Virtual load of constant-current driver of flow cytometer and debugging method of virtual load

Abstract

The invention provides a virtual load of a constant-current driver of a flow cytometer and a debugging method thereof, and belongs to the technical field of instrument debugging, and the method comprises the following steps: carrying out multiple actual tests of different set voltages on the constant-current driver in the flow cytometer to obtain a test array; arranging a peripheral LED circuit at the output end of the current constant-current driver, and respectively capturing unstable factors of the constant-current driver in each actual test; performing data analysis on each test array, extracting a to-be-optimized problem existing in the current constant-current driver in combination with an unstable factor, and constructing a corresponding sub-optimization function; performing comprehensive analysis on all the sub-optimization functions, determining an optimization direction of the current constant current driver and an optimization measure in the optimization direction, and further performing analog simulation on the virtual load; and continuing to optimize and debug the virtual load according to the difference between the analog simulation result and the simulation standard. The load precision is ensured, and the design of the virtual load is ensured to meet the required requirements as much as possible.

Description

Technical Field

[0001] The invention relates to the technical field of instrument debugging, and in particular to a virtual load of a constant current driver of a flow cytometer and a debugging method thereof. Background Art

[0002] In recent years, due to the low cost of flow cytometers, self-developed laser constant current drivers, temperature controllers, etc. have become a trend. Because the cost of purchased laser products is too high, self-developed lasers can achieve the same performance.

[0003] However, lasers are fragile and expensive devices that cannot be repaired once damaged. Therefore, during R&D and debugging, laser dummy loads are usually used first, and real lasers are not used. Only after the circuit board is debugged without any problems will the real laser be used to reduce the risk of damage.

[0004] The traditional laser constant current driver virtual load is generally obtained by connecting diodes in series. By connecting appropriate diodes in series, a voltage drop close to the laser forward conduction voltage can be obtained. Figure 1 As shown. But its problem is that the diode tolerance is large, which will cause accuracy problems due to temperature and current changes. When it is necessary to verify the compliance voltage and other parameters of the constant current source driver, the currently designed virtual load cannot meet the requirements.

[0005] Therefore, the present invention proposes a virtual load of a constant current driver of a flow cytometer and a debugging method thereof. Summary of the invention

[0006] The present invention provides a debugging method for a constant current driver of a flow cytometer, which is used to perform multiple actual voltage tests on a virtual load of the constant current driver, and combine the capture results of a peripheral LED circuit to comprehensively determine optimization measures for the constant current driver, and then continue to optimize through simulation and emulation of the virtual load, thereby ensuring the load accuracy and ensuring that the design of the virtual load meets the required requirements as much as possible.

[0007] The present invention provides a virtual load of a constant current driver of a flow cytometer and a debugging method thereof, comprising: Step 1: Perform multiple actual tests of different set voltages on the current constant current driver in the flow cytometer to obtain a test array based on each set voltage; Step 2: Setting a peripheral LED circuit to the output end of the current constant current driver, and capturing the unstable factors of the current constant current driver in each actual test according to the peripheral LED circuit; Step 3: Perform data analysis on each test array and combine the unstable factors to extract the problems to be optimized of the current constant current driver, and construct corresponding sub-optimization functions; Step 4: Comprehensively analyze all sub-optimization functions, determine the optimization direction of the current constant current driver and the optimization measures under the optimization direction, and then simulate the virtual load of the optimized driver; Step 5: When the simulation result does not meet the simulation standard, continue to optimize and debug the virtual load according to the difference between the simulation result and the simulation standard.

[0008] Preferably, the test array includes: the output signal value of each circuit device in the current constant current driver at the corresponding set voltage and the effect of the final signal value of the current constant current driver acting on the laser.

[0009] Preferably, capturing the unstable factors of the current constant current driver in each actual test includes: Real-time monitoring of the first display time of the current constant current driver after the actual test time and the brightness information of the LED during the continuous display time period; According to the initial display time and the brightness information, the instability factor of the current constant current driver under the corresponding actual test is determined.

[0010] Preferably, determining the instability factor of the current constant current driver under the corresponding actual test includes: Based on the brightness information of the LED during the continuous display period, a brightness function based on each continuous display moment is constructed ,in, Respectively represent the LED luminous flux, illuminance and chromaticity at the tth continuous display moment; Based on the brightness function at the tth continuous display moment , determine the first lighting quality ; ;

[0011] in, Indicates the initial function based on LED settings; ln indicates the sign of the logarithmic function; min indicates the sign of the minimum value; They represent the best luminous flux, best illumination and best chromaticity based on LED respectively; Based on all brightness functions , determine the second light quality based on LED ; ;

[0012] in, Indicates the total number of continuous display moments in the LED continuous display time period; Indicates all The variance of Capturing the flashing frequency of the LED at the corresponding continuous display moment and combining it with the preset frequency, determining the frequency change of the LED at each continuous display moment; Filter several groups of frequency changes at n0 consecutive moments and obtain the average change of each group; The first frequency change in each group is taken as the first basic point, the last frequency change in each group is taken as the second basic point, the average change in each group is taken as the first association point, and the middle change in each group after the frequency change is sorted is taken as the second association point, and the first basic point is placed in correspondence with the first time point in the corresponding group, the second basic point is placed in correspondence with the first time point in the corresponding group, the first association point is placed in correspondence with the last time point in the corresponding group, and the second association point is placed in correspondence with the time point in the middle position in the corresponding group; Construct a first triangular face based on the placed first base point, the first associated point, and the second associated point; At the same time, constructing a second triangular face based on the placed second base point, the first associated point and the second associated point; Constructing a first inscribed circular surface based on the first triangular surface and constructing a second inscribed circular surface based on the second triangular surface; Determine the arc length based on the corresponding inscribed circular surface and the line length based on the corresponding triangular surface at every two tangent points between each inscribed circular surface and the triangular surface respectively; Based on the sum of the arc length and the line length under each two tangent points, the vertices at the corresponding positions of the corresponding triangles are assigned, and a weight is assigned to each vertex; Based on the change amount of each vertex and the corresponding weights, an initial change amount is obtained, and a change vector is constructed by combining twice the distance between the centers of the first inscribed circular surface and the second inscribed circular surface; Inputting the change vector into a first vector analysis model to obtain a quality impact factor; The instability factor of the current constant current driver is determined according to the first light quality, the second light quality, the quality influencing factor, and the output signal value based on the output end at the initial display moment.

[0013] Preferably, extracting the problems to be optimized existing in the current constant current driver includes: Obtaining a test array corresponding to a set voltage and an instability factor of the set voltage under actual testing; Constructing an actual signal vector based on all output signal values ​​in the test array, and at the same time, performing effect analysis on the effect of the final signal value acting on the laser to construct an actual effect vector; Acquire the minimum offset and the maximum offset of the unstable factor for each circuit component from the factor-component database, and perform a first adjustment on the signal vector according to all the minimum offsets and a second adjustment on the signal vector according to all the maximum offsets; Determining an average ratio and a required ratio based on the first adjustment vector and the second adjustment vector; Combining the first sum of all minimum offsets, the second sum of all maximum offsets, the average ratio and the required ratio to obtain an influence coefficient; Obtaining a first control relationship matching the influence coefficient based on the unstable factor from the factor-coefficient-relationship database; Inputting the unstable factor and the effect vector into a second vector analysis model to obtain a second comparison relationship between the unstable factor and the effect vector; Determine a first difference relationship between a standard signal vector and an actual signal vector at the set voltage, and simultaneously determine a second difference relationship between a standard effect vector and an actual effect vector at the set voltage; According to the first comparison relationship and the second comparison relationship, the first difference relationship and the second difference relationship, the problem to be optimized is determined.

[0014] Preferably, a comprehensive analysis is performed on all sub-optimization functions, including: Extract the constant value of each predefined variable from each sub-optimization function, and construct a three-array of the corresponding predefined variables at each set voltage in combination with the corresponding set voltage and the action coefficient of each predefined variable in the corresponding sub-optimization function, and construct a combination vector of the corresponding predefined variables; Based on all sub-optimization functions, determine the interaction relationship between each predefined variable and each of the remaining variables, and combine the corresponding combination vectors to obtain the sub-optimization information of the corresponding predefined variables; Extract all sub-optimization information to obtain several optimization directions and optimization parameters for the optimization directions; Based on the direction-parameter-measure database, the optimization measures of the optimization parameters involved in each optimization direction are obtained.

[0015] Preferably, continuing to optimize and debug the virtual load according to the difference between the simulation result and the simulation standard includes: Obtaining re-optimization parameters matching the difference from the difference-parameter comparison table; The virtual load is further optimized and debugged according to the re-optimization parameters.

[0016] Preferably, the implementation circuit of the virtual load includes: a resistor R1, a resistor R2, a resistor R3, a resistor R4, a resistor R6, a capacitor C1, a capacitor C2, a power supply V1, a power supply V3, an amplifier U3, a field effect tube M1, a transistor Q1, and a diode D1; Among them, the positive electrode of the power supply V1 is connected to the power supply end of the amplifier U3, the positive electrode of the power supply V3 is connected to one end of the resistor R6, the other end of the resistor R6 is respectively connected to one end of the capacitor C1 and the negative end of the amplifier U3, the other end of the capacitor C1 is respectively connected to the output end of the amplifier U3 and one end of the capacitor R1, the other end of the capacitor R1 is respectively connected to one end of the capacitor C2 and one end of the field effect transistor M1, the other end of the capacitor C2 is respectively connected to one end of the resistor R3 and the other end of the field effect transistor M1, another end of the amplifier U3 is connected to one end of the resistor R2, the other end of the resistor R3 is respectively connected to the other end of the resistor R2, one end of the transistor Q1, and one end of the diode D1, the other end of the transistor Q1 is connected to one end of the resistor R4, and the other end of the resistor R4 is connected to the other end of the field effect transistor M1; The grounding terminals of the power source V1 , the power source V3 , the amplifier U3 , the field effect transistor M1 , the transistor Q1 , and the diode D1 are respectively connected to the ground GND.

[0017] Compared with the prior art, the present invention has the following beneficial effects: By performing multiple actual voltage tests on the constant current driver and combining the capture results of the peripheral LED circuit, the optimization measures for the constant current driver are comprehensively determined, and then further optimization is achieved by simulating the virtual load to ensure load accuracy and to ensure that the design of the virtual load meets the required requirements as much as possible.

[0018] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or 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.

[0019] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] 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: Figure 1 A circuit diagram of a conventional laser constant current driver virtual load in an embodiment of the present invention; Figure 2 It is a flowchart of a virtual load of a constant current driver of a flow cytometer and a debugging method thereof in an embodiment of the present invention; Figure 3 It is a structural diagram of a triangular face and an inscribed circle in an embodiment of the present invention; Figure 4 4 is a circuit diagram for realizing a virtual load in an embodiment of the present invention. DETAILED DESCRIPTION

[0021] The preferred embodiments of the present invention are described below in conjunction with 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.

[0022] The present invention provides a virtual load of a constant current driver of a flow cytometer and a debugging method thereof, such as Figure 1 As shown, including: Step 1: Perform multiple actual tests of different set voltages on the current constant current driver in the flow cytometer to obtain a test array based on each set voltage; Step 2: Setting a peripheral LED circuit to the output end of the current constant current driver, and capturing the unstable factors of the current constant current driver in each actual test according to the peripheral LED circuit; Step 3: Perform data analysis on each test array and combine the unstable factors to extract the problems to be optimized of the current constant current driver, and construct corresponding sub-optimization functions; Step 4: Comprehensively analyze all sub-optimization functions, determine the optimization direction of the current constant current driver and the optimization measures under the optimization direction, and then simulate the virtual load of the optimized driver; Step 5: When the simulation result does not meet the simulation standard, continue to optimize and debug the virtual load according to the difference between the simulation result and the simulation standard.

[0023] Preferably, the test array includes: the output signal value of each circuit device in the current constant current driver at the corresponding set voltage and the effect of the final signal value of the current constant current driver acting on the laser.

[0024] In this embodiment, the constant current driver is tested once at each set voltage, and the set voltage is generally the normal operating voltage of the flow cytometer, and the voltage range is (a1, a2), and then a1 is increased in units of 0.1V until a2 ends, which involves several measurements.

[0025] In this embodiment, the output signal value refers to the output voltage value.

[0026] In this embodiment, the final signal value refers to the output signal value of the last device of the current constant current driver, and the laser detects and fluorescently marks the cells under the action of the signal.

[0027] In this embodiment, the peripheral LED circuit is composed of LED devices, and one end of the LED is connected to the positive input end of the last device, and the other end of the LED is connected to the negative output end of the last device.

[0028] In this embodiment, the unstable factors refer to voltage instability caused by noise factors, device abnormality factors, etc. in the constant current driver.

[0029] In this embodiment, the data analysis is to construct an actual signal vector and an actual effect vector for the test array.

[0030] In this embodiment, the problem to be optimized refers to the problem that needs to be optimized for the constant current driver, such as the problem that the circuit accuracy needs to be adjusted, the problem that the circuit components need to be replaced, etc.; In this embodiment, the sub-optimization function is constructed based on the problem to be optimized, for example, Yz=e1x1+e2x2+,...,+emxm, where x1, x2,...,xm are different variables involved in the function to be optimized, and e1, e2,...,em are constants for different variables.

[0031] In this embodiment, the comprehensive analysis is to obtain all constants involved in the same variable in each sub-optimization function, so as to facilitate the subsequent optimization direction and optimization measures, and the optimization measures can be measures for circuit adjustment, for example, adding new devices to optimize the accuracy of the original constant current driver.

[0032] In this embodiment, the simulation is implemented based on a simulation platform to determine whether the optimized driver is reasonable.

[0033] In this embodiment, the simulation standard is pre-set and includes various simulation parameters. For example, the standard value range of the simulation parameter u1 is (u01, u01), and so on, to determine whether the various values ​​under each simulation result are within the corresponding standard value range; The difference refers to the difference between the simulation results and the simulation standard based on various values, so as to continue to optimize the virtual load, ensure its accuracy and meet related requirements.

[0034] The beneficial effect of the above technical solution is: by performing multiple actual voltage tests on the constant current driver and combining the capture results of the peripheral LED circuit, the optimization measures for the constant current driver are comprehensively determined, and then further optimization is achieved by simulating the virtual load to ensure the load accuracy and to ensure that the design of the virtual load meets the required requirements as much as possible.

[0035] The present invention provides a virtual load of a constant current driver of a flow cytometer and a debugging method thereof, which captures the unstable factors of the current constant current driver in each actual test, including: Real-time monitoring of the first display time of the current constant current driver after the actual test time and the brightness information of the LED during the continuous display time period; According to the initial display time and the brightness information, the instability factor of the current constant current driver under the corresponding actual test is determined.

[0036] In this embodiment, the actual test time refers to the time when voltage starts to be applied to the driver, the initial display time refers to the time when the LED lights up for the first time after voltage is applied to the driver, the LED continuous display time period refers to the period of time when the LED continues to light up after the initial display time, and the brightness information refers to the luminous flux, illumination and chromaticity of the LED, etc. It should be noted that the continuous display time period refers to the time period during which the voltage input test of the driver is maintained during the corresponding voltage test of the driver.

[0037] The beneficial effect of the above technical solution is that by determining the brightness information at the moment and in the corresponding time period, it is convenient to effectively determine the unstable factors, thereby providing a basis for subsequently obtaining the optimization direction.

[0038] The present invention provides a virtual load of a constant current driver of a flow cytometer and a debugging method thereof, and determines the instability factors of the current constant current driver under a corresponding actual test, including: Based on the brightness information of the LED during the continuous display period, a brightness function based on each continuous display moment is constructed ,in, Respectively represent the LED luminous flux, illuminance and chromaticity at the tth continuous display moment; Based on the brightness function at the tth continuous display moment , determine the first lighting quality ; ; in, Indicates the initial function based on LED settings; ln indicates the sign of the logarithmic function; min indicates the sign of the minimum value; They represent the best luminous flux, best illumination and best chromaticity based on LED respectively; Based on all brightness functions , determine the second light quality based on LED ; ; in, Indicates the total number of continuous display moments in the LED continuous display time period; Indicates all The variance of Capturing the flashing frequency of the LED at the corresponding continuous display moment and combining it with the preset frequency, determining the frequency change of the LED at each continuous display moment; Filter several groups of frequency changes at n0 consecutive moments and obtain the average change of each group; The first frequency change in each group is taken as the first basic point, the last frequency change in each group is taken as the second basic point, the average change in each group is taken as the first association point, and the middle change in each group after the frequency change is sorted is taken as the second association point, and the first basic point is placed in correspondence with the first time point in the corresponding group, the second basic point is placed in correspondence with the first time point in the corresponding group, the first association point is placed in correspondence with the last time point in the corresponding group, and the second association point is placed in correspondence with the time point in the middle position in the corresponding group; Construct a first triangular face based on the placed first base point, the first associated point, and the second associated point; At the same time, constructing a second triangular face based on the placed second base point, the first associated point and the second associated point; Constructing a first inscribed circular surface based on the first triangular surface and constructing a second inscribed circular surface based on the second triangular surface; Determine the arc length based on the corresponding inscribed circular surface and the line length based on the corresponding triangular surface at every two tangent points between each inscribed circular surface and the triangular surface respectively; Based on the sum of the arc length and the line length under each two tangent points, the vertices at the corresponding positions of the corresponding triangles are assigned, and a weight is assigned to each vertex; Based on the change amount of each vertex and the corresponding weights, an initial change amount is obtained, and a change vector is constructed by combining twice the distance between the centers of the first inscribed circular surface and the second inscribed circular surface; Inputting the change vector into a first vector analysis model to obtain a quality impact factor; The instability factor of the current constant current driver is determined according to the first light quality, the second light quality, the quality influencing factor, and the output signal value based on the output end at the initial display moment.

[0039] In this embodiment, the LED has its display standards (optimal luminous flux, optimal illumination and optimal chromaticity under corresponding voltage) under different output signal values, which are pre-set before the LED leaves the factory, providing convenience for setting up peripheral LED circuits and further determining the lighting quality.

[0040] In this embodiment, Indicates the display quality comparison value, and the value range is 0 to 1.

[0041] In this embodiment, the flickering frequency is directly captured when the LED is actually working, and the preset frequency is set in advance by the LED, etc. The frequency change = the flickering frequency corresponding to the continuous display moment - the preset frequency.

[0042] In this embodiment, for example, there are 6 frequency changes, namely q1, q2, q3, q4, q5, and q6, where n0 is 4. At this time, for example, 3 groups are randomly selected, and they are respectively: q1, q2, q3, q4, q2, q3, q4, q5, q3, q4, q5, q6. At this time, the average change of each group is obtained as: (q1+q2+q3+q4) / 4, (q2+q3+q4+q5) / 4, (q3+q4+q5+q6) / 4.

[0043] In this embodiment, for example, for q1, q2, and q3, the first basic point is q1, the second basic point is q3, the first association point is: (q1+q2+q3) / 4, and the second association point is: the screened middle point obtained after sorting q1, q2, q3, and q4. Since there are two middle points, the value obtained by averaging the two middle points is regarded as the second association point, and the time point at the middle position is: if: q1--t1, q2--t2, q3--t3, q4--t4, after sorting, only the order of q1, q2, q3, and q4 has changed successively, but t1, t2, t3, and t4 remain unchanged. At this time, the result is: q3--t1, q2--t2, q4--t3, q1--t4. At this time, the second association point is: (t2+t3) / 2, (q2+q4) / 2 corresponding.

[0044] In this embodiment, if Figure 3 As shown, the first base point is A1, the first associated point is A2, the second associated point is A3, and the second base point is A4. At this time, the first triangular face is composed of A1, A2 and A3, and the second triangular face is composed of A4, A2 and A3. The first inscribed circular face and the first triangular face have three tangent points, which are b1, b2 and b3 respectively. The second inscribed circular face and the second triangular face have three tangent points, which are b4, b5 and b6 respectively. At this time, the line length for point A1 is: the length of the arc segment from b1 to b2 in the first inscribed circle + the length of the b1A1 side + the length of the A1b2 side.

[0045] The line length for point A4 is: the length of the arc segment from b4 to b5 in the second inscribed circle + the length of the b4A4 side + the length of the A4b5 side.

[0046] The line length for point A2 is: (the length of the arc segment from b1 to b3 in the first inscribed circle + the length of the b1A2 side + the length of the A2b3 side + the length of the arc segment from b4 to b6 in the second inscribed circle + the length of the b4A2 side + the length of the A2b6 side) / 2.

[0047] The line length for point A3 is: (the length of the arc segment from b2 to b3 in the first inscribed circle + the length of the b2A3 side + the length of the A3b3 side + the length of the arc segment from b6 to b5 in the second inscribed circle + the length of the b6A3 side + the length of the A3b5 side) / 2.

[0048] In this embodiment, the weight assigned to each vertex = the line length of the corresponding vertex / the sum of the line lengths of all vertices.

[0049] In this embodiment, the initial change amount=the change amount of the corresponding vertex×the sum of the assigned weights.

[0050] In this embodiment, the change vector={(initial change amount in the first group+2×center distance in the corresponding group) / 2,...,initial change amount in the last group+2×center distance in the corresponding group) / 2}.

[0051] In this embodiment, the first vector analysis model is obtained by training a neural network model based on samples of different change vectors and quality impact factors of the vectors, thereby obtaining corresponding quality impact factors, wherein the quality impact factors are related to various possible factors such as noise and circuit abnormalities.

[0052] In this embodiment, the unstable factors are obtained based on the matching of the quality-factor-value-factor database, and the database includes the matching unstable factors under different combinations of the first lighting quality, the second lighting quality, the quality influencing factor, and the output signal value, so as to provide a basis for subsequent analysis.

[0053] The beneficial effects of the above technical solution are: calculating the relevant light quality in two ways to provide a data basis for subsequent matching, and combining the changes in LED frequency to construct two triangular faces and an inscribed circle, and determining the weight of each vertex by calculating the line length and arc length, thereby ensuring the comprehensiveness of the construction of the change vector and the completeness of its information, and finally obtaining unstable factors through combined matching of multiple parameters to ensure the reliability of factor acquisition and provide a basis for subsequent directional optimization.

[0054] The present invention provides a virtual load of a constant current driver of a flow cytometer and a debugging method thereof, extracting the problems to be optimized existing in the current constant current driver, including: Obtaining a test array corresponding to a set voltage and an instability factor of the set voltage under actual testing; Constructing an actual signal vector based on all output signal values ​​in the test array, and at the same time, performing effect analysis on the effect of the final signal value acting on the laser to construct an actual effect vector; Acquire the minimum offset and the maximum offset of the unstable factor for each circuit component from the factor-component database, and perform a first adjustment on the signal vector according to all the minimum offsets and a second adjustment on the signal vector according to all the maximum offsets; Determining an average ratio and a required ratio based on the first adjustment vector and the second adjustment vector; Combining the first sum of all minimum offsets, the second sum of all maximum offsets, the average ratio and the required ratio to obtain an influence coefficient; Obtaining a first control relationship matching the influence coefficient based on the unstable factor from the factor-coefficient-relationship database; Inputting the unstable factor and the effect vector into a second vector analysis model to obtain a second comparison relationship between the unstable factor and the effect vector; Determine a first difference relationship between a standard signal vector and an actual signal vector at the set voltage, and simultaneously determine a second difference relationship between a standard effect vector and an actual effect vector at the set voltage; According to the first comparison relationship and the second comparison relationship, the first difference relationship and the second difference relationship, the problem to be optimized is determined.

[0055] The actual signal vector = {all output signal values}, the actual effect vector = {the effect based on each channel of the laser}, and the effect analysis is to distinguish the cell analysis results generated by the laser according to different illumination ranges (channels).

[0056] In this embodiment, the factor-device database includes offset ranges for different circuit devices under different unstable factors, and the left boundary value of the range is the minimum offset, and the right boundary value is the maximum offset.

[0057] In this embodiment, the first adjustment and the second adjustment are both the results of adding the offset of the corresponding device to the acquired output signal value, that is, the first adjustment vector = {the result of adjusting the corresponding output signal value according to the minimum offset}, and the second adjustment vector = {the result of adjusting the corresponding output signal value according to the maximum offset}.

[0058] In this embodiment, the average ratio=the sum of the ratios of the element value at the corresponding position of the first adjustment vector / the element value at the corresponding position of the second adjustment vector, and then averaged.

[0059] In this embodiment, the required ratio refers to the sum of the ratios of the element value at the corresponding position of the first adjustment vector / the element value at the corresponding position in the corresponding standard signal vector that matches the actual signal vector, and then averaged, wherein the test standard output values ​​for different devices under different set voltages are theoretically set before the constant current driver leaves the factory.

[0060] In this embodiment, the influence coefficient = .

[0061] In this embodiment, the factor-coefficient-relationship database includes different unstable factors, influence coefficients and matching control relationships, which can be directly matched, and the control relationship is to determine the impact results caused by unstable factors. The greater the impact result, the tighter the control relationship.

[0062] In this embodiment, the second vector analysis model is obtained by training the neural network model based on different stabilizing factors and effect vectors and the sample with the combined influence close result, so the second control relationship can be directly obtained.

[0063] In this embodiment, the standard signal vector and the standard effect vector are both tested and set at the factory. The first difference relationship and the second difference relationship refer to the difference between the actual and the standard. The greater the deviation between the actual and standard vectors, the greater the corresponding difference relationship.

[0064] In this embodiment, the problem results corresponding to the known information such as two comparison relationships, two difference relationships and unstable factors are obtained from the problem database, that is, the problem to be optimized. Various information situations in the database are pre-stored and can be directly retrieved.

[0065] The beneficial effect of the above technical solution is: by analyzing the signal vector and the effect vector, the comparison relationship and the difference relationship are determined, providing a basis for obtaining the problem to be optimized.

[0066] The present invention provides a virtual load of a constant current driver of a flow cytometer and a debugging method thereof, and performs a comprehensive analysis on all sub-optimization functions, including: Extract the constant value of each predefined variable from each sub-optimization function, and construct a three-array of the corresponding predefined variables at each set voltage in combination with the corresponding set voltage and the action coefficient of each predefined variable in the corresponding sub-optimization function, and construct a combination vector of the corresponding predefined variables; Based on all sub-optimization functions, determine the interaction relationship between each predefined variable and each of the remaining variables, and combine the corresponding combination vectors to obtain the sub-optimization information of the corresponding predefined variables; Extract all sub-optimization information to obtain several optimization directions and optimization parameters for the optimization directions; Based on the direction-parameter-measure database, the optimization measures of the optimization parameters involved in each optimization direction are obtained.

[0067] In this embodiment, after the problem to be optimized is obtained, a sub-optimization function can be automatically generated through the problem analysis model, and the sub-optimization function contains different predefined variables and constant values ​​for the variables, and the constant value can also be 0. The problem analysis model is obtained by training a neural network model based on samples of different problem combinations and possible parameter values ​​for the problem combinations under different predefined variables. Therefore, the sub-optimization function can be output based on the model.

[0068] In this embodiment, the action coefficient refers to the weight of the predefined variable in the sub-optimization function. Different variables have different importance under different set voltages and are all pre-set.

[0069] In this embodiment, three arrays = {set voltage, constant value corresponding to the predefined variable under the set voltage, action coefficient under the set voltage}.

[0070] In this embodiment, the combination vector = {three groups under different set voltages}.

[0071] In this embodiment, the interaction relationship is determined by analyzing each sub-optimization function to determine whether the remaining variables have an impact on the corresponding predefined variables. If so, it is considered to have an interaction relationship. For example, the error in variable 1 causes a new error in variable 2, which can be obtained by inputting the sub-optimization function into the function analysis model. The function analysis model is obtained by training a neural network model with samples of the variables involved in different functions and the interactions between the variables.

[0072] In this embodiment, the sub-optimization information is obtained by matching a relationship-vector-information database, which includes different action relationships, combination vectors and sub-optimization information matching them. For example, the sub-optimization information for the predefined variable 01 is that the resistance value of the device w1 needs to be increased.

[0073] In this embodiment, the optimization direction is circuit adjustment, and the optimization parameter of the optimization direction is that the resistance value of the device w1 needs to be adjusted.

[0074] In this embodiment, the direction-parameter-measure database includes different optimization directions, optimization parameters involved in the optimization directions, and optimization measures matched therewith, for example, the resistance value is adjusted from c1 to c2.

[0075] In this embodiment, the predefined variables are preset, such as noise variables, delay variables, signal variation variables, etc.

[0076] The beneficial effect of the above technical solution is: by extracting the constant value i of the predefined variable from the function and combining the action coefficient, a combination vector can be obtained, and then sub-optimization information is obtained according to the action relationship between the variables, and then the optimization direction, optimization parameters and optimization measures are obtained, which provides convenience for optimizing the drive.

[0077] The present invention provides a virtual load of a constant current driver of a flow cytometer and a debugging method thereof, and further optimizes and debugs the optimized driver according to the difference between the simulation result and the simulation standard, including: Obtaining re-optimization parameters matching the difference from the difference-parameter comparison table; The optimized drive is further optimized and debugged according to the re-optimization parameters.

[0078] In this embodiment, the difference-parameter comparison table includes different result differences and re-optimization parameters under the result differences, and the re-optimization parameters can be the same as the optimization parameters under the optimization direction.

[0079] The beneficial effect of the above technical solution is: by obtaining the re-optimization parameters from the comparison table, the driver is further optimized and debugged to ensure the accuracy and reliability of the driver.

[0080] The present invention provides a virtual load of a constant current driver of a flow cytometer and a debugging method thereof. The realization circuit of the virtual load comprises: a resistor R1, a resistor R2, a resistor R3, a resistor R4, a resistor R6, a capacitor C1, a capacitor C2, a power supply V1, a power supply V3, an amplifier U3, a field effect tube M1, a transistor Q1, and a diode D1; Among them, the positive electrode of the power supply V1 is connected to the power supply end of the amplifier U3, the positive electrode of the power supply V3 is connected to one end of the resistor R6, the other end of the resistor R6 is respectively connected to one end of the capacitor C1 and the negative end of the amplifier U3, the other end of the capacitor C1 is respectively connected to the output end of the amplifier U3 and one end of the capacitor R1, the other end of the capacitor R1 is respectively connected to one end of the capacitor C2 and one end of the field effect transistor M1, the other end of the capacitor C2 is respectively connected to one end of the resistor R3 and the other end of the field effect transistor M1, another end of the amplifier U3 is connected to one end of the resistor R2, the other end of the resistor R3 is respectively connected to the other end of the resistor R2, one end of the transistor Q1, and one end of the diode D1, the other end of the transistor Q1 is connected to one end of the resistor R4, and the other end of the resistor R4 is connected to the other end of the field effect transistor M1; The grounding terminals of the power source V1 , the power source V3 , the amplifier U3 , the field effect transistor M1 , the transistor Q1 , and the diode D1 are respectively connected to the ground GND.

[0081] In this embodiment, if Figure 4As shown, OUT+ is connected to the positive output terminal of the constant current source, and GND is connected to the negative output terminal of the constant current source. If the virtual load needs to float, it can be powered by a battery. The U3 power supply here is 15V, so there is no problem in simulating a laser forward conduction voltage of 0.5~10V, which basically covers most lasers on the market.

[0082] Its working principle mainly utilizes the "virtual short" characteristic of the op amp circuit during negative feedback, so it is necessary to first confirm whether the circuit is negative feedback. Negative feedback can be judged from any point of the loop. Here we inject a positive change from the non-inverting input of U3, then U3 outputs a positive change. The node voltage connected to M1 and R3 will become smaller, and it is also the voltage that drives the base of Q1, so the OUT+ node voltage will become smaller. OUT+ is connected back to the non-inverting input of U3 through R2. Because of the virtual short characteristic of the op amp, there is almost no voltage drop across R2. At this point we can determine that this loop is a negative feedback loop: a positive change is input to U3, and a negative change is returned. This is why the loop is connected to the non-inverting input of the op amp.

[0083] V3 is an adjustable voltage source. The actual circuit can be replaced by a sliding rheostat as a voltage divider circuit, through which the purpose of accurately adjusting the forward conduction voltage of the laser simulation load can be achieved.

[0084] The beneficial effect of the above technical solution is that the risk of damaging the laser during the debugging process of the laser constant current source driver is greatly reduced.

[0085] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A virtual load of a constant current driver of a flow cytometer and a debugging method thereof, characterized in that: include: Step 1: Perform multiple actual tests of different set voltages on the current constant current driver in the flow cytometer to obtain a test array based on each set voltage; Step 2: Setting a peripheral LED circuit at the output end of the current constant current driver, and capturing the unstable factors of the current constant current driver in each actual test according to the peripheral LED circuit; Step 3: Perform data analysis on each test array and combine the unstable factors to extract the problems to be optimized of the current constant current driver, and construct corresponding sub-optimization functions; Step 4: Comprehensively analyze all sub-optimization functions, determine the optimization direction of the current constant current driver and the optimization measures under the optimization direction, and then simulate the virtual load of the optimized driver; Step 5: When the simulation result does not meet the simulation standard, continue to optimize and debug the virtual load according to the difference between the simulation result and the simulation standard.

2. The virtual load of the constant current driver of a flow cytometer and the debugging method thereof according to claim 1, characterized in that: The test array includes: the output signal value of each circuit device in the current constant current driver under the corresponding set voltage and the effect of the final signal value of the current constant current driver acting on the laser.

3. The virtual load of the constant current driver of a flow cytometer and the debugging method thereof according to claim 2, characterized in that: Capture the unstable factors of the constant current driver under each actual test, including: Real-time monitoring of the first display time of the current constant current driver after the actual test time and the brightness information of the LED during the continuous display time period; According to the initial display time and the brightness information, the instability factor of the current constant current driver under the corresponding actual test is determined.

4. The virtual load of the constant current driver of a flow cytometer and the debugging method thereof according to claim 3, characterized in that: Determine the unstable factors of the current constant current driver under the corresponding actual test, including: Based on the brightness information of the LED during the continuous display period, a brightness function based on each continuous display moment is constructed ,in, Respectively represent the LED luminous flux, illuminance and chromaticity at the tth continuous display moment; Based on the brightness function at the tth continuous display moment , determine the first lighting quality ; ； in, Indicates the initial function based on LED settings; ln indicates the sign of the logarithmic function; min indicates the sign of the minimum value; They represent the best luminous flux, best illumination and best chromaticity based on LED respectively; Based on all brightness functions , determine the second light quality based on LED ; ； in, Indicates the total number of continuous display moments in the LED continuous display time period; Indicates all The variance of Capturing the flashing frequency of the LED at the corresponding continuous display moment and combining it with the preset frequency, determining the frequency change of the LED at each continuous display moment; Filter several groups of frequency changes at n0 consecutive moments and obtain the average change of each group; The first frequency change in each group is taken as the first basic point, the last frequency change in each group is taken as the second basic point, the average change in each group is taken as the first association point, and the middle change in each group after the frequency change is sorted is taken as the second association point, and the first basic point is placed in correspondence with the first time point in the corresponding group, the second basic point is placed in correspondence with the first time point in the corresponding group, the first association point is placed in correspondence with the last time point in the corresponding group, and the second association point is placed in correspondence with the time point in the middle position in the corresponding group; Construct a first triangular face based on the placed first base point, the first associated point, and the second associated point; At the same time, constructing a second triangular face based on the placed second base point, the first associated point and the second associated point; Constructing a first inscribed circular surface based on the first triangular surface and constructing a second inscribed circular surface based on the second triangular surface; Determine the arc length based on the corresponding inscribed circular surface and the line length based on the corresponding triangular surface at every two tangent points between each inscribed circular surface and the triangular surface respectively; Based on the sum of the arc length and the line length under each two tangent points, the vertices at the corresponding positions of the corresponding triangles are assigned, and a weight is assigned to each vertex; Based on the change amount of each vertex and the corresponding weights, an initial change amount is obtained, and a change vector is constructed by combining twice the distance between the centers of the first inscribed circular surface and the second inscribed circular surface; Inputting the change vector into a first vector analysis model to obtain a quality impact factor; The instability factor of the current constant current driver is determined according to the first light quality, the second light quality, the quality influencing factor, and the output signal value based on the output end at the initial display moment.

5. The virtual load of the constant current driver of the flow cytometer and the debugging method thereof according to claim 3, characterized in that: The problems to be optimized in the current constant current driver are extracted, including: Obtaining a test array corresponding to a set voltage and an instability factor of the set voltage under actual testing; Constructing an actual signal vector based on all output signal values ​​in the test array, and at the same time, performing effect analysis on the effect of the final signal value acting on the laser to construct an actual effect vector; Acquire the minimum offset and the maximum offset of the unstable factor for each circuit component from the factor-component database, and perform a first adjustment on the signal vector according to all the minimum offsets and a second adjustment on the signal vector according to all the maximum offsets; Determining an average ratio and a required ratio based on the first adjustment vector and the second adjustment vector; Combining the first sum of all minimum offsets, the second sum of all maximum offsets, the average ratio and the required ratio to obtain an influence coefficient; Obtaining a first control relationship matching the influence coefficient based on the unstable factor from the factor-coefficient-relationship database; Inputting the unstable factor and the effect vector into a second vector analysis model to obtain a second comparison relationship between the unstable factor and the effect vector; Determine a first difference relationship between a standard signal vector and an actual signal vector at the set voltage, and simultaneously determine a second difference relationship between a standard effect vector and an actual effect vector at the set voltage; According to the first comparison relationship and the second comparison relationship, the first difference relationship and the second difference relationship, the problem to be optimized is determined.

6. The virtual load of the constant current driver of a flow cytometer and the debugging method thereof according to claim 1, characterized in that: Comprehensive analysis of all sub-optimization functions, including: Extract the constant value of each predefined variable from each sub-optimization function, and construct a three-array of the corresponding predefined variables at each set voltage in combination with the corresponding set voltage and the action coefficient of each predefined variable in the corresponding sub-optimization function, and construct a combination vector of the corresponding predefined variables; Based on all sub-optimization functions, determine the interaction relationship between each predefined variable and each of the remaining variables, and combine the corresponding combination vectors to obtain the sub-optimization information of the corresponding predefined variables; Extract all sub-optimization information to obtain several optimization directions and optimization parameters for the optimization directions; Based on the direction-parameter-measure database, the optimization measures of the optimization parameters involved in each optimization direction are obtained.

7. The virtual load of the constant current driver of a flow cytometer and the debugging method thereof according to claim 1, characterized in that: According to the difference between the simulation results and the simulation standard, the virtual load is further optimized and debugged, including: Obtaining re-optimization parameters matching the difference from the difference-parameter comparison table; The virtual load is further optimized and debugged according to the re-optimization parameters.

8. The virtual load of the constant current driver of a flow cytometer and the debugging method thereof according to claim 1, characterized in that: The implementation circuit of the virtual load includes: a resistor R1, a resistor R2, a resistor R3, a resistor R4, a resistor R6, a capacitor C1, a capacitor C2, a power source V1, a power source V3, an amplifier U3, a field effect tube M1, a transistor Q1, and a diode D1; Among them, the positive electrode of the power supply V1 is connected to the power supply end of the amplifier U3, the positive electrode of the power supply V3 is connected to one end of the resistor R6, the other end of the resistor R6 is respectively connected to one end of the capacitor C1 and the negative end of the amplifier U3, the other end of the capacitor C1 is respectively connected to the output end of the amplifier U3 and one end of the capacitor R1, the other end of the capacitor R1 is respectively connected to one end of the capacitor C2 and one end of the field effect transistor M1, the other end of the capacitor C2 is respectively connected to one end of the resistor R3 and the other end of the field effect transistor M1, another end of the amplifier U3 is connected to one end of the resistor R2, the other end of the resistor R3 is respectively connected to the other end of the resistor R2, one end of the transistor Q1, and one end of the diode D1, the other end of the transistor Q1 is connected to one end of the resistor R4, and the other end of the resistor R4 is connected to the other end of the field effect transistor M1; The grounding terminals of the power source V1 , the power source V3 , the amplifier U3 , the field effect transistor M1 , the transistor Q1 , and the diode D1 are respectively connected to the ground GND.

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