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.

The goal of an automatic monitoring system of partial discharges (PDs), based on acoustic emission (AE) detection, is the identification of the type of source of PD and its localization. In the event that multiple deterioration processes are present in the electrical equipment, more than one PD source may be active and their AE signals may overlap on the sensors. This overlapping effect modifies the temporal and frequency characteristics of the measured signals compared to the characteristics of the signals from a single PD source and thus, automatic classification becomes very difficult. In this paper we have proposed applying blind signal separation (BSS) techniques to recover the signals from each source, therefore separating each temporal and frequency characteristic. We have tested the proposed algorithm: firstly using synthetic mixed signals from two types of PD sources and secondly using real signals from a test bench specifically designed to control the position, time and amplitude of the AEs.

Partial discharges (PD) detection is a widely extended technique for the diagnosis of electrical equipment. Ultra-high frequency (UHF) detection techniques appear as the best choice if the goal is to detect PD online and to locate devices with insulation problems in substations and overhead lines. The location of PD is based on the determination of the difference of the time of arrival of electromagnetic pulses radiated by a source of PD to an array of antennas distributed around the monitored area. However, when measuring electromagnetic pulses radiated by PD activity many interfering signals, such as those coming from television (TV), global positioning system (GPS), wireless communication signals and others coming from electrical equipment distort the waveform detected by the sensors. Under these circumstances, the application of traditional techniques to estimate the time differences may fail. In this paper, the use Blind Source Separation (BSS) techniques applied to pairs of UHF sensors is proposed to extract the information of the difference of the time of arrival of the electromagnetic pulses radiated by a source of PD. The paper is focused on the application of the algorithm and the description of an experimental setup for controlled generation and detection of PD to verify the performance of the proposed technique.

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 μPa/Hz^1/2. The noise-equivalent absorption sensitivity for NH₃ detection at the absorption line at 1531.7 nm was 1.85 × 10⁻⁸ W cm⁻¹ Hz^−1/2, and the limit of detection was 785 ppbv.

We present experimental and theoretical results obtained from the study of the effects of optical feedback in low-cost Fabry–Perot laser diodes due to the presence of an external cavity created by an external reflective or diffusive vibrating target. Experimental results show that a change in the length of the external cavity produces the well-known amplitude modulation of the optical output power and, depending on the amount of optical feedback, a subperiodicity appears in the amplitude modulation of the output power. The experiments show that the subperiodicity appears independently of the length of the external cavity and is due to mode hopping between different longitudinal laser modes. Numerical analysis focused on the effects observed support that the mode hop occurs between modes whose round-trip phase delay along the external cavity is out of phase, thus producing a subperiodicity of the total amplitude modulation.

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.