scholarly journals Portable Ultrasonic Thermometer with Humidity Correction and Audible Sound Thermometry

2018 ◽  
Author(s):  
Lukas Ondraczka
Keyword(s):  
Ultrasonic Thermometer ◽  
Audible Sound

The effect of audible sound frequency on the growth and beta-carotene production of Dunaliella salina

2021 ◽  
Vol 141 ◽  
pp. 373-382
Author(s):  
Arezoo Keramati ◽  
Farshid Pajoum Shariati ◽  
Omid Tavakoli ◽  
Zahra Akbari ◽  
Mina Rezaei
Keyword(s):  
Dunaliella Salina ◽  
Beta Carotene ◽  
Sound Frequency ◽  
Audible Sound

Analysis of Sound Signal Generation Due to Flank Wear in Turning

2000 ◽  
Author(s):  
Ming-Chyuan Lu ◽  
Elijah Kannatey-Asibu
Keyword(s):  
Tool Wear ◽  
Manufacturing Systems ◽  
Cutting Process ◽  
Reconfigurable Manufacturing ◽  
Monitoring Tool ◽  
Major Step ◽  
Part Quality ◽  
Audible Sound ◽  
The Individual ◽  
Flank Surface

Abstract Ramp-up is a major step in the implementation of manufacturing systems, and is even more critical in reconfigurable manufacturing systems. For a successful reduction in ramp-up time, it is essential to analyze and monitor both the overall manufacturing system and the individual machine tools/processes that comprise the system. Towards this end, we have addressed the issue of monitoring tool wear using audible sound to enable faulty conditions associated with wear to be identified during the process before the part quality gets out of specification. Audible sound generated from the cutting process is analyzed as a source for monitoring tool wear during turning, assuming adhesive wear as the predominant wear mechanism. The analysis incorporates the dynamics of the cutting process. In modeling the interaction on the flank surface, the asperities on the surfaces are represented as a trapezoidal series function with normal distribution. The effect of changing asperity height, size, spacing, and the stiffness of the asperity interaction is investigated and compared with experimental data.

Detection of Cracks in Crankshaft Using an Intelligent Audible Sound-Based Non-Destructive Method

2021 ◽  
Author(s):  
Kwarne Twum Asamoah Boateng ◽  
Henry Nunoo-Mensah ◽  
Justice Ohene-Akoto ◽  
Prince Ebenezer Adjei ◽  
Kwame Osei Boateng
Keyword(s):  
Audible Sound ◽  
Non Destructive

Sound speed in pulmonary parenchyma

1983 ◽  
Vol 54 (1) ◽  
pp. 304-308 ◽  
Author(s):  
D. A. Rice
Keyword(s):  
Lung Volume ◽  
Sound Speed ◽  
Sulfur Hexafluoride ◽  
Ambient Pressure ◽  
Linear Regression Analysis ◽  
Free Field ◽  
Average Density ◽  
Sound Waves ◽  
Gas Phases ◽  
Audible Sound

The time it takes audible sound waves to travel across a lobe of excised horse lung was measured. Sound speed, which is the slope in the relationship between transit time and distance across the lobe, was estimated by linear regression analysis. Sound-speed estimates for air-filled lungs varied between 25 and 70 m/s, depending on lung volume. These speeds are less than 5% of sound speed in tissue and less than 20% of sound speed in air. Filling the lung with helium or sulfur hexafluoride, whose free-field sound speeds are 970 and 140 m/s, respectively, changed sound speed +/- 10% relative to air filling. Reducing the ambient pressure to 0.1 atm reduced sound speed to 30% of its 1-atm value. Increasing pressure to 7 atm increased sound speed by a factor of 2.6. These results suggest that 1) translobar sound travels through the bulk of the parenchyma and not along airways or blood vessels, and 2) the parenchyma acts as an elastic continuum to audible sound. The speed of sound is given by c = (B/rho)1/2, where B is composite volumetric stiffness of the medium and rho is average density. In the physiologic state B is affected by ambient pressure and percent gas phase. The average density includes both the tissue and gas phases of the parenchyma, so it is dependent on lung volume. These results may be helpful in the quantification of clinical observations of lung sounds.

Distance Measurement Method Effective from 0 m Using Phase Interference of Audible Sound

2014 ◽  
Vol 97 (8) ◽  
pp. 24-31
Author(s):  
Noboru Nakasako ◽  
Toshihiro Shinohara ◽  
Keiji Kawanishi ◽  
Tetsuji Uebo
Keyword(s):  
Measurement Method ◽  
Distance Measurement ◽  
Audible Sound ◽  
Phase Interference

Audio-Based Condition Monitoring in Milling of the Workpiece Material With the Hardness Variation Using Support Vector Machines and Convolutional Neural Networks

2018 ◽  
Author(s):  
Achyuth Kothuru ◽  
Sai Prasad Nooka ◽  
Rui Liu
Keyword(s):  
Neural Networks ◽  
Support Vector Machines ◽  
Tool Wear ◽  
Support Vector ◽  
Workpiece Material ◽  
Artificial Intelligent ◽  
Tool Condition ◽  
Hardness Variation ◽  
Vector Machines ◽  
Audible Sound

Machining industry has been evolving towards implementation of automation into the process for higher productivity and efficiency. Although many studies have been conducted in the past to develop intelligent monitoring systems in various application scenarios of machining processes, most of them just focused on cutting tools without considering the influence due to the non-uniform hardness of workpiece material. This study develops a compact, reliable, and cost-effective intelligent Tool Condition Monitoring (TCM) model to detect the cutting tool wear in machining of the workpiece material with hardness variation. The generated audible sound signals during the machining process will be analyzed by state of the art artificial intelligent techniques, Support Vector Machines (SVMs) and Convolutional Neural Networks (CNNs), to predict the tool condition and the hardness variation of the workpiece. A four-level classification model is developed for the system to detect the tool wear condition based on the width of the flank wear land and hardness variation of the workpiece. The study also involves comparative analysis between two employed artificial intelligent techniques to evaluate the performance of models in predicting the tool wear level condition and workpiece hardness variation. The proposed intelligent models have shown a significant prediction accuracy in detecting the tool wear and from the audible sound into the proposed multi-classification wear class in the end-milling process of non-uniform hardened workpiece.

On Minimum Audible Sound Fields

1933 ◽  
Vol 4 (3) ◽  
pp. 176-177 ◽  
Author(s):  
L. J. Sivian ◽  
S. D. White
Keyword(s):  
Sound Fields ◽  
Audible Sound

scholarly journals Device-Free Handwritten Character Recognition Method Using Acoustic Signal

2021 ◽  
Vol 33 (5) ◽  
pp. 1082-1095
Author(s):  
Atsushi Ogura ◽  
◽  
Hiroki Watanabe ◽  
Masanori Sugimoto
Keyword(s):  
Ultrasonic Wave ◽  
Character Recognition ◽  
Low Noise ◽  
Recognition Method ◽  
Handwritten Character Recognition ◽  
Handwritten Character ◽  
Average Accuracy ◽  
Audible Sound ◽  
Device Free ◽  
Additional Device

In this paper, we propose a method for recognizing handwritten characters by a finger using acoustic signals. This method is carried out using a smartphone placed on a flat surface, such as a desk. Specifically, this method uses an ultrasonic wave transmitted from the smartphone, which is reflected by the finger, and an audible sound is generated when writing a handwritten character. The proposed method does not require an additional device for handwritten character recognition because it uses the microphone/speaker built into the device. Evaluation results showed that it was able to recognize 36 types of characters with an average accuracy of 77.8% in a low noise environment for 10 subjects. In addition, it was verified that combining an audible sound and an ultrasonic wave in this method achieved higher recognition accuracy than when only an audible sound or an ultrasonic wave was used.

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