Sample analyzer and bubble identification method thereof

Abstract

The invention discloses a sample analyzer and a bubble identification method thereof. A control unit of the sample analyzer is used for obtaining an original detection data sequence of a plurality of sampling time points; obtaining a baseline value corresponding to each sampling time point based on the original detection data sequence of the plurality of sampling time points; when it is confirmed that the difference value of the baseline values corresponding to the two sampling time points is larger than or equal to a first fixed value within the first preset duration, obtaining the baseline value corresponding to the newest sampling time point and obtaining the average value of the baseline values corresponding to all the sampling time points within a second preset duration before the newest sampling time point; and determining the initial occurrence time of the first bubble based on the baseline value corresponding to the newest sampling time point and the average value of the baseline values corresponding to all the sampling time points in the second preset duration. According to the sample analyzer, large bubbles can be accurately identified, faults are identified, interference bubbles are filtered out, and the accuracy of sample detection is improved.

Description

Technical Field

[0001] This application relates to the technical field of medical devices, and particularly to a sample analyzer and a method for identifying air bubbles thereof. Background Art

[0002] A sample analyzer is a medical precision instrument that can be used to analyze and measure blood samples. When the sample analyzer detects particles in a sample, due to the interference of external noise, the signal baseline fluctuates. The fluctuation of the signal baseline will affect the accuracy of pulse amplitude measurement. For example, the sample analyzer is prone to misidentifying air bubbles as particles, affecting the accuracy of the counting result.

[0003] In related technologies, air bubbles are mainly identified by comparing the difference between the actual baseline and the reference baseline with a threshold. However, it is found in actual applications that when large air bubbles appear in the pipeline due to a fault, the current method for identifying air bubbles has low accuracy in identifying large air bubbles. Summary of the Invention

[0004] This application provides a sample analyzer and a method for identifying air bubbles thereof to solve the technical problem in the prior art that the method for identifying air bubbles has low accuracy in identifying large air bubbles.

[0005] To solve the above technical problem, a technical solution adopted by this application is: providing a sample analyzer, which includes a detection unit and a control unit. Among them, the detection unit is used to detect particles in the sample flowing through the detection channel; the control unit is connected to the detection unit, and the control unit is used to: control the detection unit to perform particle size detection on the particles in the sample flowing through the detection channel, and collect the original detection data of the detection unit at a preset frequency to obtain an original detection data sequence at multiple sampling time points; based on the original detection data sequence at multiple sampling time points, obtain the baseline value corresponding to each sampling time point; when it is confirmed that within a first preset duration, the difference between the baseline values corresponding to two sampling time points is greater than or equal to a first fixed value, then obtain the baseline value corresponding to the latest sampling time point and obtain the average value of the baseline values corresponding to all sampling time points within a second preset duration before the latest sampling time point, where the second preset duration is greater than or equal to the first preset duration; based on the baseline value corresponding to the latest sampling time point and the average value of the baseline values corresponding to all sampling time points within the second preset duration, confirm whether an air bubble appears.

[0006] Further, the control unit is further used to: when it is confirmed that the difference between the baseline value corresponding to the latest sampling time point and the average value of the baseline values corresponding to all sampling time points within the second preset duration is greater than a second fixed value, then confirm that an air bubble appears, where the second fixed value is less than the first fixed value.

[0007] Further, the ratio of the second fixed value to the first fixed value is: 1 / 4 - 3 / 4.

[0008] Further, the control unit is further configured to: when it is confirmed that the difference between the baseline value corresponding to the latest sampling time point and the average value of the baseline values corresponding to all sampling time points within the second preset duration is greater than the second fixed value, then confirm that the initial appearance time of the bubble is the latest sampling time point.

[0009] Further, the control unit is further configured to: calculate the mean value of the original detection data of each sampling time point and a predetermined number of sampling time points before and after it, to obtain the detection mean value corresponding to each sampling time point; use the detection mean value corresponding to each sampling time point and the minimum value in the original detection data of each sampling time point as the baseline value corresponding to each sampling time point.

[0010] Further, the first preset duration is greater than the appearance time of a single pulse generated by the particles in the sample, and the second preset duration is 1 - 2 times the first preset duration.

[0011] Further, the control unit is further configured to: when it is confirmed that within the third preset duration, the change amplitude of the baseline value corresponding to each sampling time point is less than the preset amplitude, then confirm that the bubble ends.

[0012] Further, the control unit is further configured to: when it is confirmed that within the third preset duration, the baseline value corresponding to each sampling time point is not 0, and the change amplitude of the baseline value corresponding to each sampling time point is less than the preset amplitude, then confirm that the bubble ends.

[0013] Further, the particle size of the bubble is greater than the particle size of the particles in the sample, and the particle size of the bubble is greater than 30 microns.

[0014] To solve the above technical problems, another technical solution adopted by this application is: to provide a method for identifying bubbles in a sample analyzer. Based on the sample analyzer in any of the above embodiments, the method for identifying bubbles includes: controlling the detection unit to perform particle size detection on the particles in the sample flowing through the detection channel, and collecting the original detection data of the detection unit at a preset frequency to obtain a sequence of original detection data at multiple sampling time points; obtaining the baseline value corresponding to each sampling time point based on the sequence of original detection data at multiple sampling time points; when it is confirmed that within the first preset duration, the difference between the baseline values corresponding to two sampling time points is greater than or equal to the first fixed value, then obtain the baseline value corresponding to the latest sampling time point and obtain the average value of the baseline values corresponding to all sampling time points within the second preset duration before the latest sampling time point, where the second preset duration is greater than or equal to the first preset duration; based on the baseline value corresponding to the latest sampling time point and the average value of the baseline values corresponding to all sampling time points within the second preset duration, confirm whether a bubble appears.

[0015] Advantages of the present application: Different from the prior art, the sample analyzer of the present application includes a detection unit and a control unit. Among them, the control unit is configured to: control the detection unit to detect the sample flowing through the detection area, and collect the original detection data of the detection unit at a preset frequency to obtain an original detection data sequence at multiple sampling time points; obtain the baseline value corresponding to each sampling time point based on the original detection data sequence at multiple sampling time points; when it is confirmed that within a first preset duration, the difference between the baseline values corresponding to two sampling time points is greater than or equal to a first fixed value, then obtain the baseline value corresponding to the latest sampling time point and the average value of the baseline values corresponding to all sampling time points within a second preset duration before the latest sampling time point, where the second preset duration is greater than or equal to the first preset duration; confirm the initial appearance time of the first bubble based on the baseline value corresponding to the latest sampling time point and the average value of the baseline values corresponding to all sampling time points within the second preset duration. In the sample analyzer of the present application, when the control unit confirms that the baseline value increases by the first fixed value within the first preset duration, it can be preliminarily considered that the baseline fluctuation amplitude is relatively large, and then the initial appearance time of the first bubble is confirmed through the baseline value corresponding to the latest sampling time point and the average value of the baseline values corresponding to all sampling time points within the second preset duration. In this way, it is possible to accurately identify large bubbles, filter out interfering bubbles, and improve the accuracy of sample detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings herein are incorporated into and constitute a part of this specification. These drawings illustrate embodiments consistent with the present application and, together with the specification, are used to explain the technical solutions of the present application.

[0017] Figure 1 is a schematic framework diagram of an embodiment of a sample analyzer provided by the present application;

[0018] Figure 2 is a schematic flowchart of an embodiment of a method for identifying bubbles in a sample analyzer provided by the present application;

[0019] Figure 3 is Figure 1 a schematic distribution diagram of the original detection data collected by the sample analyzer shown in;

[0020] Figure 4 is from Figure 3 a schematic distribution diagram of the baseline values identified from the original detection data of;

[0021] Figure 5 is from Figure 4 a schematic distribution diagram of the bubbles identified from the baseline values in;

[0022] Figure 6 is Figure 5 the corresponding recognition result inFigure 3 The distribution schematic diagram of the original data. Specific embodiments

[0023] To make the above objects, features, and advantages of the present application more obvious and understandable, the following will describe in detail the specific embodiments of the present application with reference to the accompanying drawings. It can be understood that the specific embodiments described herein are only used to explain the present application, rather than limiting the present application. Additionally, it should be noted that for the convenience of description, only the parts related to the present application rather than all the structures are shown in the drawings. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0024] The terms "first", "second", etc. in the present application are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products, or devices.

[0025] Referring to "embodiments" herein means that the specific features, structures, or characteristics described in connection with the embodiments may be included in at least one embodiment of the present application. The phrase appears at various positions in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art explicitly and implicitly understand that the embodiments described herein may be combined with other embodiments.

[0026] When abnormal situations such as pipeline abnormalities or cavitation occur, bubbles are likely to appear. The characteristics of the pulses generated by these bubbles may be similar to the characteristics of the pulses generated by the particles in the sample, which will interfere with the results of sample detection. The sample analyzer of the present application can accurately identify the bubbles caused by faults such as cavitation or pipeline abnormalities, especially large bubbles, in the pulse signal analysis. Specifically, the sample analyzer can identify whether bubbles appear and the number of bubbles that appear to determine whether there are faults such as cavitation or pipeline abnormalities. Therefore, the accuracy of particle detection by the sample analyzer can be improved.

[0027] Please refer to Figure 1 as shown Figure 1 is a schematic framework diagram of an embodiment of a sample analyzer provided by the present application. Specifically, the sample analyzer 10 includes: a detection unit 11 and a control unit 12, wherein the control unit 12 is connected to the detection unit 11.

[0028] The detection unit 11 is used to detect the particle size of the particles in the sample flowing through the detection area. Optionally, the detection unit 11 may include an optical detection component. For example, the detection unit 11 includes a light emitter and a light receiver. The light emitter is used to emit an illumination beam, and after the illumination beam passes through the sample in the flow cell, it is received by the light receiver. The light receiver is used to receive the forward scattered light signal to detect the particle size of the particles in the sample. Specifically, the illumination beam emitted by the light emitter irradiates the particles to generate a light signal, and the light receiver receives the light signal and converts the light signal into a voltage signal as the original detection data.

[0029] In other embodiments, the detection unit 11 may further include an impedance detection component. For example, the detection unit 11 detects the particle size of the particles in the sample in the impedance detection channel to obtain a voltage signal for particle size detection as the original detection data.

[0030] The control unit 12 is connected to the detection unit 11 to obtain the original detection data of the particle detection in the sample from the detection unit 11.

[0031] Based on the sample analyzer 10 of any of the above embodiments, the present application further provides a method for identifying bubbles in a sample analyzer. Please refer to Figure 2 as shown in Figure 2 which is a schematic flowchart of an embodiment of a method for identifying bubbles in a sample analyzer provided by the present application. Specifically, the method for identifying bubbles includes:

[0032] S11: Control the detection unit to detect the sample flowing through the detection area, and collect the original detection data of the detection unit at a preset frequency to obtain an original detection data sequence at multiple sampling time points.

[0033] When the sample analyzer 10 detects the sample, the sample flows through the detection area, and the detection area may be the optical detection channel of the flow cell. The control unit 12 controls the detection unit 11 to detect the particle size of the particles in the sample flowing through the detection area. The control unit 12 obtains the original detection data of the detection unit 11 at a preset frequency to obtain an original detection data sequence of the particle detection in the sample. Among them, the preset frequency may be 1M - 20MHZ.

[0034] For example, as Figure 3 shown, the light emitter in the detection unit 11 emits an illumination beam to irradiate the particles in the sample, and the light receiver can collect the forward scattered light signal and convert the light signal into an electrical signal to obtain a detection signal of the particle size as the original detection data. Continuously collect the original detection data to obtain an original detection data sequence of the particle detection in the sample.

[0035] It can be seen from the obtained original detection data sequence that bubbles often appear in clusters, the pulses are relatively dense, and the peak value of individual pulses is very large, which can reach the maximum value of the sampling.

[0036] S12: Obtain the baseline value corresponding to each sampling time point based on the original detection data sequence at multiple sampling time points.

[0037] After obtaining the original detection data sequence, calculate the baseline value corresponding to each sampling time point according to the original detection data sequence, so as to obtain the sampling baseline.

[0038] Specifically, the sampling baseline can be obtained according to the detection mean value corresponding to each sampling time point, and the detection mean value corresponding to each sampling time point can be obtained as a moving average calculated from the mean value of the original detection data of each sampling time point and a predetermined number of sampling time points before and after it.

[0039] Optionally, the baseline value corresponding to each sampling time point can also be obtained based on the moving average value corresponding to the sampling time point and the original detection data of the sampling time point, and the sampling baseline is obtained through the baseline value corresponding to each sampling time point. By calculating the moving average value corresponding to each sampling time point, better denoising can be achieved, and the accuracy of particle recognition can be improved. In other embodiments, the weighted average value of the original detection data corresponding to a predetermined number of sampling time points before and after each sampling time point can also be calculated to obtain the detection mean value corresponding to each sampling time point, or the median value of the original detection data corresponding to a predetermined number of sampling time points before and after each sampling time point can be calculated to obtain the detection mean value corresponding to each sampling time point. In this way, denoising can also be performed to reduce the measurement error.

[0040] Optionally, as Figure 4 shown, the control unit 12 can use the detection mean value corresponding to each sampling time point and the minimum value of the original detection data of the sampling time point as the baseline value corresponding to the sampling time point. For example, take the original detection data corresponding to approximately 1000 sampling time points before and after a certain sampling time point to calculate the moving average value. Suppose the obtained moving average value is A, and the original detection data corresponding to the sampling time point is B. If the moving average value A is less than the original detection data B, then the baseline value corresponding to the sampling time point is A. If the moving average value A is greater than the original detection data B, then the baseline value corresponding to the sampling time point is B. In this way, taking the minimum value of the baseline value can avoid small pulses from being filtered out, resulting in some bubbles not being recognized, thereby improving the accuracy of bubble recognition.

[0041] S13: When it is confirmed that within the first preset duration, the difference between the baseline values corresponding to two sampling time points is greater than or equal to the first fixed value, obtain the baseline value corresponding to the latest sampling time point and the average value of the baseline values corresponding to all sampling time points within the second preset duration before the latest sampling time point, where the second preset duration is greater than or equal to the first preset duration.

[0042] After the control unit 12 obtains the baseline value corresponding to each sampling time point, if it is confirmed that within the first preset duration, the baseline value increases by a first fixed value, it is considered that there is an obvious jitter in the baseline, and there may be first bubbles with a larger particle size generated. Here, within the first preset duration, the increase of the baseline value by the first fixed value means that within the first preset duration, the difference between the baseline values corresponding to two sampling time points is greater than the first fixed value. Among them, the first fixed value can be set according to the particle size of the first bubbles to be identified. The first preset duration is greater than the occurrence time of a single pulse and can be more than 10 times the occurrence time of a single pulse. The first preset duration can be 16 - 128 microseconds. For example, the first preset duration can be set to 16 microseconds, 32 microseconds, 48 microseconds, 60 microseconds, 80 microseconds, or 128 microseconds, etc.

[0043] After the control unit 12 confirms that there is an obvious jump in the baseline within the first preset duration, it obtains the baseline value corresponding to the latest sampling time point. Here, the baseline value corresponding to the latest sampling time point refers to the latest obtained baseline value. The first preset duration is within the first preset duration before the time point corresponding to the latest baseline value.

[0044] The control unit 12 obtains the average value of the baseline values corresponding to all sampling time points within the second preset duration. Among them, the second preset duration is within the second preset duration before the sampling time point corresponding to the latest baseline value. The second preset duration is greater than or equal to the first preset duration, that is, the second preset duration covers the first preset duration. The second preset duration can be 1 - 2 times the first preset duration to accurately confirm the occurrence time of the first bubbles.

[0045] S14: Based on the baseline value corresponding to the latest sampling time point and the average value of the baseline values corresponding to all sampling time points within the second preset duration, confirm the initial occurrence time of the first bubbles.

[0046] When the control unit 12 further confirms the generation of bubbles, it can further confirm whether the first bubbles are generated and the initial occurrence time of the first bubbles according to the baseline value corresponding to the latest sampling time point and the average value of the baseline values corresponding to all sampling time points obtained within the second preset duration.

[0047] Optionally, when it is confirmed that the difference between the baseline value corresponding to the latest sampling time point and the average value of the baseline values corresponding to all sampling time points within the second preset duration is greater than the second fixed value, it can be considered that the jump amplitude of the baseline value corresponding to the latest sampling time point is large, and the first bubbles appear. In a specific embodiment, as Figure 5 shown, the first bubbles are identified from the baseline, and the initial occurrence time T1 of the first bubbles is recorded. Among them, the second fixed value is less than the first fixed value. In this way, the first bubbles in the sample can be identified more accurately.

[0048] Furthermore, the ratio of the second fixed value to the first fixed value can be: 1 / 4 - 3 / 4. For example, the ratio of the second fixed value to the first fixed value can be: 1 / 4, 1 / 3, 1 / 2, 3 / 4, etc. With this setting, the baseline value corresponding to the latest sampling time point is greater than the average baseline value within the second preset duration by the second fixed value, that is, the fluctuation amplitude of the baseline value at the latest sampling time point is relatively large, and only then is it determined that the first bubble has been generated. In this way, large-particle-size particles in the sample can be filtered out, reducing the probability of large-particle-size particles being misjudged as the first bubble, thereby improving the accuracy of sample detection.

[0049] When the control unit 12 confirms the appearance of the first bubble, it can be considered that the time point when the first bubble initially appears is the latest sampling time point corresponding to the latest baseline. Therefore, the filtering of the first bubble can start from the latest sampling time point. In this way, the initial appearance time of the first bubble can be confirmed more accurately.

[0050] The sample analyzer 10 of the present application can identify first bubbles with a particle size larger than that of the particles to be measured in the sample, and the particle size of the first bubble is greater than 30 microns. Through the above method, large bubbles can be filtered out during the immunological and / or blood cell detection of the sample, improving the accuracy of sample detection.

[0051] Furthermore, as Figure 5 and Figure 6 shown, when the baseline can be stabilized within a certain up-and-down fluctuation range, it indicates that the change amplitude of the baseline is relatively small, and then it can be considered that the first bubble has ended, and the end time of the first bubble is recorded (such as Figure 5 and Figure 6 in which the T1 moment is the initial appearance time of the first bubble, and the T2 moment is the end time of the first bubble). Specifically, when the control unit 12 confirms that within the third preset duration, the change amplitude of the baseline values corresponding to multiple sampling time points is less than the preset amplitude, it can be confirmed that the first bubble has ended, the end time T2 of the first bubble is recorded, and the bubble signal between the start time T1 when the first bubble appears and the end time T2 is filtered out. In this way, the end time of the first bubble can be accurately found, improving the accuracy of bubble recognition.

[0052] Further, when the control unit 12 confirms that within a third predetermined duration, the baseline value corresponding to each sampling time point is not 0, and the change amplitude of the baseline values corresponding to multiple sampling time points is less than a preset amplitude, it is confirmed that the first bubble ends, the end time of the first bubble is recorded, and the bubble signals between the initial appearance time and the end time of the first bubble are filtered out. In some application scenarios, due to the hardware characteristics of the optical receiver and the processing circuit, etc., if the obtained baseline pulse reaches the maximum value for a long time, then after the pulse ends, the obtained baseline value will be lower than the value before the pulse, and even be 0 for a period of time. A baseline value of 0 indicates that the first bubble is very large and the baseline drops all the way to 0. If the first bubble is large enough, it will last for a period of time at 0 (i.e., it satisfies the requirement of fluctuating within the preset amplitude range). In this case, it is inaccurate to consider the first bubble to end. In such a situation, additional conditions are required to determine the end of the first bubble. That is, until the baseline values corresponding to multiple sampling time points recover to a certain size (i.e., not zero) and can be stabilized within the preset amplitude range, it is considered that the first bubble ends. In this way, the end time of the first bubble can be judged more accurately, improving the accuracy of sample detection.

[0053] The sample analyzer 10 of the present application can accurately identify faults based on the changes in the baseline values of multiple sampling points, identify large air bubbles in the sample, filter out interfering particles, and improve the accuracy of sample detection.

[0054] The detection unit 11 may include a forward scattering channel and a classification channel. The control unit 12 can identify the first large-diameter bubble based on the original detection data collected by the forward scattering channel. For the identification method of the first bubble, please refer to the introduction of any of the above embodiments, which will not be elaborated here. Through the above method, large air bubbles can be filtered out when the sample is subjected to immunoassay and / or blood cell detection.

[0055] Optionally, in other embodiments, the detection unit 11 may further include a side scattering channel, a quantitative channel, etc.; the control unit 12 can identify the first bubble based on the original detection data collected by one or more of the forward scattering channel, the classification channel, the side scattering channel, and the quantitative channel, which is not limited here.

[0056] Further, when the detection unit 11 performs an immunoassay on the sample, the control unit 12 can identify the second small-diameter bubble through the classification channel and the forward scattering channel of the detection unit 11. Specifically, the control unit 12 identifies the non-fluorescent signal region in the detection data collected by the classification channel, and based on the non-fluorescent signal region and the original detection data of the forward scattering channel, the second bubble is identified, where the particle diameter of the second bubble is smaller than that of the first bubble.

[0057] When performing immunoassay on a sample, the classification channel only receives fluorescence signals. If it is a small bubble, no fluorescence signal or only a low fluorescence signal will be generated in the classification channel. The forward scatter detection pulse corresponding to the non-fluorescent signal region in the classification channel is a bubble, that is, the particle corresponding to the non-fluorescent signal region in the classification channel. If a pulse appears in the forward scatter channel, it is considered that the pulse is a second bubble and can be filtered out.

[0058] Therefore, when performing blood cell and immunoassay on a sample, the first bubble with a larger particle size can be filtered out by the Figure 2 identification method shown. When performing immunoassay on a sample, the second bubble with a smaller particle size can be filtered out by combining the classification channel and the forward scatter channel, improving the accuracy of sample detection.

[0059] The above are only the embodiments of the present application, and do not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present application, or directly or indirectly applied to other related technical fields, shall be included in the patent protection scope of the present application by the same token.

Claims

1. A sample analyzer, characterized in that, The sample analyzer includes: A detection unit for performing particle detection on a sample flowing through a detection area; A control unit connected to the detection unit, and the control unit is configured to: Control the detection unit to detect a sample flowing through the detection area, and collect the original detection data of the detection unit at a preset frequency to obtain an original detection data sequence at multiple sampling time points; Based on the original detection data sequence at the multiple sampling time points, obtain a baseline value corresponding to each sampling time point; When it is confirmed that within a first preset duration, the difference between the baseline values corresponding to two sampling time points is greater than or equal to a first fixed value, then obtain the baseline value corresponding to the latest sampling time point and obtain the average value of the baseline values corresponding to all sampling time points within a second preset duration before the latest sampling time point, where the second preset duration is greater than or equal to the first preset duration; Based on the baseline value corresponding to the latest sampling time point and the average value of the baseline values corresponding to all sampling time points within the second preset duration, confirm the initial appearance time of the first bubble.

2. The sample analyzer according to claim 1, wherein The control unit is further configured to: When it is confirmed that the difference between the baseline value corresponding to the latest sampling time point and the average value of the baseline values corresponding to all sampling time points within the second preset duration is greater than a second fixed value, then confirm the appearance of the first bubble, where the second fixed value is less than the first fixed value.

3. The sample analyzer according to claim 2, characterized in that, The ratio of the second fixed value to the first fixed value is: 1 / 4 - 3 / 4.

4. The sample analyzer according to claim 2, wherein The control unit is further configured to: when it is confirmed that the difference between the baseline value corresponding to the latest sampling time point and the average value of the baseline values corresponding to all sampling time points within the second preset duration is greater than the second fixed value, then confirm that the initial appearance time of the first bubble is the latest sampling time point.

5. The sample analyzer according to claim 1, characterized in that, The control unit is further configured to: calculate the mean value of the original detection data of each sampling time point and a predetermined number of sampling time points before and after it to obtain the detection mean value corresponding to each sampling time point; Use the detection mean value corresponding to each sampling time point and the minimum value in the original detection data of each sampling time point as the baseline value corresponding to each sampling time point.

6. The sample analyzer according to claim 1, wherein, The first preset duration is greater than the appearance time of a single pulse generated by particles in the sample, and the second preset duration is 1 - 2 times the first preset duration.

7. The sample analyzer according to claim 1, wherein, The control unit is further configured to: When it is confirmed that within a third preset duration, the change amplitude of the baseline values corresponding to multiple sampling time points is less than a preset amplitude, then confirm the end time of the first bubble, and filter out the bubble signal between the initial appearance time of the first bubble and the end time of the first bubble.

8. The sample analyzer according to claim 1, wherein The control unit is further configured to: When it is confirmed that within a third preset duration, the baseline value corresponding to each sampling time point is not 0, and the change amplitude of the baseline values corresponding to multiple sampling time points is less than a preset amplitude, then confirm the end of the first bubble.

9. The sample analyzer according to claim 1, characterized in that, The detection unit includes a forward scatter channel and a classification channel; The control unit is further configured to perform identification of the first bubble based on the original detection data collected by the forward scatter channel; The control unit is further configured to: identify a non-fluorescent signal region in the detection data collected by the classification channel, and identify a second bubble based on the non-fluorescent signal region and the original detection data of the forward scattering channel, wherein the particle size of the second bubble is smaller than that of the first bubble.

10. A method for bubble recognition of a sample analyzer, characterized in that, Based on the sample analyzer according to any one of claims 1-9, the bubble identification method includes: Controlling the detection unit to detect the sample flowing through the detection area, and collecting the original detection data of the detection unit at a preset frequency to obtain an original detection data sequence at multiple sampling time points; Based on the original detection data sequence at the multiple sampling time points, obtaining a baseline value corresponding to each sampling time point; When it is confirmed that within a first preset duration, the difference between the baseline values corresponding to two sampling time points is greater than or equal to a first fixed value, then obtaining the baseline value corresponding to the latest sampling time point and obtaining the average value of the baseline values corresponding to all sampling time points within a second preset duration before the latest sampling time point, wherein the second preset duration is greater than or equal to the first preset duration; Based on the baseline value corresponding to the latest sampling time point and the average value of the baseline values corresponding to all sampling time points within the second preset duration, confirming the initial appearance time of the first bubble.

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