Yongqiang Bao^{1, *}, Qi Shao¹, Xuxu Zhang¹, Jiahui Jiang¹, Yue Xie¹, Tingting Liu¹, Weiye Xu²

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2557-2570, 2020, DOI:10.32604/cmc.2020.011241

Abstract The field of digital audio forensics aims to detect threats and fraud in audio signals. Contemporary audio forensic techniques use digital signal processing to detect the authenticity of recorded speech, recognize speakers, and recognize recording devices. User-generated audio recordings from mobile phones are very helpful in a number of forensic applications. This article proposed a novel method for recognizing recording devices based on recorded audio signals. First, a database of the features of various recording devices was constructed using 32 recording devices (20 mobile phones of different brands and 12 kinds of recording pens) in various environments. Second, the audio… More >

Mohamed Abbas^1,3,*, Ali Algahtani^2,6, Amir Kessentini^2,4,7, Hassen Loukil^1,5, Muneer Parayangat¹, Thafasal Ijyas¹, Abdul Wase Mohammed¹

CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.2, pp. 683-701, 2020, DOI:10.32604/cmes.2020.010304

Abstract Every new generation of antennas is characterized by increased accuracy and faster transmission speeds. However, patch antennas have been known to damage human health. This type of antenna sends out electromagnetic waves that increase the temperature of the human head and prevent nerve strands from functioning properly. This paper examines the effect of the communication between the patch antenna and the brain on the head’s temperature by developing a hypothetical multi-input model that achieves more accurate results. These inputs are an individual’s blood and tissue, and the emission power of the antenna. These forces depend on the permeability and conductivity… More >

Suhas S. Aralikatti¹, K. N. Ravikumar¹, Hemantha Kumar^1,*, H. Shivananda Nayaka¹, V. Sugumaran²

Structural Durability & Health Monitoring, Vol.14, No.2, pp. 127-145, 2020, DOI:10.32604/sdhm.2020.07595

Abstract The state of cutting tool determines the quality of surface produced on the machined parts. A faulty tool produces poor surface, inaccurate geometry and non-economic production. Thus, it is necessary to monitor tool condition for a machining process to have superior quality and economic production. In the present study, fault classification of single point cutting tool for hard turning has been carried out by employing machine learning technique. Cutting force and vibration signals were acquired to monitor tool condition during machining. A set of four tooling conditions namely healthy, worn flank, broken insert and extended tool overhang have been considered… More >

Oakyoung Han¹, Jaehyoun Kim^{2, *}

CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 553-566, 2020, DOI:10.32604/cmc.2020.09362

Abstract The processing of sound signals is significantly improved recently. Technique for sound signal processing focusing on music beyond speech area is getting attention due to the development of deep learning techniques. This study is for analysis and process of music signals to generate tow-dimensional tabular data and a new music. For analysis and process part, we represented normalized waveforms for each of input data via frequency domain signals. Then we looked into shorted segment to see the difference wave pattern for different singers. Fourier transform is applied to get spectrogram of the music signals. Filterbank is applied to represent the… More >

Jiaqi Zhen^{1, *}

CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 445-455, 2020, DOI:10.32604/cmc.2020.06385

Abstract In array signal processing, number of signals is often a premise of estimating other parameters. For the sake of determining signal number in the condition of strong additive noise or a little sample data, an algorithm for detecting number of wideband signals is provided. First, technique of focusing is used for transforming signals into a same focusing subspace. Then the support vector machine (SVM) can be deduced by the information of eigenvalues and corresponding eigenvectors. At last, the signal number can be determined with the obtained decision function. Several simulations have been carried on verifying the proposed algorithm. More >

A. Joshuva^1,*, V. Sugumaran²

Structural Durability & Health Monitoring, Vol.13, No.4, pp. 399-416, 2019, DOI:10.32604/sdhm.2019.03014

Abstract Wind energy is considered as a alternative renewable energy source due to its low operating cost when compared with other sources. The wind turbine is an essential system used to change kinetic energy into electrical energy. Wind turbine blades, in particular, require a competitive condition inspection approach as it is a significant component of the wind turbine system that costs around 20-25 percent of the total turbine cost. The main objective of this study is to differentiate between various blade faults which affect the wind turbine blade under operating conditions using a machine learning approach through histogram features. In this… More >

T. M. Alamelu Manghai¹, R. Jegadeeshwaran²

Structural Durability & Health Monitoring, Vol.11, No.2, pp. 149-167, 2017, DOI:10.3970/sdhm.2017.011.149

Abstract Hydraulic brakes in automobiles are an important control component used not only for the safety of the passenger but also for others moving on the road. Therefore, monitoring the condition of the brake components is inevitable. The brake elements can be monitored by studying the vibration characteristics obtained from the brake system using a proper signal processing technique through machine learning approaches. The vibration signals were captured using an accelerometer sensor under a various fault condition. The acquired vibration signals were processed for extracting meaningful information as features. The condition of the brake system can be predicted using a feature… More >

Pei Yu, Yong Shen^*, Ziyun Liu

Sound & Vibration, Vol.52, No.5, pp. 6-11, 2018, DOI:10.32604/sv.2018.04090

Abstract A lot of work has focused on compensating nonlinear distortions of the microspeaker under large excitation, yet it is unclear at which level the effect of nonlinear distortion is imperceptible or not annoying. In this study virtual listening tests were performed to evaluate the deterioration of sound quality in music signals with different levels of nonlinear distortion by a microspeaker. Binaural recordings of the music played by the microspeaker were made at different voltage levels, adjusted to the same RMS power, and afterwards reproduced by a low distortion reference headphone. The “double-blind triple-stimulus with hidden reference” method was used in… More >

Lingya Meng^{1, *}, Cuiwei Liu², Liping Fang², Yuxing Li², Juntao Fu³

Sound & Vibration, Vol.53, No.4, pp. 111-128, 2019, DOI:10.32604/sv.2019.03835

Abstract When acoustic method is used in leak detection for natural gas pipelines, the external interferences including operation of compressor and valve, pipeline knocking, etc., should be distinguished with acoustic leakage signals to improve the accuracy and reduce false alarms. In this paper, the technologies of extracting characteristics of acoustic signals were summarized. The acoustic leakage signals and interfering signals were measured by experiments and the characteristics of time-domain, frequency-domain and time-frequency domain were extracted. The main characteristics of time-domain are mean value, root mean square value, kurtosis, skewness and correlation function, etc. The features in frequency domain were obtained by… More >

Zeng Fan, Zhu shijian, Lou jingjun

The International Conference on Computational & Experimental Engineering and Sciences, Vol.19, No.1, pp. 5-6, 2011, DOI:10.3970/icces.2011.019.005

Abstract A signal processing electric circuit used in vibration signals processing system has been designed, which contains the pre-amplifier, the single chip ATMEGA16 and the microprocessor programmable MAX262 and so on. Its feasibility test is carried out. The center frequency and other parameters are input into the computer by VC software programmed, and the computer sends these instructions to the single chip. The single chip controls MAX262 filter to work regularly and the noise signals are well filtered. The signals output from the data sampler are analyzed and processed, and the vibration signals can be clearly recognized. The experimental results show… More >