An automated two-step dilution system and analytical method for high-concentration samples based on intelligent feedback control

Abstract

This invention relates to the field of sample dilution, specifically to an automated two-step dilution system and analytical method for high-concentration samples based on intelligent feedback control. The system includes: a primary pre-dilution module, a secondary dynamic dilution module, a sensing module, an intelligent feedback control module, and a parallel dilution chamber module. By introducing a two-step dilution structure and combining it with the intelligent feedback control module, dynamic and precise dilution of high-concentration samples is achieved. The primary pre-dilution module and the secondary dynamic dilution module work together to complete the preliminary dilution and precise dilution steps respectively, improving dilution efficiency. Data on particle concentration, size distribution, and morphology collected by the sensing module supports the dynamic optimization of the dilution process. The intelligent feedback control module adjusts the sample flow rate and diluent flow rate parameters in real time, effectively avoiding particle overlap and insufficient dilution. The alternating operation of multiple parallel dilution chamber modules is seamlessly switched through control logic, ensuring the efficient operation of the entire system.

Description

Technical Field

[0001] This invention relates to the field of sample dilution, specifically to an automatic two-step dilution system and analysis method for high-concentration samples based on intelligent feedback control. Background Technology

[0002] Particle size distribution (PSD) analysis is of great significance in industrial production, materials research, and quality control. The physical properties of particles, such as size distribution, morphology, and concentration, directly affect the performance of the final product and the stability of intermediate processes. In existing technologies, single-particle sensing (SPOS) methods, such as single-particle optical sensing (SPOS) and the electric field method, are widely used for particle size analysis. However, these methods have strict requirements on the particle concentration of the sample, necessitating the dilution of high-concentration samples to an appropriate level to obtain accurate PSD data. Therefore, a dilution system becomes an indispensable part of the particle analysis process, especially for online real-time detection systems, where its dilution efficiency and accuracy are crucial to the entire detection workflow.

[0003] Existing dilution systems mostly employ static, non-adjustable systems with fixed dilution ratios or simple flow rate adjustments, coupled with photoresist sensors to detect particle size. However, these systems generally suffer from the following shortcomings:

[0004] Existing dilution systems often employ a fixed dilution factor, with the ratio of dilution chamber volume to diluent flow rate pre-set empirically. However, this fixed approach has significant limitations in practical applications. Sample concentrations are uncertain, and concentration variations between different batches of samples can be substantial due to adjustments in production conditions or processes. A fixed dilution factor cannot accurately adapt to all samples, leading to insufficient dilution of some samples, resulting in particle overlap and affecting the accuracy of PSD measurements. For samples with concentrations below the overlap limit but above the optimal detection concentration, over-dilution results in insufficient particle counts, leading to statistically poor significance, increased detection time, and the introduction of statistical errors. Furthermore, impurities in the diluent further interfere with the results, failing to accurately reflect the true particle distribution of the sample.

[0005] Traditional particle detection systems primarily rely on photoresist sensors, which calculate the equivalent diameter of particles by monitoring the obstruction signal of laser light by the particles. However, this method has inherent limitations: photoresist is only applicable to particle models with an equivalent sphere and cannot accurately identify the true size and morphology of complex or non-spherical particles. For samples with complex material properties, this method introduces significant measurement errors. Because particles of different materials exhibit varying light absorption and scattering characteristics, photoresist cannot distinguish these differences, resulting in a lack of comprehensiveness and reliability in particle detection results. In the detection of high-concentration samples, particle overlap further exacerbates signal distortion, significantly reducing the effectiveness of the photoresist method.

[0006] In practical applications, dilution systems require frequent cleaning to prevent sample residue from interfering with subsequent dilutions. However, existing dilution systems typically only have one dilution chamber. When the dilution chamber enters cleaning mode, the entire detection process must be paused, significantly reducing the overall efficiency of the system. Furthermore, the cleaning process is lengthy, especially for high-viscosity or difficult-to-remove sample residues, making the cleaning process a bottleneck in the entire detection workflow. The inability to dilute samples during cleaning leads to sample accumulation, severely impacting the production rhythm in high-frequency detection scenarios. The frequent switching and cleaning of the dilution chamber introduces switching delays and signal fluctuations, further affecting the stability of the dilution system and the reliability of measurement results. Summary of the Invention

[0007] The purpose of this invention is to provide an automatic two-step dilution system and analysis method for high-concentration samples based on intelligent feedback control, so as to solve the technical problems mentioned in the background art.

[0008] Based on the above ideas, the present invention provides the following technical solution:

[0009] An automated two-step dilution system for high-concentration samples based on intelligent feedback control includes: a primary pre-dilution module, a secondary dynamic dilution module, a sensing module, an intelligent feedback control module, and a parallel dilution chamber module. The primary pre-dilution module is equipped with a sample injection unit and a diluent supply unit, and completes primary dilution through the pre-dilution chamber. The primary pre-dilution factor is controlled by adjusting the volume of sample injected into the primary dilution chamber. The diluted sample enters the secondary dynamic dilution module through a flow channel, simultaneously transmitting a real-time concentration signal to the intelligent feedback control module. The secondary dynamic dilution module includes a secondary dilution chamber for receiving the output from the primary dilution module. The sample flow and diluent flow are controlled; the final dilution factor is adjusted through a diluent flow rate fixing unit and a sample flow control unit; the diluted sample is output to the sensing module; the sensing module includes a flow meter, a photoresist sensor, and a CCD high-speed camera, used to acquire particle concentration, particle size distribution, and morphology data; the particle concentration output from the primary and secondary dilution chambers is detected in real time, and the concentration change data and overlap rate are transmitted to the intelligent feedback control module; the CCD camera is located in the flow channel after the secondary dynamic dilution module to supplement particle morphology analysis information; the intelligent feedback control module receives the concentration signal from the sensing module. The system uses particle count rate and PSD data to dynamically adjust the dilution parameters of the primary and secondary dynamic dilution modules via an algorithm. It calculates the dilution factor based on the target concentration and sends control signals to regulate the sample flow rate out of the primary dilution chamber. Simultaneously, it monitors the flow rate of the diluent in the secondary dilution module to ensure the concentration remains stable within the set target range, forming a dynamic and adjustable dilution system. A parallel dilution chamber module, through a dilution chamber switching mechanism, allows one dilution chamber to be used for cleaning while another continues operating, ensuring the continuity of the dilution process. The dilution chamber status is monitored by an intelligent feedback control module, which automatically adjusts the dilution parameters according to priority. Dynamic switching; the diluted sample output from the primary pre-dilution module directly enters the secondary dynamic dilution module through a pipeline, and the diluted concentration signal is fed back to the intelligent feedback control module in real time; the sensing module simultaneously monitors the particle concentration, flow rate, and PSD data during the two-stage dilution process, providing the intelligent feedback control module with a basis for optimizing dilution parameters; the intelligent feedback control module adjusts the parameters of the primary and secondary dynamic dilution modules in real time based on the sensing data to achieve dynamic optimization of the dilution factor; the alternating operation of multiple dilution chamber parallel modules is seamlessly switched through control logic, ensuring that the entire system operates efficiently while avoiding downtime caused by dilution chamber cleaning.

[0010] This invention achieves dynamic and precise dilution of high-concentration samples by introducing a two-step dynamic dilution structure combined with an intelligent feedback control module. The primary pre-dilution module and the secondary dynamic dilution module work together to complete the preliminary dilution and precise dilution steps respectively, improving dilution efficiency and solving the problem of simultaneously maintaining concentration stability and flexibly adjusting the dilution factor during a single dilution. The modules work collaboratively through real-time signal transmission, and the particle concentration, size distribution, and morphological characteristics data collected by the sensing module provide strong support for the dynamic optimization of the dilution process. The intelligent feedback control module adjusts the sample flow rate and diluent flow rate parameters in real time, effectively avoiding particle overlap and insufficient dilution. Multiple dilution chambers operating in parallel further enhance the system's efficiency, ensuring the continuity of the dilution process even during cleaning. This system can be widely applied in industrial production environments requiring high-precision particle size analysis, significantly improving testing accuracy and operational efficiency, while addressing the shortcomings of existing technologies in optimizing dilution concentration and efficiency.

[0011] Preferably, it includes a dilution factor optimization algorithm for dynamically adjusting the dilution factor of the primary pre-dilution module and the diluent flow rate of the secondary dynamic dilution module, specifically including the following steps:

[0012] S1. Initialize the system, preset the volume of the primary dilution chamber, the flow rate of the secondary dilution solution, and the overlap limit of the sensors;

[0013] S2. Collect the sample injection flow rate of the primary pre-dilution module and calculate the current pre-dilution factor based on the volume of the dilution chamber;

[0014] S3. Use the sensor module to detect the particle concentration after the first dilution in real time and determine whether it meets the input concentration requirements of the second dynamic dilution module; if not, adjust the sample injection flow rate and update the first dilution factor.

[0015] S4. Based on the output concentration of the secondary dynamic dilution module and the sensor signal feedback, further optimize the flow rate of the secondary diluent and dynamically correct the final dilution factor.

[0016] By employing a precise dilution factor optimization strategy, the operating parameters of the primary pre-dilution module and the secondary dynamic dilution module are dynamically adjusted to ensure that the final dilution factor adapts to variations in sample concentration and the limitations of sensor overlap. Dynamic adjustment of the dilution factor enables efficient control of particle concentration within the target range, avoiding problems such as insufficient particle count or significantly prolonged measurement time due to an excessively high dilution factor, while also overcoming the contamination effects of over-dilution. Through real-time acquisition of concentration signals, the algorithm can perform mid-process corrections during dilution, allowing the dilution factor optimization process to quickly converge to the optimal value, thereby significantly improving measurement efficiency and dilution accuracy. The introduction of this algorithm upgrades the dilution system from traditional fixed-factor dilution to an adaptive dynamic adjustment mode, providing a more stable and flexible foundation for particle size analysis.

[0017] Preferably, the formula for the first-stage pre-dilution factor includes:

[0018]

[0019] Where DF1 is the first-stage dilution factor, V1 is the volume of the first-stage dilution chamber, and F... S The sample injection flow rate is given, and t is the unit time.

[0020] The formula for the secondary pre-dilution factor includes:

[0021]

[0022] Wherein, DF2 is the secondary dilution factor, F D diluent flow rate

[0023] The final dilution factor calculation formula includes:

[0024] DF = DF1 × DF2

[0025] The specific formulas used in the dilution factor optimization algorithm provide a clear calculation basis for dynamically adjusting the dilution factor and flow rate, ensuring that the algorithm can achieve real-time optimization of the dilution factor in an efficient and accurate manner. The primary dilution factor formula directly calculates the pre-dilution factor based on the dilution chamber volume and sample injection volume, providing a stable foundation for subsequent dilution steps. The secondary dilution factor formula determines the final dilution effect by fixing the ratio of the diluent flow rate to the sample flow rate, ensuring that the output concentration meets the sensor's measurement requirements. The final dilution factor formula combines the calculation results of the primary and secondary dilution factors, providing clear theoretical support for the dynamic adjustment of the dilution factor. Through these formulas, the accuracy and controllability of the entire dilution process are greatly enhanced, avoiding measurement deviation problems caused by unreasonable dilution factor settings in traditional dilution processes.

[0026] Preferably, the algorithm includes a dynamic particle concentration detection algorithm that uses a CCD high-speed camera and a photoresist sensor to jointly analyze the particle characteristics of the sample, specifically including the following steps:

[0027] S1. Install a CCD probe in the flow channel at the rear end of the secondary dynamic dilution module to acquire particle images;

[0028] S2. Analyze the morphology and material properties of the particles based on the image information obtained by the CCD probe;

[0029] S3. Combine the particle size information output by the photoresist sensor to determine the equivalent sphere diameter of the particle;

[0030] S4. Compare the particle concentration with the sensor's overlap limit. If the limit is exceeded, send an adjustment signal to the feedback control module.

[0031] S5. Dynamically adjust the primary dilution factor or the secondary dilution flow rate to ensure that the particle concentration is within the target range.

[0032] By combining a high-speed CCD camera and a photoresist sensor, the shortcomings of traditional photoresist methods in particle morphology and material identification are overcome, providing more comprehensive and accurate data support for particle size distribution analysis. The high-speed CCD camera can acquire particle image information in real time and accurately analyze particle shape characteristics. Combined with the particle size detection results from the photoresist sensor, the equivalent sphere diameter and actual morphological characteristics of particles can be better assessed. This multi-dimensional particle detection method significantly improves the accuracy of PSD measurement and effectively avoids measurement distortion caused by the complexity of particle shapes. Furthermore, by dynamically monitoring particle concentration and morphological characteristics, the algorithm provides more reliable parameter support for the feedback control module, enabling further optimization of the dilution factor and laying a solid foundation for the intelligent operation of the entire dilution system.

[0033] Preferably, the formula for calculating the equivalent sphere includes:

[0034]

[0035] Where, d eq V is the equivalent sphere diameter of the particle. p The particle volume;

[0036] The formulas for calculating particle concentration include:

[0037]

[0038] Where C is the particle concentration, N is the total number of particles, and V t Total sample volume;

[0039] The formulas for dynamically adjusting signals include:

[0040] ΔDF=k×(CC target )

[0041] Where ΔDF is the adjustment amount of the dilution factor, k is the adjustment coefficient, and C target The target particle concentration.

[0042] The formulas provide specific calculation methods for morphology and concentration analysis, offering a scientific basis for the accurate measurement of particle equivalent sphere diameter and sample concentration. The equivalent sphere diameter formula calculates the effective particle size from the particle volume, enabling the transformation of complex particle shape data into standardized parameters, thereby improving the versatility and accuracy of particle size analysis. The concentration calculation formula combines the total number of particles and the total sample volume, providing a direct quantitative indicator for real-time monitoring of particle concentration during the dilution process. The dynamic adjustment signal formula calculates the adjustment amount of the dilution factor based on the difference between the particle concentration and the target concentration, achieving closed-loop control of the dilution process. Through these formulas, the system can not only accurately assess particle size and concentration but also dynamically adjust dilution parameters, significantly improving the efficiency and accuracy of the dilution system and solving the problem of incomplete particle concentration and morphology detection in existing technologies.

[0043] Preferably, the dilution chamber parallel module includes a multi-dilution chamber parallel control algorithm to realize the alternating use of the first-stage dilution chambers, specifically including the following steps:

[0044] S1. Initialize two sets of primary dilution chambers, labeling them "working chamber" and "standby chamber";

[0045] S2. When the "working chamber" enters the cleaning state, the sample is automatically switched to be injected into the "standby chamber".

[0046] S3. Record the usage status of each dilution chamber and automatically assign cleaning priorities based on usage frequency;

[0047] S4. The feedback control module is used to coordinate the switching process of the dilution chamber to ensure dilution continuity.

[0048] The multi-dilution chamber parallel control algorithm overcomes the limitation of traditional dilution systems that cannot operate continuously during dilution chamber cleaning by adding a backup dilution chamber. The alternating dilution chamber design allows the system to maintain the continuity of the dilution process using a backup dilution chamber while one chamber is being used for cleaning, thus significantly improving testing efficiency and system stability. The algorithm automatically allocates cleaning priorities based on the frequency of dilution chamber use and cleaning requirements, ensuring the rationality and efficiency of dilution chamber switching. The participation of the intelligent feedback control module makes the dilution chamber switching process more precise and seamless, avoiding potential concentration fluctuations or dilution delays during switching. Through the flexible alternation of multiple dilution chambers, the system significantly improves dilution efficiency, adapts to the needs of high-frequency testing scenarios, and provides reliable technical support for industrial applications.

[0049] Preferred,

[0050] The formula for calculating the dilution chamber switching time includes:

[0051]

[0052] Among them, T switch V is the time required for switching dilution chambers. f F represents the volume of the cleaning fluid. f The flow rate of the cleaning fluid;

[0053] The formula for calculating state priority includes:

[0054]

[0055] Among them, P i For dilution chamber priority, T i For the dilution chamber usage time, T t This represents the total running time.

[0056] The formulas in the multi-dilution chamber parallel control algorithm provide specific calculation methods for switching delay and priority allocation, offering theoretical support for efficient switching of dilution chambers. The dilution chamber switching delay formula calculates the cleaning time required by the ratio of cleaning liquid volume to flow rate, providing a basis for optimizing dilution chamber switching plans. The state priority formula calculates priority based on the ratio of dilution chamber usage time to total running time, ensuring that frequently used dilution chambers are cleaned first, effectively improving the efficiency of dilution chamber management. Through these formulas, the dilution system can achieve precise control during dilution chamber switching, avoiding interruptions or efficiency reductions caused by improper switching. Ultimately, this achieves automation and intelligence in dilution chamber management, providing a crucial guarantee for the continuous and stable operation of the dilution system.

[0057] An automated two-step dilution analysis method for high-concentration samples based on intelligent feedback control includes using the aforementioned automated two-step dilution system for high-concentration samples based on intelligent feedback control.

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] By dynamically optimizing the dilution factor, the algorithm solves the problems of inaccurate concentration control and inflexible dilution factor adjustment in the dilution of high-concentration samples. The first-stage pre-dilution module calculates the dilution factor based on the sample injection flow rate and dilution chamber volume, providing a stable foundation for subsequent dilutions. The second-stage dynamic dilution module combines a fixed-flow-rate diluent with a real-time adjusted sample flow rate to precisely control the final dilution factor, ensuring the output sample concentration remains stable within the target range. The algorithm supports dynamic adjustment of sensor overlap limits, effectively avoiding measurement distortion caused by particle overlap, while ensuring that the diluted high-concentration sample meets various detection requirements. Through real-time data acquisition and feedback mechanisms, the algorithm can quickly converge to the optimal dilution factor, significantly improving the efficiency and accuracy of the dilution process, while reducing measurement errors and resource waste caused by improper dilution.

[0060] By combining a high-speed CCD camera with a photoresist sensor, and jointly analyzing particle concentration, morphology, and size distribution, this method overcomes the limitations of existing particle detection technologies in terms of morphology and material identification. The particle size data provided by the photoresist sensor, combined with the morphological features captured by the CCD camera, makes the calculation of the equivalent sphere diameter more accurate, while also improving the precision of PSD measurements. The algorithm dynamically monitors changes in particle concentration and size, identifying and reporting abnormal concentrations and adjusting dilution parameters promptly to avoid measurement distortion caused by particle overlap or uneven particle distribution. Furthermore, the introduction of this algorithm enables the system not only to detect basic particle characteristics but also to perform multi-dimensional analysis of complex particle morphologies, adapting to more complex analysis scenarios and greatly expanding the applicability and detection capabilities of the dilution system.

[0061] By designing a parallel operating mechanism for multiple dilution chambers, the efficiency and stability of the dilution system are significantly improved. Its alternating operation mode allows one chamber to perform a cleaning task while another continues dilution, achieving seamless continuous operation and overcoming the pause issues that occur during cleaning in traditional dilution systems. Through dynamic allocation of dilution chamber usage priorities, the algorithm optimizes cleaning frequency and resource utilization efficiency, avoiding dilution instability caused by overuse or insufficient cleaning. Furthermore, precise control of switching delays ensures minimal concentration fluctuations during chamber switching, maintaining consistent dilution output. This algorithm significantly improves the adaptability of the dilution system in high-frequency, diverse sample testing scenarios while reducing the need for manual intervention, providing strong technical support for large-scale industrial applications. Attached Figure Description

[0062] Figure 1 This is a schematic diagram of the module relationships of an automatic two-step dilution system and analysis method for high-concentration samples based on intelligent feedback control according to the present invention.

[0063] Figure 2 This is a schematic diagram of the piping for an automatic two-step dilution system and analysis method for high-concentration samples based on intelligent feedback control, as described in this invention.

[0064] In the diagram, 1 is the primary pre-dilution module; 2 is the secondary dynamic dilution module; 3 is the sample injection unit; 4 is the diluent supply unit; 5 is the sensing module; 6 is the parallel dilution chamber module; and 7 is the intelligent feedback control module. Detailed Implementation

[0065] An automated two-step dilution system for high-concentration samples based on intelligent feedback control includes: a primary pre-dilution module, a secondary dynamic dilution module, a sensing module, an intelligent feedback control module, and a parallel dilution chamber module. The primary pre-dilution module is equipped with a sample injection unit and a diluent supply unit, and completes primary dilution through the pre-dilution chamber. The primary pre-dilution factor is controlled by adjusting the volume of sample injected into the primary dilution chamber. The diluted sample enters the secondary dynamic dilution module through a flow channel, simultaneously transmitting a real-time concentration signal to the intelligent feedback control module. The secondary dynamic dilution module includes a secondary dilution chamber for receiving the output from the primary dilution module. The sample flow and diluent flow are controlled; the final dilution factor is adjusted through a diluent flow rate fixing unit and a sample flow control unit; the diluted sample is output to the sensing module; the sensing module includes a flow meter, a photoresist sensor, and a CCD high-speed camera, used to acquire particle concentration, particle size distribution, and morphology data; the particle concentration output from the primary and secondary dilution chambers is detected in real time, and the concentration change data and overlap rate are transmitted to the intelligent feedback control module; the CCD camera is located in the flow channel after the secondary dynamic dilution module to supplement particle morphology analysis information; the intelligent feedback control module receives the concentration signal from the sensing module. The system uses particle count rate and PSD data to dynamically adjust the dilution parameters of the primary and secondary dynamic dilution modules via an algorithm. It calculates the dilution factor based on the target concentration and sends control signals to regulate the sample flow rate out of the primary dilution chamber. Simultaneously, it monitors the flow rate of the diluent in the secondary dilution module to ensure the concentration remains stable within the set target range, forming a dynamic and adjustable dilution system. A parallel dilution chamber module, through a dilution chamber switching mechanism, allows one dilution chamber to be used for cleaning while another continues operating, ensuring the continuity of the dilution process. The dilution chamber status is monitored by an intelligent feedback control module, which automatically adjusts the dilution parameters according to priority. Dynamic switching; the diluted sample output from the primary pre-dilution module directly enters the secondary dynamic dilution module through a pipeline, and the diluted concentration signal is fed back to the intelligent feedback control module in real time; the sensing module simultaneously monitors the particle concentration, flow rate, and PSD data during the two-stage dilution process, providing the intelligent feedback control module with a basis for optimizing dilution parameters; the intelligent feedback control module adjusts the parameters of the primary and secondary dynamic dilution modules in real time based on the sensing data to achieve dynamic optimization of the dilution factor; the alternating operation of multiple dilution chamber parallel modules is seamlessly switched through control logic, ensuring that the entire system operates efficiently while avoiding downtime caused by dilution chamber cleaning.

[0066] This invention achieves dynamic and precise dilution of high-concentration samples by introducing a two-step dilution structure combined with an intelligent feedback control module. The primary pre-dilution module and the secondary dynamic dilution module work together to complete the preliminary dilution and precise dilution steps respectively, improving dilution efficiency and solving the problem of simultaneously maintaining concentration stability and flexibly adjusting the dilution factor during a single dilution. The modules work collaboratively through real-time signal transmission, and the particle concentration, size distribution, and morphological characteristics data collected by the sensing module provide strong support for the dynamic optimization of the dilution process. The intelligent feedback control module adjusts the sample flow rate and diluent flow rate parameters in real time, effectively avoiding particle overlap and insufficient dilution. Multiple dilution chambers operating in parallel further enhance the system's efficiency, ensuring the continuity of the dilution process even during cleaning. This system can be widely applied in industrial production environments requiring high-precision particle size analysis, significantly improving testing accuracy and operational efficiency, while addressing the shortcomings of existing technologies in optimizing dilution concentration and efficiency.

[0067] Specifically, it includes a dilution factor optimization algorithm for dynamically adjusting the dilution factor of the primary pre-dilution module and the diluent flow rate of the secondary dynamic dilution module, specifically including the following steps:

[0068] S1. Initialize the system, preset the volume of the primary dilution chamber, the flow rate of the secondary dilution solution, and the overlap limit of the sensors;

[0069] S2. Collect the sample injection flow rate of the primary pre-dilution module and calculate the current pre-dilution factor based on the volume of the dilution chamber;

[0070] S3. Use the sensor module to detect the particle concentration after the first dilution in real time and determine whether it meets the input concentration requirements of the second dynamic dilution module; if not, adjust the sample injection flow rate and update the first dilution factor.

[0071] S4. Based on the output concentration of the secondary dynamic dilution module and the sensor signal feedback, further optimize the flow rate of the secondary diluent and dynamically correct the final dilution factor.

[0072] By employing a precise dilution factor optimization strategy, the operating parameters of the primary pre-dilution module and the secondary dynamic dilution module are dynamically adjusted to ensure that the final dilution factor adapts to variations in sample concentration and the limitations of sensor overlap. Dynamic adjustment of the dilution factor enables efficient control of particle concentration within the target range, avoiding problems such as insufficient particle count or significantly prolonged measurement time due to an excessively high dilution factor, while also overcoming the contamination effects of over-dilution. Through real-time acquisition of concentration signals, the algorithm can perform mid-process corrections during dilution, allowing the dilution factor optimization process to quickly converge to the optimal value, thereby significantly improving measurement efficiency and dilution accuracy. The introduction of this algorithm upgrades the dilution system from traditional fixed-factor dilution to an adaptive dynamic adjustment mode, providing a more stable and flexible foundation for particle size analysis.

[0073] Specifically, the formula for the first-stage pre-dilution factor includes:

[0074]

[0075] Where DF1 is the first-stage dilution factor, V1 is the volume of the first-stage dilution chamber, and F... S The sample injection flow rate is given, and t is the unit time.

[0076] The formula for the secondary pre-dilution factor includes:

[0077]

[0078] Wherein, DF2 is the secondary dilution factor, F D diluent flow rate

[0079] The final dilution factor calculation formula includes:

[0080] DF = DF1 × DF2

[0081] The specific formulas used in the dilution factor optimization algorithm provide a clear calculation basis for dynamically adjusting the dilution factor and flow rate, ensuring that the algorithm can achieve real-time optimization of the dilution factor in an efficient and accurate manner. The primary dilution factor formula directly calculates the pre-dilution factor based on the dilution chamber volume and sample injection flow rate, providing a stable foundation for subsequent dilution steps. The secondary dilution factor formula determines the final dilution effect by fixing the ratio of the diluent flow rate to the sample flow rate, ensuring that the output concentration meets the sensor's measurement requirements. The final dilution factor formula combines the calculation results of the primary and secondary dilution factors, providing clear theoretical support for the dynamic adjustment of the dilution factor. Through these formulas, the accuracy and controllability of the entire dilution process are greatly enhanced, avoiding measurement deviation problems caused by unreasonable dilution factor settings in traditional dilution processes.

[0082] In practical use, the sample is injected into the dilution chamber at a specific flow rate through the injection unit of the primary dilution module, while the diluent enters the dilution chamber at a specific flow rate through the diluent supply unit, mixing with the sample to complete the initial dilution. The volume of the dilution chamber is fixed by design, providing a basis for the primary dilution factor. Flow meters and dilution chamber volume sensors are used to monitor the flow rate and chamber volume in real time.

[0083] Calculate the first dilution factor using the formula.

[0084] V1 provides a physical constraint by fixing the volume of the dilution chamber.

[0085] F S The sample injection flow rate is dynamically adjusted to optimize the dilution factor.

[0086] T represents the flow rate per unit time, ensuring calculation accuracy.

[0087] The sample injection flow rate FSF_SFS is dynamically adjusted through the feedback module to maintain a reasonable first-stage dilution factor.

[0088] In the secondary dynamic dilution module, the diluent is injected at a fixed flow rate of 60-120 ml / min, and the sample flow rate F output from the primary dilution is... S Mix with it to complete the secondary dilution. Calculate the secondary dilution factor using a formula. The final dilution factor serves to dynamically adjust the sample flow rate of the primary module, ensuring that the output sample concentration meets the sensor's overlap limit.

[0089] The primary formula calculates the dilution factor based on the flow rate ratio and volume relationship within the dilution chamber. The secondary formula provides precise concentration control using the flow rate ratio of the diluent and the sample. The final factor optimizes the dilution effect, ensuring concentration suitability for the sample during detection.

[0090] Specifically, this includes a dynamic particle concentration detection algorithm that utilizes a CCD high-speed camera and a photoresist sensor to jointly analyze sample particle characteristics, specifically including the following steps:

[0091] S1. Install a CCD probe in the flow channel at the rear end of the secondary dynamic dilution module to acquire particle images;

[0092] S2. Analyze the morphology and material properties of the particles based on the image information obtained by the CCD probe;

[0093] S3. Combine the particle size information output by the photoresist sensor to determine the equivalent sphere diameter of the particle;

[0094] S4. Compare the particle concentration with the sensor's overlap limit. If the limit is exceeded, send an adjustment signal to the feedback control module.

[0095] S5. Dynamically adjust the primary dilution factor or the secondary dilution flow rate to ensure that the particle concentration is within the target range.

[0096] By combining a high-speed CCD camera and a photoresist sensor, the shortcomings of traditional photoresist methods in particle morphology and material identification are overcome, providing more comprehensive and accurate data support for particle size distribution analysis. The high-speed CCD camera can acquire particle image information in real time and accurately analyze particle shape characteristics. Combined with the particle size detection results from the photoresist sensor, the equivalent sphere diameter and actual morphological characteristics of particles can be better assessed. This multi-dimensional particle detection method significantly improves the accuracy of PSD measurement and effectively avoids measurement distortion caused by the complexity of particle shapes. Furthermore, by dynamically monitoring particle concentration and morphological characteristics, the algorithm provides more reliable parameter support for the feedback control module, enabling further optimization of the dilution factor and laying a solid foundation for the intelligent operation of the entire dilution system.

[0097] Specifically, the formula for calculating the equivalent sphere includes:

[0098]

[0099] Where, d eq V is the equivalent sphere diameter of the particle. p The particle volume;

[0100] The formulas for calculating particle concentration include:

[0101]

[0102] Where C is the particle concentration, N is the total number of particles, and V t Total sample volume;

[0103] The formulas for dynamically adjusting signals include:

[0104] ΔDF=k×(CC target )

[0105] Where ΔDF is the adjustment amount of the dilution factor, k is the adjustment coefficient, and C target The target particle concentration.

[0106] The formulas provide specific calculation methods for morphology and concentration analysis, offering a scientific basis for the accurate measurement of particle equivalent sphere diameter and sample concentration. The equivalent sphere diameter formula calculates the effective particle size from the particle volume, enabling the transformation of complex particle shape data into standardized parameters, thereby improving the versatility and accuracy of particle size analysis. The concentration calculation formula combines the total number of particles and the total sample volume, providing a direct quantitative indicator for real-time monitoring of particle concentration during the dilution process. The dynamic adjustment signal formula calculates the adjustment amount of the dilution factor based on the difference between the particle concentration and the target concentration, achieving closed-loop control of the dilution process. Through these formulas, the system can not only accurately assess particle size and concentration but also dynamically adjust dilution parameters, significantly improving the efficiency and accuracy of the dilution system and solving the problem of incomplete particle concentration and morphology detection in existing technologies.

[0107] In practical use

[0108] A photoresist sensor is used to monitor the light-blocking signal of particles as they pass through the sensing area in real time, thereby obtaining the equivalent diameter of the particles. The sensor's light source emits laser light, and the changes in light intensity are monitored. The equivalent spherical diameter of the particles is then calculated using a formula.

[0109] A CCD high-speed camera captures real-time images of particles passing through the flow channel, extracts particle morphology information, and supplements the shape defects of the photoresist method. The camera transmits the images to the processing unit, identifies the shape features of the particles (e.g., circular, elliptical, etc.), and matches them with the particle equivalent diameter data calculated by the photoresist method.

[0110] The particle concentration is calculated using a formula, where N is the number of particles counted jointly by a photoresist sensor and a CCD camera. V t The sample volume sensor records the outflow data from the dilution chamber. The concentration data is fed back to the intelligent control module, which will send a signal to adjust the dilution factor if the sensor overlap limit is exceeded.

[0111] The optical obscuration method combined with a CCD camera integrates particle morphology and concentration data, overcoming the shortcomings of single detection techniques and significantly improving the comprehensiveness and accuracy of particle detection.

[0112] Specifically, the dilution chamber parallel module includes a multi-dilution chamber parallel control algorithm to realize the alternating use of the first-stage dilution chambers, which specifically includes the following steps:

[0113] S1. Initialize two sets of primary dilution chambers, labeling them "working chamber" and "standby chamber";

[0114] S2. When the "working chamber" enters the cleaning state, the sample is automatically switched to be injected into the "standby chamber".

[0115] S3. Record the usage status of each dilution chamber and automatically assign cleaning priorities based on usage frequency;

[0116] S4. The feedback control module is used to coordinate the switching process of the dilution chamber to ensure dilution continuity.

[0117] The multi-dilution chamber parallel control algorithm overcomes the limitation of traditional dilution systems that cannot operate continuously during dilution chamber cleaning by adding a backup dilution chamber. The alternating dilution chamber design allows the system to maintain the continuity of the dilution process using a backup dilution chamber while one chamber is being used for cleaning, thus significantly improving testing efficiency and system stability. The algorithm automatically allocates cleaning priorities based on the frequency of dilution chamber use and cleaning requirements, ensuring the rationality and efficiency of dilution chamber switching. The participation of the intelligent feedback control module makes the dilution chamber switching process more precise and seamless, avoiding potential concentration fluctuations or dilution delays during switching. Through the flexible alternation of multiple dilution chambers, the system significantly improves dilution efficiency, adapts to the needs of high-frequency testing scenarios, and provides reliable technical support for industrial applications.

[0118] Specifically,

[0119] The formula for calculating the dilution chamber switching time includes:

[0120]

[0121] Among them, T switch V is the time required for switching dilution chambers. f F represents the volume of the cleaning fluid. f The flow rate of the cleaning fluid;

[0122] The formula for calculating state priority includes:

[0123]

[0124] Among them, P i For dilution chamber priority, T i For the dilution chamber usage time, T t This represents the total running time.

[0125] The formulas in the multi-dilution chamber parallel control algorithm provide specific calculation methods for switching delay and priority allocation, offering theoretical support for efficient switching of dilution chambers. The dilution chamber switching delay formula calculates the cleaning time required by the ratio of cleaning liquid volume to flow rate, providing a basis for optimizing dilution chamber switching plans. The state priority formula calculates priority based on the ratio of dilution chamber usage time to total running time, ensuring that frequently used dilution chambers are cleaned first, effectively improving the efficiency of dilution chamber management. Through these formulas, the dilution system can achieve precise control during dilution chamber switching, avoiding interruptions or efficiency reductions caused by improper switching. Ultimately, this achieves automation and intelligence in dilution chamber management, providing a crucial guarantee for the continuous and stable operation of the dilution system.

[0126] Two dilution chambers were configured, labeled "Working Chamber" and "Backup Chamber," respectively. The working chamber was used for diluting the current sample, while the backup chamber was cleaned and ready for use. Samples were injected into and guided to the available dilution chamber via a flow channel switching valve. A flow meter monitored the sample flow rate to ensure concentration stability during the switching process. The usage time T for each dilution chamber was recorded. i and cleaning time T f The priority of each cavity is calculated using a formula, and the dilution cavity used for high frequency is cleaned first.

[0127] Ti represents the cumulative usage time of the current dilution chamber, reflecting the usage frequency.

[0128] Priority data is used for the automatic switching logic of the dilution chamber to optimize the efficiency of alternating operation of the dilution chamber.

[0129] By combining the switching delay formula, the cleaning time of the dilution chamber is calculated to ensure that the system dilution process is uninterrupted during switching. The cleaning time and priority directly guide the operation of the switching control valve, ensuring the continuity and stability of sample dilution.

[0130] Priority formulas and switching delay formulas provide quantitative indicators for dilution chamber management. The cleaning and switching logic achieves optimal decision-making through data-driven approaches, avoiding uncertainties caused by manual intervention, while ensuring the efficiency and stability of system operation.

[0131] An automated two-step dilution analysis method for high-concentration samples based on intelligent feedback control includes using the aforementioned automated two-step dilution system for high-concentration samples based on intelligent feedback control.

Claims

1. An automated two-step dilution system for high-concentration samples based on intelligent feedback control, characterized in that, include: The system consists of a primary pre-dilution module, a secondary dynamic dilution module, a sensing module, an intelligent feedback control module, and a parallel dilution chamber module. The primary pre-dilution module is equipped with a sample injection unit and a diluent supply unit, and completes primary dilution through the primary dilution chamber; the primary dilution factor is controlled by adjusting the volume of sample injected into the primary dilution chamber; the diluted sample enters the secondary dynamic dilution module through the flow channel, and at the same time transmits the real-time concentration signal to the intelligent feedback control module; The secondary dynamic dilution module includes a secondary dilution chamber for receiving the sample stream and diluent stream output from the primary dilution module; adjusting the final dilution factor through a diluent fixed flow rate unit and a sample flow control unit; and outputting the diluted sample to the sensing module. The sensing module includes a flow meter, a photoresist sensor, and a CCD high-speed camera, used to collect particle concentration, particle size distribution, and morphology data; to detect the particle concentration output from the primary dilution chamber and the secondary dilution chamber in real time, and to transmit the concentration change data and overlap rate to the intelligent feedback control module; the CCD high-speed camera is located in the flow channel after the secondary dynamic dilution module, used to supplement particle morphology analysis information; The intelligent feedback control module receives concentration signals, particle count rates, and PSD data from the sensing module, and dynamically adjusts the dilution parameters of the primary and secondary dynamic dilution modules through an algorithm; it calculates the dilution factor based on the target dilution concentration and sends control signals to adjust the speed at which the sample flows out of the primary dilution chamber; at the same time, it monitors the flow rate of the diluent in the secondary dilution module to ensure that the concentration remains stable within the set target range, thus forming a dynamic and adjustable dilution system. The parallel dilution chamber module, through a dilution chamber switching mechanism, ensures the continuity of the dilution process by allowing one set of dilution chambers to operate while another set continues to work; the status of the dilution chambers is monitored by the intelligent feedback control module and automatically switched according to priority. The diluted sample output from the primary pre-dilution module enters the secondary dynamic dilution module directly through a pipeline, and the concentration signal after dilution is fed back to the intelligent feedback control module in real time. The sensing module simultaneously monitors particle concentration, flow rate, and PSD data during the two-stage dilution process, providing a basis for the intelligent feedback control module to optimize dilution parameters. The intelligent feedback control module adjusts the parameters of the primary and secondary dynamic dilution modules in real time based on sensor data to achieve dynamic optimization of the dilution factor; The parallel operation of multiple dilution chamber modules is seamlessly switched through control logic, ensuring that the entire system operates efficiently while avoiding the waste of sample detection time caused by dilution chamber cleaning, which can greatly improve sample detection efficiency. This includes a dilution factor optimization algorithm for dynamically adjusting the dilution factor of the primary pre-dilution module and the diluent flow rate of the secondary dynamic dilution module. Specifically, it includes the following steps: S1. Initialize the system, preset the volume of the primary dilution chamber, the flow rate of the secondary diluent, and the overlap limit of the photoresist sensor; S2. Collect the sample injection flow rate of the primary pre-dilution module and calculate the current pre-dilution factor based on the volume of the dilution chamber; S3. Use the sensor module to detect the particle concentration after the first dilution in real time and determine whether it meets the input concentration requirements of the second dynamic dilution module; if not, adjust the sample injection flow rate and update the first dilution factor. S4. Based on the output concentration of the secondary dynamic dilution module and the signal feedback from the photoresist sensor, further optimize the flow rate of the secondary diluent and dynamically correct the final dilution factor. The formula for the first-stage pre-dilution factor includes: Where DF1 is the first-stage dilution factor, V1 is the volume of the first-stage dilution chamber, and F... S The sample injection flow rate is given, and t is the unit time. The formula for the secondary pre-dilution factor includes: Wherein, DF2 is the secondary dilution factor, F D The flow rate of the diluent; The final dilution factor calculation formula includes: DF = DF1 × DF2 This includes a dynamic particle concentration detection algorithm that utilizes a CCD high-speed camera and a photoresist sensor to jointly analyze sample particle characteristics. Specifically, it includes the following steps: S1. Install a CCD high-speed camera in the flow channel at the rear of the secondary dynamic dilution module to acquire particle images; S2. Analyze the morphology and material properties of the particles based on the image information obtained by the CCD high-speed camera; S3. Combine the particle size information output by the photoresist sensor to determine the equivalent sphere diameter of the particle; S4. Compare the particle concentration with the limit of overlap of the photoresist sensor. If the limit is exceeded, send an adjustment signal to the feedback control module. S5. Dynamically adjust the primary dilution factor or the flow rate of the secondary diluent to ensure that the particle concentration is within the target range; The formula for calculating the equivalent sphere diameter includes: Where, d eq V is the equivalent sphere diameter of the particle. p Particle volume; The formulas for calculating particle concentration include: Where C is the particle concentration, N is the total number of particles, and V t This refers to the total volume of the sample. The formulas for dynamically adjusting signals include: ΔDF=k×(C−C target ) Where ΔDF is the adjustment amount of the dilution factor, k is the adjustment coefficient, and C target The target particle concentration.

2. The automatic two-step dilution system for high-concentration samples based on intelligent feedback control according to claim 1, characterized in that, The dilution chamber parallel module includes a multi-dilution chamber parallel control algorithm to realize the alternating use of the first-stage dilution chambers, specifically including the following steps: S1. Initialize two sets of primary dilution chambers, labeled as "working chamber" and "standby chamber"; S2. When the "working chamber" enters the cleaning state, the sample is automatically switched to be injected into the "standby chamber". S3. Record the usage status of each dilution chamber and automatically assign cleaning priorities based on usage frequency; S4. The feedback control module is used to coordinate the switching process of the dilution chamber to ensure dilution continuity.

3. The automatic two-step dilution system for high-concentration samples based on intelligent feedback control according to claim 2, characterized in that, The formula for calculating the dilution chamber switching time includes: Among them, T switch V is the time required for switching dilution chambers. f F represents the volume of the cleaning fluid. f The flow rate of the cleaning fluid; The formula for calculating state priority includes: Among them, P i For dilution chamber priority, T i For the dilution chamber usage time, T t This represents the total running time.

4. An automated two-step dilution analysis method for high-concentration samples based on intelligent feedback control, characterized in that, This includes using the automated two-step dilution system for high-concentration samples based on intelligent feedback control as described in any one of claims 1-3.

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