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A pavement condition sensor aims to estimate the pavement surface grip, and therefore the sensor must detect the presence of water, snow, slush or the like on the surface of the pavement. The leading technology for such a sensor is near infrared diffuse reflectance spectroscopy using a wavelength range around a water absorption peak. In this paper we present a pavement condition sensor based on said technique that uses an electro-optic dual optical frequency comb generator as optical source. The proposed sensor provides unique properties in terms of measuring integration time that are necessary to advance the pavement condition several meters ahead of a moving vehicle. This work was supported by the Spanish Ministry of Economy, Industry and Competitiveness (grant TEC2017-86271-R) and by the Madrid Government (Comunidad de Madrid-Spain) under personnel Grant PEJ-2019-AI/IND-13093 and under the Multiannual Agreement with UC3M in the line of Excellence of University Professors (EPUC3M26), and in the context of the V PRICIT (Regional Programme of Research and Technological Innovation)

We propose an optical thickness measurement device based on electro-optic dual-optical frequency combs (dual-OFCs). Optical frequency combs (OFCs) are light sources that provide an optical signal consisting of many equidistant monochromatic tones. In this paper, we present an agile dual-OFC architecture with adjustable frequency separation of the comb modes and total frequency span, allowing high-resolution measurements of the thickness of transparent thick samples. This architecture is based on a single continuous-wave laser diode and external electro-optic devices to implement the dual-comb sensor, allowing easy control of the optical spectrum of the interrogation source (dual-OFC). As it is characteristic of dual-OFC systems, the optical transmittance function of the sample (etalon) is directly translated to the radiofrequency domain, where detection, demodulation, and processing of signals are performed. The shift in the complexity of implementation from the optical to the electronic domain yields many advantages, as acquisition and signal processing are made independently on the optical characteristics of the sample (thickness). This work was supported by the Spanish Ministry of Economy and Competitiveness under the RTC-2015-4205-4 Salicar and TEC-2014-52147-R Mossi grants.

Optical frequency combs (OFCs) generated through the modulation of continuous-wave lasers offer higher power per component, simple comb spacing control, and lower complexity and cost than traditional OFCs. By these reasons, they are an interesting optical source for spectrometers. In this letter, a dual-comb architecture based on two OFCs generated from the same laser using optical phase modulators is presented. The system features a new placement for the spectroscopic sample that increases the versatility, robustness, and stability of the instrument without requiring any reconfiguration for carrying out different types of measurement. Besides this, a self-referenced detection setup based on digital phase sensitive multitone detection improves the SNR of the previous approaches offering more flexibility in its configuration and high data output rate. The proposed architecture is validated by measuring a ro-vibrational absorption feature of HCN at 1544.51 nm and characterizing the spectral response of a fiber-coupled Fabry–Perot filter.

A sensitive optical microphone for photoacoustic spectroscopy based on the common path topology of a fibre laser Doppler vibrometer (FLDV) using phase-generated carrier demodulation and a slim diaphragm as an acoustic wave transducer was demonstrated. A resonant gas cell was adapted to enhance gas-detection performance and simultaneously provide efficient cancellation of the window background acoustic signal. Ammonia (NH3) was selected as the target gas. The absorption line was experimentally identified using a distributed feedback laser diode emitting at 1530 nm. The linearity and sensitivity of the gas sensor were measured using wavelength modulation spectroscopy with second harmonic detection. A Teflon diaphragm was used to implement the optical microphone, along with the FLDV, showing a minimum detectable pressure of 79.5 &mu, Pa/Hz1/2. The noise-equivalent absorption sensitivity for NH3 detection at the absorption line at 1531.7 nm was 1.85 &times, 10&minus, 8 W cm&minus, 1 Hz&minus, 1/2, and the limit of detection was 785 ppbv.

The measurement of the emitted electromagnetic energy in the UHF region of the spectrum allows the detection of partial discharges and, thus, the on-line monitoring of the condition of the insulation of electrical equipment. Unfortunately, determining the affected asset is difficult when there are several simultaneous insulation defects. This paper proposes the use of an independent component analysis (ICA) algorithm to separate the signals coming from different partial discharge (PD) sources. The performance of the algorithm has been tested using UHF signals generated by test objects. The results are validated by two automatic classification techniques: support vector machines and similarity with class mean. Both methods corroborate the suitability of the algorithm to separate the signals emitted by each PD source even when they are generated by the same type of insulation defect.

In this paper a new laser range finder approach is presented. It is based on a fan of beams of different optical frequencies that are projected to the target. The detected back-reflected beams contain frequency-encoded information about its reflection angles, which are used for the calculation of the range by means of triangulation methods. The fan of beams is generated from a fieldable electro-optic dual optical frequency comb generator and a diffractive optical system, without any moving parts. A proof-of-concept prototype of a range finder based on this approach was implemented and experimentally tested. An analysis of main sources of errors is also presented.

et al., In this study the first results on evaluation and assessment of grafted bioengineered skin substitutes using an optical Diffuse Reflectance Spectroscopy (DRS) system with a remote optical probe are shown. The proposed system is able to detect early vascularization of skin substitutes expressing the Vascular Endothelial Growth Factor (VEGF) protein compared to normal grafts, even though devitalized skin is used to protect the grafts. Given the particularities of the biological problem, data analysis is performed using two Blind Signal Separation (BSS) methods: Principal Component Analysis (PCA) and Independent Component Analysis (ICA). These preliminary results are the first step towards point-of-care diagnostics for skin implants early assessment.

A novel, compact optoelectronic hardware neural network ar- chitecture based on an optical broadcast scheme is proposed and dem- onstrated. The basic cell in the system is composed of electronic neu- rons that share the same time-distributed, optical broadcast input. The system combines the computational strengths of electronics and the communication strengths of optics, and employs a modular reconfig- urable architecture that is potentially scalable to a very large number of neurons while maintaining compactness. These characteristics are real- ized in an architecture that combines the integration of the processing elements in complementary metal-oxide semiconductor (CMOS) tech- nology with the construction of efficient optical interconnection elements with focusing properties based on multiplexed volume holograms. © 2005 Society of Photo-Optical Instrumentation Engineers. (DOI: 10.1117/1.1902994) Subject terms: optical neural networks; complementary metal-oxide semiconduc- tor sensor arrays; electronic processing; optical interconnects; volume holograms.

We present the first implementation, results, and performance analysis of a vision system whose processing core is a prototype hardware neural network based on an optical broadcast architecture. The system captures an im- age by a CMOS image sensor, compares it with a set of sample patterns (classes), and provides an output that indi- cates the class which the input image corresponds to. Due to the optoelectronic neural processor characteristics, the num- ber of classes can be enlarged without penalty on the opera- tion speed of the system. © 2004 Society of Photo-Optical Instru

A new optoelectronic hardware architecture of a neural network processor is proposed. A basic cell in the system is composed of electronic neurons that share the same time-distributed input; the input is introduced by means of an optical broadcast. The system combines the computational strength of electronics and the communica- tion strength of optics in an optimal manner and it is poten- tially scalable to a very large number of neurons. A descrip- tion of the system is given and the behavior of a first prototype is shown. © 2003 Society of Photo-Optical Instrumentation