowable calendering speed is calculated in real time for each process control stage. Based on the real-time operating status data and glass property parameters of the current stage, the speed-risk coupling model is input and the comprehensive risk assessment value corresponding to different speeds at this stage is output.

5. The method for controlling the rolling and forming of nanocrystalline glass according to claim 3, Its features include: S2: In the process control stage from the speed intervention point to the end of the maximum allowable operating range, for each process control stage, based on the comprehensive risk assessment value output in real time within that process control stage, the upper limit of the allowable rolling speed for that stage is calculated, forming a speed safety boundary curve that is dynamically adjusted with the process progress, including the following steps: By filtering through reverse constraint logic, and using the safety threshold of all risk indicators as a benchmark, the speed parameters are gradually adjusted until the highest speed value corresponding to the condition that all risk indicators do not exceed the threshold is found. The highest speed value is the upper limit of the rolling speed allowed in the current process control stage. As the process progresses, the risk characteristics of different process control stages will dynamically evolve due to the heat accumulation effect of the equipment, slight fluctuations in glass composition, or changes in the state of the roll surface, causing the upper limit of the allowable rolling speed to show a gradual decreasing trend.

6. The method for controlling the rolling and forming of nanocrystalline glass according to claim 2, characterized in that: S1: Identify risk indicators that will lead to equipment performance degradation or product quality deterioration in the current process stage, and calculate the maximum permissible continuous operating speed range for all risk indicators within the safe threshold range. The endpoint of this maximum permissible continuous operating speed range is taken as the safe operating boundary point in the process control strategy, and further defined as the speed intervention point. This includes the following steps: A thermal fatigue accumulation model is constructed based on the theory of heat conduction and thermal stress to assess the risk of thermodynamic degradation of equipment. The temperature gradient and number of thermal cycles in the roller part are calculated by real-time temperature field data, and the degree of damage accumulation of material microstructure is evaluated. Vibration signal spectrum analysis technology is used to assess the risk of mechanical vibration degradation, extracting the characteristic frequency energy proportions corresponding to typical faults such as bearing wear and gear damage, and combining the vibration amplitude time series to determine the degree of abnormality of mechanical components. To address the risk of deterioration in glass forming quality, statistical process control methods are used to analyze the real-time fluctuation trends of thickness consistency standard deviation and surface waviness amplitude, and to identify the risk level of process stability deviating from the threshold. Identify risk indicators that could lead to a decline in equipment performance or a deterioration in product quality at the current stage of the process, including but not limited to excessive roller temperature, abnormal vibration, and an increase in glass defect rate. Based on the identified risk indicators, the maximum permissible continuous operating speed range is calculated so that all risk indicators remain within the safe threshold range during the current process task cycle or planned production interval.

7. The method for controlling the rolling and forming of nanocrystalline glass according to claim 1, characterized in that: In step S3: Construct a process speed control strategy that dynamically evolves with the rolling process. The logic of the control strategy is as follows: Starting from the speed intervention point, as the process progresses, the allowable upper limit of the rolling speed is gradually lowered, so that the actual rolling speed does not exceed the safe upper limit allowed for that stage at each process control stage.

8. The method for controlling the rolling and forming of nanocrystalline glass according to claim 1, characterized in that: In step S1: Collect multi-dimensional operating status data during the rolling process of nanocrystalline glass. The multi-dimensional operating status data is related to equipment performance degradation and process stability. The multi-dimensional operating status data includes the surface temperature distribution of the rolling roll, local temperature difference, thermal deformation, vibration amplitude and spectrum characteristics; roller bearing load, drive motor current fluctuation, abnormal signals of the transmission system; glass strip thickness consistency, surface waviness, edge integrity, flow uniformity; actual rolling speed, deviation between set pressure and actual pressing force, and roll gap control stability.

9. A nanocrystalline glass calendering and forming apparatus, used to implement the forming method according to any one of claims 1-8, characterized in that: The forming equipment includes a main body (1), and a circulating liquid cooling calendering mechanism (2) is provided on the main body (1). The circulating liquid cooling calendering mechanism (2) includes a frame (3). A set of calendering rollers (4) is provided on the top of the frame (3). There are two calendering rollers (4). The calendering rollers (4) are rotatably connected to the frame (3) through bearings. A motor (5) is also fixedly provided on one side of the top of the frame (3). The motor (5) drives the two calendering rollers (4) to rotate in opposite directions through a reducer (6).

10. The nanocrystalline glass calendering equipment and its control method according to claim 9, characterized in that: The interior of the calender roll (4) is provided with an S-shaped channel. The outlet and inlet of the S-shaped channel are both located on the side away from the motor (5). The interior of the calender roll (4) is also provided with multiple small impeller power generation devices. The impeller power generation devices are electrically connected to the thermometers set on the frame (3).

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