Performance prediction method for large-centrifugal ventilator
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摘要: 针对现有离心式通风机性能预测方法不能充分利用离心式通风机历史运行数据、建模周期长等问题,提出了基于最小二乘支持向量机(LSSVM)与拉丁超立方采样(LHS)的大型离心式通风机性能预测方法。选取出口压力作为衡量通风机性能的指标,利用LSSVM建立离心式通风机性能预测模型;通过LHS方法采集离心式通风机的入口温度、入口压力、入口流量和转速,将采集的数据进行归一化处理后用于LSSVM模型的训练;通过测试数据验证所建立模型的有效性。仿真结果表明,基于LSSVM与LHS的大型离心式通风机性能预测方法能够充分利用已有通风机数据信息快速准确地预测通风机性能。Abstract: In view of problems that existing performance prediction methods for centrifugal ventilator cannot fully utilize historical operation data of centrifugal ventilator and have long modeling period, performance prediction method for large-centrifugal ventilator based on LSSVM and LHS was proposed. Outlet pressure is selected as index to measure performance of ventilator, and performance prediction model of centrifugal ventilator is established by using LSSVM. Inlet temperature, inlet pressure, inlet flow rate and rotational speed of the centrifugal ventilator are collected by LHS method, and the collected data are normalized for training of LSSVM model. Validity of the established model is verified by testing data. The simulation results show that the performance prediction method for large-centrifugal ventilator based on LSSVM and LHS can make full use of existing ventilator data information to quickly and accurately predict performance of ventilator.
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