Breeding air quality detection system based on spectral analysis and detection method thereof

Abstract

The invention relates to a spectral analysis-based breeding air quality detection system, which comprises: a sensor module for detecting the concentration of ammonia gas, carbon dioxide and dust in a breeding environment in real time, the sensor module comprising: an ammonia gas sensor for quantitatively detecting the absorption characteristic of ammonia gas to light with a specific wavelength; the carbon dioxide sensor is used for measuring the concentration by adopting non-dispersive infrared light and utilizing the characteristic that carbon dioxide absorbs infrared light; the dust sensor is used for calculating the dust concentration by measuring the light scattering condition of particulate matters in the air; the data processing module is used for receiving detection data from the sensor module; according to the breeding air quality detection system based on spectral analysis and the detection method thereof, various pollutants can be accurately monitored on the basis of a modern spectral analysis technology, and real-time monitoring and dynamic adjustment of a breeding environment are realized through an intelligent data processing and automatic control mechanism, so that the health of bred animals is guaranteed, and the breeding production efficiency is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to a breeding air quality detection system based on spectral analysis and its detection method. BACKGROUND

[0002] With the continuous development of the breeding industry, the air quality problem of the breeding environment has been increasingly concerned. Ammonia, carbon dioxide and dust are the main pollutants affecting the air quality of the breeding environment, which not only affect the health of animals, but also may lead to the spread of diseases and the decline of production efficiency. Animals in the long-term poor air quality environment may have respiratory diseases, decreased immunity and other problems, thereby affecting the economic benefits and sustainable development of the breeding industry. Therefore, how to realize the real-time monitoring and intelligent adjustment of the air quality of the breeding environment has become a technical problem to be solved in modern breeding industry.

[0003] The existing air quality monitoring technology usually adopts traditional detection equipment, which can only detect a single air pollutant, and lacks real-time and accuracy. In terms of ammonia detection, traditional methods mostly use chemical absorption method or electrochemical method, but these methods are easily affected by temperature and humidity changes, and have limited detection range, which cannot cope with the complex environmental changes in the breeding farm. In the detection of carbon dioxide, although non-dispersive infrared technology is widely used in indoor air quality monitoring, its performance and stability still need to be improved in the high concentration and dynamic environment of the breeding farm. In addition, for dust detection, the traditional light scattering method and electrical measurement method have low precision and are easily disturbed by factors such as airflow and temperature, and cannot provide accurate air quality data in real time.

[0004] In addition, the existing air quality control system often relies on manual adjustment and cannot automatically respond to environmental changes. Even if there are some intelligent devices, they are mostly aimed at the purification treatment of a single pollutant, and cannot comprehensively handle the air quality problems of ammonia, carbon dioxide and dust and other multiple pollutants. Moreover, the existing system usually lacks real-time data display and intelligent alarm function, and management personnel can only rely on regular manual inspection to monitor the breeding environment, which not only increases the management cost, but also affects the efficiency of timely intervention. SUMMARY

[0005] The purpose of the present application is to provide a breeding air quality detection system based on spectral analysis and its detection method, which can accurately monitor multiple pollutants based on modern spectral analysis technology, and realize real-time monitoring and dynamic adjustment of the breeding environment through intelligent data processing and automatic control mechanism, so as to protect the health of breeding animals and improve the production efficiency of breeding.

[0006] The technical scheme adopted by the present application to solve its technical problems is:

[0007] A breeding air quality detection system based on spectral analysis, characterized by comprising:

[0008] The sensor module is used to detect the concentration of ammonia, carbon dioxide and dust in the breeding environment in real time. The sensor module includes:

[0009] Ammonia sensor uses Fourier transform infrared spectroscopy to quantitatively detect ammonia's absorption characteristics of light of specific wavelengths;

[0010] The carbon dioxide sensor uses non-dispersive infrared and uses the property of carbon dioxide absorbing infrared light to measure concentration;

[0011] The dust sensor uses laser scattering to calculate the dust concentration by measuring the scattering of light by particles in the air;

[0012] A data processing module is used to receive detection data from the sensor module and perform real-time analysis and processing of ammonia, carbon dioxide and dust concentrations;

[0013] An air purification module automatically activates air quality-related purification equipment to purify the air based on the results analyzed by the data processing module. The purification equipment includes an ammonia filter, a carbon dioxide adsorption device, and a dust collector.

[0014] The display and control module is used to display the detected ammonia, carbon dioxide and dust concentrations in real time, provide alarm functions, and operate and adjust the system through the control interface.

[0015] Preferably, the system further includes a data storage module for storing historical detection data and air quality change trends, and supporting data backup and cloud storage.

[0016] Preferably, the air purification module can automatically start the purification equipment and perform air purification according to a preset safety threshold when it detects that the concentration of ammonia, carbon dioxide or dust exceeds the threshold.

[0017] Preferably, the data processing module includes an embedded computing platform or a single chip microcomputer for quickly collecting and processing signals from various sensors to ensure real-time response of the system.

[0018] Preferably, the display and control module is operated through a touch screen, PC or mobile phone APP, providing a convenient operation interface to help breeding managers understand and control the air quality in real time.

[0019] Preferably, the system also includes an intelligent alarm function. When the concentration of ammonia, carbon dioxide or dust exceeds the standard, the system can trigger an alarm to remind management personnel to take action.

[0020] Another technical problem to be solved by the present invention is to provide a method for detecting aquaculture air quality based on spectral analysis, which realizes air quality monitoring by the following steps:

[0021] The ammonia concentration was measured using Fourier transform infrared spectroscopy;

[0022] Use non-dispersive infrared to measure carbon dioxide concentration;

[0023] Measure dust concentration using laser scattering;

[0024] Transmit the detection data to the data processing module for real-time analysis and processing;

[0025] According to the analysis results, the relevant purification equipment is automatically started to purify the air and ensure the air quality of the breeding environment.

[0026] Preferably, the method for measuring ammonia concentration using Fourier transform infrared spectroscopy is:

[0027] Passing infrared light emitted by an infrared light source through a gas sample to be measured, wherein the gas sample contains ammonia;

[0028] The detector collects the absorption spectrum data of the infrared light after passing through the sample;

[0029] Performing Fourier transform on the collected infrared spectrum data to obtain an absorption spectrum of ammonia within the infrared spectrum range;

[0030] By identifying the absorbance of the characteristic absorption peak of ammonia, the concentration of ammonia in the sample is calculated;

[0031] The concentration of ammonia was determined based on the relationship between absorbance and ammonia concentration using the Bell-Lambert law.

[0032] Preferably, the method for measuring carbon dioxide concentration using non-dispersive infrared is:

[0033] The infrared light emitted by the infrared light source passes through the gas sample to be measured, wherein the gas sample contains carbon dioxide;

[0034] The intensity of infrared light after passing through the gas sample is detected by a sensor;

[0035] Using optical filters to selectively filter out wavelengths of light not related to the carbon dioxide absorption wavelength;

[0036] Calculate the absorbance of carbon dioxide in the gas sample based on the change in transmitted light intensity;

[0037] The carbon dioxide concentration is calculated from the absorbance according to the Bell-Lambert law.

[0038] Preferably, the method for measuring dust concentration using laser scattering is:

[0039] Using a laser source to emit a laser beam, the laser beam passes through an air flow containing dust particles;

[0040] Dust particles scatter the laser beam to generate scattered light;

[0041] Using an optical detector to receive the scattered light and convert it into an electronic signal;

[0042] Processing the received scattered light signal to obtain a change in scattered light intensity;

[0043] The concentration of dust particles is estimated based on the change in scattered light intensity.

[0044] The beneficial effects of the present invention are:

[0045] This solution uses different sensor modules (Fourier transform infrared spectroscopy, non-dispersive infrared, and laser scattering technology) to achieve multi-parameter, high-precision air quality monitoring; the data processing module performs real-time analysis of sensor data and automatically activates the corresponding air purification equipment (such as ammonia filters, carbon dioxide adsorption devices, and dust collectors) to adjust air quality in a timely manner and avoid the negative impact of harmful substances on animals; by combining with intelligent air purification modules, this solution can automatically activate purification equipment based on sensor monitoring data, realizing automated and efficient air purification processing.

[0046] Through the display and control module, the system can display the detected ammonia, carbon dioxide and dust concentrations in real time, and provide an alarm function, so that managers can quickly understand the breeding environment conditions and take timely measures; through the control interface, the system provides easy-to-operate functions, allowing users to quickly operate, adjust and manage, reducing operational complexity and improving the system's ease of use. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 The present invention is a flow chart of a method for detecting aquaculture air quality based on spectral analysis. DETAILED DESCRIPTION

[0048] The principles and features of the present invention are described below with reference to the accompanying drawings. The examples given are only used to explain the present invention and are not intended to limit the scope of the present invention. The following paragraphs describe the present invention in more detail by way of example with reference to the accompanying drawings. The advantages and features of the present invention will become more apparent from the following description and claims. It should be noted that the drawings are all in a very simplified form and are not in exact proportions. They are only used to facilitate and clearly illustrate the purpose of the embodiments of the present invention.

[0049] In the description of the present invention, it should be understood that the terms "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, features defined as "first", "second", etc. may explicitly or implicitly include one or more of the features. In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be directly connected, or indirectly connected through an intermediate medium, or it can be internal communication between two elements.

[0050] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this invention pertains. The terms used in this specification of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0051] Example

[0052] See Figure 1 As shown, a breeding air quality detection system based on spectral analysis is characterized by including:

[0053] The sensor module is used to detect the concentrations of ammonia, carbon dioxide and dust in the breeding environment in real time. The sensor module includes:

[0054] Ammonia sensor uses Fourier transform infrared spectroscopy to quantitatively detect ammonia's absorption characteristics of light of specific wavelengths;

[0055] The carbon dioxide sensor uses non-dispersive infrared and uses the property of carbon dioxide absorbing infrared light to measure concentration;

[0056] The dust sensor uses laser scattering to calculate the dust concentration by measuring the scattering of light by particles in the air;

[0057] A data processing module is used to receive detection data from the sensor module and perform real-time analysis and processing of ammonia, carbon dioxide and dust concentrations;

[0058] An air purification module automatically activates air quality-related purification equipment to purify the air based on the results analyzed by the data processing module. The purification equipment includes an ammonia filter, a carbon dioxide adsorption device, and a dust collector.

[0059] The display and control module is used to display the detected ammonia, carbon dioxide and dust concentrations in real time, provide alarm functions, and operate and adjust the system through the control interface.

[0060] By using Fourier transform infrared spectroscopy (FTIR) technology to detect ammonia, non-dispersive infrared technology (NDIR) to measure carbon dioxide concentration, and laser scattering technology to monitor dust, key air quality parameters in the breeding environment can be accurately and in real time obtained, ensuring that environmental quality is continuously monitored and optimized; the system can not only detect the concentration of various pollutants such as ammonia, carbon dioxide and dust, but also automatically start the corresponding air purification equipment for purification (such as ammonia filters, carbon dioxide adsorption devices and dust collectors), realizing intelligent and automated control, greatly reducing the need for manual intervention and improving the management efficiency of the breeding environment.

[0061] By real-time monitoring and dynamic adjustment of air quality, the system can effectively reduce the impact of harmful gases and dust in the breeding environment on animal health, improve air quality, promote animal growth, and increase breeding efficiency; equipped with an alarm function, when the concentration of ammonia, carbon dioxide or dust exceeds the safe range, the system will automatically alarm to prevent harmful environments from causing irreversible effects on animal health, and at the same time provide feedback to management personnel for timely processing.

[0062] Through the display and control module, users can view various air quality indicators in real time, conveniently monitoring and adjusting air quality. The operation interface is simple and clear, easy to operate and manage. This system has certain flexibility and scalability. It can customize and add other gas sensors or optimize purification equipment according to the needs of different farms, further improving the adaptability and practicality of the system. The intelligent startup and control of the air purification module can effectively reduce energy waste, optimize the air quality improvement process, and reduce the operating costs of the farm.

[0063] The system also includes a data storage module for storing historical detection data and air quality change trends, and supports data backup and cloud storage; the air purification module can automatically start the purification equipment and perform air purification based on a preset safety threshold when it detects that the ammonia, carbon dioxide or dust concentration exceeds the threshold.

[0064] The system monitors the concentrations of pollutants such as ammonia, carbon dioxide, and dust in real time. When concentrations of certain pollutants exceed preset safety thresholds, the air purification module automatically activates purification equipment. This automated regulation ensures the aquaculture environment remains within a safe range, significantly reducing the need for manual intervention and lowering management costs. The addition of a data storage module records historical air quality data and trends. This data allows farm managers to analyze changing patterns in pollutant concentrations, understand the distribution and evolution of pollution sources in the environment, promptly identify potential problems, and implement targeted measures. Data backup and cloud storage also ensure data security, prevent data loss, and facilitate remote access and management.

[0065] By continuously optimizing air quality, the system helps improve the health of farmed animals and reduces respiratory illnesses, immune system impairment, and other issues caused by air pollution. This not only improves animal growth and productivity but also potentially reduces economic losses due to illness. Traditional air quality management often relies on manual inspection and intervention, which not only increases management difficulty and time costs but also exposes them to errors and delays. The system's automated monitoring and adjustment capabilities effectively avoid these issues, ensuring a stable and controllable environment.

[0066] If the system detects that air quality indicators exceed the set safety threshold, it will immediately issue an alarm. This early warning mechanism allows managers to respond quickly and take appropriate purification or corrective measures to prevent further deterioration of air pollution. Cloud storage and data trend analysis provide managers with detailed air quality trends and patterns, making decision-making more scientific and reasonable. For example, air purification plans can be optimized based on data analysis to avoid unnecessary energy waste or reduce the cost of excessive pollutant purification. As the scale of the farm expands or the air pollution problem changes, the system can be remotely updated and expanded through the cloud platform, allowing for rapid adaptation to new needs or challenges and ensuring the system's long-term applicability.

[0067] The data processing module includes an embedded computing platform or a single-chip microcomputer, which is used to quickly collect and process signals from various sensors to ensure real-time response of the system; the display and control module is operated through a touch screen, PC or mobile phone APP, providing a convenient operation interface to help breeding managers understand and control air quality in real time; the system also includes an intelligent alarm function. When the ammonia, carbon dioxide or dust concentration exceeds the standard, the system can trigger an alarm to remind management personnel to take action.

[0068] The data processing module, based on an embedded computing platform or single-chip microcomputer, efficiently and in real time collects and processes data from various sensors. This ensures the system can quickly respond to changes in pollutant concentrations, reducing air quality issues caused by latency. This enables the system to promptly adjust or activate purification equipment to ensure a safe and healthy farming environment. The system provides a convenient user interface through a touch screen, PC, or mobile app display and control module. These devices allow managers to monitor air quality in real time, view data trends, and perform necessary control operations anytime, anywhere. Mobile apps are particularly convenient for remote management, ensuring timely adjustments to air quality even when not on-site.

[0069] The intelligent alarm function triggers an alarm when ammonia, carbon dioxide, or dust concentrations exceed safe thresholds. This function greatly reduces the risk of human oversight or omission, ensuring that managers are promptly alerted and can take swift action (such as activating purification equipment or increasing ventilation) if an anomaly occurs. This helps prevent the negative impact of air pollution on the farming environment and animal health. The system's automated operation reduces the burden of manual monitoring, allowing farm managers to focus on other more complex tasks. Real-time monitoring and alarm functions also improve work efficiency, allowing managers to make the most effective decisions in the shortest possible time.

[0070] By rapidly collecting and processing sensor data, the system can accurately capture changing trends in air pollutants, enabling managers to more precisely control air quality. The combination of intelligent alarms, real-time displays, and control methods effectively avoids quality issues caused by human error or delayed response. The system's design allows farm managers to quickly and conveniently perform daily maintenance through a simple interface. If system expansion or upgrades are necessary, the embedded platform and application-based architecture offer flexible solutions to meet future needs. The system records air quality data, allowing managers to review historical data and analyze and optimize air quality issues. This data is valuable for long-term aquaculture management and decision-making, helping to optimize air purification strategies and improve aquaculture environment management.

[0071] A method for detecting aquaculture air quality based on spectral analysis, which implements air quality monitoring through the following steps:

[0072] The ammonia concentration was measured using Fourier transform infrared spectroscopy;

[0073] Use non-dispersive infrared to measure carbon dioxide concentration;

[0074] Measure dust concentration using laser scattering;

[0075] The detection data is transmitted to the data processing module for real-time analysis and processing;

[0076] According to the analysis results, the related purification equipment is automatically started to purify the air, ensuring the air quality of the breeding environment.

[0077] Fourier transform infrared spectroscopy, non-dispersive infrared, and laser scattering technology can provide high-precision gas and dust concentration measurements. Fourier transform infrared spectroscopy can accurately measure ammonia concentration, non-dispersive infrared can accurately detect carbon dioxide concentration, and laser scattering method can accurately measure dust concentration. These technologies can provide more reliable data to help managers understand the concentration of various pollutants in the breeding environment in real time, ensuring the accuracy and reliability of the data.

[0078] By transmitting the detection data to the data processing module for real-time analysis and processing, the system can automatically start the purification equipment when the air quality index exceeds the standard. This automatic control method can perform air purification operations in a timely manner when the pollutant concentration reaches the preset threshold, avoiding the lag of human operation and ensuring the stability and safety of the breeding environment.

[0079] The system can realize real-time monitoring and control without human intervention, significantly reducing the need for manual intervention. Breeding managers do not need to constantly monitor environmental data and can focus on other aspects, improving overall work efficiency. The automatic operation of the system not only saves time and labor costs, but also ensures the accuracy and timeliness of environmental control, thereby improving the management level of the farm.

[0080] The method for measuring ammonia concentration using Fourier transform infrared spectroscopy is as follows:

[0081] The infrared light emitted by the infrared light source passes through the gas sample to be measured, which contains ammonia gas;

[0082] The absorption spectrum data of the infrared light passing through the sample is collected by the detector;

[0083] The collected infrared spectrum data is subjected to Fourier transform to obtain the absorption spectrum of ammonia in the infrared spectrum range;

[0084] The absorbance of the characteristic absorption peak of ammonia is identified to calculate the concentration of ammonia in the sample;

[0085] The relationship between absorbance and ammonia concentration is determined according to the Beer-Lambert law to determine the concentration of ammonia.

[0086] The Fourier transform infrared spectroscopy technology can detect the characteristic absorption peak of ammonia gas and obtain the concentration of ammonia gas through accurate spectral analysis. Due to the high resolution of FTIR technology, it can accurately identify the characteristic absorption band of ammonia gas in a complex environment, ensuring that the measurement result has high sensitivity and accuracy; this method is realized through spectral analysis, without physical sampling or chemical treatment of the sample, so it belongs to a non-destructive testing method. This is particularly important for long-term monitoring and environmental protection, which can avoid damage to the sample and ensure the long-term reliability of the measurement data.

[0087] The Fourier transform infrared spectroscopy technology has a fast data acquisition speed, which can obtain the concentration of ammonia gas in the air in real time, and quickly analyze and process the infrared spectrum data through Fourier transform. This makes the method suitable for dynamic monitoring of ammonia concentration changes in the environment, timely response and adjustment, so as to ensure the safety and stability of the breeding environment or other places where ammonia monitoring is required; FTIR technology can distinguish the characteristic absorption peaks of different gases and has strong selectivity. By identifying the characteristic absorption peak of ammonia, the interference of other gases or substances can be effectively avoided, ensuring the accuracy of the measurement. This is particularly important for complex environments where multiple gases coexist.

[0088] Through the combination of Fourier transform and Beer-Lambert law, the calculation process of ammonia concentration is relatively direct and does not require complex post-processing. Using the linear relationship between absorbance and concentration, the ammonia concentration can be easily obtained, and the monitoring and alarm functions can be completed automatically through the system.

[0089] The method for measuring the concentration of carbon dioxide using non-dispersive infrared is as follows:

[0090] The infrared light emitted by the infrared light source passes through the gas sample to be measured, which contains carbon dioxide;

[0091] The intensity of the infrared light after passing through the gas sample is detected by the sensor;

[0092] An optical filter is used to selectively filter out other wavelengths that are not related to the absorption wavelength of carbon dioxide;

[0093] According to the change of the transmitted light intensity, the absorbance of carbon dioxide in the gas sample is calculated;

[0094] According to the Beer-Lambert law, the concentration of carbon dioxide is calculated using the absorbance.

[0095] The method selectively filters out other wavelengths of light unrelated to the carbon dioxide absorption wavelength through an optical filter, making the measurement highly selective. Since carbon dioxide has unique absorption characteristics at specific infrared wavelengths, NDIR technology can accurately detect the concentration of carbon dioxide, reducing the influence of other gases or spectral interference, thereby ensuring the accuracy of the measurement; Non-dispersive infrared technology has the characteristics of fast response, which can realize real-time and continuous monitoring of carbon dioxide concentration. This is suitable for environments that require real-time feedback and control, such as farms, greenhouses, industrial production lines, etc., to ensure that the carbon dioxide concentration is always within a safe or set range, avoiding excessive or excessive concentration affecting environmental quality or work safety.

[0096] NDIR technology is a non-contact, non-destructive detection method that does not require sampling or processing of samples. The gas sample is not changed or contaminated, so it can be detected for a long time and multiple times, suitable for applications that require long-term monitoring, such as air quality monitoring, climate research, etc.; Since the design of NDIR sensors is simple and stable, the maintenance cost is low. It does not involve complex mechanical parts or chemical reagents, so it has a longer service life and lower maintenance requirements than other gas detection methods (such as chemical reaction method), suitable for long-term use.

[0097] Non-dispersive infrared technology has strong adaptability to environmental factors such as temperature and humidity, so it can work stably under various environmental conditions. Whether indoors or outdoors, NDIR sensors can provide reliable carbon dioxide concentration measurement data, widely applicable to various application scenarios; NDIR technology can quickly obtain the change in infrared light intensity after passing through the gas sample and calculate the carbon dioxide concentration through the Beer-Lambert law. This method is fast and can give accurate carbon dioxide concentration in real time without complex processing steps.

[0098] The method for measuring dust concentration using laser scattering is as follows:

[0099] Use a laser source to emit a laser beam, which passes through an air flow containing dust particles;

[0100] The dust particles scatter the laser beam, producing scattered light;

[0101] Use an optical detector to receive the scattered light and convert it into an electronic signal;

[0102] Process the received scattered light signal to obtain the change in scattered light intensity;

[0103] Calculate the concentration of dust particles according to the change in scattered light intensity.

[0104] Laser scattering technology can detect extremely small dust particles in the air with high sensitivity. Because the laser beam is highly directional, the intensity of the scattered light signal is closely related to the number, size, and distribution of dust particles. By precisely analyzing changes in scattered light intensity, the dust concentration can be accurately calculated. This enables the technology to maintain high measurement accuracy even in low-concentration dust environments.

[0105] Laser scattering allows for real-time, continuous dust concentration measurement. Without interrupting the environment or taking samples, it continuously monitors changes in airborne dust concentration. This is particularly useful in environments requiring immediate response, such as industrial production workshops and mining areas, as it allows for the timely detection of fluctuations in dust concentration and the implementation of necessary control measures to ensure a safe working environment.

[0106] Laser scattering is a non-contact detection method that eliminates direct contact with dust particles and consumes no reagents or other consumables. This means the measurement process is simpler and cleaner, reducing the frequency of maintenance and parts replacement, and avoiding potential contamination or measurement errors caused by contact. Furthermore, the lack of chemical reagents reduces operating costs and environmental impact.

[0107] This embodiment also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method for visually detecting surface defects of metal foil as described above is implemented.

[0108] This embodiment also provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the method for visually detecting surface defects of metal foil as described above is implemented.

[0109] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0110] Those skilled in the art will clearly understand that for the sake of convenience and brevity in description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above.

[0111] The above embodiments of the present invention are not intended to limit the scope of protection of the present invention, and the implementation methods of the present invention are not limited thereto. All other modifications, replacements or changes made to the above structures of the present invention based on the above contents of the present invention, in accordance with common technical knowledge and customary means in this field, without departing from the above basic technical ideas of the present invention, should fall within the scope of protection of the present invention.

Claims

1. A breeding air quality detection system based on spectral analysis, characterized in that: Includes: The sensor module is used to detect the concentrations of ammonia, carbon dioxide and dust in the breeding environment in real time. The sensor module includes: Ammonia sensor uses Fourier transform infrared spectroscopy to quantitatively detect ammonia's absorption characteristics of light of specific wavelengths; The carbon dioxide sensor uses non-dispersive infrared and uses the property of carbon dioxide absorbing infrared light to measure concentration; The dust sensor uses laser scattering to calculate the dust concentration by measuring the scattering of light by particles in the air; A data processing module is used to receive detection data from the sensor module and perform real-time analysis and processing of ammonia, carbon dioxide and dust concentrations; An air purification module automatically activates air quality-related purification equipment to purify the air based on the results analyzed by the data processing module. The purification equipment includes an ammonia filter, a carbon dioxide adsorption device, and a dust collector. The display and control module is used to display the detected ammonia, carbon dioxide and dust concentrations in real time, provide alarm functions, and operate and adjust the system through the control interface.

2. The aquaculture air quality detection system based on spectral analysis according to claim 1 is characterized in that: The system also includes a data storage module for storing historical detection data and air quality change trends, and supports data backup and cloud storage.

3. The aquaculture air quality detection system based on spectral analysis according to claim 1 is characterized in that: The air purification module can automatically start the purification equipment and perform air purification according to a preset safety threshold when it detects that the concentration of ammonia, carbon dioxide or dust exceeds the threshold.

4. The aquaculture air quality detection system based on spectral analysis according to claim 1 is characterized in that: The data processing module includes an embedded computing platform or a single chip microcomputer, which is used to quickly collect and process signals from various sensors to ensure real-time response of the system.

5. The aquaculture air quality detection system based on spectral analysis according to claim 1 is characterized in that: The display and control module is operated through a touch screen, PC or mobile phone APP, providing a convenient operation interface to help farm managers understand and control air quality in real time.

6. The aquaculture air quality detection system based on spectral analysis according to claim 1 is characterized in that: The system also includes an intelligent alarm function. When the concentration of ammonia, carbon dioxide or dust exceeds the standard, the system can trigger an alarm to remind management personnel to take action.

7. A method for detecting aquaculture air quality based on spectral analysis, characterized in that: Air quality monitoring can be achieved through the following steps: The ammonia concentration was measured using Fourier transform infrared spectroscopy; Use non-dispersive infrared to measure carbon dioxide concentration; Measure dust concentration using laser scattering; Transmit the detection data to the data processing module for real-time analysis and processing; According to the analysis results, the relevant purification equipment is automatically started to purify the air and ensure the air quality of the breeding environment.

8. The method for detecting aquaculture air quality based on spectral analysis according to claim 7, wherein: The method for measuring ammonia concentration using Fourier transform infrared spectroscopy is: Passing infrared light emitted by an infrared light source through a gas sample to be measured, wherein the gas sample contains ammonia; The detector collects the absorption spectrum data of the infrared light after passing through the sample; Performing Fourier transform on the collected infrared spectrum data to obtain an absorption spectrum of ammonia within the infrared spectrum range; By identifying the absorbance of the characteristic absorption peak of ammonia, the concentration of ammonia in the sample is calculated; The concentration of ammonia was determined based on the relationship between absorbance and ammonia concentration using the Bell-Lambert law.

9. The method for detecting aquaculture air quality based on spectral analysis according to claim 7, wherein: The method for measuring carbon dioxide concentration using non-dispersive infrared is: The infrared light emitted by the infrared light source passes through the gas sample to be measured, wherein the gas sample contains carbon dioxide; The intensity of infrared light after passing through the gas sample is detected by a sensor; Using optical filters to selectively filter out wavelengths of light not related to the carbon dioxide absorption wavelength; Calculate the absorbance of carbon dioxide in the gas sample based on the change in transmitted light intensity; The carbon dioxide concentration is calculated from the absorbance according to the Bell-Lambert law.

10. The method for detecting aquaculture air quality based on spectral analysis according to claim 7, characterized in that: The method for measuring dust concentration using laser scattering is: Using a laser source to emit a laser beam, the laser beam passes through an air flow containing dust particles; Dust particles scatter the laser beam to generate scattered light; Using an optical detector to receive the scattered light and convert it into an electronic signal; Processing the received scattered light signal to obtain a change in scattered light intensity; The concentration of dust particles is estimated based on the change in scattered light intensity.

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