High-precision control method for firing chip multilayer ceramic capacitor

Abstract

The invention relates to a high-precision control method for firing a chip multilayer ceramic capacitor, which belongs to the technical field of capacitor manufacturing, and comprises the following steps of: 1, monitoring the temperature and the atmosphere in the firing process of each section in a furnace, and uploading temperature data and atmosphere data to a control module; 2, when the oxygen partial pressure is lower than the atmosphere threshold value range, reducing the hydrogen flow and increasing the nitrogen flow, and when the oxygen partial pressure is higher than the atmosphere threshold value range, increasing the hydrogen flow and reducing the nitrogen flow; 3, calculating a comprehensive temperature coefficient according to the temperature change rate and the temperature value, and triggering a temperature adjustment program when the comprehensive temperature coefficient exceeds a temperature threshold range; the method has the characteristic of high parameter control accuracy.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of capacitor manufacturing, and particularly relates to a high-precision control method for firing of a sheet type multilayer ceramic capacitor. BACKGROUND

[0002] Multilayer ceramic capacitors (MLCC) are the most widely used sheet type components in electrical equipment and are widely used in fields such as notebook computers, mobile phones, automobiles, household appliances, and unmanned aerial vehicles. Firing is one of the most critical processes in the manufacturing process of multilayer sheet capacitors. Firing changes the physical and chemical properties of raw materials to turn the raw materials into multilayer sheet capacitors with specific electrical properties.

[0003] The firing process of multilayer sheet capacitors is a complex process that needs to be run in a precisely controlled tunnel furnace according to a preset temperature-time curve and atmosphere-time curve. General processes, such as the preparation method of a low-temperature sintering II type monolithic capacitor ceramic material disclosed in Chinese Patent Publication CN109694249A, belong to the field of functional ceramics and include the following steps: Pb3O4, MgCO3, Nb2O5, TiO2, Bi2O3, and Ce2O3 are mixed by wet ball milling, and the ball-milled mixture is dried; the ball-milled mixture is pre-fired in an atmospheric atmosphere; the pre-fired product and PbO are mixed by wet ball milling, dried, and mixed with a binder. After being uniformly mixed, the mixture is pressed into a shape; the pressed shape is sintered in an atmospheric atmosphere at a sintering temperature of 880-920 DEG C for 3-5 hours, and the sintered product is obtained; the sintering temperature of the ceramic material is reduced to about 900 DEG C, the sintering temperature of the ceramic material is reduced, the ceramic body is sintered to be dense, and the number of pores is reduced, thereby improving the anti-aging performance of the capacitor.

[0004] In the above scheme, although the sintering temperature of each process is adjusted to a certain extent, the temperature in the furnace will have slight differences under mechanical errors and current fluctuations of the heating circuit. The slight differences will cause fluctuations in the firing environment, which in turn will cause the workpiece to be heated differently in each part of the furnace, affecting the processing precision and quality. At this time, the temperature in the furnace needs to be controlled in real time. However, in the above scheme, there is no high-precision real-time control of the temperature in the furnace. Therefore, a high-precision control method for firing of a sheet type multilayer ceramic capacitor with high parameter control accuracy is needed. SUMMARY

[0005] To solve the above problems in the prior art, the application provides a high-precision control method for firing of a sheet type multilayer ceramic capacitor, which has the characteristics of high parameter control accuracy.

[0006] The object of the application can be achieved by the following technical solutions: A high-precision control method for firing of a sheet type multilayer ceramic capacitor, comprising the following steps: Step 1: Monitor the temperature and atmosphere during the firing process in each section of the furnace, and upload the temperature and atmosphere data to the control module; Step 2: When the oxygen partial pressure is below the atmosphere threshold range, reduce the hydrogen flow rate and increase the nitrogen flow rate; when the oxygen partial pressure is above the atmosphere threshold range, increase the hydrogen flow rate and decrease the nitrogen flow rate. Step 3: Calculate the comprehensive temperature coefficient based on the temperature change rate and temperature value. When the comprehensive temperature coefficient exceeds the temperature threshold range, trigger the temperature adjustment program.

[0007] As a preferred embodiment of the present invention, step one further includes: uploading temperature data t and atmosphere data q to the control module; step three further includes: calculating the comprehensive temperature coefficient Z based on the temperature change rate and temperature value, where Z=(s1×t / t0+s2×q / q0) / (s1+s2)×c, t0 is a pre-inputted temperature threshold, q0 is a pre-inputted atmosphere value threshold, c is a pre-inputted correction coefficient, and s1 and s2 are pre-inputted weights.

[0008] As a preferred embodiment of the present invention, step one further includes: the control module arranges the fixed number of temperature data and atmosphere data uploaded sequentially in each segment in descending order to generate a temperature data sequence and an atmosphere data sequence, and then performs moving average filtering on the temperature data sequence and atmosphere data sequence in each segment to generate a temperature filter value and an atmosphere filter value; step two further includes: when the oxygen partial pressure in the atmosphere filter value is low, the hydrogen flow rate is reduced and the nitrogen flow rate is increased; when the oxygen partial pressure in the atmosphere filter value is high, the hydrogen flow rate is increased and the nitrogen flow rate is decreased; step three further includes: calculating a comprehensive temperature coefficient based on the temperature change rate and the temperature filter value, and triggering a temperature adjustment program when the comprehensive temperature coefficient exceeds a threshold range.

[0009] As a preferred embodiment of the present invention, step one further includes: the control module arranges the n temperature data tn and atmosphere data qn uploaded sequentially in each segment in descending order of newest, performs moving average filtering on the temperature data sequence and atmosphere data sequence in each segment, generates several temperature data filtering output samples yk1 and atmosphere data filtering output samples yk2, and then generates temperature filtering value yj1 and atmosphere filtering value yj2, where yj1 is the mean of yk1, yj2 is the mean of yk2, yk1=[tk+t(k-1)+...+t(k-M+1)] / M, yk2=[qk+q(k+1)+...+q(k+M)] / M, n is the pre-input sampling number, M is the pre-input window size value of the moving average filtering, xn is the temperature data numbered n among the n temperature data, qn is the atmosphere data numbered n among the n atmosphere data, n is an integer and n>M+1, and k is an integer and k≤nM.

[0010] As a preferred embodiment of the present invention, step one further includes: performing weighted moving average filtering on the temperature data sequence in each segment to generate a temperature filter value.

[0011] As a preferred technical solution of the present invention, step one further includes: yk1=[w0×tk+w1×t(k-1)+...+wk×t(k-M+1)] / (w0+w1+...+wk), where w0, ..., wk are pre-input weights, and w0>w1>...>wk.

[0012] As a preferred embodiment of the present invention, step one further includes: setting a temperature correction table to monitor the temperature of each section of the firing process in the furnace, and correcting the temperature data using the temperature correction table before uploading the temperature data to the control module.

[0013] As a preferred technical solution of the present invention, step one further includes: setting an atmosphere threshold range and a temperature threshold range for each section of the furnace before setting.

[0014] The beneficial effects of this invention are as follows: (1) By monitoring the atmosphere data in real time, the hydrogen flow rate is reduced and the nitrogen flow rate is increased when the oxygen partial pressure is below the atmosphere threshold range, and the hydrogen flow rate is increased and the nitrogen flow rate is decreased when the oxygen partial pressure is above the atmosphere threshold range, so as to realize the real-time adjustment of the atmosphere value. (2) By monitoring temperature data in real time, the comprehensive temperature coefficient is calculated based on the temperature change rate and temperature value. When the comprehensive temperature coefficient exceeds the temperature threshold range, the temperature adjustment program is triggered to complete the real-time control of the furnace temperature when any slight temperature difference occurs in the furnace, causing fluctuations in the firing temperature atmosphere. (3) By calculating the comprehensive temperature coefficient by normalizing and weighting the temperature value based on the temperature change rate and temperature value, compared with simply judging whether the temperature adjustment program is triggered by the temperature value, the temperature adjustment program is triggered in advance when the temperature value does not exceed the threshold but the change rate makes the temperature approach the threshold range boundary, which is likely to cause the temperature to exceed the threshold range, thus improving the accuracy of production parameter control. (4) By performing moving average filtering on several temperature and atmosphere data uploaded successively, temperature filter value and atmosphere filter value are obtained. Then, the gas flow rate is adjusted using the oxygen partial pressure in the atmosphere filter value. The comprehensive temperature coefficient is calculated based on the temperature change rate and temperature filter value. This reduces the random noise during the collection of atmosphere and temperature data and smooths the data. This reduces the impact of random noise on the collected temperature and atmosphere data and improves the accuracy of parameter adjustment based on temperature and atmosphere data. (5) By further optimizing the temperature moving average filtering method into a weighted moving average filtering method, the weight of the newest data uploaded during the filtering process is increased. In the case of the heater of the heating furnace adopting the on / off cycle or pulse width modulation heating mode, the temperature fluctuates synchronously with the heating cycle. The weight of the data that has been affected by the fluctuation is weakened, and more attention is paid to the current temperature change. Compared with the general moving average filtering, which calculates the current data and the past data simultaneously without difference, the parameter adjustment is more targeted to the current temperature situation, and thus further improves the accuracy of parameter adjustment based on temperature and atmosphere data. Attached Figure Description

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

[0016] Figure 1 This is a schematic diagram of the steps of the present invention. Detailed Implementation

[0017] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided.

[0018] Please see Figure 1 A high-precision control method for firing multilayer ceramic chip capacitors includes the following steps: Step 1: Monitor the temperature and atmosphere in each section of the furnace during the firing process, and upload the temperature and atmosphere data to the control module. Specifically, the present invention includes at least a length-running furnace and an atmosphere bell furnace. The length-running furnace is divided into multiple temperature zones along the workpiece feeding direction. Each temperature zone constitutes a segment. Each segment is equipped with a temperature sensor to periodically monitor the temperature and upload the temperature data to the control module. The atmosphere bell furnace is equipped with an atmosphere concentration sensor to monitor the atmosphere concentration in the atmosphere bell furnace and upload the atmosphere data to the control module. During production, it is necessary to adjust the furnace temperature or atmosphere in real time based on atmosphere monitoring and temperature data to prevent slight temperature differences within the furnace from causing fluctuations in the firing temperature atmosphere. This would result in uneven heating of different parts of the workpiece within the furnace, affecting processing accuracy and quality. Therefore, step one includes: setting atmosphere threshold ranges and temperature threshold ranges for each section of the furnace before making the settings; step two includes: reducing hydrogen flow and increasing nitrogen flow when the oxygen partial pressure is below the atmosphere threshold range, and increasing hydrogen flow and decreasing nitrogen flow when the oxygen partial pressure is above the atmosphere threshold range; step three includes: calculating a comprehensive temperature coefficient based on the temperature change rate and temperature value, and triggering the temperature adjustment program when the comprehensive temperature coefficient exceeds the temperature threshold range. By monitoring atmosphere data in real time, the system determines whether to reduce hydrogen flow and increase nitrogen flow when the oxygen partial pressure is below the atmosphere threshold range, and whether to increase hydrogen flow and decrease nitrogen flow when the oxygen partial pressure is above the atmosphere threshold range, thereby achieving real-time adjustment of the atmosphere value. By monitoring temperature data in real time, a comprehensive temperature coefficient is calculated based on the rate of temperature change and the temperature value. When the comprehensive temperature coefficient exceeds the temperature threshold range, the temperature adjustment program is triggered to control the furnace temperature in real time when any slight temperature difference occurs in the furnace, causing fluctuations in the firing temperature atmosphere. Specifically, the control module is pre-input with an atmosphere threshold range. The control module controls the gas flow rate of each vent in the furnace. The atmosphere threshold range is specified according to the oxygen partial pressure threshold range based on process requirements. At the same time, the atmosphere value data mainly includes oxygen partial pressure data. When the oxygen partial pressure is too high, the internal electrode will be oxidized. When it is too low, the oxygen partial pressure will cause the ceramic medium to be reduced. Therefore, when the oxygen partial pressure is lower than the atmosphere threshold range, the control module commands to reduce the hydrogen flow rate and increase the nitrogen flow rate. When the oxygen partial pressure is higher than the atmosphere threshold range, it increases the hydrogen flow rate and decreases the nitrogen flow rate. In actual production, sometimes the temperature value does not exceed the threshold, but the rate of change causes the temperature to rapidly approach the threshold range boundary. If adjustments are made only after the temperature exceeds the threshold range during rapid changes and the effects of temperature fluctuations have already acted on the workpiece, there will be a lag. Therefore, after uploading the temperature data t and atmosphere data q to the control module in step one, step three calculates the comprehensive temperature coefficient Z based on the rate of temperature change and the temperature value, where Z = (s1×t / t0 + s2×q / q0) / (s1 + s2)×c, t0 is the pre-input temperature threshold, q0 is the pre-input atmosphere value threshold, c is the pre-input correction coefficient, s1 and s2 are the pre-input weights, t≥t0, q≥q0. When t or q is less than t0 or q0, the control module takes t=t0 and q=q0. When either the temperature value or the rate of temperature change is large, it means that the temperature is at risk of exceeding the threshold range or has already exceeded the threshold range, and temperature adjustment is required. At this time, the comprehensive temperature coefficient exceeds the temperature threshold range, triggering the temperature adjustment procedure. By calculating the comprehensive temperature coefficient based on the normalized weighted average of the temperature change rate and temperature value, compared to simply judging whether to trigger the temperature adjustment program based on the temperature value, the temperature adjustment program is triggered in advance when the temperature value has not exceeded the threshold but the rate of change causes the temperature to approach the threshold range boundary, which is likely to cause the temperature to exceed the threshold range. This improves the accuracy of production parameter control.

[0019] In actual production, the data collected by temperature sensors or atmosphere sensors may be affected by random errors, and the collected data may not represent the real situation. Adjusting the parameters based on the collected data deviates from the actual requirements, reducing the accuracy of production parameter control. Therefore, step one also includes: the control module arranges the fixed number of temperature data and atmosphere data uploaded in each segment in order from newest to oldest to generate temperature data sequence and atmosphere data sequence. Then, the temperature data sequence and atmosphere data sequence in each segment are subjected to moving average filtering to generate temperature filter value and atmosphere filter value. Specifically, in step one, the control module arranges the latest n uploaded temperature data tn and atmosphere data qn in each segment in ascending order. It then performs a moving average filter on the temperature and atmosphere data sequences within each segment, generating several temperature data filter output samples yk1 and atmosphere data filter output samples yk2. Subsequently, it generates temperature filter values ​​yj1 and atmosphere filter values ​​yj2, where yj1 is the mean of the several temperature data filter output samples yk1, and yj2 is the mean of the several temperature data filter output samples yk1. The mean of the atmospheric data filtering output sample yk2 is yk1=[tk+t(k-1)+...+t(k-M+1)] / M, yk2=[qk+q(k+1)+...+q(k+M)] / M, where n is the pre-input number of samples, M is the pre-input window size of the moving average filter, xn is the temperature data numbered n among the n temperature data, qn is the atmosphere data numbered n among the n atmosphere data, n is an integer and n>M+1, and k is an integer and k≤nM; For example, in each segment of sequentially uploaded temperature and atmosphere data, the data participating in the moving average filtering are specified as the 8 most recently uploaded data points, i.e., n=8. The data points participating in the moving average filtering are numbered 1, 2, ..., 3. Simultaneously, the window size for the moving average filtering is M=3. Then, there are a total of nM filtered output samples, or 6 samples: y11=(t1+t2+t3) / 3, y21=(t2+t3+t4) / 3,..., y61=(t6+t7+t8) / 3; y12=(q1+q2+q3) / 3, y22=(q2+q3+q4) / 3,..., y62=(q6+q7+q8) / 3; yj1=(y11+y21+y31+y41+y51+y61) / 6; yj2=(y12+y22+y32+y42+y52+y62) / 6; After completing the filtering calculation, in step two, the oxygen partial pressure in the atmosphere filtering value is used for judgment. When the oxygen partial pressure in the atmosphere filtering value is too low, the hydrogen flow rate is reduced and the nitrogen flow rate is increased. When the oxygen partial pressure in the atmosphere filtering value is too high, the hydrogen flow rate is increased and the nitrogen flow rate is decreased. In step three, the comprehensive temperature coefficient is calculated using the temperature filter value. Specifically, the comprehensive temperature coefficient is calculated based on the temperature change rate and the temperature filter value. When the comprehensive temperature coefficient exceeds the threshold range, the temperature adjustment program is triggered. By performing moving average filtering on several successively uploaded temperature and atmosphere data, temperature and atmosphere filter values ​​are obtained. Then, the gas flow rate is adjusted using the "oxygen partial pressure" part of the filtered atmosphere value. The comprehensive temperature coefficient is calculated based on the temperature change rate and temperature filter value. This process reduces random noise during the collection of atmosphere and temperature data and smooths the data, thereby reducing the impact of random noise on the collected temperature and atmosphere data and improving the accuracy of parameter adjustment based on temperature and atmosphere data. In actual production, because the heater of the firing furnace has a control cycle, it is not a continuous heating process, but a heating mode of on / off cycle or pulse width modulation. This will cause the actual temperature to fluctuate synchronously with the heating mode. When filtering, this unique temperature fluctuation mode needs to be considered to eliminate the temperature fluctuation as much as possible and make the temperature filter value close to the actual temperature. Therefore, the method of performing weighted moving average filtering on the temperature data sequence in each segment of step one is preferably weighted moving average filtering to generate temperature filtered values. Specifically, yk1 = [w0×tk + w1×t(k-1) + ... + wk×t(k-M+1)] / (w0 + w1 + ... + wk), where w0, ..., wk are pre-input weights, and w0 > w1 > ... > wk; Since w0>w1>...>wk, the closer the data is to the temperature data sequence, the larger the weight of the newly uploaded data, and the greater the weight in the filtering calculation. The weight of data that has been affected by fluctuations is weakened. Compared with the general moving average filter that calculates current data and past data at the same time without difference, it focuses more on the current temperature change. Furthermore, the moving average filtering method for temperature is preferably a weighted moving average filtering method, with newer data receiving greater weight during the filtering process. For heating furnaces where the heater uses on / off cycles or pulse width modulation heating modes, causing temperature fluctuations synchronized with the heating cycle, the weight of data already affected by these fluctuations is reduced, focusing more on current temperature changes. Compared to general moving average filtering, which indiscriminately calculates both current and past data, this improves the targeting of parameter adjustments to the current temperature situation, thereby further enhancing the accuracy of parameter adjustments based on temperature and atmosphere data. In actual use, operators can judge the error between the temperature sensor and the actual temperature based on their experience. To facilitate correction by operators, a temperature correction table is also set up in step one to monitor the temperature of each section of the firing process in the furnace. Before uploading the temperature data to the control module, the temperature correction table is used for correction.

[0020] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A high-precision control method for firing multilayer ceramic chip capacitors, characterized in that: Includes the following steps: Step 1: Monitor the temperature and atmosphere in each section of the furnace during the firing process, and upload the temperature and atmosphere data to the control module. Step 2: When the oxygen partial pressure is below the atmosphere threshold range, reduce the hydrogen flow rate and increase the nitrogen flow rate; when the oxygen partial pressure is above the atmosphere threshold range, increase the hydrogen flow rate and decrease the nitrogen flow rate. Step 3: Calculate the comprehensive temperature coefficient based on the temperature change rate and temperature value. When the comprehensive temperature coefficient exceeds the temperature threshold range, trigger the temperature adjustment program.

2. The high-precision control method for firing multilayer ceramic chip capacitors according to claim 1, characterized in that: Step one further includes: uploading temperature data t and atmosphere data q to the control module; Step three further includes: calculating the comprehensive temperature coefficient Z based on the temperature change rate and temperature value, where Z=(s1×t / t0+s2×q / q0) / (s1+s2)×c, t0 is the pre-input temperature threshold, q0 is the pre-input atmosphere value threshold, c is the pre-input correction coefficient, and s1 and s2 are pre-input weights.

3. The high-precision control method for firing multilayer ceramic chip capacitors according to claim 1, characterized in that: Step one further includes: the control module arranges the fixed number of temperature and atmosphere data uploaded sequentially in each segment in ascending order to generate temperature data sequences and atmosphere data sequences, and then performs moving average filtering on the temperature and atmosphere data sequences in each segment to generate temperature filter values ​​and atmosphere filter values; Step two further includes: when the oxygen partial pressure in the atmosphere filter value is low, the hydrogen flow rate is reduced and the nitrogen flow rate is increased; when the oxygen partial pressure in the atmosphere filter value is high, the hydrogen flow rate is increased and the nitrogen flow rate is decreased; Step three further includes: calculating a comprehensive temperature coefficient based on the temperature change rate and the temperature filter value; when the comprehensive temperature coefficient exceeds a threshold range, the temperature adjustment program is triggered.

4. The high-precision control method for firing a multilayer ceramic chip capacitor according to claim 3, characterized in that: Step one further includes: the control module arranges the n temperature data tn and atmosphere data qn uploaded sequentially in each segment in ascending order, performs moving average filtering on the temperature data sequence and atmosphere data sequence in each segment, generates several temperature data filtering output samples yk1 and atmosphere data filtering output samples yk2, and then generates temperature filtering value yj1 and atmosphere filtering value yj2, where yj1 is the mean of yk1, yj2 is the mean of yk2, yk1=[tk+t(k-1)+...+t(k-M+1)] / M, yk2=[qk+q(k+1)+...+q(k+M)] / M, n is the pre-input number of samples, M is the pre-input window size value of the moving average filter, xn is the temperature data numbered n among the n temperature data, qn is the atmosphere data numbered n among the n atmosphere data, n is an integer and n>M+1, k is an integer and k≤nM.

5. The high-precision control method for firing a multilayer ceramic chip capacitor according to claim 4, characterized in that: Step one further includes: performing a weighted moving average filter on the temperature data sequence in each segment to generate a filtered temperature value.

6. The high-precision control method for firing a multilayer ceramic chip capacitor according to claim 5, characterized in that: Step one further includes: yk1=[w0×tk+w1×t(k-1)+...+wk×t(k-M+1)] / (w0+w1+...+wk), where w0, ..., wk are pre-input weights, and w0>w1>...>wk.

7. The high-precision control method for firing a multilayer ceramic chip capacitor according to claim 6, characterized in that: Step one also includes: setting a temperature correction table to monitor the temperature of each section of the firing process in the furnace, uploading the temperature data to the control module, and correcting it using the temperature correction table.

8. The high-precision control method for firing a multilayer ceramic chip capacitor according to claim 1, characterized in that: Step one also includes: before setting, setting the atmosphere threshold range and temperature threshold range for each section of the furnace.

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