The invention discloses a load-lightweight 125% rated load brake test method for an elevator, and the method comprises the steps: obtaining an elevator feature data set under a preset rated load condition; training a preset neural network model by using the elevator feature data set to obtain an optimal neural network model; target load braking test characteristics are obtained, the target load braking test characteristics are mapped into 125% rated load braking test characteristics, and the target load is smaller than 125% rated load; and inputting the 125% rated load braking test characteristics into the optimal neural network model to obtain the braking performance of the elevator under the 125% rated load. On the basis of the characteristic neural network model, the braking performance of the elevator to be tested under the 125% rated load can be obtained only by conducting the braking test of the load smaller than 125% rated load on the elevator to be tested to obtain the target load braking test characteristics, and load lightweight is achieved.

    本发明公开了一种载荷轻量化的电梯125%额定载荷制动试验方法,包括:在预设额定载荷条件下,获取电梯特征数据集;利用所述电梯特征数据集,对预设神经网络模型进行训练,获取最优神经网络模型;获取目标载荷制动试验特征,并将所述目标载荷制动试验特征映射为125%额定载荷制动试验特征,其中,所述目标载荷小于125%额定载荷;将所述125%额定载荷制动试验特征输入所述最优神经网络模型,获取电梯125%额定载荷下的制动性能。本发明基于特征神经网络模型,只需通过对于待测电梯进行小于125%额定载荷制动试验得到目标载荷制动试验特征,就能得到待测电梯125%额定载荷下的制动性能,实现了载荷轻量化。


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    Title :

    Load-lightweight 125% rated load braking test method for elevator


    Additional title:

    一种载荷轻量化的电梯125%额定载荷制动试验方法


    Contributors:
    WANG HAIJIAN (author) / MO HAN (author) / LIAN FENGWU (author) / LI XINGJUN (author) / ZHANG JINGTIE (author) / ZHAI YONGZHI (author) / SUN PENGYAO (author) / GENG LIYANG (author)

    Publication date :

    2023-12-15


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    B66B Aufzüge , ELEVATORS



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