Parameter Estimation Employing a Dual-Channel Sine-Wave Model Under a Gaussian Assumption

2008 ◽  
Vol 57 (8) ◽  
pp. 1661-1669 ◽  
Author(s):  
P. Handel
Author(s):  
Luana M. Gonçalves ◽  
Gabriel A. e S. Ferraz ◽  
Marcelo S. de Oliveira ◽  
Brenon D. S. Barbosa ◽  
Carlos J. da Silva ◽  
...  

ABSTRACT Noise is one of the harmful and stressful physical agents present in the workplace. Research performed with geostatistics to adjust the semivariogram of tractor noise were performed using the Gaussian and spherical model. In this way, the aim was to map the spatial variability of the noise emitted by a power tiller through the sine wave model, besides testing other fitting methods, in order to identify health zones for the workers. The experiment was performed with an agricultural power tiller (10.3 kW) placed in a working regime (1500 rpm), coupled to a brushcutter, and a digital sound level meter to collect noises in points distributed along a regular grid sampling of 2.0 × 2.0 m around the tractor. The spatial dependence of noise was analyzed through semivariogram fitting by different methods and by the wave model to obtain the spatial distribution map interpolated by kriging. It was possible to characterize the structure and the magnitude of the spatial dependence of the noise levels emitted by the tractor, as well as to map the spatial distribution. A maximum noise level of 96.5 dB was observed close to the tractor engine, a value above the limit of 85.0 dB for 8 h of daily exposure (NR-15). Thus, the use of ear protectors is recommended for both the tractor driver and the professionals who support agricultural operation within a radius of 6 m from the emitting source under the conditions studied.


Author(s):  
Kwen Hsu ◽  
Dan Hoyniak ◽  
M. S. Anand

Flutter analysis for a first stage rotor of a compressor assembly was performed using the traditional Single-Passage, Single-Row (SPSR) flow model, and the prediction results did not correlate well with the test findings. In the tests flutter was observed but the SPSR simulation results indicated no flutter. It was suspected that influences from the upstream and downstream rows, which were omitted by the use of the SPSR model, might have significantly altered the flutter behavior of this rotor in a multistage environment. To confirm this hypothesis and to better understand the multistage turbomachinery flutter problem, FAMR (Full-Annulus, Multi-Row) models were employed in the current study to accurately take into account the interferences generated by the presence of the neighboring rows and to capture the time-varying flow variations in all directions. It was found that the flutter performance predicted by a FAMR model can be dramatically different from that predicted by a SPSR model of the same design. The FAMR model showed that flutter can occur for this design, as indicated by test results. Present results indicate the potential impact of complex blade row interactions and aliasing on flutter behavior in a multi-blade row turbomachinery configuration. A simple sine-wave model was also used to better explain the FAMR simulation results and help the analyst in judging the efficacy of the FAMR simulation.


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