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Abstract <p>During the picking, storage, and transportation processes, collisions between fruits can cause mechanical damage and reduce the overall quality of the fruit. In order to ensure the quality of fruits, it is necessary to carry out nondestructive testing on fruits. This paper investigates a method for nondestructive evaluation (NDE) of early mechanical damage in apples using pulsed infrared thermography (PIRT). Thermal excitation was applied to apples, and temperature differences were captured with an infrared camera. Fast Fourier transform, principal component analysis, and morphological algorithms were used to process and analyze the images. The experimental results show that the morphological algorithm performs better than other algorithms in defect edge detection, enabling clear identification of defect features and reducing noise interference. We provide an efficient and accurate NDE solution for mechanical damage in apples, which is significant for improving the quality of agricultural products and extending their shelf life.</p>

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Nondestructive Detection of Mechanical Damages in Apples Using Pulsed Infrared Thermography

  • 期刊论文

  • 发表日期：

    2025年5月1日

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  • Sen Wang,
  • Xin Huang,
  • Bin Wang,
  • Tao Peng,
  • Chiwu Bu

摘要

Abstract

During the picking, storage, and transportation processes, collisions between fruits can cause mechanical damage and reduce the overall quality of the fruit. In order to ensure the quality of fruits, it is necessary to carry out nondestructive testing on fruits. This paper investigates a method for nondestructive evaluation (NDE) of early mechanical damage in apples using pulsed infrared thermography (PIRT). Thermal excitation was applied to apples, and temperature differences were captured with an infrared camera. Fast Fourier transform, principal component analysis, and morphological algorithms were used to process and analyze the images. The experimental results show that the morphological algorithm performs better than other algorithms in defect edge detection, enabling clear identification of defect features and reducing noise interference. We provide an efficient and accurate NDE solution for mechanical damage in apples, which is significant for improving the quality of agricultural products and extending their shelf life.