一种光电复合式水体石油烃类污染物厚度的无线传感方法及装置

本发明公开一种光电复合式水体石油烃类污染物厚度的无线传感方法及装置，蓝光LED灯阵列发出的经第一测量池的光通过硅光电池阵列接收后传输至控制单元；控制单元根据接收来的信号检测出石油和海水分界线的初步位置；控制单元根据所述初步位置的数据驱动电机将线阵CCD移动到石油和海水分界线的初步位置，再通过线阵CCD检测出石油和海水分界线的精确位置；最后控制单元将该区域的位置信息和石油层的厚度信息通过无线通信模块发送给控制终端。本发明的优点：操作方便，成本低，精度高等优点，可通过机载、船载投弃式对水体油膜进行实时测量，能够适应实际环境下的复杂情况，实时测量水体石油烃类污染物厚度

Phase demodulation type petroleum hydrocarbon pollutant identification device

本实用新型涉及一种相位解调式石油烃类污染物鉴定装置，装置中控制器输出控制信号至光源模块，光源模块输出的光源照射到采集模块中的样品池中；信号采集模块采集被测样品激发的光传送至数据转换模块，数据转换模块与控制器进行双向连接；光源模块中第一激光二极管和第一准直透镜的几何中心在一条直线上；第二激光二极管和第二准直透镜的几何中心在一条直线上；由第一激光二极管到第一准直透镜的射线与由第二激光二极管到第二准直透镜的射线同向平行；第一准直透镜与第二准直透镜与样品池相邻。本实用新型鉴定速度快、不会产生其它污染；采用双通道光源结构，能够产生稳定、充足的光源，各通道之间信号传输隔离、独立，具有极高的测量准确性

Spectral analysis method based on Gaussian multi-peak fitting

本发明公开一种基于高斯多峰拟合的光谱解析方法，先确定含待定高斯特征参数的吸收拟合函数，对拟合误差进行数学建模，然后确定迭代初值单元的中心坐标和迭代步长，持续迭代、比较、改变迭代步长直至求得最优拟合误差，再由最优拟合误差反推出相应分割单元中心坐标值，即待求高斯特征参数，确定吸收拟合函数，从而将混合光谱分解成多个分峰。本发明优点是：高斯函数曲线和光谱数据曲线具有很好的亲和性，可以表达谱图中峰形、峰高和峰位等具有明确物理意义的参数；将混合吸收光谱曲线分解为若干个高斯函数曲线，可以保持原始光谱数据的有效信息，将原始光谱数据统一为少量唯一确定的高斯特征参数，实现简化光谱数据、研究精细结构的目的

Nitrate Measurement in the Ocean Based on Neural Network Model

Nitrate concentration is an important indicator for the marine ecosystem.Compared with laboratory chemical methods such as Cadmium-Reduction method,in-situ nitrate optical sensor is much faster and reagent-free in a long time and continuous monitoring.Partial Least Squares(PLS)method is often used in ultraviolet absorption spectrum modeling,which is difficult to optimize and has low generalization ability.The neural network can compel any no-linear function by any precision,which has high generalization ability in the modeling.A neural network model is established in the in-situ nitrate sensor to measure the nitrate concentration in seawater in which the nitrate concentration range is 30~750mug·L~(-1).Double-hidden layer neural network model is determined to adopt by contrasting performance of single-hidden layer and double-hidden layer to measure nitrate concentration,the input layer is absorption spectrum from 200to 275nm,the output layer is nitrate concentration,and sigmoid function is used as the activation function.Gradient descent method is used to update weighting parameters for the neural network of each layer,after 55 000times iteration,network training is conducted based on the learning rate of 0.26. After validation for the blind test of the model through 8-group randomized validation data,the nitrate concentration using double-hidden layer neural network model is higher in linear correlation to its actual concentration(R~2=0.997)in which the Root Mean Squared Error is 10.864,average absolute error is 8.442mug·L~(-1),average the relative error is 2.8%.Compared with single-hidden layer neural network model,the double-hidden layer neural network model has higher accuracy in which the average relative error is reduced by 4.92%,the Root Mean Squared Error of PLS is 4.58%using the same spectral data,while the mean relative error is 11.470.The result shows that the neural network model is much better than the Partial Least Squares model under certain conditions.It verifies the superiority of the neural network model applied to the nitrate concentration measurement by ultraviolet absorption spectrometry.The application test was carried out on theEnvironmental Monitoring 01 monitoring vessel of the Ministry of Natural Resources,the measurement results are basically identical with the laboratory method in 11stations,which is further proved from the reliability and practicality

硫和某些微量元素与大骨节病关系的研究

本所地方病环境研究组自1969—1974年，在陕西渭北高原等地区对大骨节病区的生态化学环境因素进行了大量调查研究。通过研究提出以下重要结果，使大骨节病的病因研究取得明显进展：(一)大骨节病是与一定的生物气候类型和相应的土壤生物地球化学相联系的地方性疾病。该病与地形、母岩以及水土流失影响到水、土中的易溶元素迁移以至缺乏有密切关系。(二)否定了当时盛行的该病是饮水缺乏硫、镁元素的看法，提出饮水缺乏硫、镁不是致病因素，而饮水中的硒低及粮食含硒偏低是值得注意的因素。(三)提出病区的水化学特点及粮食元素特点，并对铜、锰等防治该病做出了初步评价