In this paper, the authors used an acoustic wave acting as a disturbance (acoustic vibration), which travelled in all directions on the whole surface of a dried strawberry fruit in its specified area. The area of space in which the acoustic wave occurs is defined as the acoustic field. When the vibrating surface-for example, the surface of the belt-becomes the source, then one can observe the travelling of surface waves. For any shape of the surface of the dried strawberry fruit, the signal of travelling waves takes the form that is imposed by this irregular surface. The aim of this work was to research the effectiveness of recognizing the two trials in the process of convection drying on the basis of the acoustic signal backed up by neural networks. The input variables determined descriptors such as frequency (Hz) and the level of luminosity (dB). During the research, the degree of crispiness relative to the degree of maturity was compared. The results showed that the optimal neural model in respect of the lowest value of the root mean square turned out to be the Multi-Layer Perceptron network with the technique of dropping single fruits into water (data included in the learning data set Z2). The results confirm that the choice of method can have an influence on the effectives of recognizing dried strawberry fruits, and also this can be a basis for creating an effective and fast analysis tool which is capable of analyzing the degree of ripeness of fruits including their crispness in the industrial process of drying fruits.

中文翻译：

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用人工神经网络分析声学声对草莓干进行分类。

在本文中，作者使用了作为干扰（声波振动）的声波，该声波在指定区域的干燥草莓果实的整个表面上沿所有方向传播。将其中发生声波的空间区域定义为声场。当振动表面（例如，皮带的表面）成为源时，可以观察到表面波的传播。对于草莓干果表面的任何形状，行波信号都采用这种不规则表面所施加的形式。这项工作的目的是研究在对流干燥过程中基于神经网络支持的声学信号识别这两项试验的有效性。输入变量确定描述符，如频率（Hz）和发光度（dB）。在研究过程中，比较了脆度和成熟度。结果表明，关于均方根最小值的最佳神经模型是多层感知器网络，它采用了将单个果实滴入水中的技术（数据包含在学习数据集中Z2中）。结果证实，方法的选择可能会影响识别干草莓果实的效果，这也可以为建立一个有效，快速的分析工具提供基础，该工具能够分析水果的成熟度，包括其脆度。在干燥水果的工业过程中。结果表明，关于均方根最小值的最佳神经模型是多层感知器网络，它采用了将单个果实滴入水中的技术（数据包含在学习数据集中Z2中）。结果证实，方法的选择可能会影响识别干草莓果实的效果，这也可以为建立一个有效，快速的分析工具提供基础，该工具能够分析水果的成熟度，包括其脆度。在干燥水果的工业过程中。结果表明，关于均方根最小值的最佳神经模型是多层感知器网络，它采用了将单个果实滴入水中的技术（数据包含在学习数据集中Z2中）。结果证实，方法的选择可能会影响识别干草莓果实的效果，这也可以为建立一个有效，快速的分析工具提供基础，该工具能够分析水果的成熟度，包括其脆度。在干燥水果的工业过程中。