A method and system for identifying centrifuge speed

Abstract

This invention discloses a centrifuge speed identification method and system, relating to the field of centrifuge technology. A Hall sensor and a photoelectric sensor are mounted on the centrifuge to simultaneously acquire the first and second speeds of the centrifuge. Threshold processing (preprocessing) is performed on the first and second speeds measured by the Hall sensor and the photoelectric sensor respectively to improve the speed measurement effect. Then, the preprocessed speeds are fused using an adaptive Kalman data fusion algorithm to obtain the fused speed. Finally, threshold parameter adjustment (preprocessing adjustment) is performed based on the effect of the fused speed to obtain the optimal speed identification effect.

Description

Technical Field

[0001] This invention relates to the field of centrifuge technology, and specifically to a centrifuge speed identification method and system. Background Technology

[0002] Centrifuges, as devices that use centrifugal force to separate liquids from solid particles or components in liquid mixtures, require precise identification and control of their rotational speed as a key performance indicator. In fields such as biomedicine, chemical analysis, and food testing, the stability of centrifuge rotational speed directly affects the separation effect and the repeatability of experimental results.

[0003] Currently, the commonly used methods for centrifuge speed identification in existing technologies mainly include those based on photoelectric sensors, Hall effect sensors, vibration acceleration sensors, and image recognition. Specifically, photoelectric sensors use reflective marks or gratings on the rotor to calculate the speed by using the frequency of light pulses; Hall effect sensors rely on changes in the magnetic field to generate electrical pulse signals; vibration acceleration sensors indirectly estimate the speed by detecting the vibration frequency of the bearings or casing during centrifuge operation; and image recognition methods use high-speed cameras to capture the position of rotor marks and calculate the speed using image processing algorithms.

[0004] However, the aforementioned traditional speed identification methods often suffer from inherent limitations, such as simplistic methods and limited accuracy. These limitations become even more pronounced in the high-speed operating range of centrifuges or when operating near their resonant frequencies. For example, when a centrifuge is rotating at high speed, photoelectric sensors are susceptible to interference from ambient light and changes in the reflectivity of the rotor surface, leading to attenuation of the optical pulse signal amplitude or waveform distortion. Simultaneously, Hall sensors may experience pulse loss at high speeds due to structural resonance. When the centrifuge speed approaches or is within the mechanical resonance zone, severe vibrations further deteriorate the installation stability of the photoelectric and Hall sensors and the signal coupling path, resulting in misidentification of the pulse signal, timing jitter, or even brief interruptions.

[0005] The aforementioned signal instability directly leads to distorted speed recognition results, failing to accurately reflect the centrifuge's instantaneous speed. In systems employing closed-loop motor control, this distorted speed feedback signal can trigger erroneous controller adjustments, such as generating excessively large or small compensation values. This, in turn, can cause increased motor speed fluctuations, control overshoot, system response lag, and even instability. This not only reduces the centrifuge's separation accuracy and operating efficiency but may also pose a potential risk of fatigue damage to the motor drive system and rotor structure. Summary of the Invention

[0006] To address the limitations of traditional centrifuge speed identification methods, such as those based on photoelectric sensors, Hall sensors, vibration acceleration sensors, and image recognition, which often suffer from limited accuracy and reliance on single methods, photoelectric and Hall sensors are prone to errors or loss of pulse signals during high-speed or resonant centrifuge operation. This leads to unstable speed identification, affecting the stability of speed feedback and motor closed-loop control. The present invention aims to provide a centrifuge speed identification method and system. This method performs threshold processing (preprocessing) on ​​the speeds measured by Hall sensors and photoelectric sensors to improve measurement performance. The preprocessed speeds are then fused using an adaptive Kalman data fusion algorithm to obtain a fused speed. Finally, threshold parameter adjustment (preprocessing adjustment) is performed based on the fused speed effect. This process is repeated to achieve optimal speed identification performance.

[0007] The above-mentioned technical objective of the present invention is achieved through the following technical solution:

[0008] This solution provides a method for identifying centrifuge rotation speed, the method comprising:

[0009] The Hall sensor and photoelectric sensor are tooled on a centrifuge to simultaneously collect the first and second rotational speeds of the centrifuge.

[0010] Preprocessing is performed on the first speed and the second speed respectively;

[0011] The fused speed is obtained by adaptive Kalman data fusion based on the preprocessed first and second speeds;

[0012] Adjust the pretreatment process based on the effect of the fusion rotation speed.

[0013] A further optimized solution is that the tooling method for the Hall sensor and the photoelectric sensor includes:

[0014] The Hall sensor and photoelectric sensor are fixedly mounted on the periphery of the centrifuge spindle, and are installed below the rotor; the photoelectric sensor is used to collect data from below the rotor. The number of times each reflective surface passes by; the Hall sensor is used to collect data below the rotor. The number of times each magnetic column passes through;

[0015] The Hall sensor and the photoelectric sensor are mounted in the same cylindrical structure, which is located around the centrifuge spindle. The rotation axis of the cylindrical structure overlaps with the rotation axis of the centrifuge spindle. When the centrifuge is working, the centrifuge spindle drives the rotor to rotate, and the cylindrical structure does not rotate with the centrifuge spindle.

[0016] The photoelectric sensor fixture is positioned at the first diameter position of the vertical projection of the cylindrical structure, and the Hall sensor fixture is positioned at the second diameter position of the vertical projection of the cylindrical structure. The first diameter and the second diameter are not the same diameter.

[0017] A further optimized solution is that the methods for obtaining the first rotational speed and the second rotational speed include:

[0018] The rotational speed is calculated every n revolutions of the rotor.

[0019] The first rotational speed Calculate according to the following formula:

[0020] The unit is r / min;

[0021] Second speed Calculate according to the following formula:

[0022] The unit is r / min;

[0023] in, This indicates the number of times the magnetic column passes through the sensor. The number of times the reflective surface passes by, as captured by the photoelectric sensor; This represents the time it takes for the rotor to rotate n revolutions.

[0024] A further optimized solution is that the preprocessing method for the first rotational speed includes:

[0025] Obtain the abnormal fluctuation speed range of the Hall sensor and the first speed difference threshold ,in, This indicates the lower limit of the rotational speed during abnormal fluctuations. Indicates the upper limit of abnormal speed fluctuations;

[0026] The first speed is corrected by combining the abnormal fluctuation speed range and the first speed difference threshold:

[0027] ;

[0028] in, This represents the rotational speed measured by the Hall sensor at time k; This represents the rotational speed measured by the Hall sensor at time k-1.

[0029] A further optimized solution is that the preprocessing method for the second rotational speed includes:

[0030] Obtain the abnormal fluctuation speed range of the photoelectric sensor Second speed difference threshold ,in, This indicates the lower limit of the rotational speed during abnormal fluctuations. Indicates the upper limit of abnormal speed fluctuations;

[0031] The first speed is corrected by combining the abnormal fluctuation speed range and the first speed difference threshold:

[0032] ;

[0033] in, This represents the rotational speed measured by the photoelectric sensor at time k; This represents the rotational speed measured by the photoelectric sensor at time k-1.

[0034] A further optimization scheme is that the adaptive Kalman data fusion method includes:

[0035] Initialize configuration state vector State covariance matrix P, state transition matrix Basic process noise covariance Q, measurement matrix and the measurement noise covariance R; where, Indicates the sampling interval;

[0036] The state prediction vector is predicted based on the initial configuration. State covariance prediction matrix : ; Where T represents transpose;

[0037] Based on the state prediction vector and the state covariance prediction matrix, the state update is performed by combining the preprocessed first and second rotational speeds to obtain the fused rotational speed.

[0038] A further optimized solution is that the state update method includes:

[0039] Calculate the innovation vector y based on the preprocessed first and second rotational speeds and the state prediction vector:

[0040] ;

[0041] in, This represents the measurement value at time k;

[0042] Establish a sliding time window to store the innovation vector and the change in measurement value, and dynamically adjust the measurement noise covariance R after the sliding time window is full of data;

[0043] Calculate the innovation covariance and Kalman gain based on the dynamically adjusted measurement noise covariance R;

[0044] The state covariance matrix and state vector are updated by combining Kalman gain.

[0045] A further optimization scheme is that the measurement noise covariance R is dynamically adjusted according to the following formula:

[0046] ;

[0047] in, , This represents the Hall sensor weight and photoelectric sensor weight determined based on the fluctuation of measurements from the Hall sensor and photoelectric sensor within the sliding time window. , Rn1 represents the information covariance matrix taken from the sliding time window; Rn2 represents the dynamically adjusted measurement noise covariance corresponding to the Hall sensor; and Rn3 represents the dynamically adjusted measurement noise covariance corresponding to the photoelectric sensor.

[0048] A further optimization scheme is that the state covariance matrix and state vector are updated according to the following formula:

[0049] ;

[0050] ;

[0051] ;

[0052] ;

[0053] Where S represents the innovation covariance; T represents the transpose; K represents the Kalman gain; and I represents the identity matrix. ; Indicates the fusion rotation speed.

[0054] This solution also provides a centrifuge speed identification method system for implementing the above-mentioned centrifuge speed identification method, the system comprising:

[0055] The acquisition module is used to mount the Hall sensor and photoelectric sensor on the centrifuge and simultaneously acquire the first and second rotational speeds of the centrifuge.

[0056] The preprocessing module is used to preprocess the first rotational speed and the second rotational speed respectively;

[0057] The fusion module is used to perform adaptive Kalman data fusion based on the preprocessed first and second rotational speeds to obtain the fused rotational speed;

[0058] The adjustment module is used to adjust the preprocessing process based on the effect of the fusion rotation speed.

[0059] Compared with the prior art, the present invention has the following beneficial effects:

[0060] 1. This invention provides a centrifuge speed identification method and system. Addressing the inherent problems of pulse signal loss, misidentification, or timing jitter in traditional photoelectric and Hall sensors during high-speed centrifuge operation and resonance zones, this invention innovatively employs a dual-source heterogeneous sensor fusion architecture. By preprocessing and thresholding the two raw speed signals, abnormal jump values ​​and outliers caused by instantaneous interference can be effectively eliminated, suppressing severe fluctuations caused by pulse loss or false triggering. Based on this, an adaptive Kalman data fusion algorithm is introduced, utilizing its recursive optimal estimation characteristics to dynamically weight and fuse the threshold-corrected dual signals in a statistical sense, fully leveraging the complementary advantages of photoelectric and Hall sensors. Even under conditions where one sensor experiences temporary distortion due to vibration or excessive speed, the fusion algorithm can still output continuous, smooth, and reliable speed estimates, significantly improving the system's robustness under harsh operating conditions.

[0061] 2. This invention provides a centrifuge speed identification method and system; it only requires the use of existing centrifuge hardware resources (Hall sensors and photoelectric sensors are both conventional configurations), and performance can be improved through software algorithm optimization, without the need to add high-cost components such as gyroscopes, accelerometer arrays or high-speed image acquisition systems, and has good economic efficiency and engineering scalability. Attached Figure Description

[0062] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be considered as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings:

[0063] Figure 1 This is a schematic diagram of the centrifuge speed identification method.

[0064] Figure 2 This is a schematic diagram illustrating the principle of centrifuge speed recognition.

[0065] Figure 3 A schematic diagram showing the positions of the centrifuge rotor and sensor fixtures;

[0066] Figure 4 This is a schematic diagram showing the distribution of reflective surfaces and magnetic pillars;

[0067] Figure 5 This is a schematic diagram showing the distribution of photoelectric and Hall sensors;

[0068] Figure 6 This is a schematic diagram of a centrifuge speed recognition system.

[0069] Figure 7This is a comparison chart of centrifuge speed identification results.

[0070] In the attached diagram:

[0071] 1-Centrifuge rotor; 2-Cylindrical structure; 3-Centrifuge main shaft; 4-Reflective surface; 5-Magnetic column; 6-Photoelectric sensor; 7-Hall sensor. Detailed Implementation

[0072] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0073] Traditional centrifuge speed identification methods often suffer from limitations in terms of simplistic approaches and accuracy. For instance, when the centrifuge is operating at high speed or resonating, photoelectric and Hall effect sensors are prone to errors in pulse signal identification or loss, leading to unstable speed identification and consequently affecting the stability of speed feedback and motor closed-loop control. In view of this, this solution provides the following embodiments to address the aforementioned technical problems.

[0074] Example 1

[0075] This embodiment provides a method for identifying centrifuge speed, such as... Figure 1 and Figure 2 As shown, the method includes:

[0076] Step 1: Mount the Hall sensor and photoelectric sensor on the centrifuge and simultaneously collect the first and second rotational speeds of the centrifuge.

[0077] In step one, the tooling method for the Hall sensor and the photoelectric sensor includes:

[0078] like Figures 3-5 As shown, the Hall sensor and photoelectric sensor are fixedly mounted on the periphery of the centrifuge spindle 3, and the Hall sensor 6 and photoelectric sensor 7 are installed below the rotor; the photoelectric sensor is used to collect data from below the rotor. The number of times each reflective surface passes by; Hall effect sensors are used to collect data from below the rotor. The number of times each magnetic column passes through;

[0079] Assuming the actual number of reflective surfaces (4) installed around the bottom of the rotor is... The maximum number of reflective surfaces that can be set is [number]. , The glossy and dark sides can be distinguished by applying reflective sheets, painting, coating, or other methods; the glossy side is the reflective side. The magnetic pillars are symmetrically distributed, with a quantity of [missing information]. , Furthermore, the magnetic columns must be evenly distributed in a circle to ensure the dynamic balance of the rotor rotation.

[0080] Hall sensor 6 and photoelectric sensor 7 are tooled in the same cylindrical structure 2. The cylindrical structure 2 is tooled around the centrifuge main shaft, and the rotation center axis of the cylindrical structure 2 overlaps with the rotation center axis of the centrifuge main shaft 3. When the centrifuge is working, the centrifuge main shaft 3 drives the centrifuge rotor 1 to rotate, and the cylindrical structure 2 does not rotate with the centrifuge main shaft 3.

[0081] The photoelectric sensor fixture is positioned at the first diameter location of the cylindrical structure's vertical projection, while the Hall sensor fixture is positioned at the second diameter location of the cylindrical structure's vertical projection. The first and second diameters are not the same. This is to prevent the rotor from vibrating excessively in a particular phase, which could affect the pulse acquisition by both sensors.

[0082] The sensor fixture is fixed to the centrifuge body. When the centrifuge is working, the main shaft drives the rotor to rotate. Each time the reflective surface passes the photoelectric sensor, the controller receives a pulse signal from the photoelectric sensor. Each time the magnetic column passes the Hall sensor, the controller receives a pulse signal from the Hall sensor. For each revolution of the rotor, the controller receives a pulse signal from the photoelectric sensor. A pulse signal was received from the Hall sensor. A pulse signal.

[0083] In step one, the methods for obtaining the first rotational speed and the second rotational speed include:

[0084] The rotational speed is calculated every n revolutions of the rotor.

[0085] First speed Calculate according to the following formula:

[0086] The unit is r / min;

[0087] Second speed Calculate according to the following formula:

[0088] The unit is r / min;

[0089] in, This indicates the number of times the magnetic column passes through the sensor. The number of times the reflective surface passes by, as captured by the photoelectric sensor; This represents the time it takes for the rotor to rotate n revolutions.

[0090] Step two: Preprocess the first speed and the second speed respectively;

[0091] In step two, the preprocessing method for the first rotational speed includes:

[0092] S21, Obtain the abnormal fluctuation speed range from the Hall sensor. and the first speed difference threshold ,in, This indicates the lower limit of the rotational speed during abnormal fluctuations. Indicates the upper limit of abnormal speed fluctuations;

[0093] Specifically, a preliminary test is conducted first, in which the rotor is accelerated from a standstill to its maximum speed and stabilized for a period of time before being decelerated back to a standstill. According to the results of the preliminary test, the abnormal fluctuations in the measured speed caused by interference to the Hall sensor and photoelectric sensor are different at different rotor speed stages.

[0094] In the speed range where the speed measured by the Hall sensor shows obvious abnormal fluctuations In some cases, the Hall sensor experiences significant pulse signal loss, resulting in a measured speed that is far lower than the actual speed. However, in other speed ranges, the abnormal fluctuations in the measured speed by the Hall sensor are not obvious. To address this issue, a threshold is set. The rotational speed measured by the Hall sensor at time k is compared with that at time k-1. By performing calibration, the speed measurement performance of the Hall sensor can be significantly improved.

[0095] S22, Correct the first speed by combining the abnormal fluctuation speed range and the first speed difference threshold:

[0096] ;

[0097] in, This represents the rotational speed measured by the Hall sensor at time k; This represents the rotational speed measured by the Hall sensor at time k-1.

[0098] In step two, the preprocessing method for the second rotational speed includes:

[0099] G21, acquire abnormal fluctuation speed range of photoelectric sensor. Second speed difference threshold ,in, This indicates the lower limit of the rotational speed during abnormal fluctuations. Indicates the upper limit of abnormal speed fluctuations;

[0100] In the speed range where the speed measured by the photoelectric sensor shows obvious abnormal fluctuations In the middle range, the photoelectric sensor is significantly affected by interference, causing noticeable fluctuations in the measured rotational speed. However, in other speed ranges, the abnormal fluctuations in the measured rotational speed are not obvious. To address this issue, a threshold is set. Compare the rotational speed measured by the photoelectric sensor at time k and time k-1. By performing calibration, the speed measurement performance of the Hall sensor can be significantly improved.

[0101] G22, corrects the first speed by combining the abnormal fluctuation speed range and the first speed difference threshold:

[0102] ;

[0103] in, This represents the rotational speed measured by the photoelectric sensor at time k; This represents the rotational speed measured by the photoelectric sensor at time k-1.

[0104] The above speed range , It is not necessarily unique. Both Hall sensors and photoelectric sensors may detect multiple speed ranges with obvious abnormal fluctuations in speed. It is necessary to select the appropriate range and perform threshold processing based on the actual situation.

[0105] Step 3: Based on the preprocessed first and second rotational speeds, perform adaptive Kalman data fusion to obtain the fused rotational speed;

[0106] In step three, the adaptive Kalman data fusion method includes:

[0107] S31, Initialize the configuration state vector State covariance matrix P, state transition matrix Basic process noise covariance Q, measurement matrix and the measurement noise covariance R; where, Indicates the sampling interval;

[0108] S32, predict the state prediction vector based on the initial configuration. State covariance prediction matrix : ; Where T represents transpose;

[0109] S33, based on the state prediction vector and the state covariance prediction matrix, combines the preprocessed first speed and second speed to perform state update fusion and speed.

[0110] In step S33, the method for updating the state includes:

[0111] S331, calculate the innovation vector y based on the preprocessed first and second rotational speeds and the state prediction vector:

[0112] ;

[0113] in, This represents the measurement value at time k;

[0114] S332, establish a sliding time window to store the innovation vector and the change in measurement value, and dynamically adjust the measurement noise covariance R after the sliding time window is full of data;

[0115] In step S332, the measurement noise covariance R is dynamically adjusted according to the following formula:

[0116] ;

[0117] in, , This represents the Hall sensor weight and photoelectric sensor weight determined based on the fluctuation of measurements from the Hall sensor and photoelectric sensor within the sliding time window. , Rn1 represents the information covariance matrix taken from the sliding time window; Rn2 represents the dynamically adjusted measurement noise covariance corresponding to the Hall sensor; and Rn3 represents the dynamically adjusted measurement noise covariance corresponding to the photoelectric sensor.

[0118] S333, calculate the innovation covariance and Kalman gain based on the dynamically adjusted measurement noise covariance R;

[0119] S334 combines Kalman gain to update the state covariance matrix and state vector.

[0120] In step S334, the state covariance matrix and the state vector are updated according to the following formula:

[0121] ;

[0122] ;

[0123] ;

[0124] ;

[0125] Where S represents the innovation covariance; T represents the transpose; K represents the Kalman gain; and I represents the identity matrix. ; Indicates the fusion rotation speed.

[0126] Step 4: Adjust the pretreatment process based on the effect of the fusion rotation speed.

[0127] Specifically, threshold parameter tuning is performed based on the speed effect after fusion, such as... Repeat the above process to obtain the optimal speed recognition effect.

[0128] After preprocessing (preliminary correction) the speed measured by the Hall sensor and the first and second rotational speeds collected by the photoelectric sensor, there are still slight fluctuations that are difficult to eliminate and affect the speed measurement effect. Therefore, this embodiment can use the above-mentioned adaptive Kalman data fusion method to fuse and correct the speed measurement results of the Hall sensor and the photoelectric sensor, so as to obtain the optimal speed measurement effect.

[0129] Example 2

[0130] This embodiment provides a centrifuge speed identification method system, such as Figure 6 As shown, the system for implementing the centrifuge speed identification method described in Example 1 includes:

[0131] The acquisition module is used to mount the Hall sensor and photoelectric sensor on the centrifuge and simultaneously acquire the first and second rotational speeds of the centrifuge.

[0132] The preprocessing module is used to preprocess the first rotational speed and the second rotational speed respectively;

[0133] The fusion module is used to perform adaptive Kalman data fusion based on the preprocessed first and second rotational speeds to obtain the fused rotational speed;

[0134] The adjustment module is used to adjust the preprocessing process based on the effect of the fusion rotation speed.

[0135] Example 3

[0136] This embodiment performs offline simulation of the centrifuge speed identification method to obtain the fused speed as follows: Figure 7 As shown in the waveform of the fusion result, the speed recognition effect after fusion is good.

[0137] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for identifying centrifuge rotation speed, characterized in that, The method includes: The Hall sensor and photoelectric sensor are tooled on a centrifuge to simultaneously collect the first and second rotational speeds of the centrifuge. Preprocessing is performed on the first speed and the second speed respectively; The fused speed is obtained by adaptive Kalman data fusion based on the preprocessed first and second speeds; Adjust the pretreatment process based on the effect of the fusion rotation speed.

2. The centrifuge speed identification method according to claim 1, characterized in that, The tooling method for the Hall sensor and photoelectric sensor includes: The Hall sensor and photoelectric sensor are fixedly mounted on the periphery of the centrifuge spindle, and are installed below the rotor; the photoelectric sensor is used to collect data from below the rotor. The number of times each reflective surface passes by; the Hall sensor is used to collect data below the rotor. The number of times each magnetic column passes through; The Hall sensor and the photoelectric sensor are mounted in the same cylindrical structure, which is located around the centrifuge spindle. The rotation axis of the cylindrical structure overlaps with the rotation axis of the centrifuge spindle. When the centrifuge is working, the centrifuge spindle drives the rotor to rotate, and the cylindrical structure does not rotate with the centrifuge spindle. The photoelectric sensor fixture is positioned at the first diameter position of the vertical projection of the cylindrical structure, and the Hall sensor fixture is positioned at the second diameter position of the vertical projection of the cylindrical structure. The first diameter and the second diameter are not the same diameter.

3. The centrifuge speed identification method according to claim 2, characterized in that, The methods for obtaining the first rotational speed and the second rotational speed include: The rotational speed is calculated every n revolutions of the rotor. The first rotational speed Calculate according to the following formula: The unit is r / min; Second speed Calculate according to the following formula: The unit is r / min; in, This indicates the number of times the magnetic column passes through the sensor. The number of times the reflective surface passes by, as captured by the photoelectric sensor; This represents the time taken for the rotor to rotate n times, expressed in seconds.

4. The centrifuge speed identification method according to claim 3, characterized in that, The preprocessing method for the first rotational speed includes: Obtain the abnormal fluctuation speed range of the Hall sensor and the first speed difference threshold ,in, This indicates the lower limit of the rotational speed during abnormal fluctuations. Indicates the upper limit of abnormal speed fluctuations; The first speed is corrected by combining the abnormal fluctuation speed range and the first speed difference threshold: ； in, This represents the rotational speed measured by the Hall sensor at time k; This represents the rotational speed measured by the Hall sensor at time k-1.

5. A centrifuge speed identification method according to claim 3, characterized in that, The preprocessing method for the second rotational speed includes: Obtain the abnormal fluctuation speed range of the photoelectric sensor Second speed difference threshold ,in, This indicates the lower limit of the rotational speed during abnormal fluctuations. Indicates the upper limit of abnormal speed fluctuations; The first speed is corrected by combining the abnormal fluctuation speed range and the first speed difference threshold: ； in, This represents the rotational speed measured by the photoelectric sensor at time k; This represents the rotational speed measured by the photoelectric sensor at time k-1.

6. The centrifuge speed identification method according to claim 1, characterized in that, The adaptive Kalman data fusion method includes: Initialize configuration state vector State covariance matrix P, state transition matrix Basic process noise covariance Q, measurement matrix and the measurement noise covariance R; where, Indicates the sampling interval; The state prediction vector is predicted based on the initial configuration. State covariance prediction matrix : ; Where T represents transpose; Based on the state prediction vector and the state covariance prediction matrix, the state update is performed by combining the preprocessed first and second rotational speeds to obtain the fused rotational speed.

7. A centrifuge speed identification method according to claim 6, characterized in that, The method for updating the state includes: Calculate the innovation vector y based on the preprocessed first and second rotational speeds and the state prediction vector: ； in, This represents the measurement value at time k; Establish a sliding time window to store the innovation vector and the change in measurement value, and dynamically adjust the measurement noise covariance R after the sliding time window is full of data; Calculate the innovation covariance and Kalman gain based on the dynamically adjusted measurement noise covariance R; The state covariance matrix and state vector are updated by combining Kalman gain.

8. A centrifuge speed identification method according to claim 7, characterized in that, The measurement noise covariance R is dynamically adjusted according to the following formula: ； in, , This represents the Hall sensor weight and photoelectric sensor weight determined based on the fluctuation of measurements from the Hall sensor and photoelectric sensor within the sliding time window. , Rn1 represents the information covariance matrix taken from the sliding time window; Rn2 represents the dynamically adjusted measurement noise covariance corresponding to the Hall sensor; and Rn3 represents the dynamically adjusted measurement noise covariance corresponding to the photoelectric sensor.

9. A centrifuge speed identification method according to claim 7, characterized in that, The state covariance matrix and state vector are updated according to the following formula: ； ； ； ； Where S represents the innovation covariance; T represents the transpose; K represents the Kalman gain; and I represents the identity matrix. ; Indicates the fusion rotation speed.

10. A centrifuge speed identification method system, characterized in that, The system for implementing the centrifuge speed identification method according to any one of claims 1-8, the system comprising: The acquisition module is used to mount the Hall sensor and photoelectric sensor on the centrifuge and simultaneously acquire the first and second rotational speeds of the centrifuge. The preprocessing module is used to preprocess the first rotational speed and the second rotational speed respectively; The fusion module is used to perform adaptive Kalman data fusion based on the preprocessed first and second rotational speeds to obtain the fused rotational speed; The adjustment module is used to adjust the preprocessing process based on the effect of the fusion rotation speed.

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