Current Issue : January - March Volume : 2019 Issue Number : 1 Articles : 5 Articles
A novel surface acoustic wave (SAW) sensor array based on wireless communication\nnetwork is prepared. The array is composed of four SAW sensors, a wireless communication\nnetwork module, and a global positioning system (GPS) module. The four SAW sensors\nof the array are coated with triethanolamine, polyepichlorohydrin, fluoroalcoholpolysiloxane,\nand L-glutamic acid hydrochloride to detect hydrogen sulfide (H2S), 2-chloroethyl ethyl sulfide\n(CEES), dimethylmethylphosphonate (DMMP), and ammonia (NH3) at film thicknesses of 50â??100 nm.\nThe wireless communication network module consists of an acquisition unit, a wireless control unit,\nand a microcontroller unit. By means of Zigbee and Lora technologies, the module receives and\ntransmits the collected data to a PC work station in real-time; moreover, the module can control\nthe sensor arrayâ??s working mode and monitor the working status. Simultaneously, the testing\nlocation is determined by the GPS module integrated into the SAW sensor array. H2S, CEES, DMMP,\nand NH3 are detected in 300 m at different concentrations. Given the practical future application\nin environment in the future, the low, safe concentrations of 1.08, 0.59, 0.10, and 5.02 ppm for H2S,\nCEES, DMMP, and NH3, respectively, are detected at the lowest concentration, and the sensitivities\nof different sensors of the sensor array are 32.4, 14.9, 78.1 and 22.6 Hz/ppm, respectively. With the\nobtained fingerprints and pattern recognition technology, the detected gases can be recognized....
Inspection of a pipeline is essential for the safe use of such facilities. A trial\nsensor using an electromagnetic acoustic transducer (EMAT), which can\ngenerate the SH-mode plate wave propagating in the circumferential direction,\nhas been developed to realize this objective. It consists of a circulating\nelectromagnetic induction coil around the pipe and many permanent magnets\narranged on the surface of the pipe in the circumferential direction. It is\npostulated that the intensity of the SH-mode plate wave propagating in the\ncircumferential direction is dependent on any defects in the circumferential\ndirection. A resonance method was then utilized to obtain a stronger received\nsignal. As a result, it was confirmed that the resonance status can be detected.\nThe relationship between the signal intensity and the pipe thickness was then\nevaluated. It was confirmed that the wall thickness of about 20% can be detected\nunder a static condition. Finally, a moving test has been executed by\nusing an axially traveling device manufactured by trial. The test pipes with\ndifferent sizes of drilled holes were prepared. The change in the received signal\nintensity according to different sizes of the drilled holes was successfully\ndetected....
Pulsed illumination of a sample, e.g., of a biological tissue, causes a sudden temperature\nincrease of light absorbing structures, such as blood vessels, which results in an outgoing acoustic\nwave, as well as heat diffusion, of the absorbed energy. Both of the signals, pressure and temperature,\ncan be measured at the sample surface and are used to reconstruct the initial temperature or pressure\ndistribution, called photoacoustic or photothermal reconstruction respectively. We have demonstrated\nthat both signals at the same surface pixel are connected by a temporal transformation. This allows\nfor the calculation of a so-called acoustical virtual wave from the surface temperature evolution\nas measured by an infrared camera. The virtual wave is the solution of a wave equation and can\nbe used to reconstruct the initial temperature distribution immediately after the excitation pulse.\nThis virtual wave reconstruction method was used for the reconstruction of inclined steel rods in\nan epoxy sample, which were heated by a short pulse. The reconstructed experimental images\nshow clearly the degradation of the spatial resolution with increasing depth, which is theoretically\ndescribed by a depth-dependent thermographic point-spread-function....
Currently gear fault diagnosis is mainly based on vibration signals with a few studies on\nacoustic signal analysis. However, vibration signal acquisition is limited by its contact measuring\nwhile traditional acoustic-based gear fault diagnosis relies heavily on prior knowledge of signal\nprocessing techniques and diagnostic expertise. In this paper, a novel deep learning-based gear\nfault diagnosis method is proposed based on sound signal analysis. By establishing an end-to-end\nconvolutional neural network (CNN), the time and frequency domain signals can be fed into the\nmodel as raw signals without feature engineering. Moreover, multi-channel information from\ndifferent microphones can also be fused by CNN channels without using an extra fusion algorithm.\nOur experiment results show that our method achieved much better performance on gear fault\ndiagnosis compared with other traditional gear fault diagnosis methods involving feature engineering.\nA publicly available sound signal dataset for gear fault diagnosis is also released and can be\ndownloaded as instructed in the conclusion section....
This experiment aims to study the effects and modifications that occurred on\nacoustic signal harmonics when travelling through wood. The experiment\nmeasured the output amplitudes and frequencies of the travelling signals and\ncompared them with the original input signal. The factors under investigation\nin this experiment included: wood type, wood moisture content (MC), input\nsignal frequencies, signal travelling distance and wood condition (wood\nwith/without cracks). The experiment findings demonstrated that higher input\nsignal frequencies results in higher attenuation of acoustic emissions (AE)\ntravelling through the wood. The results also indicate that: wood type, MC,\nthe signalâ??s travelling distance, and the orientation of the travelling signal,\ncompared to the woodâ??s grain direction, affected the signal propagation....
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