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On this paper a bearing defects diagnosis method is introduced. This diagnosis method is based on time domain signal processing first step being the kurtosis based filtering. This filtering is based on the detection of the shock pulses generated by bearing defects. The diagnosis is done using the detected defects periods which are the inputs for a fuzzy classifier that provide defect alerts for each kind of bearing localize defect

Numerical solutions for signal processing are described in this work as acontribution to study of echo detection methods for ionospheric sounder design. The ionospheric sounder is a high frequency radar for geophysical applications. The main detection approach has been done by implementing the spread-spectrum techniques using coding methods to improve the radar?s range resolution by transmitting low power. Digital signal processing has been performed and the numerical methods were checked. An algorithm was proposed and its computational complexity was calculated. The proposed detection process combines two channels correlations with the local code and calculates threshold (Vt) by statistical evaluation of the background noise to design adetection algorithm. The noisy signals treatment was performed depending on the threshold and echo amplitude. In each case, the detection was improved by using coherent integration. Synthetic signals, close loop and actual echoes, obtained from the Advanced Ionospheric Sounder (AIS-INGV) at Rome Ionospheric Observatory, were used to verify the process. The results showed that, even in highly noisy environments, the echo detection is possible. Given that these are preliminary results, further studies considering data sets corresponding to other geophysical conditions are needed. Fil: Molina, María G.. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnologia; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Electricidad, Electrónica y Computación. Laboratorio de Telecomunicaciones; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Física. Laboratorio de Ionosfera; Argentina Fil: Cabrera, Miguel A.. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Física. Laboratorio de Ionosfera; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Electricidad, Electrónica y Computación. Laboratorio de Telecomunicaciones; Argentina. Universidad Tecnologica Nacional. Facultad Regional Tucuman; Argentina Fil: Ezquer, Rodolfo Gerardo. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Física. Laboratorio de Ionosfera; Argentina. Universidad Tecnologica Nacional. Facultad Regional Tucuman; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tucumán; Argentina Fil: Fernández, P. M.. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnologia; Argentina Fil: Zuccheretti, E.. Istituto Nazionale di Geofisica e Vulcanologia; Italia

Time domain signal processing (TDSP) encodes information into time rather than voltage with higher efficiency than conventional digital design. This paper performs systematical analysis on the design principle and energy efficiency of TDSP. Variation impact, which poses significant challenges to TDSP, is evaluated and a variation driven design methodology is proposed to achieve an optimum tradeoff between energy efficiency and design robustness. Several novel circuit level design techniques such as dual encoding strategy and bit-scalable design are also proposed in this work to significantly improve the energy efficiency of TDSP. Design example on a critical building block of facial recognition application was used to demonstrate the potential of the technique. The result in a 45nm technology shows 3.3X energy-delay product reduction and 34% area saving can be achieved using TDSP compared with conventional digital design technique.

In many industries where flow parameters measurement is essential to control manufacturing process, the use of a reliable, cost effective and high accuracy instrument is an important issue. Appropriate measurement method and design leads to improvement of pneumatic conveyors operation and process efficiency. This paper present an instrumentation design based on passive charge detection using a single electrostatic sensor. Two different sensor electrodes are applied to show the flexibility of electrostatic sensor application. A time domain signal processing algorithm is developed to measurement of mass flow rate and concentration profile from acquired electrical charge signal. The findings is led to a low cost and high accuracy design, the experimental test results of the design shows less than ±5% error between measured parameters and reference reading acquired from the manual weighing.

International audience; In this paper, we model and give experimental evidence of the efficiency of pulsed-mode actuation for the characterization of capacitive MEMS resonators. In particular, we show how to process the pulsed-mode response in two modes (harmonic and subharmonic) so as to eliminate parasitic feedthrough effects and characterize the resonator more accurately. We test our approach on a pressure sensor, developed by THALES Avionics, used for avionics applications. In contrast to the existing state-of-the-art techniques, the methods described in this paper can be used to characterize electrostatic MEMS without the use of a spectrum analyzer or high-performance ADC.

This book is based on the 18 tutorials presented during the 23rd workshop on Advances in Analog Circuit Design. Expert designers present readers with information about a variety of topics at the frontier of analog circuit design, serving as a valuable reference to the state-of-the-art, for anyone involved in analog circuit research and development. Includes coverage of high-performance analog-to-digital and digital to analog converters, integrated circuit design in scaled technologies, and time-domain signal processing; Provides a state-of-the-art reference in analog circuit design, written by experts from industry and academia; Presents material in a tutorial-based format.

Current solutions of sleep apnea diagnosis require the patient to undergo overnight studies at a specialized sleep laboratory. Due to such inconvenience and high cost, millions of sleep apnea patients remain undiagnosed and thus untreated. Based on a micro-electro-mechanical systems (MEMS) sensor and an effective apnea detection algorithm, we propose a low-cost single-channel apnea screening solution applicable in the comfort of patients' homes. A prototype device was designed and assembled including a MEMS sensor for measuring the patient's nasal air flows, and a time-domain signal processing IC for apnea detection and autonomous scoring. The IC chip was fabricated in standard 0.5- $\mu{\rm m}$ CMOS technology. The proposed device was tested for both respiratory rhythm detection and sleep apnea screening under clinical environment. Apnea-hypopnea indices (AHI) were scored to indicate severity of sleep apnea conditions. Test results suggest that the proposed device can be a valuable screening solution for the broader public with undiagnosed apnea conditions.

International audience; In this paper, we analyze and give experimental evidence of the efficiency of pulsed-mode actuation for the characterization of capacitive MEMS resonators. In particular, we show how to process the output signal in pulsed mode to eliminate parasitic feedthrough effects and characterize the resonator. We test our approach on a pressure sensor, developed by THALES Avionics, used for avionics applications. Contrary to the existing state-of-the-art techniques, the method described in this paper can be used to characterize an electrostatic MEMS without a spectrum analyzer or high-performance ADC.

A delay circuit using four-terminal magnetic-random-access-memory (MRAM) devices was designed for power-efficient time-domain signal processing. A cell area of 6.4 μm 2 was obtained using 90-nm CMOS/MRAM technologies. The basic operations to both store the data and control the delay time were confirmed on the fabricated test chips. In addition, we proposed a power-efficient neuromorphic core using the delay circuit.

The detection and identification of insect pests is often carried out manually using trapping methods, however, recent advances in signal processing and computer technology have introduced the possibility of automatically identifying species by several means including image analysis and acoustics. Insects can generate sound either deliberately as a means of communication or as a by-product of eating, flight or other movement, which may be employed for detection and identification. Research at Hull University is investigating techniques for automatically identifying Orthoptera (grasshoppers and crickets) with time domain signal processing and artificial neural networks. 25 species of British Orthoptera have been selected as a test set and preliminary results indicate very high classification rates approaching 100% with extremely low misclassification rates. The technique is widely applicable to many insect pests and other phyla such as birds.

A periodogram scheme, a multi-taper scheme, and a filter-bank scheme are proposed for spectrum sensing for dynamic spectrum access. The filter-bank scheme is advantageous in hardware implementation since the hardware required for communications can be reused for spectrum sensing. However, it is difficult for the conventional filter-bank scheme to change the detection bandwidth, filter type and frequency channel since the conventional filter-bank is based on time domain signal processing. This paper proposes a new spectrum sensing scheme using overlap FFT filter-bank based on frequency domain signal processing, which can flexibly change the detection bandwidth, filter type and frequency channel. In addition, this paper proposes a windowing method to improve the false-detection performance and confirms its improvement by computer simulation. Furthermore, false-detection and miss-detection performance of the proposed spectrum sensing scheme are evaluated and compared with those of the periodogram scheme according to the roll-off factor of the filter and modulation scheme.

Somatosensory evoked potentials are used along with motor evoked potentials for ensuring patient safety during scoliosis surgery. The operating room is a difficult recording environment with electromagnetic noise overlapping the few μV signal that is used to asses the status of the somatosensory tract of the patient during the operation. In this paper we study three methods to improve the signal-to-noise ratio of the recorded samples. The widely used arithmetic mean is compared with median and trimmed mean methods.

A novel CMOS Impulse Radar for CMOS implementation is proposed exploring the concept of swept-threshold sampling. Time-domain signal processing with counter-based integration in parallel structures is used. With continuous time, delayline based parallel sampling topologies we achieve a sampling rate in excess of 20GHz. A functional CMOS Impulse radar is implemented in silicon with measured system performance.