scholarly journals In-field failure assessment of tractor hydraulic system operation via pseudospectrum of acoustic measurements

2019 ◽  
Vol 27 (4) ◽  
pp. 2718-2729 ◽  
Author(s):  
Saurabh GUPTA ◽  
Mahdi KHOSRAVY ◽  
Neeraj GUPTA ◽  
Hemant DARBARI
Keyword(s):  
Hydraulic System ◽  
Acoustic Measurements ◽  
System Operation ◽  
Failure Assessment ◽  
Field Failure

Energy Efficient Mechanical Press and Hydraulic System Operation

2012 ◽  
Author(s):  
Jesse A. Monn ◽  
Timothy Sullivan Raffio ◽  
Kelly Kissock
Keyword(s):  
Energy Efficient ◽  
Hydraulic System ◽  
System Operation ◽  
Mechanical Press

Dynamic Simulation Research on Three-Position Four-Way Reversing Valve

2012 ◽  
Vol 619 ◽  
pp. 503-507
Author(s):  
Yu Lan Li ◽  
Xiang Bi An ◽  
Dao Wei Zhu
Keyword(s):  
Dynamic Simulation ◽  
Dynamic Characteristics ◽  
Hydraulic System ◽  
Simulation Analysis ◽  
System Operation ◽  
Simulation Research ◽  
Operation Results

The reversing valve is a vital servo component in the hydraulic system, which reversing the movement of the execute component by the movement of the valve core to change on-off of the hydraulic channels. The model for a three-position four-way electromagnetic reversing valve used in some hydraulic system was established based on AMESim. The simulation operation results showed that the model had realized the same function with that of the actual valve, and had been consistent with the actual one on dynamic characteristics. The established of the model and the dynamic simulation analysis laid foundation for the hydraulic system operation reliably and effectively.

Modeling and Simulation of Hydraulic Power System for Maintenance Training Simulator

2013 ◽  
Vol 816-817 ◽  
pp. 851-856
Author(s):  
Qing Xia Qin ◽  
Hong Geng
Keyword(s):  
Power System ◽  
Modeling And Simulation ◽  
Hydraulic System ◽  
Normal System ◽  
Training Simulator ◽  
System Operation ◽  
Hydraulic Power ◽  
Functional Simulation ◽  
Simulation Results ◽  
Training Simulation

Study of Hydraulic Power System for development of Maintenance Training Simulator is very important. By analyzing the operational principle of the hydraulic system, presents an aircraft hydraulic system functional simulation model. After the whole hydraulic model has been established, attach to the maintenance training simulation platform. Simulation results show that this model can simulate the normal system operation and indication, and can simulate the impacts of fault disturbances under various conditions, which meets the simulation demand.

scholarly journals Hydraulic Systems Safety by Reducing Operation and Maintenance Mistakes

2019 ◽  
Vol 1 (1) ◽  
pp. 700-707
Author(s):  
Andrzej Sobczyk ◽  
Janusz Pobędza
Keyword(s):  
Hydraulic System ◽  
Hydraulic Systems ◽  
System Operation ◽  
Safety Risk ◽  
Typical Situation ◽  
Operation And Maintenance ◽  
Safety Improvement ◽  
The Subject

AbstractThe subject of the article is concern towards hydraulic systems safety improvement by elimination or/and reduction the possible mistakes which could be the reason of operator accidents and damage of the machine and surroundings. The most typical situation which could be present during hydraulic system operation and maintenance have been analysed and classified to help understand its correlation with safety. Finally each of specified danger situation during system operation and/or maintenance contents rules and warning advice to avoid safety risk.

Evaluation of Acoustic Analyses of Voice in Nonoptimized Conditions

2020 ◽  
Vol 63 (12) ◽  
pp. 3991-3999
Author(s):  
Benjamin van der Woerd ◽  
Min Wu ◽  
Vijay Parsa ◽  
Philip C. Doyle ◽  
Kevin Fung
Keyword(s):  
Repeated Measures ◽  
Voice Quality ◽  
Data Sets ◽  
Acoustic Measurements ◽  
Sample Collection ◽  
Experimental Conditions ◽  
Environment Analysis ◽  
Acoustic Measures ◽  
Recording Conditions ◽  
Cepstral Peak Prominence

Objectives This study aimed to evaluate the fidelity and accuracy of a smartphone microphone and recording environment on acoustic measurements of voice. Method A prospective cohort proof-of-concept study. Two sets of prerecorded samples (a) sustained vowels (/a/) and (b) Rainbow Passage sentence were played for recording via the internal iPhone microphone and the Blue Yeti USB microphone in two recording environments: a sound-treated booth and quiet office setting. Recordings were presented using a calibrated mannequin speaker with a fixed signal intensity (69 dBA), at a fixed distance (15 in.). Each set of recordings (iPhone—audio booth, Blue Yeti—audio booth, iPhone—office, and Blue Yeti—office), was time-windowed to ensure the same signal was evaluated for each condition. Acoustic measures of voice including fundamental frequency ( f o ), jitter, shimmer, harmonic-to-noise ratio (HNR), and cepstral peak prominence (CPP), were generated using a widely used analysis program (Praat Version 6.0.50). The data gathered were compared using a repeated measures analysis of variance. Two separate data sets were used. The set of vowel samples included both pathologic ( n = 10) and normal ( n = 10), male ( n = 5) and female ( n = 15) speakers. The set of sentence stimuli ranged in perceived voice quality from normal to severely disordered with an equal number of male ( n = 12) and female ( n = 12) speakers evaluated. Results The vowel analyses indicated that the jitter, shimmer, HNR, and CPP were significantly different based on microphone choice and shimmer, HNR, and CPP were significantly different based on the recording environment. Analysis of sentences revealed a statistically significant impact of recording environment and microphone type on HNR and CPP. While statistically significant, the differences across the experimental conditions for a subset of the acoustic measures (viz., jitter and CPP) have shown differences that fell within their respective normative ranges. Conclusions Both microphone and recording setting resulted in significant differences across several acoustic measurements. However, a subset of the acoustic measures that were statistically significant across the recording conditions showed small overall differences that are unlikely to have clinical significance in interpretation. For these acoustic measures, the present data suggest that, although a sound-treated setting is ideal for voice sample collection, a smartphone microphone can capture acceptable recordings for acoustic signal analysis.

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