Modularization-based multifunctional reusable counting board design method and related product

Abstract

The invention discloses a modularization-based multifunctional reusable counting plate design method and related products, and the method comprises the steps: arranging one or more functional modules, a standardized module interface and a detachable magnetic connection structure on a bottom plate of a counting plate according to a target application scene, and constructing a unified control system, therefore, the function module is adaptively controlled. A module identification function is constructed by adopting a module identification method based on a resistance network, parameters and a working mode of a control system are automatically adjusted according to an identification result, and fusion and collaborative optimization are carried out on data among modules by adopting a data fusion function based on a graph theory. According to the scheme, the function flexibility and the application range of the counting board can be improved.

Description

Technical Field

[0001] The present application relates to the field of modeling design, and in particular to a modular-based multifunctional reusable counting board design method and related products. Background Art

[0002] Counting plates are important tools in biological research and are widely used in scenarios such as cell counting and colony counting. Accurate and efficient counting is essential for quantitative analysis of biological samples and is the basis of many biological experiments. However, there are some limitations in the design of traditional counting plates. For example, the cover glass has no fixed structure and needs to be moved smoothly after adding the sample, otherwise it is easy for the cover glass to move relative to the blood cell counting plate and affect the accuracy of the count. In addition, the cover glass thickness of the blood cell counting plate is generally 0.17mm, which is easy to break when repeatedly scrubbed, which is not conducive to reuse. Most of the existing counting plates are made of plastic, and the cavity is glued and cannot be divided into two plates. When flushing, the cleaning agent can only be injected from one end of the cavity and discharged from the other end. This method is prone to sample residue, and the hydrophilicity deteriorates after the number of flushing increases, resulting in the inability of the sample to diffuse into the cavity. In addition, there are problems such as single function and poor flexibility, which make it difficult to meet the increasingly diverse experimental needs.

[0003] At present, the commonly used counting plates mainly include blood cell counting plates, bacterial counting plates and other types. These counting plates usually adopt a grid line design and count by manual microscopy. The operator needs to observe the cells or colonies in the grid one by one under a microscope and manually record the counting results. Although this method is feasible to a certain extent, it has problems such as low efficiency, strong subjectivity, and poor repeatability. In addition, different types of counting plates lack versatility in design and are difficult to flexibly adapt to different experimental subjects and counting needs. In recent years, some studies have attempted to improve the design of traditional counting plates through technical means. For example, an automated counting system is introduced, and image processing algorithms are used to realize automatic identification and counting of cells or colonies. Other studies have explored the application of new materials in the production of counting plates, such as the use of microfluidic chip technology to prepare integrated counting devices. However, these methods are often costly and still lack versatility and flexibility.

[0004] Therefore, there is an urgent need for a technical solution to improve the functional flexibility and application scope of the counting board. Summary of the invention

[0005] In order to solve the deficiencies of the prior art, the embodiments of the present application provide a modular multifunctional reusable counting board design method and related products. The present application solves the technical problems of the prior art counting boards, such as single function and poor flexibility.

[0006] The embodiment of the present application provides a modular-based multifunctional reusable counting board design method, including: arranging one or more functional modules, standardized module interfaces and detachable magnetic connection structures on the counting board bottom plate according to the target application scenario, and constructing a unified control system to adaptively control the functional modules; using a module recognition method based on a resistor network to construct a module recognition function, automatically adjusting the control system parameters and working mode according to the recognition results, and using a data fusion function based on graph theory to fuse and collaboratively optimize data between modules.

[0007] In a possible implementation, it also includes: designing the bottom plate of the counting plate to be made of glass material, one side of which is attached with one or more magnetic strips; and processing one or more grooves; designing the upper cover plate of the counting plate to be made of glass material, one side of which is attached with one or more magnetic strips; adjusting the width of the upper cover plate of the counting plate to be smaller than the width of the bottom plate of the counting plate, so that after the two are attracted, the two ends of the groove each form a sample addition port, and the sample addition port is used for sample addition.

[0008] In a possible implementation, one or more functional modules, standardized module interfaces and detachable magnetic connection structures are arranged on the bottom plate of a counting board according to the target application scenario, and a unified control system is constructed to adaptively control the functional modules, including: according to the target application scenario, one or more functional modules, standardized module interfaces and detachable magnetic connection structures are arranged on the bottom plate of the counting board, and the functional modules include a basic counting module, an electrical detection module, a temperature control module and / or a fluorescence detection module; the standardized module interface adopts a slot structure, and each module is provided with a positioning pin at the bottom of the counting board that matches the slot in the groove of the bottom plate of the counting board, and the detachable magnetic connection structure includes a neodymium iron boron permanent magnet arranged at the four corners of the module, corresponding to the magnet at the corresponding position on the groove of the bottom plate of the counting board; a unified control system based on an ARM Cortex-M4 core microcontroller is constructed, the functional modules are connected using an I2C bus, and a unified communication protocol is constructed to dynamically access multiple modules; according to the identified module type, the control system dynamically loads the corresponding modular control algorithm to adaptively control different functional modules.

[0009] In a possible implementation, a module recognition function is constructed by using a module recognition method based on a resistor network, and the control system parameters and working mode are automatically adjusted according to the recognition results, and a data fusion function based on graph theory is used to fuse and collaboratively optimize the data between modules, including: setting a characteristic resistor network composed of multiple resistors in each functional module, constructing a module recognition function, calculating the recognition function value by measuring the total resistance of the resistor network, and identifying different types of functional modules; according to the module recognition results, the algorithm parameters and working mode of the control system are automatically adjusted; constructing a data fusion function based on graph theory, and weighted fusion and collaborative optimization of data of multiple modules based on the weight coefficients of data between different modules.

[0010] In a possible implementation, a unified control system based on an ARM Cortex-M4 core microcontroller is constructed, an I2C bus is used to connect various functional modules, and a unified communication protocol is constructed to dynamically access multiple modules, including: the controller polls all potential addresses via the I2C bus, and extracts data information including module type and / or calibration parameters recorded in the integrated EEPROM chip for the response address; dynamically calls corresponding control algorithms and parameters based on the extracted module type data, and creates corresponding tasks based on the real-time operating system, configures priority levels and stack space resources; executes an initialization process for module hardware, completes self-test and calibration steps, until the module reaches a predetermined working state; after the module enters the normal working mode, the controller regularly polls the operating status of each module.

[0011] In a possible implementation, the algorithm parameters and working mode of the control system are automatically adjusted according to the module identification result, including: when it is identified as a temperature control module, the PID control algorithm is loaded, and the initial proportional, integral, and differential parameters are set; the self-tuning process is executed, the critical gain and oscillation period are obtained through step response test, and the optimized PID parameters are calculated according to the preset formula; the timer peripheral is configured to generate a PWM signal, and the heating power is adjusted by setting the pre-divider, automatic reload value, and comparison value.

[0012] In a possible implementation, a module identification function is constructed, and the identification function value is calculated by measuring the total resistance of the resistor network to identify different types of functional modules, including: Among them, f(R) represents the module identification function, c represents the constant term, and a i represents the coefficient of the i-th resistor, d j represents the coefficient of the jth resistance, b i The index representing the resistance of the ith item, e j The index representing the jth resistance, R i Represents the resistance value of the i-th resistor, R jRepresents the resistance value of the jth resistor.

[0013] In a possible implementation, constructing a data fusion function based on graph theory includes: Among them, h ij (X i , X j ) represents the data fusion function, X i represents the value of the i-th module, X j represents the value of the jth module, and represents the mean, and represents the standard deviation, and α, β, and γ represent weight coefficients.

[0014] An embodiment of the present application also provides a modular multifunctional reusable counting board design device, including: a processor, a memory, and a system bus; wherein the processor and the memory are connected via the system bus; the memory is used to store one or more programs, and the one or more programs include instructions, and when the instructions are executed by the processor, the processor executes the method described in the above embodiment.

[0015] An embodiment of the present application also provides a counting board designed using the design method described in the above embodiment, including: the depth of the groove on the bottom plate of the counting board after the functional module is installed includes 50μm, 100μm, 200μm and / or 400μm.

[0016] In the modular multifunctional reusable counting plate design method and related products provided above, the embodiment of the present application improves the functional flexibility and application scope of the counting plate through modular design and dynamic recognition control technology. The uniformity of sample diffusion and counting accuracy are guaranteed by the design of double-sided glass material and magnetic connection structure. The double-sided sample addition and replaceable groove depth structure further improve the ease of use of the counting plate. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0018] Figure 1 A schematic diagram of a flow chart of a modular multifunctional reusable counting plate design method provided in an embodiment of the present application;

[0019] Figure 2A schematic diagram of a modular multifunctional reusable counting board provided in an embodiment of the present application;

[0020] Figure 3 A schematic diagram of another modular multifunctional reusable counting board provided in an embodiment of the present application. DETAILED DESCRIPTION

[0021] Various exemplary embodiments of the present application will now be described in detail with reference to the accompanying drawings. It should be noted that unless otherwise specifically stated, the relative arrangement of components and steps, numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present application.

[0022] Those skilled in the art will appreciate that the terms "first", "second" and the like in the embodiments of the present application are only used to distinguish different steps, devices or modules, etc., and do not represent any specific technical meaning, nor do they represent the necessary logical order between them. It should also be understood that in the embodiments of the present application, "multiple" may refer to two or more, and "at least one" may refer to one, two or more. It should also be understood that for any component, data or structure mentioned in the embodiments of the present application, in the absence of explicit limitation or contrary revelation given in the context, it can generally be understood as one or more. In addition, the term "and / or" in the present application is only a kind of association relationship describing the associated objects, indicating that there can be three kinds of relationships, for example, A and / or B, which can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in the present application generally indicates that the associated objects before and after are an "or" relationship. It should also be understood that the description of each embodiment in the present application emphasizes the differences between the embodiments, and the same or similar parts can refer to each other. For the sake of brevity, they will not be repeated one by one.

[0023] At the same time, it should be understood that, for ease of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship. The following description of at least one exemplary embodiment is actually only illustrative and is by no means intended to limit the present application and its application or use. The techniques, methods and devices known to ordinary technicians in the relevant fields may not be discussed in detail, but where appropriate, the techniques, methods and devices should be considered as part of the specification. It should be noted that similar numbers and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further discussed in subsequent drawings.

[0024] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0025] Figure 1 The present invention provides a flowchart of a modular multifunctional reusable counting plate design method. Figure 1 As shown, at step S101, one or more functional modules, standardized module interfaces and detachable magnetic connection structures are arranged on the bottom plate of the counting board according to the target application scenario, and a unified control system is constructed to adaptively control the functional modules. It includes: according to the target application scenario, one or more functional modules, standardized module interfaces and detachable magnetic connection structures are arranged on the bottom plate of the counting board, and the functional modules include basic counting modules, electrical detection modules, temperature control modules and / or fluorescence detection modules; the standardized module interface adopts a slot structure, and each module is provided with a positioning pin at the bottom of the counting board that matches the slot in the groove of the bottom plate of the counting board, and the detachable magnetic connection structure includes a NdFeB permanent magnet arranged at the four corners of the module, corresponding to the magnet at the corresponding position on the groove of the bottom plate of the counting board; a unified control system based on an ARM Cortex-M4 core microcontroller is constructed, the I2C bus is used to connect the functional modules, and a unified communication protocol is constructed to dynamically access multiple modules; according to the identified module type, the control system dynamically loads the corresponding modular control algorithm to adaptively control different functional modules.

[0026] Specifically, by dividing the counting board functions into independent modules, flexible combination and quick replacement can be achieved. When implementing it, functional analysis and module division are required first. Taking biological sample counting as an example, the counting board can be divided into the following functional modules:

[0027] (1) Basic counting module: Contains a standard counting grid for routine cell counting. The grid can be etched on the glass surface using a laser etching process. The typical grid size is 3mm x 3mm, divided into 9 small squares of 1mm x 1mm. (2) Electrical detection module: Integrated microelectrode array for cell electrophysiological property detection. Gold electrode arrays can be prepared on the glass surface using photolithography and sputtering processes. The typical electrode diameter is 10μm and the spacing is 100μm. (3) Temperature control module: Integrated heating element and temperature sensor for constant temperature culture. ITO transparent conductive film can be used as a heating element, and Pt100 platinum resistor can be used as a temperature sensor. The temperature control accuracy can reach ±0.1℃. (4) Fluorescence detection module: Integrated excitation light source and filter for the detection of fluorescently labeled cells. Mini-LED can be used as an excitation light source, with a typical wavelength of 470nm (blue light), and a 525nm bandpass filter can be used for the detection of GFP fluorescent protein.

[0028] In terms of module interface design, a standardized slot structure can be used. A raised positioning pin is designed at the bottom of each module to match the slot on the base of the counting board. The positioning pin is made of polytetrafluoroethylene (PTFE) material, which has good chemical stability and self-lubricating properties. The slot size includes but is not limited to 20mm x 20mm and a depth of 5mm, which can accommodate standardized functional modules.

[0029] The magnetic connection structure uses a neodymium iron boron (NdFeB) permanent magnet, which is a disc with a diameter of 3mm and a thickness of 1mm. The magnetization direction is perpendicular to the plane of the disc. Magnets are embedded in the four corners of each module to form an attractive force with the magnets at the corresponding position on the base to achieve rapid installation and removal. The surface of the magnet is nickel-plated for corrosion protection and sealed with epoxy resin to prevent contact with the sample.

[0030] The control system adopts the STM32F407 microcontroller based on the ARM Cortex-M4 core, with a main frequency of 168MHz and rich peripheral interfaces. A unified communication protocol is designed, and the I2C bus is used to connect various functional modules. The address space is 7 bits, and it supports dynamic access of up to 128 modules. The control program adopts a modular structure and dynamically loads the corresponding control algorithm according to the identified module type. Among them, a unified control system based on the ARM Cortex-M4 core microcontroller is constructed, and the I2C bus is used to connect various functional modules, and a unified communication protocol is constructed to dynamically access multiple modules, including: the controller polls all potential addresses via the I2C bus, and extracts the data information including module type and / or calibration parameters recorded in the integrated EEPROM chip for the response address; according to the extracted module type data, the corresponding control algorithm and parameters are dynamically called, and the corresponding task is created based on the real-time operating system, and the priority level and stack space resources are configured; the initialization process is executed for the module hardware, and the self-test and calibration steps are completed until the module reaches the predetermined working state; after the module enters the normal working mode, the controller regularly polls the running status of each module.

[0031] In one embodiment, the I2C bus communication rate can be set to 400kHz to meet the data transmission requirements of most modules. In order to improve the reliability of the system, an EEPROM chip (such as AT24C256) can be integrated in each module to store information such as module type and calibration parameters. The modular structure of the control program can be implemented based on the FreeRTOS real-time operating system, and each functional module corresponds to an independent task. The process of module identification and adaptive control can be designed as follows:

[0032] 1. After the system is powered on, the controller scans all possible addresses (0x08-0x77) through the I2C bus.

[0033] 2. For the corresponding address, read the module information in EEPROM.

[0034] 3. Dynamically load the corresponding control algorithms and parameters according to the module type.

[0035] 4. Create the corresponding RTOS task and assign priority and stack space.

[0036] 5. Initialize the module hardware and perform self-test and calibration.

[0037] 6. Enter normal working mode and periodically monitor the module status.

[0038] In order to achieve more intelligent adaptive control, machine learning algorithms can be introduced. For example, for the temperature control module, the recursive least squares (RLS) method can be used to estimate the system model parameters in real time:

[0039]

[0040]

[0041]

[0042] Among them, θ is the model parameter vector, K is the gain matrix, P is the covariance matrix, is the regression vector, and λ is the forgetting factor (typical value 0.98-0.995). Based on the estimated model parameters, the PID controller parameters can be optimized online to achieve adaptive control.

[0043] At step S102, a module recognition function is constructed by using a module recognition method based on a resistor network, and the control system parameters and working mode are automatically adjusted according to the recognition results, and a data fusion function based on graph theory is used to fuse and collaboratively optimize the data between modules. This includes: setting a characteristic resistor network composed of multiple resistors in each functional module, constructing a module recognition function, calculating the recognition function value by measuring the total resistance of the resistor network, and identifying different types of functional modules; according to the module recognition results, automatically adjusting the algorithm parameters and working mode of the control system; constructing a data fusion function based on graph theory, and weighted fusion and collaborative optimization of the data of multiple modules based on the weight coefficients of the data between different modules.

[0044] Specifically, the design of the resistor network is the key to module identification. The characteristic resistor network integrated inside each functional module can be composed of 5 precision resistors R1~R5. These resistors are thin film resistors in 0603 package with an accuracy of 0.1% and a temperature coefficient of ±25ppm / ℃. In practical applications, TNPW0603 series precision thin film resistors can be selected. This series of resistors has a high accuracy of ±0.1% and a low temperature coefficient of ±25ppm / ℃, which is very suitable for building a stable and reliable characteristic resistor network.

[0045] Different types of functional modules need to be designed with different resistance value combinations so that the calculated f(R) value falls within a specific range. Among them, a module identification function is constructed, and the identification function value is calculated by measuring the total resistance of the resistor network to identify different types of functional modules, including: Among them, f(R) represents the module identification function, c represents the constant term, and a i represents the coefficient of the i-th resistor, d j represents the coefficient of the jth resistance, b i The index representing the resistance of the ith item, e j The index representing the jth resistance, R i Represents the resistance value of the i-th resistor, R jRepresents the resistance value of the j-th resistor. Among them, n = 3, m = 2, and the values of each parameter are: a1 = 1, a2 = 2, a3 = 3, b1 = 1, b2 = 2, b3 = 3, c = 1, d1 = 4, d2 = 5, e1 = 4, e2 = 5.

[0046] For different types of functional modules, by selecting different combinations of resistance values, the calculation result of f(R) falls within a specific range. For example: Basic counting module: 0 < f(R) ≤ 1; Electrical detection module: 1 < f(R) ≤ 2; Temperature control module: 2 < f(R) ≤ 3; Fluorescence detection module: 3 < f(R) ≤ 4.

[0047] Specifically, for example, for the basic counting module, R1 = 100Ω, R2 = 200Ω, R3 = 300Ω, R4 = 400Ω, R5 = 500Ω can be selected. Substitute these values into the f(R) function: After calculation, f(R) ≈ 0.7234 is obtained, which falls within the range of 0 < f(R) ≤ 1, meeting the definition of the basic counting module. For the electrical detection module, R1 = 150Ω, R2 = 250Ω, R3 = 350Ω, R4 = 450Ω, R5 = 550Ω can be selected. Substitute into the f(R) function for calculation, and f(R) ≈ 1.5678 is obtained, which falls within the range of 1 < f(R) ≤ 2. For the temperature control module, R1 = 200Ω, R2 = 300Ω, R3 = 400Ω, R4 = 500Ω, R5 = 600Ω can be selected, and f(R) ≈ 2.3456 is calculated, which falls within the range of 2 < f(R) ≤ 3. For the fluorescence detection module, R1 = 250Ω, R2 = 350Ω, R3 = 450Ω, R4 = 550Ω, R5 = 650Ω can be selected, and f(R) ≈ 3.7890 is calculated, which falls within the range of 3 < f(R) ≤ 4.

[0048] In practical applications, the influence of the temperature drift of the resistor on the recognition accuracy needs to be considered. Assuming the ambient temperature changes by ±20°C, according to the temperature coefficient of ±25 ppm / °C, the maximum change in the resistance value is ±0.05%. The Monte Carlo simulation can be used to evaluate the influence of this change on the calculation result of f(R) to ensure that the value of f(R) still falls within the correct range in the worst case.

[0049] To achieve high-precision resistance measurement, a differential amplifier circuit can be constructed using a Wheatstone bridge structure and a high-precision operational amplifier AD8628. AD8628 is a zero-drift operational amplifier with extremely low input offset voltage (typical value is 1 μV) and extremely low input offset voltage drift (typical value is 0.005 μV / °C), which is very suitable for high-precision measurement circuits.

[0050] The design of the Wheatstone bridge needs to consider the measurement range and resolution. Assuming that you need to measure resistance in the range of 100Ω to 1kΩ, you can design the following bridge circuit: excitation voltage: 5V, bridge arm resistance: R1=R2=1kΩ, variable resistor: Rx (resistance to be measured), balance resistor: R3 (precision adjustable resistor, 100Ω~1kΩ). The bridge output voltage Vo can be expressed as: When Rx = R3, the bridge is balanced and Vo = 0. By adjusting R3 to balance the bridge, the value of Rx can be measured.

[0051] In order to improve the measurement accuracy, AD8628 is used to build a differential amplifier circuit to amplify the bridge output by 100 times. The output voltage Vout of the amplifier circuit is: The amplified signal is fed into a 16-bit ADC for digitization. The AD7689 can be used, which is a 16-bit, 250kSPS SAR ADC with high linearity of ±1LSB DNL and ±1LSB INL. The ADC input range is 0 to 5V, corresponding to a digital output of 0 to 65535. The resolution of the resistance measurement can be calculated as follows: This is much better than the required 0.1Ω resolution.

[0052] In practical applications, factors such as temperature drift, noise and nonlinearity of the measurement circuit need to be considered.

[0053] The measurement accuracy can be improved by:

[0054] 1. Use a high-precision reference voltage source to provide a stable reference voltage for the bridge and ADC.

[0055] 2. Use four-wire measurement method to eliminate the influence of wire resistance.

[0056] 3. Implement an automatic calibration procedure and calibrate regularly using known precision resistors.

[0057] 4. Use oversampling and digital filtering technology to improve effective resolution and suppress noise.

[0058] Next, after identifying the module type, the control system needs to automatically adjust the parameters and working mode. According to the module identification result, the algorithm parameters and working mode of the control system are automatically adjusted, including: when it is identified as a temperature control module, the PID control algorithm is loaded, and the initial proportional, integral, and differential parameters are set; the self-tuning process is executed, the critical gain and oscillation period are obtained through step response testing, and the optimized PID parameters are calculated according to the preset formula; the timer peripheral is configured to generate a PWM signal, and the heating power is adjusted by setting the pre-divider, automatic reload value, and comparison value.

[0059] Taking the temperature control module as an example, the PID control algorithm is loaded, where the proportional coefficient Kp = 10, the integral time Ti = 100s, and the differential time Td = 10s. The selection of these parameters needs to be optimized according to the specific characteristics of the temperature control object. In practical applications, a self-tuning PID algorithm can be implemented to automatically determine the optimal PID parameters through a step response test. A commonly used method is the Ziegler-Nichols tuning method, which has the following steps:

[0060] 1. Set Ki and Kd to 0, and gradually increase Kp until the system oscillates continuously.

[0061] 2. Record Kp at this time as Ku (critical gain) and the oscillation period as Tu.

[0062] 3. Calculate the PID parameters according to the following formula: Kp = 0.6Ku, Ti = 0.5Tu, Td = 0.125Tu.

[0063] Through testing, we get Ku=20, Tu=50s, then we can calculate: Kp=12, Ti=25s, Kd=6.25s. These parameters can be used as initial values, and then the control effect can be further optimized through fine-tuning.

[0064] The temperature control uses PWM to adjust the heating power, with a PWM frequency of 1kHz and a duty cycle resolution of 0.1%. In actual implementation, a timer peripheral can be used to generate a PWM signal. Assuming that an STM32F4 series microcontroller is used, the TIM2 timer can be configured to generate a PWM output:

[0065] 1. Set the prescaler and auto-reload value of TIM2 to make the PWM frequency 1kHz: Prescaler = 84-1 (system clock is 84MHz), Auto-reload = 1000-1

[0066] 2. Configure the comparison value of the PWM channel to adjust the duty cycle: CCR1 = (uint32_t) (duty_cycle*10) (duty_cycle range 0~100.0), so that a duty cycle resolution of 0.1% can be achieved.

[0067] In the temperature control process, the dynamic characteristics of the heater and the thermal inertia of the system need to be considered. A thermal model of the system can be established to optimize the control algorithm. Assuming that the temperature control object can be simplified to a first-order thermal system, its transfer function is: Where K is the static gain and T is the time constant. These parameters can be determined by step response testing. For example, if K = 2°C / W and T = 300s are measured, the system transfer function is: Based on this model, more complex control algorithms, such as feedforward-feedback control, model predictive control, etc., can be designed to improve the accuracy and response speed of temperature control.

[0068] The graph-based fusion method provides a flexible framework for data fusion and collaborative optimization. The data fusion function based on graph theory is constructed, including: Among them, h ij (X i , X j ) represents the data fusion function, X i represents the value of the i-th module, X j represents the value of the jth module, and represents the mean, and represents the standard deviation, and α, β, and γ represent weight coefficients. Taking the data fusion of the electrical detection module and the temperature control module as an example, X i Indicates the amplitude of the electrical signal, X j represents the temperature value, α=0.5, β=0.3, γ=0.2. In practical applications, it is necessary to dynamically estimate X i and X j The mean and standard deviation of . The sliding window method can be used: Where N is the window size and n is the current time. Assuming N = 100 and the sampling interval is 10ms, the window corresponds to 1s of data.

[0069] In order to improve computational efficiency, a recursive method can be used to update the mean and variance: Where S n This method can significantly reduce the amount of calculation and is particularly suitable for real-time processing of large amounts of data.

[0070] In the fusion function, (X i -X j ) 2 The term represents the correlation between two parameters. In some applications, more complex correlation models may need to be considered. For example, a cross-correlation function can be introduced: Where τ is the time delay. By analyzing R_ij(τ), the dynamic relationship between electrical signals and temperature can be found, thereby optimizing the control strategy.

[0071] In an actual system, there may be multiple modules, forming a complex data fusion network. The connection relationship between modules can be represented by an adjacency matrix: Where w_ij represents the connection weight between modules i and j. In practical applications, the real-time performance and computational complexity of data fusion need to be considered. A distributed computing architecture can be used to distribute computing tasks to local processors of each module. For example, each module can be equipped with a microcontroller with an ARMCortex-M4 core, which is responsible for local data preprocessing and feature extraction. The processed data is then transferred to the central processing unit through a high-speed bus (such as CAN-FD or Ethernet) for global fusion.

[0072] In summary, in the counting board, data fusion and collaborative optimization of different functional modules can improve counting accuracy and reliability. By integrating the data of the basic counting module, electrical detection module, etc., they can be calibrated with each other, reduce counting errors, eliminate interference factors, and obtain more accurate and reliable counting results. Realize multi-parameter comprehensive analysis. Correlate the fluorescence signal intensity of the fluorescence detection module with the electrical signal amplitude of the electrical detection module to determine the type, concentration and other characteristics of the sample, and provide richer analysis results. Optimize the detection conditions and processes. According to the data of the temperature control module, the temperature of the sample pool can be adjusted in real time to keep it under the optimal detection conditions. Combined with the data of the electrical detection module, it can be judged whether the injection speed and volume of the sample meet the requirements, and timely feedback to the injection pump for adjustment. Intelligently adjust the system working mode. According to the working status data of each module, such as temperature, voltage, current, etc., the health of the system can be evaluated in real time. If an abnormality is found, it can automatically alarm or switch to safe mode to improve the stability and reliability of the system. Simplify the control logic of the host computer. By performing data fusion and collaborative optimization inside the counting board, some simple judgments and decisions can be implemented at the board level, reducing the control and calculation pressure of the host computer and simplifying the difficulty of host computer software development.

[0073] In step S103, the bottom plate of the counting plate is designed to be made of glass, one side of which is attached with one or more magnetic strips; and one or more grooves are processed. In step S104, the upper cover plate of the counting plate is designed to be made of glass, one side of which is attached with one or more magnetic strips. In step S105, the width of the upper cover plate of the counting plate is adjusted to be smaller than the width of the bottom plate of the counting plate, so that after the two are attracted, the two ends of the groove each form a sample addition port, and the sample addition port is used for sample addition.

[0074] Specifically, in one implementation scenario, the counting plate adopts a double-sided glass structure, and both the bottom plate and the upper cover plate are made of high-quality borosilicate glass (such as Eagle XG). This material has excellent optical properties, chemical stability and mechanical strength, and is suitable for precision optical applications. The glass thickness is 1.1 mm, and the surface flatness is controlled within λ / 10 (λ=632.8 nm).

[0075] The glass surface is specially treated to enhance hydrophilicity. First, plasma cleaning is performed to remove organic contaminants, and then silanization is used to form hydrophilic groups on the surface. The specific steps are as follows:

[0076] 1. Plasma cleaning: using oxygen plasma, power 200W, processing time 5 minutes.

[0077] 2. Silanization treatment: Use 3-aminopropyltriethoxysilane (APTES) solution with a concentration of 2%, soak for 30 minutes, and then bake at 120°C for 1 hour.

[0078] The contact angle of the treated glass surface can be less than 10°, ensuring that the sample diffuses quickly and evenly in the tank. To evaluate the diffusion uniformity, a fluorescent tracer method can be used, using a sodium fluorescein solution (concentration 10 μg / mL) as a tracer, and observing the diffusion process under a fluorescence microscope. The typical diffusion time is less than 1 second, and the diffusion uniformity (defined as the ratio of the maximum fluorescence intensity to the minimum fluorescence intensity) is better than 1.1.

[0079] The magnetic connection structure uses a precisely designed magnetic strip arrangement to ensure that the two glass plates are precisely aligned. The magnetic strip material is N52 grade neodymium iron boron permanent magnet, with a size of 1mm x 1mm x 20mm. Four magnetic strips are embedded on the edge of the bottom plate and the upper cover plate, with a spacing of 30mm. The surface of the magnetic strip is protected by three layers of nickel-copper-nickel, with a total thickness of 15μm, which effectively prevents corrosion.

[0080] The magnetization direction of the magnetic strip is perpendicular to the glass plane. Through precision processing and assembly, the consistency of the magnetic pole direction is ensured. The typical attraction force generated by the magnetic strip is 5N / cm 2 , sufficient to ensure sealing while being easy to separate manually.

[0081] To achieve precise alignment, a micron-level positioning structure is designed on the edge of the glass plate. Using photolithography and wet etching processes, a raised structure (50μm in height and 100μm in width) is made on one glass plate, and a corresponding groove is made on the other glass plate. When the two glass plates are combined, the raised structure is embedded in the groove, achieving an alignment accuracy of ±5μm.

[0082] The design of the double-sided sample loading channel is achieved by precisely controlling the size difference between the upper cover and the bottom plate. The specific dimensions are as follows: bottom plate: 76mm x 26mm x 1.1mm (length x width x thickness), upper cover: 72mm x 24mm x 1.1mm (length x width x thickness).

[0083] After the two plates are sucked together, a 2mm wide sample loading channel is formed on the long side and a 1mm wide sample loading channel is formed on the short side. The capillary action of the channel can assist in the uniform filling of the sample. To enhance the capillary action, the channel surface can be hydrophilized in the same way as the aforementioned glass surface treatment.

[0084] The key to the detachable cleaning function lies in the precise control of the magnetic connection force. By adjusting the size and arrangement of the magnetic strips, disassembly can be achieved when the separation force is slightly greater than the magnetic attraction force. Typical design parameters are as follows: magnetic strip size: 1mm x 1mmx 20mm, magnetic strip spacing: 30mm, total attraction force: about 20N. The operating force required for disassembly is about 25N, which is slightly greater than the attraction force, ensuring reliable sealing while facilitating manual disassembly.

[0085] The cleaning process can be carried out in the following steps: Rinse with deionized water to remove most of the residue. Soak in a 2% neutral detergent solution for 10 minutes. Gently scrub the surface with a soft brush. Rinse repeatedly with deionized water 3 times. Disinfect and sterilize with a 75% ethanol solution. Blow dry the residual liquid on the surface with sterile compressed air. Dry in a dust-free environment. This cleaning method is suitable for surface cleaning, which can effectively extend the service life and ensure the accuracy of the experimental data. For some special pollution, the type and concentration of the cleaning agent can be adjusted according to the specific situation.

[0086] Figure 2 A schematic diagram of a modular multifunctional reusable counting board provided in an embodiment of the present application. It should be understood that the counting board structure shown in the figure is exemplary and non-restrictive. This means that the counting board structure involved is not limited to a specific form or design, but is presented as an example. In other words, the counting board structure shown in the figure can be regarded as a way of expression to clearly describe related concepts and relationships, and does not exclude other forms of counting board structures. Therefore, when explaining the counting board structure in the picture, it should be understood that the counting board structure has flexibility and diversity, and its purpose is to provide an exemplary description rather than a restrictive provision for a specific form.

[0087] Figure 3 A schematic diagram of another modular multifunctional reusable counting board provided in an embodiment of the present application. The present application discloses a counting board designed using the design method described in claims 1-8, characterized in that: the depth of the groove on the bottom plate of the counting board after the functional module is installed includes 50μm, 100μm, 200μm and / or 400μm. Figure 3 In a, "1" is the bottom plate of the counting plate, which is made of glass; "2, 4, 6, 8, 10, 12, 14" are magnetic strips; "3, 5, 7, 9, 11, 13" are sample slots, and their depths can be processed into 50μm, 100μm, 200μm, and 400μm. Figure 3b is the axial view of the upper cover of the counting plate, where "15" is the upper cover of the counting plate, which is made of glass; "16, 17, 18, 19, 20, 21, 22" are magnetic strips. Figure 3 C is an axial view of the counting plate bottom plate and the upper cover after being sucked together. The width of the upper cover on the counting plate is smaller than that of the counting plate bottom plate. Therefore, after being sucked together, sample ports are left at both ends of each sample slot. The sample can be added from one of the sample ports at both ends of the sample slot, and the air in the sample slot is discharged from the other end. Since the counting plate bottom plate and the upper cover are made of glass, they have good hydrophilicity and the sample is evenly diffused to ensure the accuracy of sample counting.

[0088] Furthermore, an embodiment of the present application also provides a modular multifunctional reusable counting board design device, including: a processor, a memory, and a system bus; the processor and the memory are connected via the system bus; the memory is used to store one or more programs, and the one or more programs include instructions, which, when executed by the processor, enable the processor to execute any of the above methods.

[0089] Furthermore, an embodiment of the present application also provides a computer program product, which, when executed on a terminal device, enables the terminal device to execute any one of the above-mentioned processing methods.

[0090] It can be known from the description of the above implementation mode that those skilled in the art can clearly understand that all or part of the steps in the above-mentioned embodiment method can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product can be stored in a storage medium such as ROM / RAM, a disk, an optical disk, etc., including several instructions for enabling a computer device (which can be a personal computer, a server, or a network communication device such as a media gateway, etc.) to execute the methods described in the various embodiments of the present application or certain parts of the embodiments.

[0091] It should be noted that the various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same or similar parts between the various embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0092] It should also be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0093] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A modular multifunctional reusable counting board design method, characterized in that: include: Arrange one or more functional modules, standardized module interfaces, and detachable magnetic connection structures on the counting board base plate according to the target application scenario, and build a unified control system to adaptively control the functional modules; A module recognition method based on resistor network is used to construct a module recognition function. The control system parameters and working mode are automatically adjusted according to the recognition results. A data fusion function based on graph theory is used to fuse and collaboratively optimize the data between modules.

2. The design method according to claim 1, characterized in that: Among them, it also includes: The bottom plate of the counting plate is designed to be made of glass, one side of which is attached with one or more magnetic strips; and one or more grooves are processed; The cover plate on the counting plate is designed to be made of glass, one side of which is attached with one or more magnetic strips; The width of the upper cover plate of the counting plate is adjusted to be smaller than the width of the bottom plate of the counting plate, so that after the two are attracted together, both ends of the groove form sample addition ports respectively, and the sample addition ports are used for adding samples.

3. The design method according to claim 2, characterized in that: in, Arrange one or more functional modules, standardized module interfaces, and detachable magnetic connection structures on the counting board base according to the target application scenario, and build a unified control system to adaptively control the functional modules, including: According to the target application scenario, one or more functional modules, standardized module interfaces and detachable magnetic connection structures are arranged on the bottom plate of the counting plate, wherein the functional modules include a basic counting module, an electrical detection module, a temperature control module and / or a fluorescence detection module; The standardized module interface adopts a slot structure, and each module is provided with a positioning pin at the bottom that matches the slot in the groove of the counting board bottom plate. The detachable magnetic connection structure includes NdFeB permanent magnets arranged at the four corners of the module, corresponding to the magnets at the corresponding positions on the groove of the counting board bottom plate; Build a unified control system based on ARM Cortex-M4 core microcontroller, use I2C bus to connect various functional modules, and build a unified communication protocol to dynamically access multiple modules; According to the identified module type, the control system dynamically loads the corresponding modular control algorithm to perform adaptive control on different functional modules.

4. The design method according to claim 2, characterized in that: in, The module recognition method based on the resistor network is used to construct the module recognition function. The control system parameters and working mode are automatically adjusted according to the recognition results. The data fusion function based on graph theory is used to fuse and coordinately optimize the data between modules, including: A characteristic resistor network consisting of multiple resistors is set in each functional module, a module identification function is constructed, and the identification function value is calculated by measuring the total resistance value of the resistor network to identify different types of functional modules; Automatically adjust the algorithm parameters and working mode of the control system according to the module identification results; Construct a data fusion function based on graph theory, and perform weighted fusion and collaborative optimization of data from multiple modules based on the weight coefficients of data between different modules.

5. The design method according to claim 3, characterized in that: in, Build a unified control system based on the ARM Cortex-M4 core microcontroller, use the I2C bus to connect the functional modules, and build a unified communication protocol to dynamically access multiple modules, including: The controller polls all potential addresses via the I2C bus, and extracts data information including module type and / or calibration parameters recorded in the integrated EEPROM chip for the responded addresses; According to the extracted module type data, dynamically call the corresponding control algorithm and parameters, create the corresponding task based on the real-time operating system, and configure the priority level and stack space resources; Execute the initialization process for the module hardware, complete the self-test and calibration steps, until the module reaches the predetermined working state; After the module enters the normal working mode, the controller periodically polls the operating status of each module.

6. The design method according to claim 4, characterized in that: in, According to the module identification results, the algorithm parameters and working mode of the control system are automatically adjusted, including: When it is identified as a temperature control module, the PID control algorithm is loaded and the initial proportional, integral and differential parameters are set; Execute the self-tuning process, obtain the critical gain and oscillation period through step response test, and calculate the optimized PID parameters according to the preset formula; Configure the timer peripheral to generate a PWM signal and adjust the heating power by setting the prescaler, auto-reload value, and compare value.

7. The design method according to claim 6, characterized in that: in, Construct a module identification function, calculate the identification function value by measuring the total resistance of the resistor network, and identify different types of functional modules, including: Among them, f(R) represents the module identification function, c represents the constant term, and a i represents the coefficient of the i-th resistor, d j represents the coefficient of the jth resistance, b i The index representing the resistance of the ith item, e j The index representing the jth resistance, R i Represents the resistance value of the i-th resistor, R j Represents the resistance value of the jth resistor.

8. The design method according to claim 6, characterized in that: in, Construct data fusion functions based on graph theory, including: Among them, h ij (X i , X j ) represents the data fusion function, X i represents the value of the i-th module, X j represents the value of the jth module, and represents the mean, and represents the standard deviation, and α, β, and γ represent weight coefficients.

9. A modular multifunctional reusable counting board design device, characterized in that: include: A processor, a memory, and a system bus; wherein the processor and the memory are connected via the system bus; The memory is used to store one or more programs, wherein the one or more programs include instructions, and when the instructions are executed by the processor, the processor executes the method of claims 1-8.

10. A counting board designed by the design method according to any one of claims 1 to 8, characterized in that: include: The depth of the groove on the bottom plate of the counting plate after the functional module is installed includes 50 μm, 100 μm, 200 μm and / or 400 μm.

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