Prognosis and fault detection in agricultural tractors using numerical simulation and artificial immune system algorithms

• Autor(a) principal: Oliveira, Dionatan Pontes de
• Data de Publicação: 2020
• Outros Autores: Silva, Wayrone Klaiton, Oliveira, Daniela Cabral de, Chavarette, Fábio Roberto, Oliveira, Daniel Emanuel Cabral de, Ortiz , Luis Cláudio Villani, Souza, Dorgival Fidellis de, Barbosa Júnior, João Areis Ferreira
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Research, Society and Development
• Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/11191
• topic: Trator agrícola; Monitoramento de integridade estrutural; Seleção negativa; Seleção clonal.; Tractor agrícola; Monitoreo de integridad estructural; Selección negativa; Selección clonal.; Agricultural tractor; Structural integrity monitoring; Negative selection; Clonal selection.

In view of the growing technological advance in agriculture, and with a view to promoting increased productivity and job security for individuals involved in the techno-agricultural evolution process, this article develops an inteligente diagnostic system, proposing artificial immunological algorithms, inspired by the Immune System Biological, to apply to the process of monitoring the structural integrity of an agricultural tractor and the consequent analysis of structural failures, under normal soil conditions and in the short term. For this, the detection of failures in structural integrity in agricultural tractors is obtained to capture data continuously for machine learning, so that a numerical model is created and fel, under the calculation of differential equations, in order to measure the displacements of the tractor at as the tractor speed parameters change and the distance between ground levels are interspersed and, thus, result in possible structural risk prognoses. Computationally, through the Octave software, the analysis, identification and classification of the obtained data is possible with the use of negative selection and clonal selection algorithms. The inspection of the tractor structure with a focus on better conservation is the main point of the study, and with the relevant quality and consistency of the methodology presented and resulting from the research, it allows to indicate whether the tractor is in normal conditions or shows signs of failure structural, because if there are risks, the failure can be identified.