Methods for monitoring and controlling the thermal field distribution in ceramic denture sintering
By acquiring digital denture models to calculate structural sensitivity and thermal response characteristic indices, and combining them with material hardening coefficients, the temperature control strategy is dynamically adjusted. This solves the problem of monitoring and controlling the thermal response of dentures with uneven thickness during the sintering process of zirconia ceramic dentures, achieving adaptive temperature regulation in high-noise environments, reducing warping deformation, and improving the quality of finished products.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SHENZHEN JIAHONG DENTAL MEDICAL CO LTD
- Filing Date
- 2026-04-21
- Publication Date
- 2026-05-26
AI Technical Summary
Existing technologies cannot effectively monitor and control the thermal response of dentures with uneven thickness during the sintering process of zirconia ceramic dentures, leading to warping and deformation of the finished product, especially when the monitoring results fail under strong noise background.
By acquiring a digital denture model, calculating structural sensitivity parameters and thermal response characteristic index, and combining the material hardening coefficient, the temperature control strategy is dynamically adjusted to achieve adaptive temperature regulation to eliminate internal temperature differences.
It enables accurate monitoring of denture thermal response in high-noise environments, reduces warping and deformation, and improves the finished product quality of sintered ceramic dentures.
Smart Images
Figure CN122083702A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of dental prosthesis temperature control technology, specifically to a method for monitoring and controlling the thermal field distribution and temperature of ceramic prosthesis sintering. Background Technology
[0002] During the sintering process of zirconia ceramic dentures, the controlled cooling stage causes the material to transition from viscoplastic to brittle. For complex dentures with varying thicknesses (such as long-span dental bridges), the thin-walled areas cool faster, while the thick-walled areas remain at high temperatures. This asynchronous volume shrinkage accumulates thermal stress internally, leading to warping and deformation of the finished product.
[0003] Existing technologies typically employ linear cooling at a uniform rate, failing to detect the actual thermal response within the denture and thus hindering effective temperature control. While some devices attempt to infer load status by monitoring heating power, the heat capacity of a single or small number of dentures is extremely small, and their released heat flow signals are easily drowned out by background noise such as furnace heat dissipation, heating element aging, and power grid fluctuations, rendering the acquired monitoring results invalid. Therefore, there is an urgent need for a method that can extract weak load thermal characteristics from a strong noise background and adaptively control temperature based on individual denture geometric differences. Summary of the Invention
[0004] To address the technical problems in related technologies where linear cooling at a uniform rate fails to detect the actual thermal response inside the denture and obtain accurate monitoring results, this application provides a method for monitoring the thermal field distribution and controlling the temperature during the sintering of ceramic dentures.
[0005] The specific technical solution adopted is as follows: The digital denture model of the target denture to be sintered and the heating output power collected in real time during the denture sintering process are obtained. The digital denture model is then sliced and analyzed to calculate the structural sensitivity parameters characterizing the geometric features of the denture. Based on the heating output power and maintenance temperature during the high-temperature isothermal stage, a dynamic power reference value applicable to the controlled cooling stage is calculated. Based on the deviation between the heating output power during the controlled cooling phase and the dynamic power reference value, the thermal response characteristic index is calculated. The thermal response characteristic index is used to represent the load thermal response characteristics of the environment in which the target denture is located. The thermal stress risk index is obtained by coupling the structural sensitivity parameters, thermal response characteristic index and preset material hardening coefficient. When the thermal stress risk index exceeds the standard, a state transition operation between cooling and temperature suspension is performed to control the temperature of the target denture.
[0006] In one possible implementation of this application, a slice analysis is performed on the digital denture model to calculate structural sensitivity parameters characterizing the geometric features of the denture, including: The digital denture model is sliced along a preset axis to obtain multiple model slices; Based on the cross-sectional area and perimeter of the model slice, the local heat dissipation modulus is calculated. The structural sensitivity parameter characterizing the geometric features of the denture is calculated based on the ratio between the maximum and average values of the local heat dissipation modulus.
[0007] In one possible embodiment of this application, a dynamic power reference value suitable for the controlled cooling stage is calculated based on the heating output power and the maintained temperature during the high-temperature isothermal stage, including: Based on the heating output power during the high-temperature isothermal stage, the actual maintenance power and the maximum maintenance temperature during the high-temperature isothermal stage are determined. The energy consumption drift value is calculated based on the difference between the actual sustained power and the preset standard no-load power. Based on the maximum maintained temperature, the energy consumption drift value is corrected, and a dynamic power reference value suitable for the controlled cooling stage is calculated.
[0008] In one possible implementation of this application, based on the maximum maintained temperature, the energy consumption drift value is corrected to calculate a dynamic power reference value suitable for the controlled cooling phase, including: The temperature correction factor is calculated based on the maximum sustained temperature and the ratio between the corresponding temperature values within different sintering time periods; By combining the product of the temperature correction factor and the energy consumption drift value with the maintenance power during different sintering time periods, a dynamic power reference value applicable to the controlled cooling stage is calculated.
[0009] In one possible embodiment of this application, a thermal response characteristic index is calculated based on the deviation between the heating output power during the controlled cooling phase and the dynamic power reference value, including: Obtain the cooling temperature corresponding to the heating output power during the controlled cooling stage, and calculate the dynamic power reference value at the cooling temperature; The thermal response characteristic index is calculated based on the deviation between the dynamic power reference value at the cooling temperature and the heating output power.
[0010] In one possible embodiment of this application, the structural sensitivity parameter, thermal response characteristic index, and preset material hardening coefficient are coupled and calculated to obtain a thermal stress risk index, including: Based on the thermal capacity parameters and thermal response characteristic index of the target denture, the signal effectiveness weight is calculated. The signal effectiveness weight is used to characterize the degree of matching between the thermal response characteristic index and the theoretical reference power. The thermal stress risk index is obtained by coupling the thermal response characteristic index, structural sensitivity parameter, signal effectiveness weight, and preset material hardening coefficient.
[0011] In one possible implementation of this application, the signal effectiveness weight is calculated based on the thermal capacity parameter and thermal response characteristic index of the target denture, including: The theoretical heat capacity of the denture is calculated based on the material volume and specific heat capacity of the target denture. The theoretical reference power is calculated based on the theoretical heat capacity of dentures and the preset target cooling rate. The signal effectiveness weight is calculated based on the theoretical reference power and the thermal response characteristic index.
[0012] In one possible embodiment of this application, a thermal stress risk index is obtained by coupling calculations of the thermal response characteristic index, structural sensitivity parameter, signal validity weight, and preset material hardening coefficient, including: The instantaneous risk value is obtained by coupling the thermal response characteristic index, the signal effectiveness weight, and the preset material hardening coefficient. The thermal stress risk index is obtained by applying a moving average filter to the instantaneous risk values at different temperatures.
[0013] In one possible implementation of this application, when the thermal stress risk index exceeds the limit, a state transition operation between cooling and temperature suspension is performed to control the temperature of the target denture, including: Based on the thermal stress risk index, the upper limit and lower limit of risk intervention are determined; The target denture is cooled to the target temperature. If the thermal stress risk index is found to be greater than the risk intervention limit, it is determined that the thermal stress risk index is in an excessive state, and the temperature hovering operation is triggered. If the thermal stress risk index is detected to be less than the risk intervention limit during the temperature hovering operation, the temperature hovering state is switched to the cooling state to control the temperature of the target denture.
[0014] In one possible implementation of this application, after triggering the temperature hovering operation, the method further includes: Read the ambient temperature of the furnace where the target denture is located; The target setpoint of the preset temperature controller is locked to the furnace ambient temperature to prevent the temperature of the target denture from continuously dropping.
[0015] This application has, but is not limited to, the following technical effects: By acquiring a digital model of the target denture to be sintered and the real-time heating output power collected during the denture sintering process, and then performing slice analysis on the digital denture model, structural sensitivity parameters characterizing the denture's geometric features are calculated. Combined with the heating output power during the high-temperature isothermal stage and the controlled cooling stage, thermal response characteristic coefficients are calculated. The thermal response characteristic index is used to represent the load thermal response characteristics of the environment in which the target denture is located, thereby separating the true thermal hysteresis trend from various noises. Then, the structural sensitivity parameters, thermal response characteristic index, and preset material hardening coefficient are coupled and calculated to obtain the thermal stress risk index, thereby obtaining accurate monitoring results. The thermal stress risk index combines the individual geometric features of the target denture with the thermal response characteristic index and adaptively adjusts the ambient temperature of the target denture, using natural conduction to eliminate internal temperature differences and achieve adaptive temperature control. Attached Figure Description
[0016] Figure 1 This is a flowchart illustrating the first embodiment of the method for monitoring and controlling the thermal field distribution and temperature of ceramic denture sintering according to this application. Figure 2 This is a schematic diagram of the device structure of the hardware operating environment involved in the embodiments of this application. Detailed Implementation
[0017] It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.
[0018] This application provides a method for monitoring and controlling the thermal field distribution and temperature in ceramic denture sintering. In the first embodiment of this method, refer to... Figure 1 The methods include: Step S10: Obtain the digital denture model of the target denture to be sintered and the heating output power collected in real time during the denture sintering process. Perform slice analysis on the digital denture model and calculate the structural sensitivity parameters characterizing the geometric features of the denture.
[0019] As an example, the method for monitoring and controlling the thermal field distribution of ceramic dentures can be applied to a device for monitoring and controlling the thermal field distribution of ceramic dentures. This device belongs to the category of a system for monitoring and controlling the thermal field distribution of ceramic dentures, which in turn belongs to the category of equipment for monitoring and controlling the thermal field distribution of ceramic dentures.
[0020] As an example, the method for monitoring and controlling the thermal field distribution in ceramic denture sintering can also be applied to a monitoring and control system for the thermal field distribution in ceramic denture sintering. This system includes a static feature analysis module, a dynamic reference reconstruction module, a real-time thermal response monitoring module, and a hysteresis intervention control module. The functions implemented by each module are as follows: Static Feature Analysis Module: Used to perform volume integral and slice differential analysis on the input digital denture model, and to digitize the physical properties of the load before sintering, which serve as the basic constants for subsequent calculations.
[0021] Dynamic reference reconstruction module: It is used to process the measured heating power value and standard power meter value obtained in the high temperature constant temperature stage, calculate the energy consumption drift value, construct a dynamic function in combination with the temperature correction coefficient, calculate the dynamic power reference value, eliminate equipment aging deviation in sintering, and provide an accurate comparison scale for cooling monitoring.
[0022] Real-time thermal response monitoring module: used to acquire real-time power and temperature, energy consumption drift value, and dynamic power reference value during the cooling phase, and perform calculations to obtain thermal response characteristic index and thermal stress risk index. This allows for real-time calculation of the current stress accumulation state of the load in a high-noise environment.
[0023] Hysteresis intervention control module: used to perform dual threshold state machine judgment on thermal stress risk index, control the locking and releasing of target value of thermostat, and execute final control command (cooling or hovering) on heating element, thereby transforming the monitored risk into specific time domain compensation action.
[0024] As an example, in the pre-processing stage before the sintering process starts, the inherent physical properties and geometric heterogeneity characteristics of the load on the denture to be sintered are quantified by digital analysis. Since zirconia ceramics have low thermal conductivity, the internal temperature field distribution is highly dependent on the thickness distribution of the geometric shape. In order to achieve accurate compensation for individual differences, the system first reads the computer-aided manufacturing layout data or STL three-dimensional model file of the task to be sintered, that is, the digital denture model, and extracts the thermophysical and morphological characteristic parameters of the load.
[0025] As an example, to quantify the risk of asynchronous shrinkage caused by uneven thickness of the geometric structure, the system calculates a structural sensitivity index, generates the required structural sensitivity parameters, establishes a local coordinate system with the tangent direction of the dental arch curve (i.e., the mesiodistal diameter direction / preset axis) as the axis, and discretizes the digital model along this axis. Three equally spaced slices of the differential model, with slice indices denoted as . ( The slice thickness is set according to the required calculation accuracy (e.g., ).
[0026] As an example, the structural sensitivity parameter is used to characterize the degree of structural inhomogeneity of the target denture, which can reflect the local heat dissipation differences in the internal geometry of the denture.
[0027] As an example, the heating output power is the output power collected in real time during the denture sintering process. It can refer to the average effective power or root mean square (RMS) power within a preset control period (e.g., 2-5 seconds). The heating output power is different at different sintering stages. For example, the output power in the high temperature isothermal stage is greater than the output power in the controlled cooling stage.
[0028] Step S10 includes: The digital denture model is sliced along a preset axis to obtain multiple model slices.
[0029] Based on the cross-sectional area and perimeter of the model slice, the local heat dissipation modulus is calculated.
[0030] As an example, for any _th The system extracts the cross-sectional area of each model slice. With the perimeter of the cross section Based on the ratio of heat dissipation area to heat storage volume, the system calculates the local heat dissipation modulus at that location. ): in, The higher the value, the higher the "body surface area ratio" of the slice location, the more difficult it is for internal heat to dissipate, and it belongs to a potential high-temperature lag region (such as a thick-walled abutment); conversely, it is a rapid cooling region (such as a thin-walled connector).
[0031] The structural sensitivity parameter characterizing the geometric features of the denture is calculated based on the ratio between the maximum and average values of the local heat dissipation modulus.
[0032] As an example, after completing all After traversing and calculating each model slice, the system constructs a dataset of local heat dissipation moduli. To quantify the disparity between the slowest heat dissipation area and the average level on the same denture, the system extracts the maximum local heat dissipation moduli from this dataset. The arithmetic mean of the local heat dissipation modulus of all model slices And based on this, calculate the cross-sectional thickness difference ratio ( ): This parameter As a dimensionless constant, when the value is significantly greater than 1, it indicates that the denture contains both extremely thick and extremely thin regions, and the risk of asynchronous shrinkage is high. The calculated cross-sectional thickness difference ratio is used as the structural sensitivity parameter in the risk calculation formula, so that dentures with uneven thickness can be calculated with higher risk values under the same thermal conditions.
[0033] Step S20: Based on the heating output power and maintenance temperature during the high-temperature isothermal stage, a dynamic power reference value suitable for the controlled cooling stage is calculated.
[0034] As an example, during the highest temperature holding period of the current sintering batch, the system continuously collects the actual output power of the heating element at a preset sampling rate and calculates the average power during this time period. As the heating output power during the high-temperature constant temperature stage, the constant furnace temperature at this time is the maintenance temperature.
[0035] As an example, the dynamic power reference value can be a comparison reference value for the cooling phase after temperature correction, and the dynamic power reference value is dynamically updated as the temperature changes.
[0036] The step S20, which involves monitoring the thermal field distribution and controlling the temperature during the sintering of ceramic dentures, further includes steps S21 to S23, including: Step S21: Based on the heating output power during the high-temperature constant temperature stage, determine the actual maintenance power and the maximum maintenance temperature during the high-temperature constant temperature stage.
[0037] As an example, by collecting the heating output power during the high-temperature isothermal stage in real time, the actual maintaining power during that stage can be determined. Similarly, the constant furnace temperature at this power can also be obtained, thus yielding the maximum maintaining temperature. Then, the pre-stored standard power table of the empty furnace for this type of sintering furnace is invoked. This data sheet records the maintenance of different furnace temperatures by the new equipment under no-load conditions. The required reference electrical power.
[0038] Step S22: Calculate the energy consumption drift value based on the difference between the actual maintenance power and the preset standard no-load power.
[0039] As an example, energy drift value ( The calculation method for ) can be: in, This represents the preset standard no-load power while maintaining the maximum temperature. This represents the actual sustaining power; the energy consumption drift value. It characterizes the energy consumption deviation of the current equipment under the highest temperature operating condition relative to the factory standard. This deviation is usually caused by the increase in the resistance of the heating element (such as silicon molybdenum rod) due to aging or the change in heat loss of the furnace insulation layer.
[0040] Step S23: Based on the maximum maintained temperature, the energy consumption drift value is corrected to calculate the dynamic power reference value applicable to the controlled cooling stage.
[0041] As an example, considering that the aging characteristics of heating elements (such as resistivity changes) typically exhibit a non-linear relationship with temperature, and that furnace wall heat loss is also related to temperature difference, the energy consumption drift value measured in the high-temperature isothermal section is directly applied... Linear superposition to the low-temperature cooling section will cause severe distortion of the reference. Therefore, the system introduces a temperature correction coefficient to construct a dynamic power reference value applicable to the entire temperature range.
[0042] As an example, by maintaining the maximum temperature and the current temperature, a temperature correction factor is calculated. The energy consumption drift value is then corrected using the temperature correction factor to calculate a dynamic power reference value suitable for the controlled cooling phase.
[0043] Step S23 includes: The temperature correction coefficient is calculated based on the maximum sustained temperature and the ratio between the corresponding temperature values within different sintering time periods.
[0044] As an example, the temperature correction factor is used to describe how the drift decreases with temperature. The calculation method can be: Where T represents the current temperature T, This indicates the maximum temperature to be maintained.
[0045] As an example, if the system stores the nominal resistance-temperature profile of the heating element... Then a more accurate resistance correction model and temperature correction coefficient can be used. The calculation method can also be: in, The resistance value of the heating element at temperature T. Similarly.
[0046] By combining the product of the temperature correction factor and the energy consumption drift value with the maintenance power during different sintering time periods, a dynamic power reference value applicable to the controlled cooling stage is calculated.
[0047] As an example, the dynamic power reference value can also be called the dynamic power reference function (…). This value varies with temperature; dynamic power reference value. The calculation method can be: in, This represents the no-load sustaining power at time T. This represents the energy consumption drift value. This represents the temperature correction factor.
[0048] Step S30: Based on the deviation between the heating output power during the controlled cooling stage and the dynamic power reference value, the thermal response characteristic index is calculated. The thermal response characteristic index is used to represent the load thermal response characteristics of the environment in which the target denture is located.
[0049] As an example, this step is repeated cyclically during the cooling phase of the sintering process, in which the system utilizes the generated static constant and dynamic power reference value ( It performs feature extraction and analysis on real-time sensor data.
[0050] As an example, to ensure the physical validity of the monitoring data, the system first performs applicable scenario detection; this method is only activated during the controlled cooling phase. The controlled cooling phase refers to the temperature control system using a PID algorithm to control the heating element to output non-zero power to maintain a preset linear cooling rate (e.g., (instead of natural cooling by directly cutting off the power supply).
[0051] The system monitors the output status of the heating element in real time. If it detects that the duty cycle of the heating element is 0 or the output power is continuously lower than the preset minimum maintenance threshold (e.g., If the system determines that it is currently in power-off cooling or door-open cooling mode, it will automatically suspend this monitoring function and maintain the output of the risk value or the preset safety low value from the previous moment.
[0052] In addition, to prevent data oscillations caused by the lack of a steady-state thermal flow field during the initial cooling phase, a cold start shielding period is set in the system. Before entering the cooling phase. Within seconds (in this embodiment, it is set to...) The system forcibly sets the thermal stress risk index to 0, does not perform subsequent calculations, and gives the sensor and the furnace thermal environment sufficient time to stabilize.
[0053] As an example, this step aims to extract a trend signal characterizing the thermal state of the load from the electrical feedback of the heating element. Since zirconia dentures have extremely low heat capacity, the released heat flow signal is typically weak and drowned out by background noise. Direct physical power measurement is difficult to achieve a high signal-to-noise ratio. Therefore, this application does not pursue measuring the absolute physical heat flow value, but instead constructs an algorithmically amplified thermal response characteristic index (…). ).
[0054] Step S30 includes: Obtain the cooling temperature corresponding to the heating output power during the controlled cooling stage, and calculate the dynamic power reference value at the cooling temperature.
[0055] As an example, a preset sampling frequency (e.g., Real-time acquisition of the current furnace ambient temperature during the controlled cooling stage, i.e., the cooling temperature. With the actual output power of the heating element Corresponding to the heating output power, the dynamic power reference value at the cooling temperature is calculated using the function expression corresponding to the dynamic power reference value. .
[0056] The thermal response characteristic index is calculated based on the deviation between the dynamic power reference value at the cooling temperature and the heating output power.
[0057] As an example, in order to capture subtle thermal hysteresis trends, the system introduces a sensitivity gain coefficient. This coefficient is a dimensionless parameter, and its value is directly proportional to the furnace's full load rate. It is usually set at... Between (in this embodiment, the value is taken as) The system calculates the thermal response characteristic index according to the following formula. : in, This represents the heating output power during the controlled cooling phase, under this definition. It is not the physical load heat output power, but an amplified control variable. When the internal temperature of the denture is higher than the ambient temperature (there is thermal hysteresis), its heating output power is... It will be lower than the reference power. ,lead to The value is positive and increases significantly with the degree of lag; while the background noise, due to the lack of systematic bias, still exhibits random fluctuations with a mean of zero after gain amplification, which facilitates subsequent filtering processing.
[0058] Step S40: The structural sensitivity parameters, thermal response characteristic index and preset material hardening coefficient are coupled and calculated to obtain the thermal stress risk index.
[0059] As an example, the risk of denture warping is the result of the coupling of three factors: "geometric sensitivity", "thermal hysteresis strength" and "material rheological state". Based on this, a single quantitative indicator for the final control decision - the thermal stress risk index - is generated according to the above indicators.
[0060] As an example, the thermal stress risk index is a decision indicator that integrates geometric characteristics, thermal flow characteristics, and material state, and can be used as a judgment parameter when adjusting the temperature later.
[0061] Step S40 includes steps S41 to S42: Step S41: Based on the thermal capacity parameters and thermal response characteristic index of the target denture, the signal effectiveness weight is calculated. The signal effectiveness weight is used to characterize the degree of matching between the thermal response characteristic index and the theoretical reference power.
[0062] As an example, the thermal parameters of the target denture include specific heat capacity and material volume.
[0063] Step S41 includes: Based on the material volume and specific heat capacity of the target denture, the theoretical heat capacity of the denture is calculated.
[0064] As an example, the theoretical heat capacity of a denture is a physical constant characterizing the overall heat storage capacity of a load. A volume integral operation is performed on the closed surface of the imported digital denture model to obtain the volume of the denture material for that batch of loads. ), volume is Subsequently, the preset zirconia material physical property database is invoked to extract the material density ( In this embodiment, the value is taken as... ) and specific heat capacity ( In this embodiment, the value is taken as... The system calculates the theoretical heat capacity of the denture based on the following formula ( ): The theoretical reference power is calculated based on the theoretical heat capacity of dentures and the preset target cooling rate.
[0065] As an example, this is achieved by invoking the theoretical heat capacity of the denture and reading the preset target cooling rate of the current sintering process. (That is, the absolute value of the rate of temperature change, in units of...) ).
[0066] According to the law of conservation of energy, assuming that the denture cools down completely with the environment and has no thermal hysteresis, its ideal released heat power is the theoretical reference power. ): in, This indicates the preset target cooling rate, which is set to the greater of the current program's cooling rate and the minimum non-zero constant (e.g., 0.1 K / s). This is the theoretical reference power. Although the value is small, it provides a physically plausible reference, which the system will use in subsequent steps to compare with... The confidence intervals constructed from the coefficients are related to the observed thermal response characteristic index. Weighted gating is used to eliminate false signals that do not conform to the laws of physics and thermodynamics.
[0067] The signal effectiveness weight is calculated based on the theoretical reference power and the thermal response characteristic index.
[0068] As an example, a single thermal response characteristic index The signal may contain non-load noise caused by power grid surges or poor sensor contact. To remove the true thermal hysteresis component from the amplified signal, a signal validity weight needs to be calculated using a signal weighting filtering mechanism based on a theoretical model. This weight reflects the degree of matching between the observed characteristic index and the theoretical expectation. In this embodiment, a Gaussian membership function is used to construct the soft-gated logic. The mathematical expression is as follows: The parameters in the formula are defined as follows: : Amplifying the tiny theoretical power to the level of the thermal response characteristic index Establish a comparison benchmark based on the same magnitude.
[0069] Heat transfer efficiency correction factor (in this embodiment, the value is : Since some heat is directly dissipated and not captured by the sensor, the actual observed trend is often slightly lower than the theoretical upper limit.
[0070] Tolerance bandwidth factor (in this embodiment, the value is ) This coefficient defines the allowable range of measurement error distribution. The wider the bandwidth, the higher the system's tolerance to noise, but the lower the sensitivity.
[0071] Numerical stability constant (with values of ) This is used to prevent calculation errors where the denominator is zero when the theoretical reference value is close to zero (e.g., the cooling rate is extremely slow). exp is the natural constant.
[0072] when When it falls within a reasonable physical range defined by the theoretical value, If the value approaches 1, the system confirms the signal is valid; if a sudden maximum or minimum value (far from the theoretical range) occurs... It rapidly decays to 0, thereby suppressing noise interference.
[0073] Step S42 involves coupling the thermal response characteristic index, structural sensitivity parameter, signal validity weight, and preset material hardening coefficient to obtain the thermal stress risk index.
[0074] As an example, the preset material hardening coefficient can be a temperature-dependent material hardening coefficient, and the system uses a Sigmoid function to describe the process of zirconia transitioning from viscoplastic to brittle: in, The brittle-ductile transition temperature (value) ), The width of the phase transition interval (value) ), This coefficient represents the furnace ambient temperature during the controlled cooling stage. When the temperature is below the brittle point, the coefficient approaches 1, indicating that the thermal stress at this point is very easy to solidify into permanent deformation.
[0075] Step S42 includes: The instantaneous risk value is obtained by coupling the thermal response characteristic index, the signal effectiveness weight, and the preset material hardening coefficient.
[0076] As an example, the system calculates the instantaneous risk value. : The physical meanings of the parameters in the formula are as follows: The cross-sectional thickness difference ratio, as a structural sensitivity parameter, makes dentures with high geometric heterogeneity have a higher risk value calculated under the same thermal conditions.
[0077] Normalized reference power: To avoid using unfounded fixed values, this embodiment uses... Set to the rated power of the sintering furnace (e.g., )of ,Right now It is used to eliminate the influence of dimensions and normalize the exponent to a numerical range that is easy to control. Indicates the signal validity weight. Indicates the preset material hardening coefficient. This represents the thermal response characteristic index.
[0078] The thermal stress risk index is obtained by applying a moving average filter to the instantaneous risk values at different temperatures.
[0079] As an example, to prevent occasional strong interference from causing the signal validity weight to instantly drop to zero and thus triggering a control deadlock (i.e., the logical loophole of "misjudging safety when encountering interference"), the system monitors instantaneous risk values. Perform moving average filtering and set the time window length. (For example, The system calculates the arithmetic mean of the data within the time window to obtain the final output thermal stress risk index. .
[0080] Step S50: When the thermal stress risk index exceeds the standard, perform a state transition operation between cooling and temperature suspension to control the temperature of the target denture.
[0081] As an example, after calculating the thermal stress risk index, the thermal stress risk index is compared with a preset risk intervention threshold to determine whether the thermal stress risk index exceeds the standard. Then, it is determined whether to perform cooling or temperature suspension operations to compensate for temperature shrinkage and control the temperature of the target denture.
[0082] Step S50 includes: Based on the thermal stress risk index, the upper limit and lower limit of risk intervention are determined.
[0083] As an example, a batch of denture samples was selected, and a rapid linear cooling procedure was performed under uncompensated conditions (e.g., Meanwhile, the background system records the thermal stress risk index for the entire process. Curve. The degree of warpage of the sintered sample is detected by 3D scanning to identify the points where warpage begins to exceed tolerances (e.g., edge fit error). For the sample, trace its cooling process back, extract the peak value of the risk index during this process, and record it as the critical risk value. Furthermore, setting a cap on risk intervention. Reserved A safety margin is provided to prevent deformation. A lower limit for risk intervention is set. This serves as a safe release point where the thermal hysteresis has been fully dissipated. In this embodiment, the calibrated parameters are set as follows: , .
[0084] The target denture is cooled to the target temperature. If the thermal stress risk index is detected to be greater than the risk intervention limit, it is determined that the thermal stress risk index is in an excessive state, and the temperature hovering operation is triggered.
[0085] As an example, the target temperature is the preset temperature value that needs to be reached for cooling, which can be 10 degrees, 20 degrees, etc.
[0086] As an example, the system in this embodiment includes two temperature regulation states: a normal cooling state (the system is initially in this state or recovers from the temperature hovering state) and a temperature hovering state. First, the change curve of the thermal stress risk index is monitored. When the thermal stress risk index is found to be greater than the risk intervention limit, it is determined that the thermal stress risk index is in an over-limit situation, and then the current cooling state is switched to the temperature hovering state.
[0087] As an example, the system is initially in a cooling state, and the specific actions performed are: the PID temperature controller operates according to the cooling rate preset in the sintering program (e.g., ...). The target temperature setpoint is dynamically updated, and the thermal stress risk index is monitored. This indicates that the current cooling rate has caused the thermal gradient inside the denture to accumulate to a critical point that could trigger warping. The system immediately triggers an "intervention" event and switches to a temperature hovering state. When entering the temperature hovering state, the dynamic power reference value formula for the cooling phase is suspended. At this time, the calculation of the thermal stress risk index should be switched to monitoring the rate of change (slope) of the thermal response characteristic index, or the static isothermal maintenance power at the current hovering temperature should be used as a temporary reference.
[0088] The step of triggering the temperature hovering operation also includes: Read the ambient temperature of the furnace where the target denture is located; The target setpoint of the preset temperature controller is locked to the furnace ambient temperature to prevent the temperature of the target denture from continuously dropping.
[0089] As an example, after triggering the temperature hover operation, the state is switched to the temperature hover state, in which the current furnace ambient temperature is immediately read. The target setpoint of the preset temperature controller is locked to the furnace ambient temperature to prevent the temperature of the target denture from continuously decreasing. The timer of the sintering process is paused. During the pause, the ambient temperature stops cooling, and convective heat dissipation on the denture surface is suppressed. At this time, the heat accumulated in the denture core gradually diffuses to the surface through internal conduction, reducing the internal and external temperature difference and decreasing the thermal response characteristic index released to the outside. The thermal stress risk index then naturally decays, driving the thermal stress risk index. Automatically falls back down.
[0090] If the thermal stress risk index is detected to be less than the risk intervention limit during the temperature hovering operation, the temperature hovering state is switched to the cooling state to control the temperature of the target denture.
[0091] As an example, if the thermal stress risk index is monitored... or current hover time > ,(in, The timeout threshold (which can be 15 minutes) indicates that the thermal hysteresis inside the denture has been sufficiently dissipated, the risk of asynchronous shrinkage has been eliminated, and the system triggers the "recovery" event, switching back to the cooling state.
[0092] When switching back from the temperature hovering state to the cooling state, the system releases the target value lock of the PID temperature controller, reactivates the time axis timer, and continues to execute subsequent cooling at the original rate. Through this mechanism, the continuous cooling process is adaptively reconstructed into a stepped path of "cooling-hovering-recovery". This path is not pre-fixed, but is entirely determined by the geometric features / structural sensitivity parameters of the individual denture. ) and real-time thermal response characteristic index ( The temperature is dynamically generated, thus achieving optimal shrinkage compensation for each batch of load, thereby achieving adaptive temperature control.
[0093] This application provides a method for monitoring the thermal field distribution and controlling the temperature during the sintering of ceramic dentures. It acquires a digital model of the target denture to be sintered, along with real-time data on the heating output power during the sintering process. The digital denture model is then sliced and analyzed to calculate structural sensitivity parameters characterizing the denture's geometric features. Combined with the heating output power during the high-temperature isothermal stage and the controlled cooling stage, a thermal response characteristic coefficient is calculated. This thermal response characteristic index represents the load-induced thermal response characteristics of the target denture's environment, thus separating the true thermal hysteresis trend from various noises. Furthermore, the structural sensitivity parameters, thermal response characteristic index, and a preset material hardening coefficient are coupled to calculate a thermal stress risk index, thereby obtaining accurate monitoring results. This allows the thermal stress risk index to incorporate the individual geometric features of the target denture and the thermal response characteristic index, adaptively adjusting the ambient temperature of the target denture and utilizing natural conduction to eliminate internal temperature differences, achieving adaptive temperature control.
[0094] Reference Figure 2 , Figure 2 This is a schematic diagram of the device structure of the hardware operating environment involved in the embodiments of this application.
[0095] like Figure 2 As shown, the thermal field distribution monitoring and temperature control device for ceramic denture sintering may include: a processor 1001, a memory 1003, and a communication bus 1002. The communication bus 1002 is used to realize the connection and communication between the processor 1001 and the memory 1003.
[0096] Optionally, the thermal field distribution monitoring and temperature control device for ceramic denture sintering may also include a user interface, a network interface, a camera, RF (Radio Frequency) circuitry, sensors, a WiFi module, etc. The user interface may include a display screen and an input submodule such as a keyboard; optional user interfaces may also include standard wired or wireless interfaces. The network interface may include standard wired or wireless interfaces (such as a Wi-Fi interface).
[0097] Those skilled in the art will understand that Figure 2 The structure of the thermal field distribution monitoring and temperature control device for ceramic denture sintering shown in the figure does not constitute a limitation on the thermal field distribution monitoring and temperature control device for ceramic denture sintering. It may include more or fewer components than shown, or combine certain components, or have different component arrangements.
[0098] like Figure 2 As shown, the memory 1003, serving as a storage medium, may include an operating system, a network communication module, and a program for monitoring and controlling the thermal field distribution during ceramic denture sintering. The operating system is a program that manages and controls the hardware and software resources of the thermal field distribution monitoring and temperature control equipment for ceramic denture sintering, supporting the operation of the thermal field distribution monitoring and temperature control program for ceramic denture sintering, as well as other software and / or programs. The network communication module is used to enable communication between the various components within the memory 1003, as well as communication with other hardware and software in the thermal field distribution monitoring and temperature control system for ceramic denture sintering.
[0099] exist Figure 2 In the thermal field distribution monitoring and temperature control device for ceramic denture sintering shown, the processor 1001 is used to execute the thermal field distribution monitoring and temperature control program for ceramic denture sintering stored in the memory 1003 to implement the steps of the thermal field distribution monitoring and temperature control method for ceramic denture sintering described above.
[0100] The specific implementation of the thermal field distribution monitoring and temperature control device for ceramic denture sintering in this application is basically the same as the embodiments of the thermal field distribution monitoring and temperature control method for ceramic denture sintering described above, and will not be repeated here.
[0101] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.
[0102] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.
[0103] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.
[0104] The above are merely preferred embodiments of this application and do not limit the scope of this application. Any equivalent structural or procedural transformations made based on the description and drawings of this application, or direct or indirect applications in other related technical fields, are similarly included within the scope of protection of this application.
[0105] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
[0106] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.
Claims
1. A method for monitoring the thermal field distribution and controlling the temperature during the sintering of ceramic dentures, characterized in that, The method includes: A digital denture model of the target denture to be sintered and the heating output power collected in real time during the denture sintering process are obtained. The digital denture model is then sliced and analyzed to calculate the structural sensitivity parameters characterizing the geometric features of the denture. Based on the heating output power and maintenance temperature during the high-temperature isothermal stage, a dynamic power reference value applicable to the controlled cooling stage is calculated. Based on the deviation between the heating output power during the controlled cooling phase and the dynamic power reference value, a thermal response characteristic index is calculated. This thermal response characteristic index is used to represent the load thermal response characteristics of the environment in which the target denture is located. The thermal stress risk index is obtained by coupling the structural sensitivity parameter, the thermal response characteristic index and the preset material hardening coefficient. When the thermal stress risk index exceeds the standard, a state transition operation between cooling and temperature suspension is performed to control the temperature of the target denture.
2. The method for monitoring the thermal field distribution and controlling the temperature in ceramic denture sintering as described in claim 1, characterized in that, The step of performing slicing analysis on the digital denture model to calculate structural sensitivity parameters characterizing the geometric features of the denture includes: The digital denture model is sliced along a preset axis to obtain multiple model slices; Based on the cross-sectional area and perimeter of the model slice, the local heat dissipation modulus is calculated. Based on the ratio between the maximum and average values of the local heat dissipation modulus, the structural sensitivity parameter characterizing the geometric features of the denture is calculated.
3. The method for monitoring the thermal field distribution and controlling the temperature in ceramic denture sintering as described in claim 1, characterized in that, The calculation of the dynamic power reference value applicable to the controlled cooling stage based on the heating output power and maintenance temperature during the high-temperature isothermal stage includes: Based on the heating output power during the high-temperature isothermal stage, the actual maintenance power and the maximum maintenance temperature during the high-temperature isothermal stage are determined. The energy consumption drift value is calculated based on the difference between the actual maintenance power and the preset standard no-load power. Based on the maximum maintained temperature, the energy consumption drift value is corrected to calculate a dynamic power reference value suitable for the controlled cooling stage.
4. The method for monitoring the thermal field distribution and controlling the temperature in ceramic denture sintering as described in claim 3, characterized in that, The step of correcting the energy consumption drift value based on the maximum maintained temperature to calculate a dynamic power reference value suitable for the controlled cooling stage includes: Based on the maximum maintenance temperature and the ratio between the corresponding temperature values within different sintering time periods, the temperature correction coefficient is calculated. By combining the product of the temperature correction coefficient and the energy consumption drift value with the maintenance power during different sintering time periods, a dynamic power reference value suitable for the controlled cooling stage is calculated.
5. The method for monitoring the thermal field distribution and controlling the temperature in ceramic denture sintering as described in claim 1, characterized in that, The thermal response characteristic index is calculated by the deviation between the heating output power during the controlled cooling phase and the dynamic power reference value, including: Obtain the cooling temperature corresponding to the heating output power during the controlled cooling stage, and calculate the dynamic power reference value at the cooling temperature; The thermal response characteristic index is calculated based on the deviation between the dynamic power reference value at the cooling temperature and the heating output power.
6. The method for monitoring the thermal field distribution and controlling the temperature in ceramic denture sintering as described in claim 1, characterized in that, The process of coupling the structural sensitivity parameter, the thermal response characteristic index, and the preset material hardening coefficient to obtain the thermal stress risk index includes: Based on the thermal capacity parameters of the target denture and the thermal response characteristic index, a signal effectiveness weight is calculated. The signal effectiveness weight is used to characterize the degree of matching between the thermal response characteristic index and the theoretical reference power. The thermal stress risk index is obtained by coupling the thermal response characteristic index, the structural sensitivity parameter, the signal effectiveness weight, and the preset material hardening coefficient.
7. The method for monitoring the thermal field distribution and controlling the temperature in ceramic denture sintering as described in claim 6, characterized in that, The signal validity weight is calculated based on the thermal capacity parameter of the target denture and the thermal response characteristic index, including: Based on the material volume and specific heat capacity of the target denture, the theoretical heat capacity of the denture is calculated. The theoretical reference power is calculated based on the theoretical heat capacity of the denture and the preset target cooling rate. Based on the theoretical reference power and the thermal response characteristic index, the signal effectiveness weight is calculated.
8. The method for monitoring the thermal field distribution and controlling the temperature in ceramic denture sintering as described in claim 6, characterized in that, The thermal stress risk index is obtained by coupling the thermal response characteristic index, the structural sensitivity parameter, the signal effectiveness weight, and the preset material hardening coefficient, including: The instantaneous risk value is obtained by coupling the thermal response characteristic index, the signal effectiveness weight, and the preset material hardening coefficient. The thermal stress risk index is obtained by applying a moving average filter to the instantaneous risk values at different temperatures.
9. The method for monitoring the thermal field distribution and controlling the temperature in ceramic denture sintering as described in claim 1, characterized in that, When the thermal stress risk index exceeds the standard, a state transition operation between cooling and temperature suspension is performed to control the temperature of the target denture, including: Based on the aforementioned thermal stress risk index, the upper limit and lower limit of risk intervention are determined; The target denture is cooled to the target temperature. If the thermal stress risk index is detected to be greater than the risk intervention limit, it is determined that the thermal stress risk index is in an excessive state, and the temperature hovering operation is triggered. During the temperature hovering operation, if the thermal stress risk index is detected to be less than the risk intervention lower limit, the temperature hovering state is switched to the cooling state to control the temperature of the target denture.
10. The method for monitoring the thermal field distribution and controlling the temperature in ceramic denture sintering as described in claim 9, characterized in that, Following the temperature hovering operation, the following is also included: Read the ambient temperature of the furnace where the target denture is located; The target setpoint of the preset temperature controller is locked to the furnace ambient temperature to prevent the temperature of the target denture from continuously dropping.