激光诱导荧光水体叶绿素a浓度监测仪器研制

叶绿素a浓度是反映水质的重要参数之一，常作为水产养殖、渔场预测、环境保护等领域的重要评价指标。针对现有叶绿素a监测仪器实时性差、自动化程度低、环境干扰严重等问题，该研究以实时监测叶绿素a浓度为主要目标，提出了环境光校正算法和数据处理算法，设计了一种基于激光诱导荧光技术的水体叶绿素a浓度监测装置。该装置可向水体发射波长440 nm的激光，诱导激发叶绿素a产生中心波长680 nm的荧光，利用可见光传感器获取叶绿素a受激产生的680 nm荧光强度，即可实现对叶绿素a浓度的监测。以绿藻门小球藻和蓝藻门铜绿微囊藻为对象，利用680 nm荧光值和叶绿素a浓度的线性关系建立拟合模型，模型决定系数R²为0.99；基于统计分析法设计的数据处理可有效剔除误差数据，提高测量结果的稳定性；利用环境光校正算法可有效降低环境光对测量结果的干扰。在仪器稳定性试验中，通过测量激光模块的供电电流和光谱模块的440 nm通道光强值，4 min后两者的标准差系数均为0.001，皮尔逊相关系数为0.84，表明可通过控制电流强度控制激光输出。在性能验证试验中，2组不同光照强度和6组不同藻种的待测水样的平均测量误差在5.48%以内。研究结果可为水质监测领域提供设备支持。

Monitoring instrument of the water Chlorophyll-a concentration with laser-induced fluorescent

Water quality monitoring is of great significance to maintaining human health, environmental protection and sustainable economic development. Much attention has also been drawn to water quality safety in recent years. Among them, the concentration of chlorophyll-a is one of the most important indicators of water quality in the fields of aquaculture, fishery management, and environmental protection. Multi-point deployment and continuous monitoring are then required to accurately assess the overall evolution of water quality in large-scale water areas. However, the current instruments of chlorophyll detection are limited for the implementation of large-scale water body monitoring, due to the high price and low degree of automation. In this study, a monitoring device was designed to detect the water chlorophyll-a concentration using laser-induced fluorescence technology. An ambient light correction and data processing were also proposed for the real-time monitoring of chlorophyll-a concentration. The laser light was emitted with a wavelength of 440 nm into the water body, in order to induce and excite chlorophyll-a for the fluorescence with a central wavelength of 680 nm. The concentration of chlorophyll-a was then monitored using the visible light sensor in the device, indicating the 680 nm fluorescence intensity excited by chlorophyll-a. There was a low overall manufacturing cost of the device. Low-power device design introduced the standby and serial port wake-up modes for online automatic monitoring. The two-way communication module was used to realize the data interaction. Data processing was evaluated to reduce the influence of the non-uniform distribution of chlorophyll-a in the water body on the measurement using statistical analysis. The mean value was calculated in time and space. A stable and accurate measurement was achieved in the instrument. An ambient light correction was proposed to reduce the impact of ambient light changes on the instrument measurement. A similar corrected value of the 680 nm light intensity was obtained in the water body chlorophyll-a with the same concentration under 6 groups of ambient light. Experiments show that this device effectively reduced the interference of ambient light on the measurement. The instrument stability test was carried out to observe the power supply circuit of the laser module and the 440 nm light intensity value, where the standard deviation coefficients were both 0.001 after 4 minutes, and the Pearson correlation coefficient was 0.84. It indicated that the laser output was controlled by the current intensity. A short time was obtained for the laser module power supply current to reach a stable state after precisely controlling the current, further reducing the overall power consumption of the instrument. 20 groups of water samples were configured with different chlorophyll-a concentrations using Chlorella chlorophyll in the instrument calibration test, referring to the range of chlorophyll-a concentration under different water bloom levels. The fitting model was established using the linear relationship between the fluorescence value at 680nm and the concentration of chlorophyll-a, where the coefficient of determination R² was 0.99. In the performance verification test, the green algae Chlorella and Microcystis aeruginosa were used to prepare 6 groups of water samples to be tested with different dominant algae species. The average measurement error of the instrument was within 5.48% under 2 groups of different light intensities. The test results show that the instrument performed stably to effectively detect the samples to be tested. There was no significant effect of the chlorophyll content in the water samples on the detection, due to the different types of algae, indicating the high detection accuracy. The finding can provide more convenient, cost-effective equipment support in the field of water quality monitoring, in order to realize all-weather monitoring chlorophyll-a concentration.