Real-time Spectrum Analysis Research Articles

Synthesis of NbC@C(Nx) nanoparticles using DC arc discharge plasma for highly efficient oxygen reduction reaction

Development of the low-cost, high-efficiency, and durable non-precious metal electrocatalysts for cathodic oxygen reduction reaction (ORR) is of vital importance for fuel cells and metal-air batteries. Herein, the carbon-coated NbC nanoparticles (NbC@C NPs) were prepared using DC arc discharge plasma under a methane atmosphere. Then, the nitrogen-doping was conducted by heat treatment, resulting in nitrogen-doped carbon-coated NbC nanoparticles (NbC@C(Nx) NPs). Benefiting from the merit of unique core-shell structure and best synergy between the nitrogen-doped carbon shell and the NbC core, the obtained highest nitrogen-doped NbC@C(N1.36) NPs showed an onset potential (Eonset) of 0.89 V (vs. RHE) and a half-wave potential (E1/2) of 0.79 V, which are comparable to those of commercial Pt/C (20 wt%) (Eonset = 0.90 V, E1/2 = 0.80 V), and its diffusion-limited current density (JL) of 5.99 mA·cm−2 is even higher than that of commercial Pt/C (5.43 mA·cm−2). Moreover, it exhibited a remarkable long-term durability and impressive methanol resistance than Pt/C catalyst. In addition, the real-time optical emission spectrum (OES) analysis of arc plasma shows that the electron temperature (Te) is 7562.9 K in local thermal equilibrium (LTE) plasma. Therefore, the use of the DC arc discharge plasma method opens a fast and simple way to develop cost-effective and highly efficient non-precious metal catalysts for ORR.

High-frequency resolution diamond nitrogen-vacancy center wide-spectrum imaging technology

High-resolution wide-spectrum measurement techniques have important applications in fields such as astronomy, wireless communication, and medical imaging. Nitrogen-vacancy (NV) center in diamond is well known for its high stability, high sensitivity, real-time monitoring, single-point detection, and suitability for long-term measurement, and has an outstanding choice for spectrum analyzers. Currently, spectrum analyzers based on NV centers as detectors can perform real-time spectrum analysis in the range of several tens of gigahertz, but their frequency resolution is limited to a MHz level. In this study, we construct a quantum diamond microwave spectrum imaging system by combining continuous wave-mixing techniques. According to the spin-related properties of the NV center in diamond, we implement optical pumping by 532 nm green laser light illuminating the diamond NV center. A spherical magnet is used to produce a magnetic field gradient along the direction of the diamond crystal. By adjusting the size and direction of the magnetic field gradient, spatial encoding of the resonance frequency of the NV center is achieved. The magnetic field gradient induces the Zeeman effect on the diamond surface at different positions, generating corresponding ODMR signals. Through accurate programming, we coordinate the frequency scanning step size of the microwave source with the camera exposure and image storage time, and synchronize them circularly according to the order of image acquisition. Ultimately, after algorithmic processing, we successfully obtain comprehensive spectrum data in a range from 900 MHz to 6.0 GHz. Within the measurable spectrum range, the system employs continuous wave-mixing, simultaneously applying resonant microwaves and slightly detuning auxiliary microwaves to effectively excite the NV center. This method triggers off microwave interference effects, disrupting the balance between laser-induced polarization and microwave-induced spontaneous relaxation. Specifically, microwave interference causes the phase and amplitude of the fluorescence signal to change, leading to the generation of alternating current fluorescence signals. This further enhances the response of the NV magnetometer to weak microwave signals. The method enables the system to achieve a frequency resolution of 1 Hz in the measurable spectrum range, and it can separately measure the frequency resolution of multiple frequency points with a frequency step size of 1 MHz. The research results indicate that the wide-spectrum measurement based on NV centers can achieve sub-hertz frequency resolution, providing robust technical support for future spectrum analysis and applications.

The vibration registration system with the use of a seismic sensor and a real-time spectrum analyzer in the room intended for the TERS-STM system installations

The vibration registration system with the use of a seismic sensor and a real-time spectrum analyzer in the room intended for the TERS-STM system installations

In situ thermal noise measurements under nanoindentation of suspended graphene

We demonstrated thermal noise measurement under the nanoindentation of monolayer and bilayer graphene nanodrums. The resonant oscillation of the cantilever excited only by a thermal energy is detectable even in the case of contact with a suspended graphene. The contact resonance fRequency can be obtained in 1 millisecond intervals during the force curve measurement by optimizing the parameters of a real-time spectrum analyzer. The pretension value of the graphene nanodrum is evaluated by the minimum frequency just when the applied force of the cantilever becomes zero. The simultaneous measurement of the force and the resonant frequency with respect to the deformation of the graphene nanodrum enables us to determine the value of InvOLS (inverse optical lever sensitivity) more accurately in each measurement. From the analysis scheme, force curve measurements of the graphene nanodrums with the same diameters show good reproducibility. We also revealed that the effective spring constant of the graphene nanodrums consists of a weak sample-dependent pretension factor and a deformation-dependent factor proportional to the number of graphene layers.

Machine-Learning-Based Classification of Frequency Hopping in Radio Networks for Communication Reconnaissance

Abstract This article presents a customized approach for training a supervised learning neural network with the adaptive moment estimation algorithm, to classify the number of frequency hopping networks in an operational area. The algorithm was constructed based on data experimentally collected from a real-time spectrum analyzer for military very high frequency hopping networks. The impact of some training parameters on classification efficiency is briefly discussed while the obtained accuracy was above 97% for both test and validation data in all training variations. With this promising result, the proposed algorithm has the potential to be utilized in developing operational systems capable of real-time signal reconnaissance for military frequency hopping radio networks.

Design and Implementation of an Orbitrap Mass Spectrometer Data Acquisition System for Atmospheric Molecule Identification

Orbitrap mass spectrometers have gained widespread popularity in ground-based environmental component analysis. However, their application in atmospheric exploration for space missions remains limited. Existing data acquisition solutions for Orbitrap instruments primarily rely on commercial systems and computer-based spectrum analysis. In this study, we developed a self-designed data acquisition solution specifically tailored for atmospheric molecule detection. The implementation involved directly integrating a spectrum analysis algorithm onto a field programmable gate array (FPGA), enabling miniaturization, real-time performance, and meeting the desired requirements. The system comprises signal conditioning circuits, analog-to-digital conversion (ADC) circuits, programmable logic circuits, and related software. These components facilitate real-time spectrum analysis and signal processing on hardware, enabling high-speed acquisition and analysis of signals generated by the Orbitrap. Experimental results demonstrate that the system can sample front-end analog signals at a rate of 25 MHz and differentiate signal spectra with an error margin of less than 7 kHz. This establishes the viability of the designed data acquisition system for atmospheric mass spectrometry analysis.

Compact real-time RF spectrum analyzer with 16 GHz instantaneous bandwidth based on photonic frequency-shifting loops

Spectral analysis of broadband RF signals in real time is of primary importance for numerous applications. So far, the instantaneous bandwidth of real-time spectrum analyzers based on conventional digital techniques is limited to a few GHz. This limitation is set by the clock jitter of the analog-to-digital converters, and by the processing capabilities in real time of digital electronics. On the contrary, analog architectures based on microwave photonics are not constrained by such limitations, and offer potentially a very high instantaneous bandwidth. However, they generally suffer from inherent limitations, such as large footprint and high complexity. Here, we propose a much simpler architecture of RF spectrum analyzer based on frequency-shifting loops. It utilizes only compact commercial telecom components, a single CW laser, and slow electronic resources (10 MSa/s). The probability of intercept is 100%, the instantaneous bandwidth reaches 16 GHz, and the spectral and temporal resolutions are respectively equal to 160 MHz and 50 µs. Our system is expected to open new avenues in embedded applications of microwave photonics.

Development of Double Channel Transformer Voiceprint Detection System Based on MEMS Digital Silicon Microphone

Aiming for on-line monitoring of typical mechanical faults of transformer, a two-channel MEMS digital silicon wheat voice print detection system is developed, which consists of two channel MEMS digital silicon wheat array, the host of sound acquisition system and the upper computer software with the function of displaying real-time waveform and spectrum analysis. The device can operate reliably in complex environments by adjusting the array spacing, improving the power quality, and adjusting the network protocol. Further, different test environments were built to test the resolution performance of the equipment to the center frequency of the sound source at different distances and angles of the sound source. The results show that the system can realize the resolution of the center frequency of different sound source distance and Angle, and still has a good center frequency resolution performance in the case of environmental noise. At the same time, the system has strong stability, environmental adaptability, easy installation and non-contact detection characteristics, can be used for real-time detection and diagnosis of transformer faults.

Time-frequency characteristics of microwaves generated by hypervelocity impact

When space debris impinges upon a spacecraft shield structure at an ultra-high speed, part of the debris’ kinetic energy is converted into electromagnetic energy, which radiates outward in the form of electromagnetic waves and can interfere with the spacecraft's normal communication. To investigate the radiation characteristics of the emitted electromagnetic waves, a series of experiments were conducted using a two-stage light gas gun, in which a spherical aluminum alloy (diameter:6.4 mm) projectile impinges on a 23-mm-thick target of the same material at velocities of 3.3–6.3 km/s. A real-time spectrum analyzer and super-heterodyne receiver were used to measure the microwaves in the frequency and time domains, respectively. Then, the time–frequency spectrum of the microwaves was obtained by Hilbert-Huang Transform. Further, two mechanisms of microwave generation—plasma expansion and material destruction—in an aluminum–aluminum impact are proposed, and the radiation powers of the two mechanisms are estimated based on the theoretical analysis and experimental results. Finally, the effect of the plasma cutoff frequency on the microwave propagation is explained, and the relationship between the radiation mechanism and the impact velocity is obtained. When the impact velocity is less than 5.2 km/s, material destruction is the main mechanism of microwave radiation, whereas at impact velocities > 5.2 km/s, plasma expansion dominates.

The 5G-FR1 Signals: Beams of the Phased Antennas Array and Time-Recurrence of Emissions with Consequences on Human Exposure

The fifth generation (5G) of mobile communication technology poses lots of questions while introducing significant improvements compared with previous generations. The most sensitive question is related to the safety of human exposure. The aim of present work was to analyze, with a few chosen examples, two of the most significant features of 5G emissions: the extreme spatial variability of the exposure and the nonlinear dynamics characteristics of the temporal variability of the exposure. Two models of patch antenna arrays operating at 3.7 GHz with varying beam forming and beam steering capabilities were considered for an analysis of the specific absorption rate of electromagnetic energy deposition in tissues of a head model. This allowed clear emphasis on the influence of the antenna geometry and feeding peculiarities on the spatial variability of exposure. The second approach implemented the original idea of following the nonlinear recurrence behavior of exposure in time, and underlined the time variability characteristics of emissions with a real-life mobile phone running different 5G applications. Time series of the emitted electric-field strengths were recorded by means a real-time spectrum analyzer and two near-field probes differently positioned in the beam. The presence of laminar emissions, chaotic emissions, determinism and recurrence in the exposures prove the potential for recurrence quantification in predicting time variability features of 5G exposure. Overall, the impact of 5G signals on living bodies, with the highest possible man-made spatial and temporal variability, may have very unpredictable bio-medical consequences.

Real-time load spectrum analysis for lifetime prediction of e-mobility drivetrains

Real-time load spectrum analysis for lifetime prediction of e-mobility drivetrains

Real-time load spectrum analysis for lifetime prediction of e-mobility drivetrains

Real-time load spectrum analysis for lifetime prediction of e-mobility drivetrains

Broadband radio frequency signal measurement based on quantum compression sensing

With the rapid development of radio frequency technology such as radar, electronic warfare and 5G communication, the measurement and real-time spectrum characterization of broadband radio frequency signals become increasingly important. The traditional radio frequency signal real-time measurement technology is limited by the sampling rate of analog-to-digital converter and the ability to process digital signals, and encounters the problems of narrow measurement band, large data volume, and susceptibility to electromagnetic interference. This work is to study a radio frequency signal measurement technology based on quantum compression sensing, which uses integrated electro-optical crystal as radio frequency sensor, and constructs a compression sensing machine by modulating the photon wave function of the measured radio frequency signal to realize the compression measurement of broadband radio frequency signal, significantly improving the spectrum sensing bandwidth. The experiment demonstrates the long-term spectrum monitoring of power frequency and intermediate frequency high voltage signals, and the real-time spectrum measurement of high frequency radio frequency signals. Under the Fourier limit spectrum resolution, the real-time spectrum analysis bandwidth of GHz magnitude is realized, and the data compression rate reaches 1.7×10<sup>–5</sup>, which can meet the needs of 5G wireless communication, cognitive radio and other applications for broadband radio frequency signal spectrum measurement, and provide a new technical path for developing the next-generation broadband spectrum sensing technology.

Detection Technology of Intentional Electromagnetic Co-channel Interference Source

The characteristics and action mechanisms of intentional interference sources were analyzed. Then, a fast detection method of intentional co-channel interference was proposed based on such technologies as real-time spectrum analysis, digital phosphor display, and co-channel signal direction-finding. Next, two classical intentional interference scenarios were reproduced, and interference sources were detected fast through the proposed method.

Optimizing the Design of a Vocal Teaching Platform Based on Big Data Feature Analysis of the Audio Spectrum

With the development of electronics and communication technology, digital audio processing technologies such as digital audio broadcasting and multimedia communication have been widely used in society, and their influence on people’s lives has become increasingly profound. At present, the real-time and accuracy of musical instrument tuners on the market need to be improved, which hinders the design of vocal music teaching system. Based on the BP neural network algorithm and fast Fourier transform algorithm in FPGA, this paper designs a real-time and efficient audio spectrum analysis system, which realizes the spectrum analysis function of music signal. The methods to calculate fast discrete Fourier transform are the FFT algorithm based on time extraction and the FFT algorithm based on frequency extraction. The characteristic of BP neural network algorithm is that it can not only obtain the corresponding estimation results by forward propagation of the input data but also carry out back propagation from the output layer according to the error between the estimation results and the actual results, so as to optimize the connection weight between each layer. This paper proposes to add Nios II system to FPGA processor and adopt cyclone IV in the hardware design of the system, which can be better compatible with the system designed in this paper. In the software part, WM8731 is used to process the audio data. WM8731 consumes very little power to the system, which will effectively improve the processing efficiency of the system. Compared with the original system, the data model obtained after screening and processing of the system model designed in this paper has an algorithm accuracy of more than 90%, among which the audio spectrum clarity of vocal music can reach 95%. Based on the above, the circuit of each module is tested, and in the specific experimental process, the audio frequency spectrum under different conditions is analyzed and data processed. The system can complete the collection and analysis of various music signals in real time, overcome the limitation of single function of traditional tuner, improve the utilization rate of tuner and the clarity of timbre, and also tune a variety of musical instruments and greatly improve the intonation of musical instruments and the utilization rate of tuner, which has a certain practical value.

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The Dynamics of the Radiated Field Near a Mobile Phone Connected to a 4G or 5G Network

Characterizing the time variations of signals emitted by mobile terminals provides complementary information to health authorities, especially with the increase of frequency and energy of radiation towards millimeter waves. This experimental work aimed to quantify and classify the time variability of the electric field level measured at 10cm from a mobile phone connected sequentially to a 4th and 5th generation mobile network. Statistic analysis was performed on data from real-time spectrum analyzers, while self-similarity was computed by first recurrence plots of the radiated emissions, corresponding to five different types of mobile applications. Moreover, specificities to the communication standard and the type of application were identified.

Reconfigurable and Resource Efficient Implementation of a Parallel FFT Core in FPGA

Resource efficient implementation of a highly reconfigurable, parallel and pipelined FFT core that provides 1.2GS/s throughput rate with 24-bits wide input samples for the real-time spectrum analysis applications is developed and realized. Physical placement constraints are used to improve the timing performance of implemented design in FPGA. Some design techniques to reduce the memory complexities of design are also provided. Full implementation of the design is completed and implementation details are provided.

In the Twilight of Electromechanical Encryption, an Exceptional Machine Figured in a Major Spy Scandal

Growing up in New York City, I always wanted to be a spy. But when I graduated from college in January 1968, the Cold War and Vietnam War were raging, and spying seemed like a risky career choice. So I became an electrical engineer, working on real-time spectrum analyzers for a U.S. defense contractor. In 1976, during a visit to the Polish Army Museum in Warsaw, I saw an Enigma, the famous German World War II cipher machine. I was fascinated. Some years later, I had the good fortune of visiting the huge headquarters of the cipher machine company Crypto AG (CAG), in Steinhausen, Switzerland, and befriending a high-level cryptographer there. My friend gave me an internal history of the company written by its founder, Boris Hagelin. It mentioned a 1963 cipher machine, the HX-63.

Effect of electroacupuncture preconditioning on neuronal activities in lateral hypothalamus area of myocardial ischemia reperfusion injury rats

To observe the effect of electroacupuncture (EA) preconditioning of "Shenmen" (HT7)-"Tongli" (HT5) segment of the Heart Meridian on neuronal electrical activities of lateral hypothalamus area (LHA) in rats with myocardial ischemia reperfusion injury (MIRI), so as to investigate its possible mechanism underlying improvement of MIRI. Twenty-four SD rats were randomly divided into sham, model, EA and damage + EA (D+EA) groups, with 6 rats in each group. The MIRI model was established by occlusion of the anterior descending branch (ADB) of the left coronary artery for 30 min, followed by reperfusion for 2 h. In the sham operation group, the ADB was only threaded beneath the artery without ligation. EA (2 Hz, 1 V) was applied to bilateral HT7-HT5 for 20 min, once daily for 7 days. In the D+EA group, FN was injected with 0.4 μL of 1 g/L kainic acid solution. Electrocardiogram (ECG) of the neck-thoracic lead was recorded by using PowerLab. The electrical activities of the LHA region were recorded by the implanted microelectrode array (2×4) and Plexon multi-channel acquisition system. Cluster analysis of neuronal signals was carried out by Offline Sorter software. The discharge waveforms, autocorrelation and cross-correlation of neuronal activities were analyzed by using Neuro Explorer software. Compared with the sham group, the ECG-ST height was significantly increased (P<0.05), the discharge frequency of pyramidal neurons was significantly reduced (P<0.01), while the discharge frequency of interneurons was increased (P<0.01) in the model group. After EA treatment, the ECG-ST height was significantly decreased (P<0.05), the discharge frequency of pyramidal neurons was significantly increased (P<0.01) relevant to the model group. In comparison with the EA group, the ECG-ST height in the D+EA group was significantly elevated (P<0.05), whereas the discharge frequency of pyramidal neurons was significantly decreased (P<0.01). The discharge frequency of interneurons was kept increasing after MIRI. Real-time spectrum analysis showed that the local field potential spectrum energy of the EA group was significantly lower than that of the model group and the D+EA group. EA preconditioning of Heart Meridian can significantly increase the discharge frequency of LHA excitatory pyramidal neurons and reduce the energy of the local field potential spectrum, which maybe one of the important mechanisms of EA in anti -MIRI.