Automatic experimental sample processing and collecting system of high-speed centrifugal machine

Abstract

The invention relates to the field of centrifugal machines, in particular to an automatic experimental sample processing and collecting system of a high-speed centrifugal machine, which comprises an automatic mechanical arm module, a centrifugal machine, a centrifugal machine main control module, a spectrum detection module, a sample layering and collecting module and a sample storage module, the spectrum detection module is used for detecting the spectrum of the processed sample and obtaining a density parameter distribution curve of the processed sample according to the spectrum, and the sample layering collection module is used for conducting layering collection on the processed sample according to the detection result of the spectrum detection module and obtaining a layered sample. And the sample storage module is used for storing the layered samples. According to the scheme, by introducing the spectrum detection module and the density parameter distribution curve, the density change can be detected under the condition of not damaging the sample, the layered interface position of the sample is accurately identified, and the layered detection sensitivity and accuracy are improved.

Description

Technical Field

[0001] This invention relates to the field of centrifuges, and more particularly to an automated experimental sample processing and collection system for high-speed centrifuges. Background Technology

[0002] High-speed centrifuges are key devices that utilize the centrifugal force generated by high-speed rotation to separate, concentrate, and purify substances of different densities and sizes. They are widely used in numerous fields, including biomedicine, molecular biology, clinical testing, pharmaceuticals, chemical engineering, and environmental science. For example, in biomedical research, they are used to separate cells, subcellular organelles (such as mitochondria and the cell nucleus), viruses, and purify proteins and nucleic acids. In clinical diagnostics, they are used to separate serum and plasma from blood, or to precipitate formed elements from urine, providing high-quality samples for subsequent biochemical analysis, immunoassay, and gene testing.

[0003] For example, prior art CN118807871A discloses an integrated automated sample processing and chromatography-mass spectrometry testing device. Its sample tube working area includes a movable sample tube support mechanism and a rotatable gripper for positioning and gripping each sample tube. Its sample processing area, equipped with a second robotic arm, includes a high-speed centrifuge, a transfer rack for transferring centrifuge tubes between areas, and a centrifuge tube cap opening / closing and mixing module for adding reagents and applying vortex mixing. Its processing area, equipped with a third robotic arm, includes a nitrogen blowing module, an injection module for transferring reagents from centrifuge tubes and injecting them into the downstream chromatography module for detection, and a centrifuge tube cap opening / closing and mixing module. This device encompasses pipetting, vortex mixing, high-speed centrifugation, isothermal nitrogen blowing, and online capture functions, covering current chromatographic and mass spectrometric sample processing methods through different functional combinations. Simultaneously, multi-channel chromatographic separation is set up in the downstream chromatography section to maximize detector utilization.

[0004] In the prior art, the accuracy of stratification of centrifuged samples is low. In order to solve the common problem in this field, the present invention was made. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of current systems by proposing an automated experimental sample processing and acquisition system for high-speed centrifuges.

[0006] To overcome the shortcomings of the prior art, the present invention adopts the following technical solution: An automated experimental sample processing and acquisition system for a high-speed centrifuge includes an automated robotic arm module, a centrifuge, a centrifuge main control module, a spectral detection module, a sample stratification acquisition module, and a sample storage module. The automated robotic arm module is used to automatically perform sample tube picking and placing actions according to set instructions, placing sample tubes into or removing sample tubes from the centrifuge. The sample tubes contain samples. The centrifuge is used to process the samples and obtain processed samples. The centrifuge main control module is used to control the centrifuge and detect various parameters of the centrifuge. The spectral detection module is used to detect the spectrum of the processed samples and obtain the density parameter distribution curve of the processed samples based on the spectrum. The sample stratification acquisition module is used to perform stratified acquisition of the processed samples based on the detection results of the spectral detection module and obtain stratified samples. The sample storage module is used to store the stratified samples.

[0007] Furthermore, the automated robotic arm module includes a robotic arm body, a multi-joint drive unit, and a clamping end. The multi-joint drive unit and the clamping end are disposed on the robotic arm body. The multi-joint drive unit is used to adjust and control various parts of the robotic arm body according to set instructions. The clamping end is used to clamp the sample tube and pick up and put down the sample through the sample tube.

[0008] Furthermore, the centrifuge main control module includes a program storage unit, a control unit, and a detection unit. The program storage unit is used to store various programs for controlling the centrifuge. The control unit is used to control the centrifuge according to the programs stored in the program storage unit. The detection unit is used to detect various parameters of the centrifuge operation in real time.

[0009] Furthermore, the spectral detection module includes a light source emitting unit, a spectral receiving unit, and a light density conversion unit. The light source emitting unit is used to emit light signals of different wavelengths to illuminate the processed sample in the sample tube. The spectral receiving unit is used to receive the transmitted light signal passing through the processed sample. The light density conversion unit is used to convert the acquired spectral information into density parameter information.

[0010] Furthermore, the sample stratification acquisition module includes an acquisition needle unit, a driving unit, and a delivery unit. The acquisition needle unit is used to acquire the processed sample after separation by centrifugation. The driving unit is used to control the acquisition needle unit to acquire processed samples of different strata and obtain stratified samples based on the density information obtained by the light source emission unit. The delivery unit is used to deliver the stratified samples to the sample processing module.

[0011] Furthermore, the sample storage module includes a sample identification and encoding unit and a partitioned sample storage bin. The sample identification and encoding unit is used to automatically generate corresponding sample identifiers and mark the partitioned samples according to the sample type before processing and the size relationship of the density parameters of each layered sample. The partitioned sample storage bin is used to store different layered samples in different areas according to the marking results.

[0012] Furthermore, the system's workflow includes the following steps: S1, The automated robotic arm module places the sample tube into the centrifuge; S2, The centrifuge processes the sample and obtains the processed sample; S3, the centrifuge main control module controls the centrifuge and detects various parameters of the centrifuge; S4, the spectral detection module detects the spectrum of the processed sample and obtains the density parameter distribution curve of the processed sample based on the spectrum; S5, the sample stratification acquisition module performs stratified acquisition on the processed sample according to the detection results of the spectral detection module and obtains the stratified sample; S6, The sample storage module stores the stratified samples. The beneficial effects achieved by this invention are as follows: 1. By introducing a spectral detection module and a density parameter distribution curve calculation formula, and through the coupling relationship between the spectral signal and the density spectral coupling factor, combined with temperature, viscosity, and conductivity control factors, multi-dimensional correction is achieved. This design can detect density changes without damaging the sample, accurately identify the layering interface position of the sample, and improve the sensitivity and accuracy of layering detection. Attached Figure Description

[0013] The invention will be further understood from the following description taken in conjunction with the accompanying drawings. The components in the drawings are not necessarily drawn to scale, but rather the emphasis is on illustrating the principles of the embodiments. In different views, the same reference numerals designate the same parts.

[0014] Figure 1 This is a schematic diagram of the structure of the present invention.

[0015] Figure 2 This is a flowchart of the process of the present invention.

[0016] Figure 3 This is a graph showing the relationship between conductivity and conductivity control factor in this invention.

[0017] Figure 4 This is a comparison chart showing the effects of the present invention and existing manual observation methods. Detailed Implementation

[0018] The following specific embodiments illustrate the implementation of the present invention. Those skilled in the art can understand the advantages and effects of the present invention from the content disclosed in this specification. The present invention can be implemented or applied through other different specific embodiments, and various details in this specification can also be modified and changed based on different viewpoints and applications without departing from the spirit of the present invention. Furthermore, the accompanying drawings of the present invention are for simple illustrative purposes only and are not depictions of actual dimensions; this is stated beforehand. The following embodiments will further describe the relevant technical content of the present invention in detail, but the disclosed content is not intended to limit the scope of protection of the present invention.

[0019] Example 1: According to Figure 1 , Figure 2 and Figure 3 This embodiment provides an automated experimental sample processing and acquisition system for a high-speed centrifuge, including an automated robotic arm module, a centrifuge, a centrifuge main control module, a spectral detection module, a sample stratification acquisition module, and a sample storage module. The automated robotic arm module is used to automatically complete the picking and placing of sample tubes according to set instructions, placing sample tubes into or removing sample tubes from the centrifuge. The sample tubes contain samples. The centrifuge is used to process the samples and obtain processed samples. The centrifuge main control module is used to control the centrifuge and detect various parameters of the centrifuge. The spectral detection module is used to detect the spectrum of the processed samples and obtain the density parameter distribution curve of the processed samples based on the spectrum. The sample stratification acquisition module is used to perform stratified acquisition of the processed samples according to the detection results of the spectral detection module and obtain stratified samples. The sample storage module is used to store the stratified samples.

[0020] Furthermore, the automated robotic arm module includes a robotic arm body, a multi-joint drive unit, and a clamping end. The multi-joint drive unit and the clamping end are disposed on the robotic arm body. The multi-joint drive unit is used to adjust and control various parts of the robotic arm body according to set instructions. The clamping end is used to clamp the sample tube and pick up and put down the sample through the sample tube.

[0021] Specifically, the setting instructions are pre-set by those skilled in the art and stored in the control platform, which is used to control the automated robotic arm module.

[0022] Specifically, the clamping section is also used to add tracer particles into the sample tube. The tracer particles can be inert fluorescent microspheres, and the tracer particles are used to assist in detecting the sample concentration in the sample tube.

[0023] Furthermore, the centrifuge main control module includes a program storage unit, a control unit, and a detection unit. The program storage unit is used to store various programs for controlling the centrifuge. The control unit is used to control the centrifuge according to the programs stored in the program storage unit. The detection unit is used to detect various parameters of the centrifuge operation in real time.

[0024] Specifically, the program storage unit stores, but is not limited to, programs for controlling centrifugation speed, centrifugation time, and centrifugation temperature; the detection data of the detection unit includes, but is not limited to, speed, temperature, and moment of inertia.

[0025] Furthermore, the spectral detection module includes a light source emitting unit, a spectral receiving unit, and a light density conversion unit. The light source emitting unit is used to emit light signals of different wavelengths to illuminate the processed sample in the sample tube. The spectral receiving unit is used to receive the transmitted light signal passing through the processed sample. The light density conversion unit is used to convert the acquired spectral information into density parameter information.

[0026] Specifically, the spectrum needs to be filtered before it is received to prevent tracer particles from affecting the spectral detection results.

[0027] Furthermore, the sample stratification acquisition module includes an acquisition needle unit, a driving unit, and a delivery unit. The acquisition needle unit is used to acquire the processed sample after separation by centrifugation. The driving unit is used to control the acquisition needle unit to acquire processed samples of different strata and obtain stratified samples based on the density information obtained by the light source emission unit. The delivery unit is used to deliver the stratified samples to the sample processing module.

[0028] Furthermore, the sample storage module includes a sample identification and encoding unit and a partitioned sample storage bin. The sample identification and encoding unit is used to automatically generate corresponding sample identifiers and mark the partitioned samples according to the sample type before processing and the size relationship of the density parameters of each layered sample. The partitioned sample storage bin is used to store different layered samples in different areas according to the marking results.

[0029] Specifically, the density parameter is related to but not equal to density. The density parameter distribution curve is only used to obtain the density change trend and the relative size of the density. Based on the sample type before processing, the sample type and corresponding density of each stratified sample that should be included in the stratification can be obtained. By comparing the size relationship between the density of each stratified sample and the size relationship between its density parameters, the type of stratified sample corresponding to each density parameter can be obtained.

[0030] Furthermore, the system's workflow includes the following steps: S1, The automated robotic arm module places the sample tube into the centrifuge; S2, The centrifuge processes the sample and obtains the processed sample; S3, the centrifuge main control module controls the centrifuge and detects various parameters of the centrifuge; S4, the spectral detection module detects the spectrum of the processed sample and obtains the density parameter distribution curve of the processed sample based on the spectrum; Specifically, the density parameter distribution curve can be obtained using the following formula: in, This is a sample density parameter function at height z of the sample tube. The density parameter characterizes the density relationship between samples at different heights, rather than representing the actual density of the samples. This is the conductivity control factor at height z, used to eliminate the influence of added tracer particles on the sample conductivity. The method for obtaining this factor has been given in formula form above. The heat flux control factor at height z is given above in formula form. This factor is used to control the detected spectral intensity based on the sample temperature and viscosity. A is the number of wavelength types of light waves used by the light source emitting unit. This is the density spectral modulation factor for the a-th wavelength light at height z of the processed sample, used to adjust the density spectral coupling factor. The density at different heights of the processed sample was amplified. The density-spectral coupling factor of the unprocessed sample to light of wavelength a is given. This factor can be obtained by consulting past experimental results based on the sample type. The density-spectral coupling factor characterizes the ratio of the density of the unprocessed sample to the spectral intensity obtained by illuminating the unprocessed sample with light of wavelength a. This ratio can be obtained experimentally. The total height of the sample. The intensity of the light of wavelength a is detected at height z of the sample tube. Specifically, through settings This is beneficial for scaling the density at different heights of the processed sample based on the height z, thus expanding the range of different heights. The differences between them are used to improve the sensitivity of stratification and the accuracy of stratification results; e is the natural constant. To obtain the sample reference temperature value when the density spectral coupling factor is obtained experimentally, The sample viscosity was obtained experimentally when the density spectral coupling factor was being measured, and T was the average temperature of the treated sample. This represents the viscosity value at height z of the processed sample. The diffusion coefficient can be calculated by photographing the Brownian motion of the tracer particle at height z, and then substituted into the Stokes-Einstein relation. The formula for calculating the diffusion coefficient and the Stokes-Einstein relation are existing technologies and will not be elaborated upon here. This is an empirical coefficient for temperature. This is an empirical coefficient for viscosity. The empirical coefficient can be set by those skilled in the art between 0 and 1 based on the rate of change of the spectral intensity difference of the untreated sample with the temperature difference and the rate of change of the spectral intensity difference with the viscosity difference obtained from the experiment. The larger the rate of change, the larger the corresponding empirical coefficient. By setting a heat flow control factor, it is beneficial to consider the spectral changes under different temperatures and viscosities to control the density parameter. By considering the influence of temperature and viscosity on the spectrum, it is beneficial to reduce errors and improve the accuracy of the stratification results. At the same time, by introducing tracer particles, non-contact viscosity detection can be achieved, which avoids sample damage caused by disturbance of the processed sample in the general detection method compared with the contact viscosity detection method. This is an empirical coefficient for conductivity. This empirical coefficient can be set by someone skilled in the art based on the rate of change of the spectral intensity difference of the untreated sample with respect to conductivity, obtained experimentally. The larger the rate of change, the larger the corresponding empirical coefficient. The conductivity detected at height z of the processed sample. The average conductivity of the sample before the addition of the tracer factor is calculated by introducing a conductivity control factor. This factor takes into account the conductivity deviation (resulting in a decrease in conductivity) and the corresponding spectral deviation caused by the introduction of tracer particles to detect viscosity. This helps to reduce the error in the final calculation result and improve the accuracy of the calculation result. The conductivity can be obtained by winding several sets of ring-shaped sensing electrodes around the sample tube.

[0031] like Figure 3 As shown, Figure 3 Assuming the conductivity of the sample before treatment It is 1000 uS / cm. The graph shows the relationship between the conductivity detected at height z of the processed sample and the conductivity control factor at height z when the value is 0.1.

[0032] Specifically, The points where the density parameter changes abruptly are the boundary points of each part of the processed sample. The processed sample can be stratified by using the points where the density parameter changes abruptly.

[0033] S5, the sample stratification acquisition module performs stratified acquisition on the processed sample according to the detection results of the spectral detection module and obtains the stratified sample; S6, the sample storage module stores the stratified samples.

[0034] The beneficial effects of this scheme are as follows: 1. By introducing a spectral detection module and a density parameter distribution curve calculation formula, and through the coupling relationship between the spectral signal and the density spectrum coupling factor, combined with temperature, viscosity, and conductivity control factors, multi-dimensional correction is achieved. This design can detect density changes without damaging the sample, accurately identify the location of the sample's layering interface, and improve the sensitivity and accuracy of layering detection.

[0035] 2. By introducing tracer particles, non-contact viscosity detection can be achieved, avoiding sample damage caused by disturbance of the processed sample in contact viscosity detection methods. By introducing a conductivity control factor, the conductivity deviation and corresponding spectral deviation caused by introducing tracer particles to detect viscosity are taken into account, which helps to improve the accuracy of the calculation results.

[0036] Example 2: This example should be understood as including all the features of any of the foregoing examples, and further improving upon them. It also includes a method for calculating the density parameter distribution curve based on the spectral momentum compensation factor. To implement this method, the spectral detection module further includes a wave vector detection unit and a spectral compensation factor calculation unit. The wave vector detection unit is coaxially arranged with the laser light path emitted by the laser emission unit. The wave vector detection unit is used to detect the phase difference of light after propagation in the sample. The wave vector detection unit can be a fiber-coupled coherent interferometer probe or a fiber-coupled interferometric Mach-Zehnder / Michelson micro probe. The spectral compensation factor calculation unit is used to calculate the spectral compensation factor of the processed sample for light of different wavelengths. Specifically, the spectral compensation factor calculation unit calculates it according to the following formula: The corrected sample density parameter is calculated using the following formula: in, To correct the sample density parameter function at height z of the sample tube, the density parameter is used to characterize the density relationship between samples at different heights, rather than representing the actual density of the samples. The result can be obtained using the formula proposed in Example 1. This is the sample density parameter function at height z of the corrected sample tube. As the spectral compensation factor, The number of wavelength types of light waves used by the light source emitting unit. Let be the wave vector length of the light of wavelength a at height z of the processed sample. Let be the reference wave vector length of light of wavelength a. The reference wave vector length can be the wave vector length of light of wavelength a in the reference medium. The wave vector length can be obtained through existing methods such as interferometry, Bragg scattering / diffraction angle measurement, etc. The reference medium can be set by those skilled in the art according to actual needs. The selected reference medium will not affect the final calculation result (through...). accomplish), Let be the modulation coefficient of light at wavelength a. This modulation coefficient can be obtained experimentally by those skilled in the art. Through experiments, the spectral intensity difference corresponding to different ratios of wave vector length to reference wave vector length at the same wavelength can be obtained. This is used to characterize the influence of the ratio of wave vector length to reference wave vector length on the spectral intensity difference; this influence can be obtained by fitting experimental data. Let be the phase detected at height z of the processed sample for light of wavelength a. To ensure and Given the same effective optical path length, the phase detected by light of wavelength a in the reference medium. for The corresponding optical path length can be the product of the length of the light propagation path and the refractive index of the propagation path.

[0037] The scheme in Example 1 may have the following two problems leading to errors: 1. When there is a temperature gradient or viscosity gradient in the sample tube, the light propagation path bends, resulting in density calculation errors; 2. When the tracer particles are unevenly distributed or have slight differences in particle size, local interference appears in the scattering spectrum signal. To solve these two problems, a density parameter distribution curve calculation method based on spectral momentum compensation factor is proposed. This method, by introducing a spectral compensation factor, can reflect in real time the light fluctuation disturbance caused by the change in refractive index with height inside the sample. Traditional spectral detection based solely on light intensity cannot distinguish the signal differences caused by concentration changes and light path bending. The spectral compensation factor corresponds to the "propagation path deflection intensity" of light in the sample, which can keenly capture the abrupt change points of interlayer refractive index, thereby significantly improving the ability to identify sub-millimeter-level layered interfaces. At the same time, when there is a local temperature difference or uneven distribution of tracer particles in the sample, false peaks are prone to appear. The momentum change trend reflected by the spectral compensation factor can suppress the errors caused by such refractive index gradients.

[0038] The beneficial effects of this embodiment are: by introducing a spectral compensation factor to correct the sample density parameter function, the errors caused by the bending of the light propagation path and uneven particle distribution can be reduced, which helps to improve the accuracy of the calculation and achieve more precise stratification.

[0039] Example 3: This example should be understood as including all the features of any of the foregoing examples, and further improving upon them. The automated robotic arm module uses an ABB IRB120 six-axis robotic arm with a rated load of 3 kg, a working radius of 580 mm, and a repeatability of ±0.03 mm. A special gripper is installed at the end of the robotic arm, with an adjustable gripping force of 5–10 N, suitable for sample tubes of different diameters (10–50 mL). The drive unit uses a servo motor (model: Panasonic MSME012G1C).

[0040] The centrifuge used is a Thermo Scientific Sorvall ST16R high-speed centrifuge with a maximum speed of 15,000 rpm, a temperature control range of 0–40 ℃, and a centrifugal radius of 85 mm. The main control module is connected to the control platform via an RS485 communication interface, allowing for real-time adjustment of the speed and temperature.

[0041] The spectral detection module employs a broadband light source (wavelength range 400–900 nm) and a fiber optic spectrometer (model Ocean Optics USB4000). The light source has an emission power of 5 mW and a spectral resolution of 0.3 nm. A narrow-band filter is placed in front of the detection unit to reduce stray light interference, and the signal acquisition frequency is 5 Hz.

[0042] The sample stratification acquisition module uses a miniature acquisition needle (0.5 mm outer diameter, 0.3 mm inner diameter), driven by a stepper motor (model 17HS4401), with a control resolution of 0.01 mm. The delivery unit uses a polytetrafluoroethylene (PTFE) flexible tube to connect the sample acquisition needle and the sample storage module to avoid sample adsorption.

[0043] The sample storage module has 8 sample compartments, each with a volume of 10 mL, and is equipped with a temperature control unit (maintaining a constant temperature of 4 ℃). The storage module automatically generates sample codes and completes location matching through a barcode recognition system.

[0044] Specifically, if the experimental platform space is limited, the ABB IRB120 six-axis robotic arm can be replaced with a three-axis linear module structure, which can still achieve automatic pick-and-place functions.

[0045] Specifically, when the sample viscosity is high, the inner diameter of the sampling needle can be increased to 0.5 mm, and a solenoid valve control unit can be added to the front end of the sampling needle to prevent cross-contamination.

[0046] Specifically, if long-term sample preservation is required, a low-temperature refrigeration unit (-20 ℃) ​​can be added to the sample chamber or an external constant temperature refrigerator module can be used.

[0047] The following table compares the effects of the manual observation method and the system provided in Example 1. Figure 4 The corresponding rendering: Detection method Layer recognition error (mm) Layer detection time (s) Sample corruption rate (%) Result stability (repeatability bias) (mm) Manual observation method ±0.6 110 3.8 ±0.5 Example 1 System ±0.3 85 1.5 ±0.2 The above-disclosed content is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Therefore, all equivalent technical changes made based on the description and drawings of the present invention are included within the scope of protection of the present invention. Furthermore, the elements therein can be updated as technology develops. The above units are merely examples, and those skilled in the art can adopt corresponding units according to actual needs when implementing this solution.

Claims

1. An automated experimental sample processing and collection system for a high-speed centrifuge, characterized in that, The system includes an automated robotic arm module, a centrifuge, a centrifuge main control module, a spectral detection module, a sample stratification acquisition module, and a sample storage module. The automated robotic arm module is used to automatically perform sample tube loading and unloading actions according to set instructions, placing sample tubes into or removing sample tubes from the centrifuge. The sample tubes contain samples. The centrifuge is used to process the samples and obtain processed samples. The centrifuge main control module is used to control the centrifuge and detect various parameters of the centrifuge. The spectral detection module is used to detect the spectrum of the processed samples and obtain the density parameter distribution curve of the processed samples based on the spectrum. The sample stratification acquisition module is used to perform stratified acquisition of the processed samples based on the detection results of the spectral detection module and obtain stratified samples. The sample storage module is used to store the stratified samples.

2. The automated experimental sample processing and acquisition system for a high-speed centrifuge according to claim 1, characterized in that, The automated robotic arm module includes a robotic arm body, a multi-joint drive unit, and a clamping end. The multi-joint drive unit and the clamping end are disposed on the robotic arm body. The multi-joint drive unit is used to adjust and control various parts of the robotic arm body according to set instructions. The clamping end is used to clamp the sample tube and pick up and put down the sample through the sample tube.

3. The automated experimental sample processing and acquisition system for a high-speed centrifuge according to claim 1, characterized in that, The centrifuge main control module includes a program storage unit, a control unit, and a detection unit. The program storage unit is used to store various programs for controlling the centrifuge. The control unit is used to control the centrifuge according to the programs stored in the program storage unit. The detection unit is used to detect various parameters of the centrifuge operation in real time.

4. The automated experimental sample processing and acquisition system for a high-speed centrifuge according to claim 1, characterized in that, The spectral detection module includes a light source emitting unit, a spectral receiving unit, and a light density conversion unit. The light source emitting unit is used to emit light signals of different wavelengths to illuminate the processed sample in the sample tube. The spectral receiving unit is used to receive the transmitted light signal passing through the processed sample. The light density conversion unit is used to convert the acquired spectral information into density parameter information.

5. The automated experimental sample processing and acquisition system for a high-speed centrifuge according to claim 1, characterized in that, The sample stratification acquisition module includes an acquisition needle unit, a driving unit, and a delivery unit. The acquisition needle unit is used to acquire the processed sample after separation by centrifugation. The driving unit is used to control the acquisition needle unit to acquire processed samples of different strata and obtain stratified samples based on the density information obtained by the light source emission unit. The delivery unit is used to deliver the stratified samples to the sample processing module.

6. The automated experimental sample processing and acquisition system for a high-speed centrifuge according to claim 1, characterized in that, The sample storage module includes a sample identification and encoding unit and a partitioned sample storage bin. The sample identification and encoding unit is used to automatically generate corresponding sample identifiers and mark the partitioned samples according to the sample type before processing and the size relationship of the density parameters of each layered sample. The partitioned sample storage bin is used to store different layered samples in different areas according to the marking results.

7. The automated experimental sample processing and acquisition system for a high-speed centrifuge according to claim 1, characterized in that, The system's workflow includes the following steps: S1, The automated robotic arm module places the sample tube into the centrifuge; S2, The centrifuge processes the sample and obtains the processed sample; S3, the centrifuge main control module controls the centrifuge and detects various parameters of the centrifuge; S4, the spectral detection module detects the spectrum of the processed sample and obtains the density parameter distribution curve of the processed sample based on the spectrum; S5, the sample stratification acquisition module performs stratified acquisition on the processed sample according to the detection results of the spectral detection module and obtains the stratified sample; S6, the sample storage module stores the stratified samples.

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