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Assessment of the technical condition of the units of mobile robotechnical complexes based on the approaches of nonlinear dynamics and artificial intelligence
| Content Provider | Scilit |
|---|---|
| Author | Kabaldin, Yu.G. Shatagin, D. A. Sidorenkov, D. A. Zhelonkin, M. V. Anosov, M. S. |
| Copyright Year | 2019 |
| Description | Journal: Iop Conference Series: Materials Science and Engineering Neural network algorithms for monitoring and diagnosing the technical condition of parts of the MRC drive axle are considered. The formalized task is a comprehensive assessment of the technical condition in the neural network basis. An engineering technique is proposed that can be applied at the stages of bench tests of critical components and assemblies. |
| Related Links | https://iopscience.iop.org/article/10.1088/1757-899X/695/1/012011/pdf |
| ISSN | 17578981 |
| e-ISSN | 1757899X |
| DOI | 10.1088/1757-899x/695/1/012011 |
| Journal | Iop Conference Series: Materials Science and Engineering |
| Issue Number | 1 |
| Volume Number | 695 |
| Language | English |
| Publisher | IOP Publishing |
| Publisher Date | 2019-11-01 |
| Access Restriction | Open |
| Subject Keyword | Journal: Iop Conference Series: Materials Science and Engineering Automotive Engineering Neural Network Algorithms Technical Condition |
| Content Type | Text |
| Resource Type | Article |