Numerical Prediction and Verification of Noise Radiation Characteristics of Diesel Engine Block

To assess the contribution of structure-borne noise from an engine, it is critical to characterize the dynamic and vibro-acoustic properties of the engine components and assembly. In this paper, a component level study of a three-cylinder diesel engine block is presented. Virtual analysis was done to predict the natural frequencies and mode shapes of an engine block in the first step. Then, these results were used to decide the optimum test locations and an experimental modal test was conducted on the engine block. The initial virtual model results for the natural frequencies and mode shapes were correlated with the results from test. Then, the virtual model was updated with the damping derived from experimental modal test to match the vibration frequency response functions. Further, the virtual model was used for prediction of vibro-acoustic transfer functions. The vibro-acoustic transfer functions were also obtained from test. The results of transfer function were correlated with the test. In future, we plan to use this approach for prediction of the vibration and vibro-acoustic transfer functions for sub-assembly and eventually entire engine assembly to be able to use the models to predict the structure-borne noise from an engine.

• Record URL:
  • https://doi.org/10.4271/2019-01-1591
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/01487191
• Supplemental Notes:
  • Abstract reprinted with permission of SAE International.
• Authors:
  • Mandke, Devendra
  • Ghaisas, Deepak
  • Pawar, Sachin
  • Suh, Sanghoon
• Conference:
  • Noise and Vibration Conference & Exhibition
  • Location: Grand Rapids Michigan, United States
  • Date: 2019-6-10 to 2019-6-13
• Publication Date: 2019-6-5

Language

• English

Media Info

• Media Type: Web
• Features: Figures; Illustrations; Photos; References;
• Serial:
  • SAE Technical Paper
  • Publisher: Society of Automotive Engineers (SAE)
  • ISSN: 0148-7191
  • EISSN: 2688-3627
  • Serial URL: http://papers.sae.org/

Subject/Index Terms

• TRT Terms: Diesel engines; Engine components; Mathematical prediction; Noise; Sound transmission; Vibration
• Subject Areas: Highways; Maintenance and Preservation; Vehicles and Equipment;

Filing Info

• Accession Number: 01715264
• Record Type: Publication
• Source Agency: SAE International
• Report/Paper Numbers: 2019-01-1591
• Files: TRIS, SAE
• Created Date: Aug 29 2019 5:30PM