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首页> 外文会议>IEEE International Conference on Control Applications >Particle filters for estimating average grain diameter of material excavated by hopper dredger
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Particle filters for estimating average grain diameter of material excavated by hopper dredger

机译：用于估计料斗挖泥船挖掘出材料平均粒径的颗粒过滤器

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Hopper dredgers are massive ships that excavate sediments from the sea bottom while sailing. The excavated material is then transported and discharged at a specified location. The efficiency of this process is highly dependent on the detailed knowledge of the excavated soil. When the soil is composed mainly of sand, the parameter of the greatest importance is the average grain diameter. This, however cannot be directly measured by available sensors. Therefore, in this paper a particle filter is proposed to estimate the average grain diameter. The estimation is based on online measurements of the total height of the mixture in the hopper, total mass, the incoming mixture density and flow-rate and the height of a sand bed, together with estimates of the outgoing mixture density and flow-rate. The loading process is naturally decomposed into three phases and the filter is applied to the first two phases. In order to match different types of nonlinearities, a separate observer is proposed for each phase under consideration. This increases the modularity of the filter and makes tuning easier. The performance of the filter is evaluated in simulations and the results are encouraging.
机译：料斗疏浚者是巨大的船舶，帆船挖掘海底沉积物。然后在指定位置运输挖掘材料并排出。该过程的效率高度依赖于挖掘土壤的详细知识。当土壤主要由砂组成时，最重要的参数是平均粒径。然而，这不能通过可用的传感器直接测量。因此，在本文中，提出了一种颗粒过滤器来估计平均粒径。估计基于料斗中混合物总高度的在线测量，总质量，进入的混合密度和流速以及沙床的高度以及输出混合密度和流速的估计。将加载过程自然分解成三个相，将过滤器施加到前两个阶段。为了匹配不同类型的非线性，为正在考虑的每个阶段提出单独的观察者。这增加了过滤器的模块化，更容易调整。过滤器的性能在模拟中评估，结果令人鼓舞。

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