Charge coupled device (CCD) multi-wavelength fluorescence microorganism curve analyzer

Abstract

The invention relates to the technical field of biological detection, in particular to a CCD (Charge Coupled Device) multi-wavelength fluorescence microorganism curve analyzer which is mainly used for monitoring and analyzing processes such as growth, metabolism and reaction of microorganisms in real time. According to the analyzer, a CCD (Charge Coupled Device) is adopted as a main detector, so that high-sensitivity and high-resolution detection on fluorescence signals of microorganisms is realized. CCD multi-wavelength fluorescence microorganism curve analysis is jointly formed by integrating an MCU microcontroller, a light path system, a CCD detection module, a motor control module, an automatic temperature control module, a data processing module, a light source driving module, a communication module and an image processing algorithm module. Algorithms of signal enhancement, real-time image analysis, accurate dynamic change capture and the like are introduced in the aspect of image processing algorithms. And accurate real-time monitoring and analysis can be provided. Powerful technical support is provided for research in multiple fields such as microbiological research, environment monitoring, food safety detection and medical diagnosis.

Description

Technical Field

[0001] The present invention relates to the field of biological detection instruments, and in particular to a biological detection instrument based on CCD multi-wavelength fluorescence microbial curve analysis. The instrument is mainly used to quickly and efficiently detect and analyze the growth curve of microorganisms, and provides real-time monitoring and accurate analysis of the growth dynamics of microorganisms through multi-wavelength fluorescence detection technology. Background Art

[0002] In recent years, the rapid development of biotechnology and microbial research has put forward higher requirements for efficient and accurate detection methods. The growth curve of microorganisms is an important indicator for studying the growth dynamics, metabolic characteristics and environmental adaptability of microorganisms. Although traditional microbial detection methods such as optical density method and plate count method can provide certain detection information, they have problems such as slow detection speed, cumbersome operation and low sensitivity, which can hardly meet the needs of modern biological research and industrial production.

[0003] With the development of fluorescence detection technology, multi-wavelength fluorescence detection technology has been widely used in the field of biological detection. This technology can simultaneously detect different fluorescent markers in a sample by using excitation light of different wavelengths, thus realizing multi-parameter analysis of the sample. However, existing multi-wavelength fluorescence detection equipment is often bulky, complex in structure, and expensive, making it difficult to be widely used in laboratories and field environments.

[0004] Limitations of traditional detection methods: 1. Plate count method: Although it can directly reflect the number of microorganisms, the operation is cumbersome and the detection cycle is long. It usually takes hours or even days to obtain results. Moreover, the plate count method has high requirements for sample processing and is easily interfered by environmental factors, resulting in poor repeatability. 2. Turbidimetry and optical density method: These two methods rely on detecting changes in the optical density of bacterial suspensions to indirectly reflect the growth of microorganisms. However, they have low sensitivity and it is difficult to detect low concentrations of microorganisms. In addition, since these methods rely on changes in optical density, they cannot distinguish different types of microorganisms and are easily affected by factors such as culture medium turbidity, and the accuracy of the test results is limited.

[0005] In view of the above background and needs, the present invention proposes a biological detection instrument based on CCD multi-wavelength fluorescence microbial curve analysis. The instrument combines a high-performance MCU control system, an advanced optical system and a CCD detector, and realizes real-time monitoring and analysis of microbial growth curves through multi-wavelength fluorescence detection technology. The instrument adopts an automated design and has high-throughput detection capabilities, which can greatly improve detection efficiency and sensitivity. Through the combination of WiFi module and host computer software, wireless transmission and real-time processing of data are realized, meeting the needs of modern biotechnology research and industrial applications for efficient, accurate and automated detection methods. Summary of the invention

[0006] The core goal of the present invention is to develop a microbial curve analysis instrument based on CCD multi-wavelength fluorescence technology, aiming to solve the problems of low sensitivity, low detection efficiency, and complex operation in the current field of microbial detection. With the continuous advancement of biotechnology, especially in the fields of medical diagnosis, environmental monitoring, and food safety, the demand for accurate monitoring and rapid analysis of microorganisms is increasing. The present invention significantly improves the efficiency and accuracy of microbial detection by integrating multi-wavelength fluorescence detection and high-precision control technology.

[0007] To achieve this goal, the present invention designs a highly integrated microbial curve analysis instrument, which contains multiple functional modules and builds a complete automated detection system. First, the instrument adopts an advanced optical system and is equipped with multiple LED light sources of different wavelengths, which can provide multi-wavelength excitation light for microbial samples. By using filters and condensers, the optical system can selectively collect fluorescence signals of specific wavelengths, thereby achieving the distinction and detection of different types of microorganisms.

[0008] The core control module of the present invention adopts STM32 series microcontroller, whose main frequency can reach 168MHz, has powerful processing ability and rich peripheral interfaces, and is used to coordinate the work of optical system, CCD detector, motor control module and other peripheral devices. The microcontroller integrates multi-channel analog-to-digital converter (ADC) and pulse width modulation controller (PWM), can efficiently process detection signals, and accurately control various operations of the instrument.

[0009] The CCD detector is a key component used in the present invention to capture fluorescent signals. A highly sensitive CCD sensor is selected to ensure efficient capture and high-resolution imaging of fluorescent signals. The CCD detector is connected to the MCU through a photoelectric detection module, converts the collected fluorescent signals into digital signals, and performs real-time data processing and analysis through the MCU.

[0010] The automatic temperature control module is an important component used to maintain a stable microbial growth environment in the present invention. The module integrates a high-precision temperature sensor and a PID control algorithm, and can automatically adjust the temperature in the sample chamber according to the needs of microbial growth to ensure that the microorganisms grow under optimal conditions. The temperature data is monitored in real time by the MCU, and combined with the WiFi module to transmit the data to the host computer software for further analysis.

[0011] The data processing module uses advanced digital signal processing technology. After preliminary processing by the MCU, the data will be transmitted to the host computer software through the WiFi module. The host computer software is not only responsible for data storage and visualization, but also integrates advanced data analysis algorithms, such as multi-dimensional curve fitting and statistical analysis, which can automatically generate microbial growth curves and predict microbial growth trends.

[0012] The light source driver module is responsible for adjusting the intensity and wavelength of the light source to meet different experimental requirements. The module is controlled by the MCU and can automatically adjust the working parameters of the light source according to the sample type and experimental requirements. The automatic control of the light source ensures the stability and consistency of the fluorescence signal detection and improves the reliability of the experimental results.

[0013] The communication module in the present invention adopts WiFi technology to provide an efficient and wide-area solution for wireless data transmission between the detection instrument and the host computer. Through the WiFi communication module, the user can remotely monitor the operating status of the instrument in real time, adjust the experimental parameters, and obtain the test results immediately through the host computer software. The module supports multi-device connection and is suitable for multi-user environments, so that different researchers can easily share data and work together. This design significantly improves the intelligence level and operation convenience of the detection instrument, is suitable for a variety of application scenarios, and provides users with more flexible remote control and data management functions.

[0014] In addition, the present invention introduces an algorithm module based on image processing to further improve the accuracy and stability of detection. The image processing algorithm includes steps such as image enhancement, denoising, edge detection and segmentation, which can intelligently process the fluorescent image acquired by the CCD and effectively enhance the contrast between the fluorescent signal and the background. By separating and analyzing fluorescent signals of different wavelengths, the algorithm can automatically identify and track the growth changes of microorganisms to ensure the high accuracy and consistency of the detection data. The image processing algorithm can not only eliminate environmental noise interference, but also support automated analysis of the dynamic changes of microorganisms, providing a solid technical foundation for the generation of microbial growth curves. The application of this algorithm module enables the detection instrument to maintain efficient and stable detection capabilities under complex detection environments.

[0015] In summary, the microbial detection instrument based on CCD multi-wavelength fluorescence microbial curve analysis provided by the present invention realizes efficient detection and intelligent analysis of microbial samples by integrating multiple advanced technologies. The instrument not only improves the sensitivity and accuracy of detection, but also greatly simplifies the operation process, providing strong support for applications in the fields of biomedicine, food safety and environmental monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly explain the technical details and operation processes in the embodiments of the present invention or the prior art, the drawings cited in the embodiments or the prior art descriptions are briefly described below. These drawings are intended to provide intuitive visual aids for the present invention and deepen the understanding of the present invention. As an important part of the specification, they constitute a complete explanation system together with the embodiments of the present invention. However, these drawings are not intended to limit the scope or content of the present invention, and they are merely auxiliary explanatory materials. In the drawings:

[0017] Figure 1 The system block diagram design of the CCD multi-wavelength fluorescence microbial curve analysis proposed by the present invention is presented;

[0018] Figure 2 The overall flow chart of instrument detection based on CCD multi-wavelength fluorescence microbial curve analysis proposed by the present invention is shown;

[0019] Figure 3 The overall flow chart of data processing based on an algorithm for CCD multi-wavelength fluorescence microbial curve analysis proposed by the present invention is shown.

[0020] Figure 4 The overall flow chart of the host computer operation based on CCD multi-wavelength fluorescence microbial curve analysis proposed by the present invention is shown.

[0021] Figure 5 The pin diagram of the main control chip STM32F407G-DISC1 based on CCD multi-wavelength fluorescence microbial curve analysis proposed in the present invention is shown.

[0022] Figure 6 The optical path schematic diagram of the CCD multi-wavelength fluorescence microbial curve analysis proposed by the present invention is shown.

[0023] Figure 7 A WiFi module chip diagram based on CCD multi-wavelength fluorescence microbial curve analysis proposed by the present invention is shown.

[0024] Figure 8 The present invention shows a semiconductor refrigeration chip diagram for temperature control based on CCD multi-wavelength fluorescence microbial curve analysis.

[0025] Fig. 9 The internal structure diagram of the CCD multi-wavelength fluorescence microbial curve analysis proposed by the present invention is shown.

[0026] Fig.10 The present invention shows a CCD module structure diagram based on CCD multi-wavelength fluorescence microbial curve analysis.

[0027] Fig.11The present invention shows a motor drive structure diagram based on CCD multi-wavelength fluorescence microbial curve analysis.

[0028] Fig.12 The figure shows the appearance structure diagram of a CCD multi-wavelength fluorescence microbial curve analysis proposed by the present invention.

[0029] Fig.13 A data output diagram based on CCD multi-wavelength fluorescence microbial curve analysis proposed by the present invention is shown. DETAILED DESCRIPTION

[0030] The technical solutions in the embodiments of the present invention will be described in detail below, and the corresponding drawings will be used for clear and comprehensive description. It should be clear that the embodiments mentioned are only examples of some of the present invention, and are not exhaustive of all possible implementation methods. Within the scope of the present invention, any other embodiments based on the embodiments of the present invention and obtained without creative changes should be deemed to belong to the protection scope of the present invention.

[0031] like Figure 1 As shown, the present invention provides a microbial curve analyzer based on CCD multi-wavelength fluorescence detection. The system uses STM32F407VGT6 as the core MCU, which is responsible for the coordination and control of various modules. The system is equipped with an efficient data processing module, and the fluorescence signal collected by the CCD detector is analyzed and processed in real time on the host computer through an algorithm. The host computer communicates bidirectionally with the hardware system through the WiFi module to realize the control of the experimental process and the reception and analysis of data. The system light source driver module controls the wavelength and brightness of the excitation light by adjusting the output intensity of the LED light source. The excitation light generated by the light source passes through the filter and condenser in the optical path system and accurately irradiates the sample to excite the fluorescence in the sample. The fluorescence emitted by the sample is captured by the CCD detector TCD1304DG after being focused by the optical path system, and the CCD detector converts the fluorescence signal into an electrical signal. The optical path system uses a high-quality filter to ensure that only fluorescence signals of a specific wavelength are collected. The analog signal output by the CCD detector is converted into a digital signal through the analog-to-digital conversion module and sent to the data processing module for processing. The data processing module conducts in-depth analysis of the CCD signal through filtering, curve fitting and signal enhancement, generates high-precision data of the microbial growth curve, and transmits the processed data to the host computer through the WiFi module. The host computer can monitor the experimental process in real time, and display the growth curve and fluorescence intensity distribution diagram of the microorganism through a graphical interface, providing users with detailed data analysis and reports. During the experiment, the automatic temperature control module cooperates with the temperature sensor to monitor the sample temperature in real time to ensure that the sample reacts under constant temperature conditions. The temperature control module automatically adjusts the power of the heater or refrigerator according to the detected temperature data to maintain a stable temperature environment.

[0032] like Figure 2 As shown, the instrument operation flow chart of the present invention shows the operating steps of the entire detection process. First, the instrument performs a self-test to ensure the normal operation of each module. Next, the sample is loaded into the instrument, and the appropriate temperature and oscillation frequency are set to simulate the optimal microbial growth environment. Then, the detection is started by emitting an excitation light of a specific wavelength through the optical path system, and the sample will emit fluorescence after being excited. The instrument detects the emitted light of the sample through the CCD, obtains data and sends the test results to the host computer or the cloud through the WiFi module. During the detection process, the system will continuously check whether the data transmission is successful. If the data is not successfully transmitted, it will be resent. Once the detection is completed, the instrument ends the operation and the entire process ends.

[0033] like Figure 3 As shown, the image processing algorithm module of the present invention mainly includes several key steps. First, the CCD detector collects the fluorescence signal and converts it into a digital signal. After entering the preprocessing stage, the algorithm performs noise elimination and baseline correction on the collected signal to ensure the purity of the signal. Then, the image enhancement algorithm will further optimize the image quality by adjusting parameters such as contrast and brightness to make the weak fluorescence signal clearer. The image segmentation algorithm is used to accurately distinguish the fluorescence intensity of different regions. This process is achieved by thresholding the light intensity of the signal, thereby separating the microbial reaction area from the background. The segmented image data will further enter the classification decoding module to decode the status of different microorganisms and judge their growth. After the processing steps of filtering and signal enhancement, the key characteristic parameters of the microbial growth curve are extracted, and a comprehensive analysis is performed in combination with multi-wavelength data to generate a complete growth curve. These data will be transmitted to the host computer software in real time for dynamic monitoring, helping researchers to understand the trend of microbial growth in real time.

[0034] like Figure 4 As shown, the real-time channel growth curve host computer flow chart based on CCD multi-wavelength fluorescence microbial curve analysis of the present invention mainly includes the following steps:

[0035] First, after the experiment starts, the host computer software establishes a connection with each module of the detection instrument through the WiFi communication module to ensure smooth data communication. The host computer software first sends an initialization command to start the light source driver module, CCD detector and automatic temperature control module to prepare for collecting the fluorescence data of the sample. Then, the host computer software sends a control command to the light source driver module to select and excite the LED light source of a specific wavelength, and the light source irradiates the excitation light onto the sample through the optical path system. The fluorescence signal emitted by the sample is captured by the CCD detector and converted into an electrical signal. The host computer software collects real-time fluorescence signal data. The received data will immediately enter the data processing module for real-time analysis, including processing steps such as filtering, curve fitting and data normalization. After processing, the data will be used by the host computer software to draw a growth curve in real time and display it on the user interface. Users can intuitively observe the changes in the fluorescence intensity of each sample through the interface and understand the growth status of the microorganisms. The host computer is also responsible for storing the data so that detailed analysis and report generation can be performed after the experiment. At the same time, the host computer software will continue to monitor various parameters during the experiment, such as temperature, light source status, etc., to ensure the stability of the experimental conditions. If there is any abnormality, the software will issue an alarm and record it in the log. The whole process forms an automated, real-time sample fluorescence analysis process. The host computer software, as the core control and analysis platform of the system, realizes real-time monitoring, data processing and storage of sample growth curves.

[0036] like Figure 5 As shown, in response to the demand for biological detectors based on CCD multi-wavelength fluorescence microbial curve analysis, the present invention selects the STM32F407G-DISC1 STLINK / V2-A (SWD only) chip based on the ARM Cortex-M4 core as the core control unit. The chip has a main frequency of 168MHz, a built-in floating-point unit and a rich peripheral interface, which can meet the needs of complex tasks such as efficient processing of CCD detection data, multi-wavelength light source control, temperature regulation and data transmission. The chip's built-in multiple timers and PWM output functions support precise light source control and motor drive, ensuring the stability of the optical path system and sample processing.

[0037] like Figure 6As shown, the optical path design of the present invention is intended to achieve efficient light transmission and precise wavelength selection. The entire optical path design starts with a xenon lamp as the light source. The xenon lamp is focused by a set of lenses to produce a light beam. The focused light beam is first preliminarily split by a grating, which separates light of different wavelengths. The separated light beam is directed to the first reflector, which redirects the light beam to the second grating to further screen out the light beam of the desired wavelength. This process enables the system to accurately control and select excitation light of a specific wavelength to meet the requirements of different experiments. The screened light beam continues to pass through the spectroscope, which divides the light beam into two parts, one part is directly guided to the photodiode for real-time monitoring of light intensity and stability, and the other part is output through optical fiber and finally irradiated onto the sample to be tested. Through this optical path design, the present invention achieves efficient light energy utilization and precise light wavelength selection, providing reliable excitation for CCD multi-wavelength fluorescence microbial curve analysis.

[0038] like Figure 7 As shown, the WiFi module of the present invention can transmit the detection data based on CCD multi-wavelength fluorescence microbial curve analysis to the host computer in real time. The WiFi module is connected to the core control unit of the system, and the fluorescence signal intensity and related data obtained by the CCD detector are efficiently and stably transmitted through the wireless communication protocol. Users can remotely monitor the growth curve of microorganisms through the host computer software or mobile devices, and obtain the analysis results in real time, further improving the convenience and intelligence level of the system. The WiFi module supports high-bandwidth data transmission, ensures the stable and rapid transmission of large amounts of data, and provides a strong technical guarantee for remote control and data sharing.

[0039] like Figure 8 As shown, the semiconductor refrigeration plate of the present invention generates a temperature difference by inputting current, so that one side absorbs heat and the other side releases heat. The heat-releasing side cooperates with a fan to dissipate heat, thereby effectively reducing the temperature of the experimental cavity. This design has the characteristics of high efficiency and fast response speed, and can accurately control the low-temperature environment. During the heating stage, the system provides uniform heat through the heating plate. The heating plate is made of resistive material, and its temperature is controlled by adjusting the input current. The heating process has the advantages of controllable temperature and uniform heating, which can ensure that the sample is tested under stable temperature conditions. The temperature control circuit is also combined with a high-precision temperature sensor for real-time monitoring. In conjunction with the control algorithm, the system can automatically adjust the power output of the refrigeration plate and the heating plate according to the set target temperature to maintain a constant temperature environment.

[0040] like Fig. 9As shown, the internal structure of the present invention includes a plurality of key components, which cooperate closely to realize the functions of the device. Specifically, the base plate (2) supports the entire device and cooperates with the bottom plate of the outer shell (1) to provide a stable foundation. The cover (3) cooperates with the base plate to protect the internal components, and there is a bracket (4) for installing the motor-driven temperature control board (5) to ensure the normal operation of the temperature control system of the device. In order to optimize the heat dissipation effect of the device, the heat dissipation component (7) and the heat dissipation copper block (8) are designed as a heat dissipation structure, which is connected to the centrifuge tube (9) through the centrifuge tube rack (6) to ensure that the temperature of the device remains stable during operation. In addition, the CCD module is installed below the heat dissipation copper block (8) and is located in the center of the device to avoid performance fluctuations caused by overheating.

[0041] like Fig.10 As shown, the CCD detection module used in the present invention has a compact structure and is mainly composed of an upper detection window and a lower CCD sensor. The detection window is arranged at the top of the module and has a plurality of small holes for the transmission of light signals. The CCD sensor is installed at the bottom of the module and is responsible for receiving and processing light signals from the sample. The entire module is fixed by a precise housing to ensure accurate transmission and detection of light signals. The various components inside the module are closely connected, which helps to improve detection efficiency and data accuracy.

[0042] like Fig.11 As shown, the motor drive structure of the present invention mainly includes a motor (6) mounted on a base, a slide rail (1) and a slider assembly connected to the motor. The motor drives the slider to perform precise linear motion on the slide rail through a transmission device. The drive structure is used to adjust the position of key components inside the analyzer, such as a light source, a filter or a sample tray, to ensure that fluorescence of different wavelengths can be accurately detected. This structure has high stability and accuracy, can meet the needs of multi-wavelength fluorescence detection, and at the same time reduce the interference of mechanical vibration on the detection results.

[0043] like Fig.12 As shown, the overall orientation view of the present invention is as follows: the left view shows the position of the power switch, the bottom view shows the bottom plate layout, the right view shows the shell assembly, heat dissipation holes, USB holes and audio holes, the front view shows the display screen and foot pads, the rear view is marked with the nameplate, letter nylon shaft and back cover, and the top view shows the design of the top of the device.

[0044] like Fig.13As shown in the figure, the trend of the number of different microorganisms changing over time reflects the accuracy and stability of the invented instrument in detecting the growth of microorganisms. Through these curves, the monitoring effect of the instrument on the number of microorganisms at different time periods can be clearly observed, indicating that the instrument has high resolution and accuracy and can capture the dynamic changes of microbial growth in real time. The growth curves of various microorganisms reflect the perfection of the invention's functions, indicating that it can adapt to the detection needs of different types of microorganisms and has a wide range of application potential.

[0045] Specifically, first, place the sample to be tested in the dedicated sample slot of the CCD multi-wavelength fluorescence analyzer. Then, the built-in multi-wavelength LED light source of the instrument will gradually emit light of different bands according to the set wavelength, and evenly irradiate the sample. At this time, the microorganisms in the sample will emit fluorescence signals of different intensities and wavelengths according to their types and states. The CCD sensor can accurately capture these weak fluorescence signals and transmit them to the data processing system in real time. The data processing system analyzes and processes the fluorescence signals captured by the CCD, and the system will draw the fluorescence response curve of the microorganism based on parameters such as fluorescence intensity and wavelength. This curve can intuitively reflect a variety of information about the microorganism. The signal after noise reduction and filtering is then deeply analyzed by the data system to generate high-precision analysis results.

[0046] Specifically, in the field of life science research, the CCD multi-wavelength fluorescence analyzer can monitor the growth and metabolic activities of microorganisms under different environmental conditions in real time, helping researchers explore the growth patterns of microorganisms; in drug testing, by recording the effects of different drugs on microbial fluorescence signals, researchers can evaluate the effectiveness of drugs and provide data support for drug optimization. It should be emphasized that the above description only shows some implementation cases of this application and does not mean to limit the scope of its patent protection. Any equivalent structural conversion of the contents described in this specification and drawings, or direct or indirect application to other related technical fields, under the guidance of the technical concept of this application, should be deemed to be included in the scope of patent protection of this application.

[0047] It should be emphasized that the above description only shows some implementation cases of this application and does not mean to limit the scope of its patent protection. Any equivalent structural conversion of the contents described in this specification and drawings, or direct or indirect application to other related technical fields under the guidance of the technical concept of this application, shall be deemed to be included in the scope of patent protection of this application.

Claims

1. The present invention relates to a biological detection instrument based on CCD multi-wavelength fluorescence microbial curve analysis, including a detection instrument body, which is composed of an MCU microcontroller, an optical path system, a CCD detection module, a motor control module, an automatic temperature control module, a data processing module, a light source drive module, a communication module and other devices, and is combined with an algorithm module based on image processing of the host computer software to analyze the microbial growth curve.

2. A biological detection instrument based on CCD multi-wavelength fluorescence microbial curve analysis according to claim 1, characterized in that: The MCU microcontroller is used to control and coordinate the various modules of the detection equipment; the MCU microcontroller adopts the STM32F407 series MCU, which has a main frequency of 168MHz, 1MB of Flash memory, 192KB of SRAM, and rich external setting interfaces. Through these interfaces, the optical path system, CCD detector, motor control module, automatic temperature control module, data processing module, light source drive module, and communication module are connected to achieve unified control and data transmission of various modules.

3. A biological detection instrument based on CCD multi-wavelength fluorescence microbial curve analysis according to claim 1, characterized in that: The optical path system is used to accurately guide multiple excitation lights of different wavelengths to the sample, and transmit the fluorescence signal emitted by the sample to the CCD detector; the optical path system includes multiple high-efficiency optical components, including reflectors, lens groups, spectroscopes and filters; one of the key components of the optical path system is the spectroscope, which is used to separate the multi-wavelength excitation light into respective monochromatic light beams, and select the appropriate wavelength for sample excitation according to experimental needs; the lens group is responsible for focusing the excitation light beam so that it can be concentrated on the designated area of ​​the sample, thereby ensuring that the sample is evenly illuminated; in addition, the reflector is used to adjust the direction of the light path to adapt to the needs of different experimental environments and sample positions.

4. A biological detection instrument based on CCD multi-wavelength fluorescence microbial curve analysis according to claim 1, characterized in that: The CCD detection module has the characteristics of high sensitivity and low noise, and can effectively capture the weak fluorescence signal emitted by the sample; the light source irradiates the excitation light of a specific wavelength onto the sample through the optical path system, and the sample emits a fluorescence signal after absorbing the excitation light. The CCD detector detects the fluorescence signal emitted by the sample and measures its intensity, thereby inferring the concentration of the sample under the excitation light; this detection method can accurately reflect the growth state and characteristics of the microbial sample, and provides a reliable technical means for real-time monitoring and analysis of microorganisms.

5. According to claim 1, a biological detection instrument based on CCD multi-wavelength fluorescence microbial curve analysis has a characteristic module setting, and the motor control is used to control the movement of the sample processing unit so as to accurately position the sample; the motor control module is combined with a stepper motor and a slave motor, a position feedback module and a speed control module to achieve precise positioning and smooth movement of the sample processing unit.

6. The biological detection instrument based on CCD multi-wavelength fluorescence microbial curve analysis according to claim 1, characterized in that: The automatic temperature control module includes a temperature sensor, a heating plate and a fan, which are used to monitor and adjust the system temperature; the temperature sensor adopts a high-precision digital temperature sensor, and the heating module and the fan are adjusted by the controller to achieve rapid adjustment and precise control of the system temperature.

7. The detection instrument according to claim 1, characterized in that: The data processing module is used to collect, process and analyze the fluorescence signal from the CCD detector to generate a microbial growth curve and perform relevant data statistics; the module integrates a high-performance microcontroller STM32F407 and converts analog signals into digital signals through an analog-to-digital converter (ADC) to facilitate subsequent precise processing.

8. The detection instrument according to claim 1, characterized in that: The light source driving module is used to accurately control the intensity, frequency and wavelength of the excitation light source to ensure that the sample is subjected to stable and appropriate lighting conditions; the light source driving module adopts pulse width modulation technology to achieve precise control of the brightness of the light source by adjusting the pulse width of the current; in addition, the light source driving module is also equipped with a feedback control system, which can monitor the working status of the light source in real time through an algorithm to ensure that the light source works under optimal conditions and avoid overheating or instability that affects the experimental results; the design of the light source driving module ensures that the light source can stably output the required lighting conditions during long-term operation of the detection instrument, thereby improving the repeatability and reliability of the experiment.

9. The detection instrument according to claim 1, characterized in that: The communication module adopts WiFi technology to realize wireless data transmission and remote control between the detection instrument and the host computer; the communication module can transmit data in a larger range through WiFi connection, is suitable for multi-user environment, and supports simultaneous connection of multiple devices; the module is designed with a multi-layer encryption communication mechanism to ensure the security of data transmission and prevent unauthorized access and tampering; the communication module also supports remote monitoring function, and users can view the detection progress, adjust experimental parameters, and obtain analysis results in real time through the host computer software, which improves the convenience of operation and intelligence level of the detection instrument.

10. The detection instrument according to claim 1, characterized in that: The host computer module is the core control and data analysis platform of the detection instrument; the host computer module receives the experimental data from the detection instrument in real time through the communication module of the detection instrument, and stores, processes and analyzes the data; the host computer module supports a variety of image processing algorithms: image denoising: eliminates interference caused by uneven ambient lighting or sensor noise to ensure that the collected image is clearer; grayscale and enhancement: converts the collected color image into a grayscale image, and improves the contrast through histogram equalization to make the outline of the sample more obvious; Through the above algorithms, the host computer module can accurately generate key analysis results such as microbial growth curves and fluorescence intensity distribution diagrams, providing users with intuitive visual data display.

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