智能铅鱼研究与开发

发布时间：2019-06-10 21:15

【摘要】：传统测流装置只具备流速仪开关量测量能力而无法测量水流流向和铅鱼三维姿态,主要采用铅鱼入水延时一段时间后测流的方法进行流速测量,这会因为人工估计延时、流速仪与水流流向间偏角、铅鱼在水下未稳定时测流而带来较大测量误差,导致低流速时测流时间延长,高流速时铅鱼未稳定测流带来的较大测量误差。采用缆道计数方式施测缆道水深,会因水面波浪、水深求算公式非最优、缆道位移测量误差、铅鱼重量等影响而导致测深精度不高。传统水文测量装置因能耗高而无法满足水文测站在汛期长时间监测水域水情的需求。本文在详细分析研究水文测流、测深原理的基础上,开发研制出智能铅鱼水文信息测量系统。该系统采用超低功耗电路延长装置工作时长,采用三维姿态电路实时测量铅鱼三维姿态并结合卡尔曼数据融合算法提高测流精度并获取水流流向,采用水深测量电路实时测量水深并结合涌浪传感器滤除波浪对水深测量精度影响的方法解决了人工测深精度低的问题并大幅提高水深测量精度。为了降低铅鱼测量装置功耗,本文提出了一种智能铅鱼超低功耗电路设计方法,该方法能够有效降低测量装置功耗。为了满足获取铅鱼三维姿态的需求,本文提出了一种利用姿态测量电路测量铅鱼姿态并结合卡尔曼数据融合算法解算铅鱼三维姿态的方法。实验结果表明,相比四元数解算算法,卡尔曼数据融合算法解算误差更小,相比传统测流方法,采用姿态测量电路能实时测量铅鱼水下三维姿态和水流流向,缩短低流速时测流时间,减小高流速时测流误差。为了提高水文测深精度,本文提出了一种水深测量电路,该电路采用水深压力传感器测量水深并结合涌浪传感器滤除波浪对测深精度的影响从而达到大幅提高测深精度的目的。
[Abstract]:The traditional flow measuring device only has the ability of measuring the flow direction and the three-dimensional attitude of the lead fish, which is mainly measured by the method of measuring the flow rate after the lead fish enters the water for a period of time, which will be due to the manual estimation of the delay. The deviation angle between the velocimeter and the flow direction leads to a large measurement error when the lead fish is unstable under water, which leads to the prolongation of the flow measurement time at low velocity and the large measurement error caused by the unstable current measurement at high velocity. Using the method of cable counting to measure the depth of cable will not be optimal because of the wave of water surface, the formula of water depth calculation, the measurement error of cable displacement, the weight of lead fish and so on, which will lead to the low precision of depth measurement. Because of the high energy consumption, the traditional hydrological measuring device can not meet the needs of hydrological stations to monitor the water regime for a long time in flood season. Based on the detailed analysis and study of hydrological current survey and bathymetric principle, an intelligent lead fish hydrological information measurement system is developed in this paper. The system adopts ultra-low power circuit to prolong the working time, adopts three-dimensional attitude circuit to measure the three-dimensional attitude of lead fish in real time, and combines Kalman data fusion algorithm to improve the accuracy of flow measurement and obtain the flow direction. The method of using water depth measuring circuit to measure water depth in real time and filtering out the influence of wave on the accuracy of water depth measurement with surge sensor solves the problem of low precision of manual bathymetric measurement and greatly improves the accuracy of water depth measurement. In order to reduce the power consumption of lead fish measuring device, an intelligent lead fish ultra-low power consumption circuit design method is proposed in this paper, which can effectively reduce the power consumption of the measuring device. In order to meet the needs of obtaining the three-dimensional attitude of lead fish, this paper presents a method to measure the attitude of lead fish by using attitude measurement circuit and to solve the three-dimensional attitude of lead fish combined with Kalman data fusion algorithm. The experimental results show that the error of Kalman data fusion algorithm is smaller than that of quaternion algorithm. Compared with the traditional flow measurement method, the attitude measurement circuit can measure the underwater three-dimensional attitude and flow direction of lead fish in real time. Shorten the time of flow measurement at low velocity and reduce the error of flow measurement at high velocity. In order to improve the accuracy of hydrological bathymetric, a water depth measuring circuit is proposed in this paper. the circuit uses water depth pressure sensor to measure water depth and filters out the influence of wave on bathymetric accuracy combined with surge sensor, so as to greatly improve the bathymetric accuracy.
【学位授予单位】：昆明理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：P335

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