Constant temperature module, constant temperature control method and full-automatic dry biochemical analyzer

Abstract

The invention belongs to the technical field of biochemical analyzers, and provides a constant temperature module, a constant temperature control method and a full-automatic dry biochemical analyser, the constant temperature module comprises a composite heating layer, a heat conduction substrate, a temperature sensing array and a heat dissipation layer; the composite heating layer comprises a plurality of groups of independently controlled heating units, and the heating units are made of a carbon nanotube film and metal alloy composite material; the heat conduction substrate is attached to the lower portion of the composite heating layer and is made of a high-heat-conduction ceramic material. The temperature sensing array comprises a plurality of temperature sensors, and the temperature sensors are uniformly distributed on the surface of the heat conduction substrate; and the heat dissipation layer is arranged above the composite heating layer and comprises a micro fan and a semiconductor chilling plate. According to the invention, the precision and efficiency of constant temperature control can be improved, and the biochemical analyzer can maintain stable reaction temperature during sample detection.

Description

Technical Field

[0001] The present invention relates to the technical field of biochemical analyzers, and in particular to a constant temperature module, a constant temperature control method and a full-automatic dry-type biochemical analyzer. Background Art

[0002] Biochemical analyzers are used to test various biochemical indicators in blood and body fluid samples, such as blood sugar and liver function indicators. Fully automatic biochemical analyzers, such as the Roche Cedex biochemical analyzer, are compact, easy to operate, highly robust, and highly sensitive, making them widely used in hospitals at all levels. Doctors use fully automatic biochemical analyzers to measure various biochemical indicators in blood or other body fluids, using these indicators as the data basis for making scientific medical diagnoses.

[0003] The performance of a biochemical analyzer depends heavily on the accuracy of its temperature control system. Traditional biochemical analyzer temperature control equipment typically uses Peltier elements for temperature control. This technology uses the temperature difference generated when current passes through two different conductors to regulate temperature. Although Peltier elements have advantages in miniaturization and rapid response, they have significant shortcomings in temperature uniformity. This unevenness leads to uneven temperature distribution within the analyzer, which affects sample processing and ultimately reduces the accuracy of test results. In addition, over time, the material of the heating plate may gradually age due to continuous thermal cycling, further exacerbating the instability of temperature control. Poor temperature uniformity and heating plate aging will significantly affect the final test accuracy of the equipment, and thus the reliability of experimental data.

[0004] Therefore, it is necessary to provide a constant temperature module, a constant temperature control method and a full-automatic dry-type biochemical analyzer. Summary of the Invention

[0005] The present invention provides a constant temperature module, a constant temperature control method and a fully automatic dry biochemical analyzer, which can improve the temperature control accuracy and stability of the biochemical analyzer; the constant temperature module adopts temperature control technology to ensure uniform temperature distribution inside the analyzer, effectively avoiding the temperature unevenness problem caused by traditional Peltier elements; by precisely controlling the heating and cooling processes, the module can quickly reach and maintain the set temperature, thereby improving the sample processing effect and the accuracy of the test results; in addition, the constant temperature module of the present invention also adopts durable heating materials, which effectively slows down the aging speed of the heating plate, extends the service life of the equipment, and further enhances the stability of temperature control; in combination with this constant temperature module, the present invention also proposes a new constant temperature control method, which can monitor and adjust the temperature in the module in real time, ensuring that the analyzer is always in the best working state; finally, the constant temperature module and constant temperature control method are applied to the fully automatic dry biochemical analyzer, significantly improving the test accuracy of the equipment and the reliability of experimental data.

[0006] The present invention provides a constant temperature module, comprising: a composite heating layer, a thermally conductive substrate, a temperature sensing array and a heat dissipation layer; the composite heating layer comprises a plurality of independently controlled heating units, the heating units being made of a composite material of carbon nanotube film and metal alloy; the thermally conductive substrate is attached to the underside of the composite heating layer, the thermally conductive substrate being made of a high thermal conductivity ceramic material; the temperature sensing array comprises a plurality of temperature sensors, the temperature sensors being evenly distributed on the surface of the thermally conductive substrate; the heat dissipation layer is arranged above the composite heating layer, the heat dissipation layer comprising a micro fan and a semiconductor refrigeration sheet.

[0007] Furthermore, the distribution density of the heating units increases from the center to the edge based on a set density gradient.

[0008] Furthermore, a bionic micro-groove structure is provided on the surface of the heat-conducting substrate; and a flexible heat-conducting adhesive is filled between the heat-conducting substrate and the heating unit.

[0009] Furthermore, the temperature sensing array transmits temperature data in real time via a set wireless communication network.

[0010] Furthermore, the heat dissipation layer further comprises a phase change material, and the phase change temperature of the phase change material is 35-45°C.

[0011] A constant temperature control method is provided, which utilizes a constant temperature module to implement constant temperature control in a fully automatic dry biochemical analyzer, comprising the following steps:

[0012] S1: Real-time acquisition of temperature data from multiple monitoring points set in the fully automatic dry biochemical analyzer through a temperature sensing array;

[0013] S2: Calculate the temperature distribution standard deviation based on the temperature data. If the temperature distribution standard deviation exceeds the set temperature distribution standard deviation threshold, start the constant temperature control mode.

[0014] S3: In constant temperature control mode, the corresponding PID adjustment parameters are generated according to the temperature difference value of each heating unit, and the heating power of the heating unit is dynamically adjusted;

[0015] S4: When it is detected that the resistance change rate of the heating unit exceeds a preset value, or when the cumulative working time of the heating unit exceeds a set time threshold, the aging compensation algorithm is triggered to correct the power distribution weight of the heating power of the heating unit.

[0016] Furthermore, in S3, the PID adjustment parameters are dynamically optimized using a fuzzy logic algorithm; specifically, the following steps are performed:

[0017] Define the input variables and output variables of fuzzy logic; the input variables are temperature error and temperature error change rate; the output variable is the PID parameter adjustment amount;

[0018] Design a fuzzy rule base; the fuzzy rule is: if the temperature error is large and the temperature error change rate is positive, increase the proportional gain parameter of the PID controller;

[0019] The PID parameters are dynamically updated based on the input variables, output variables and fuzzy rule base.

[0020] Furthermore, S4 includes:

[0021] An aging coefficient model of the resistance change and working time of the heating unit is established; the aging coefficient model is:

[0022] R(t)=R0*(1+α*ln(1+β*t))

[0023] In the above formula, R(t) represents the change in resistance of the heating unit over time, R0 represents the initial resistance, α represents the material aging rate coefficient, β represents the time attenuation factor, and t represents the cumulative working time; the logarithmic function ln(1+βt) represents the nonlinear growth of resistance over time;

[0024] Obtain historical operating data of the heating unit, predict the resistance change trend based on the aging coefficient model, and obtain resistance change data;

[0025] When the resistance change rate in the resistance change data exceeds a preset resistance change rate threshold, or the cumulative operating time of the heating unit exceeds a set time threshold, the aging compensation algorithm is triggered to modify the power distribution weight of the heating power of the heating unit; wherein the power distribution weight of the heating unit is defined as:

[0026]

[0027] In the above formula, w irepresents the proportion of the i-th unit in the total compensation power, V represents the working voltage of the resistance of the heating unit, R0 represents the initial resistance, R i (t) represents the change in resistance of the i-th heating unit over working time, R j (t) represents the change in resistance of the jth heating unit over the working time, and n represents the number of heating units; represents the compensation power of the i-th heating unit; Represents the total compensation power of n heating units, represents the calibration factor, which is used to prevent overcompensation; ε0 represents the maximum calibration factor, ρ T Represents the standard deviation of temperature distribution, δ represents the adjustment coefficient; the value of the calibration factor is optimized in real time according to the standard deviation of temperature distribution fed back by the temperature sensor. If the standard deviation of temperature distribution ρ T If the temperature distribution standard deviation is less than the set threshold, the calibration factor is reduced; if the temperature distribution standard deviation ρ T If the value is greater than the set temperature distribution standard deviation threshold, the calibration factor value is increased to approach the maximum calibration factor.

[0028] A fully automatic dry biochemical analyzer includes: a sample processing module, an optical detection module, a control module and a constant temperature module; the sample processing module is used to load, distribute and detect biochemical samples; the optical detection module is configured below the constant temperature module and is used to perform absorbance detection; the control module is used to integrate a constant temperature control method and execute a temperature control adjustment strategy based on the temperature detection results.

[0029] Furthermore, the control module includes a temperature adjustment implementation unit and a remote assistance diagnosis unit;

[0030] The temperature adjustment implementation unit is used to predict the temperature monitoring results based on the set temperature prediction model and the target temperatures in the sample processing stage and the detection stage, obtain the temperature prediction value, and execute the temperature control adjustment strategy based on the temperature prediction value and the target temperature;

[0031] The remote assistance diagnosis unit is used to upload the temperature control implementation data to the cloud platform and receive optimization instructions from the cloud platform, and optimize the temperature control implementation process based on the optimization instructions.

[0032] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0033] Firstly, by adopting a design combining a composite heating layer with a thermally conductive substrate, a rapid response and uniform distribution of temperature can be achieved, thereby improving heating efficiency. The heating unit made of a composite material of carbon nanotube film and metal alloy not only has excellent thermal conductivity, but also ensures uniformity and stability of heating. At the same time, the thermally conductive substrate made of high thermal conductivity ceramic material further enhances the heat transfer efficiency, allowing the entire constant temperature module to quickly reach the preset temperature and maintain a constant temperature.

[0034] Secondly, the introduction of the temperature sensor array realizes real-time monitoring of the temperature of multiple monitoring points, providing accurate data support for constant temperature control. The real-time transmission of temperature data through the wireless communication network not only improves the efficiency and accuracy of data transmission, but also makes remote monitoring and fault diagnosis possible.

[0035] Third, the design of the heat dissipation layer fully considers heat dissipation and temperature control. The combination of micro fans and semiconductor refrigeration sheets can not only quickly dissipate heat, but also provide cooling as needed, thereby achieving precise temperature control. The addition of phase change materials further improves the thermal management performance of the heat dissipation layer, allowing the constant temperature module to remain stable over a wider temperature range.

[0036] In addition, the constant temperature control method proposed in the present invention realizes dynamic adjustment and optimization of the heating power of the heating unit through the combined use of PID adjustment parameters and aging compensation algorithm. The application of fuzzy logic algorithm enables the PID adjustment parameters to be dynamically optimized according to the temperature error and the temperature error change rate, thereby improving the accuracy and stability of temperature control. The aging compensation algorithm takes into account the impact of aging of the heating unit on the heating power, and ensures the long-term stable operation of the heating unit by predicting the resistance change trend and correcting the power distribution weight.

[0037] Finally, the integrated design of the fully automatic dry biochemical analyzer enables the constant temperature module to work in conjunction with other functional modules to jointly complete the detection and analysis of biochemical samples. The introduction of the control module not only achieves precise control of the constant temperature module, but also facilitates remote monitoring and fault diagnosis of the instrument. The cloud platform's optimization instruction receiving function enables the instrument to adjust according to the latest optimization strategies, thereby continuously improving detection accuracy and efficiency.

[0038] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0039] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0041] Figure 1 This is a schematic diagram of the structure of a constant temperature module;

[0042] Figure 2 Schematic diagram of the steps of a constant temperature control method;

[0043] Figure 3 Schematic diagram of the structure of a fully automatic dry biochemical analyzer. DETAILED DESCRIPTION

[0044] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0045] The present invention provides a constant temperature module, such as Figure 1 Shown, including:

[0046] A composite heating layer, a thermally conductive substrate, a temperature sensing array and a heat dissipation layer; the composite heating layer includes multiple sets of independently controlled heating units, and the heating units are made of a composite material of carbon nanotube film and metal alloy; the thermally conductive substrate is attached to the bottom of the composite heating layer, and the thermally conductive substrate is made of high thermal conductivity ceramic material; the temperature sensing array includes several temperature sensors, and the temperature sensors are evenly distributed on the surface of the thermally conductive substrate; the heat dissipation layer is arranged above the composite heating layer, and the heat dissipation layer includes a micro fan and a semiconductor cooling plate.

[0047] The working principle of the above technical solution is as follows: in order to realize a constant temperature module, the present invention proposes a composite heating layer, a thermally conductive substrate, a temperature sensing array and a heat dissipation layer; the composite heating layer realizes precise heating of different areas through independently controlled heating units, and the composite material of carbon nanotube film and metal alloy enables the heating unit to have excellent heating efficiency and thermal uniformity; the thermally conductive substrate quickly conducts the heat generated by the heating unit to the entire substrate surface, and the high thermal conductivity ceramic material ensures efficient heat transfer; the temperature sensing array monitors the temperature distribution on the surface of the thermally conductive substrate in real time to ensure precise temperature control; when the temperature exceeds the set value, the heat dissipation layer starts, the micro fan accelerates the air flow, and the semiconductor refrigeration plate absorbs heat through the Peltier effect to achieve rapid cooling.

[0048] The beneficial effect of the above technical solution is that: by adopting the solution provided in this embodiment, the design of the constant temperature module can reach and maintain the set temperature in a short time, providing a reliable solution for the precise temperature control of the fully automatic dry biochemical analyzer.

[0049] In one embodiment, the distribution density of the heating units increases from the center to the edge based on a set density gradient.

[0050] The working principle of the above technical solution is as follows: the heating units of the composite heating layer are sparsely distributed in the central area and densely distributed in the edge area; this design takes into account the uniformity and efficiency of heat conduction. The heating demand in the central area is relatively low, while the edge area has more frequent heat exchange with the external environment, so higher heating power is required to maintain a constant temperature; by precisely controlling the power of each heating unit, the temperature of the entire thermal conductive substrate surface can be ensured to be evenly distributed, further improving the heating efficiency and temperature control accuracy of the constant temperature module.

[0051] The beneficial effects of the above technical solution are: by adopting the solution provided in this embodiment, the non-uniform distribution design of the composite heating layer not only optimizes the distribution of heat, but also reduces unnecessary energy consumption, avoids local overheating or overcooling that may occur in traditional heating methods, thereby improving the stability and reliability of the entire system.

[0052] In one embodiment, a bionic micro-groove structure is provided on the surface of the heat-conducting substrate; and a flexible heat-conducting adhesive is filled between the heat-conducting substrate and the heating unit.

[0053] The working principle of the above technical solution is as follows: the bionic microgroove structure can greatly increase the surface area of the thermally conductive substrate, thereby enhancing the heat conduction efficiency. The flexible thermally conductive adhesive acts as a thermal bridge to efficiently transfer the heat generated by the heating unit to the thermally conductive substrate, and further diffuses it to the entire constant temperature area through the bionic microgroove structure; when the heating unit starts working, the flexible thermally conductive adhesive quickly transfers the heat to the thermally conductive substrate, and the bionic microgroove structure acts like a fine thermal conductive channel, evenly distributing the heat to the entire substrate surface.

[0054] The beneficial effects of the above technical solution are: the solution provided in this embodiment not only improves the heat conduction efficiency, but also ensures the uniform distribution of temperature in the entire constant temperature module; at the same time, due to the presence of the bionic microgroove structure, heat can be quickly compensated even in the edge area, avoiding the phenomenon of local low temperature.

[0055] In one embodiment, the temperature sensing array transmits temperature data in real time via a wireless communication network.

[0056] The working principle of the above technical solution is: the temperature sensor array is arranged at a key position in the constant temperature module, which can sense and record the temperature of each monitoring point in real time. Through the established wireless communication network, these temperature data are quickly and accurately transmitted to the control unit.

[0057] The beneficial effect of the above technical solution is that: by adopting the solution provided by this embodiment, the use of a wireless communication network simplifies the transmission process of temperature data and reduces the complexity and maintenance cost of the system.

[0058] In one embodiment, the heat dissipation layer further comprises a phase change material, and the phase change temperature of the phase change material is 35-45°C.

[0059] The working principle of the above technical solution is: when the phase change material in the heat dissipation layer is working in the constant temperature module, when the temperature rises to the range of 35-45°C, the phase change material begins to undergo phase change, from solid to liquid or gas (depending on the specific type of phase change material). This phase change process absorbs a large amount of heat, which helps to maintain the stability of the internal temperature of the constant temperature module; with the continuous input of heat, the phase change material gradually completes the phase change. When all the phase change materials are transformed into the heat-absorbing state, the temperature of the constant temperature module will tend to a relatively constant level; at this time, even if the external heat source continues to provide heat, since the phase change material has completed the phase change, its heat absorption capacity will be greatly reduced.

[0060] The beneficial effect of the above technical solution is that the solution provided by this embodiment can effectively prevent the internal temperature of the constant temperature module from being too high, ensuring that the working environment temperature of the biochemical analyzer is maintained within an appropriate range.

[0061] A constant temperature control method, such as Figure 2 As shown, the constant temperature module is used to implement constant temperature control in the fully automatic dry biochemical analyzer, including the following steps:

[0062] S1: Real-time acquisition of temperature data from multiple monitoring points set in the fully automatic dry biochemical analyzer through a temperature sensing array;

[0063] S2: Calculate the temperature distribution standard deviation based on the temperature data. If the temperature distribution standard deviation exceeds the set temperature distribution standard deviation threshold, start the constant temperature control mode.

[0064] S3: In constant temperature control mode, the corresponding PID adjustment parameters are generated according to the temperature difference value of each heating unit, and the heating power of the heating unit is dynamically adjusted;

[0065] S4: When it is detected that the resistance change rate of the heating unit exceeds a preset value, or when the cumulative working time of the heating unit exceeds a set time threshold, the aging compensation algorithm is triggered to correct the power distribution weight of the heating power of the heating unit.

[0066] The working principle of the above technical solution is as follows: in order to realize the constant temperature control method, the present invention utilizes a constant temperature module to implement constant temperature control in a fully automatic dry biochemical analyzer, including the following steps: in step S1, the temperature sensing array can accurately sense the temperature fluctuations at different positions inside the analyzer to ensure the comprehensiveness and accuracy of the data; in step S2, the unevenness of the temperature distribution can be quickly identified by calculating the standard deviation of the temperature distribution. Once the preset threshold is exceeded, the constant temperature control mode is immediately started to deal with possible temperature abnormalities; the PID adjustment parameters in step S3 are dynamically generated according to the specific temperature differences of each heating unit. This personalized adjustment method helps to achieve more precise temperature control; in step S4, the aging problem of the heating unit is taken into account. By monitoring the resistance change rate and the accumulated working time, the aging compensation algorithm is triggered and the heating power is adjusted in time to ensure the continued effectiveness and accuracy of the constant temperature control.

[0067] The beneficial effect of the above technical solution is that by adopting the solution provided in this embodiment and designing a constant temperature control method, the temperature stability and working efficiency of the fully automatic dry biochemical analyzer can be improved.

[0068] In one embodiment, in S3, the PID adjustment parameters are dynamically optimized using a fuzzy logic algorithm, specifically including:

[0069] Define the input variables and output variables of fuzzy logic; the input variables are temperature error and temperature error change rate; the output variable is the PID parameter adjustment amount;

[0070] Design a fuzzy rule base; the fuzzy rule is: if the temperature error is large and the temperature error change rate is positive, increase the proportional gain parameter of the PID controller;

[0071] The PID parameters are dynamically updated based on the input variables, output variables and fuzzy rule base.

[0072] The working principle of the above technical solution is: in step S3, by defining the temperature error and the temperature error change rate as the input variables of the fuzzy logic, the trend of temperature fluctuation can be captured more accurately, thereby providing a more scientific basis for the adjustment of the PID parameters; the setting of the output variable PID parameter adjustment amount ensures that the PID controller can be adjusted timely and reasonably according to the current temperature conditions; the design of the fuzzy rule base fully considers the complexity and uncertainty of temperature control. For example, when the temperature error is large and the temperature error change rate is positive, it means that the deviation between the current temperature and the target temperature is expanding. At this time, a significant increase in the proportional gain parameter of the PID controller can quickly respond to temperature changes and effectively shorten the temperature adjustment time, thereby improving the stability and response speed of temperature control; based on the input variables, output variables and fuzzy rule base, the PID parameters are dynamically updated.

[0073] The beneficial effect of the above technical solution is: by adopting the solution provided by this embodiment, the dynamic optimization mechanism enables the PID controller to perform adaptive adjustment according to different temperature conditions, thereby ensuring the high precision and stability of the fully automatic dry biochemical analyzer during the constant temperature control process.

[0074] In one embodiment, S4 includes:

[0075] An aging coefficient model of the resistance change and working time of the heating unit is established; the aging coefficient model is:

[0076] R(t)=R0*(1+α*ln(1+β*t))

[0077] In the above formula, R(t) represents the change in resistance of the heating unit over time, R0 represents the initial resistance, α represents the material aging rate coefficient, β represents the time attenuation factor, and t represents the cumulative working time; the logarithmic function ln(1+βt) represents the nonlinear growth of resistance over time;

[0078] Obtain historical operating data of the heating unit, predict the resistance change trend based on the aging coefficient model, and obtain resistance change data;

[0079] When the resistance change rate in the resistance change data exceeds a preset resistance change rate threshold, or the cumulative operating time of the heating unit exceeds a set time threshold, the aging compensation algorithm is triggered to modify the power distribution weight of the heating power of the heating unit; wherein the power distribution weight of the heating unit is defined as:

[0080]

[0081] In the above formula, w i represents the proportion of the i-th unit in the total compensation power, V represents the working voltage of the resistance of the heating unit, R0 represents the initial resistance, R i (t) represents the change in resistance of the i-th heating unit over working time, R j (t) represents the change in resistance of the jth heating unit over the working time, and n represents the number of heating units; represents the compensation power of the i-th heating unit; Represents the total compensation power of n heating units, represents the calibration factor, which is used to prevent overcompensation; ε0 represents the maximum calibration factor, ρ T Represents the standard deviation of temperature distribution, δ represents the adjustment coefficient; the value of the calibration factor is optimized in real time according to the standard deviation of temperature distribution fed back by the temperature sensor. If the standard deviation of temperature distribution ρ T If the temperature distribution standard deviation is less than the set threshold, the calibration factor is reduced; if the temperature distribution standard deviation ρ TIf the value is greater than the set temperature distribution standard deviation threshold, the calibration factor value is increased to approach the maximum calibration factor.

[0082] The working principle of the above technical solution is: by real-time monitoring of the resistance changes of the heating unit, combined with historical working data, and using the aging coefficient model to predict the resistance change trend, when it is predicted that the resistance change rate exceeds the preset range or the cumulative working time of the heating unit is too long, the system automatically triggers the aging compensation algorithm. The algorithm dynamically adjusts the power allocation weight of each unit based on the resistance change and compensation power requirements of each heating unit to ensure the stability and uniformity of the overall heating effect; at the same time, by introducing a calibration factor, the compensation strategy is optimized in real time according to the standard deviation of the temperature distribution feedback from the temperature sensor to avoid the occurrence of over-compensation, thereby achieving precise control of the constant temperature module and improving the performance and stability of the fully automatic dry biochemical analyzer.

[0083] The beneficial effects of the above technical solution are as follows: the solution provided in this embodiment can significantly improve the temperature control accuracy and response speed of the constant temperature module; through real-time monitoring and prediction of resistance changes, combined with an intelligent aging compensation algorithm, the service life of the heating unit is effectively extended, the temperature fluctuations caused by component aging are reduced, and the stability and reliability of the constant temperature module under long-term operation are ensured; in addition, by dynamically adjusting the power allocation weight and optimizing the compensation strategy in real time, not only the uniformity of temperature control is improved, but also the energy consumption is significantly reduced, and the overall performance and stability of the fully automatic dry biochemical analyzer are enhanced.

[0084] A fully automatic dry biochemical analyzer, such as Figure 3 As shown, it includes: a sample processing module, an optical detection module, a control module and a constant temperature module; the sample processing module is used to load, distribute and detect biochemical samples; the optical detection module is configured at the bottom of the constant temperature module and is used for absorbance detection; the control module is used to integrate the constant temperature control method and execute the temperature control adjustment strategy according to the temperature detection results.

[0085] The working principle of the above technical solution is as follows: when the fully automatic dry biochemical analyzer is in operation, the sample processing module is first responsible for loading the biochemical samples and sending the samples to the designated location for detection through a precise distribution mechanism; the optical detection module is located below the constant temperature module and uses optical principles to detect the absorbance of the samples; the control module, as the core of the entire system, integrates the constant temperature control method mentioned above. It continuously receives data from the temperature sensor and compares it with the preset ideal temperature range. Once it finds that the actual temperature deviates from the ideal range, the control module will immediately activate the temperature control adjustment strategy and quickly restore the temperature to the preset range by adjusting the power output of the heating unit; at the same time, the control module is also responsible for coordinating the operations between various modules to ensure the smoothness and efficiency of the entire analysis process.

[0086] The beneficial effects of the above technical solution are: by adopting the solution provided in this embodiment, the temperature stability during the detection process is effectively maintained through the close cooperation between the constant temperature module and the control module, thereby reducing the detection error caused by temperature changes; in addition, the collaborative work of the sample processing module and the optical detection module not only improves the degree of automation of sample processing, but also ensures the accuracy and reliability of absorbance detection.

[0087] In one embodiment, the control module includes a temperature adjustment implementation unit and a remote assistance diagnosis unit;

[0088] The temperature adjustment implementation unit is used to predict the temperature monitoring results based on the set temperature prediction model and the target temperatures in the sample processing stage and the detection stage, obtain the temperature prediction value, and execute the temperature control adjustment strategy based on the temperature prediction value and the target temperature;

[0089] The remote assistance diagnosis unit is used to upload the temperature control implementation data to the cloud platform and receive optimization instructions from the cloud platform, and optimize the temperature control implementation process based on the optimization instructions.

[0090] The working principle of the above technical solution is as follows: In the control module, the temperature adjustment implementation unit uses a temperature prediction model to accurately predict the temperature change trend at the target temperature required in the sample processing and detection stages. By receiving real-time data from the temperature sensor, the temperature adjustment implementation unit compares this data with the temperature prediction value output by the prediction model. If it finds that the actual temperature is about to deviate from the target range, it will immediately initiate a preset temperature control adjustment strategy. These strategies may include adjusting the power of the heating unit, changing the operating status of the cooling system, or activating a backup temperature control device to ensure that the temperature is quickly and smoothly restored to the preset ideal range. At the same time, the remote assistance diagnosis unit provides powerful remote support capabilities for the entire system. It can upload key data during the temperature control implementation process to the cloud platform in real time. This data includes but is not limited to temperature sensor readings, execution records of temperature control adjustment strategies, and output results of the temperature prediction model. The cloud platform uses advanced data analysis technology and expert systems to deeply mine and analyze this data to identify potential temperature control issues or optimization space. Once the cloud platform finds a point that needs optimization, it immediately generates optimization instructions and sends them back to the remote assistance diagnosis unit via the network. After receiving these instructions, the diagnosis unit automatically adjusts the temperature control strategy to further improve the accuracy and stability of temperature control.

[0091] The beneficial effects of the above technical solution are as follows: by adopting the solution provided in this embodiment, the control module not only realizes precise control of temperature, but also provides strong support for the continuous optimization and performance improvement of the fully automatic dry biochemical analyzer through the remote assisted diagnosis function.

[0092] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A constant temperature module, characterized in that: include: Composite heating layer, thermal conductive substrate, temperature sensor array and heat dissipation layer; the composite heating layer includes multiple sets of independently controlled heating units, and the heating units are made of a composite material of carbon nanotube film and metal alloy; The thermal conductive substrate is attached to the bottom of the composite heating layer, and the thermal conductive substrate is made of high thermal conductivity ceramic material; the temperature sensing array includes several temperature sensors, and the temperature sensors are evenly distributed on the surface of the thermal conductive substrate; the heat dissipation layer is arranged above the composite heating layer, and the heat dissipation layer includes a micro fan and a semiconductor cooling plate.

2. The constant temperature module according to claim 1, characterized in that The distribution density of the heating units increases from the center to the edge based on the set density gradient.

3. The constant temperature module according to claim 1, characterized in that The surface of the heat-conducting substrate is provided with a bionic micro-groove structure; and a flexible heat-conducting adhesive is filled between the heat-conducting substrate and the heating unit.

4. The constant temperature module according to claim 1, characterized in that The temperature sensing array transmits temperature data in real time through the set wireless communication network.

5. The constant temperature module according to claim 1, characterized in that The heat dissipation layer further comprises a phase change material, and the phase change temperature of the phase change material is 35-45°C.

6. A constant temperature control method, characterized in that: Implementing constant temperature control in a fully automatic dry biochemical analyzer using the constant temperature module according to any one of claims 1 to 5 comprises the following steps: S1: Real-time acquisition of temperature data from multiple monitoring points set in the fully automatic dry biochemical analyzer through a temperature sensing array; S2: Based on the temperature data, calculate the temperature distribution standard deviation. If the temperature distribution standard deviation exceeds the set temperature distribution standard deviation threshold, start the constant temperature control mode; S3: In constant temperature control mode, the corresponding PID adjustment parameters are generated according to the temperature difference value of each heating unit, and the heating power of the heating unit is dynamically adjusted; S4: When it is detected that the resistance change rate of the heating unit exceeds a preset value, or when the cumulative working time of the heating unit exceeds a set time threshold, the aging compensation algorithm is triggered to correct the power distribution weight of the heating power of the heating unit.

7. A constant temperature control method according to claim 6, characterized in that: In S3, PID control parameters are dynamically optimized using a fuzzy logic algorithm; specifically: Define the input variables and output variables of fuzzy logic; the input variables are temperature error and temperature error change rate; the output variable is the PID parameter adjustment amount; Design a fuzzy rule base; the fuzzy rule is: if the temperature error is large and the temperature error change rate is positive, increase the proportional gain parameter of the PID controller; The PID parameters are dynamically updated based on the input variables, output variables and fuzzy rule base.

8. A constant temperature control method according to claim 6, characterized in that S4 include: An aging coefficient model of the resistance change and working time of the heating unit is established; the aging coefficient model is: R(t)=R0*(1+α*(ln(1+β*t)) In the above formula, R(t) represents the change in resistance of the heating unit over working time, R0 represents the initial resistance, α represents the material aging rate coefficient, β represents the time attenuation factor, and t represents the cumulative working time; The logarithmic function ln(1+βt) represents the nonlinear growth of resistance over time; Obtain historical operating data of the heating unit, predict the resistance change trend based on the aging coefficient model, and obtain resistance change data; When the resistance change rate in the resistance change data exceeds a preset resistance change rate threshold, or the cumulative operating time of the heating unit exceeds a set time threshold, the aging compensation algorithm is triggered to modify the power distribution weight of the heating power of the heating unit; wherein the power distribution weight of the heating unit is defined as: In the above formula, w i represents the proportion of the i-th unit in the total compensation power, V represents the working voltage of the resistance of the heating unit, R0 represents the initial resistance, R i (t) represents the change in resistance of the i-th heating unit over the working time, R j (t) represents the change in resistance of the jth heating unit over the working time, and n represents the number of heating units; represents the compensation power of the i-th heating unit; Represents the total compensation power of n heating units, represents the calibration factor, which is used to prevent overcompensation; ε0 represents the maximum calibration factor, ρ T Represents the standard deviation of temperature distribution, δ represents the adjustment coefficient; the value of the calibration factor is optimized in real time according to the standard deviation of temperature distribution fed back by the temperature sensor. If the standard deviation of temperature distribution ρ T is less than the set temperature distribution standard deviation threshold, the calibration factor value is reduced; if the temperature distribution standard deviation ρ T If the value is greater than the set temperature distribution standard deviation threshold, the calibration factor value is increased to approach the maximum calibration factor.

9. A fully automatic dry biochemical analyzer, characterized in that: include: A sample processing module, an optical detection module, a control module, and a constant temperature module according to any one of claims 1 to 5; The sample processing module is used to load, distribute and detect biochemical samples; the optical detection module is configured at the bottom of the constant temperature module and is used for absorbance detection; the control module is used to integrate the constant temperature control method described in any one of claims 6 to 8 and execute the temperature control adjustment strategy according to the temperature monitoring results.

10. The fully automatic dry biochemical analyzer according to claim 9, characterized in that: The control module includes a temperature adjustment implementation unit and a remote assistance diagnosis unit; The temperature adjustment implementation unit is used to predict the temperature monitoring results based on the set temperature prediction model and the target temperatures in the sample processing stage and the detection stage, obtain the temperature prediction value, and execute the temperature control adjustment strategy based on the temperature prediction value and the target temperature; The remote assistance diagnosis unit is used to upload the temperature control implementation data to the cloud platform and receive optimization instructions from the cloud platform, and optimize the temperature control implementation process based on the optimization instructions.

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