Signal Analyzer Research Articles

Spectrum sensing and communication functionalities verification in cognitive radio

SummaryThis paper is intended to discuss hardware setup implementation for realizing the spectrum sensing and communication functionalities of a five‐port integrated ultrawideband and narrowband antenna system. The five‐port integrated antenna system consists of one ultrawideband antenna and four narrowband antennas. The ultrawideband antenna is used for spectrum sensing in cognitive radio, whereas the four narrowband antennas are used for communication. In order to validate functionalities of the antennas, their spectrum sensing and communication performance is verified using an arbitrary waveform generator, real‐time signal analyzer, and Universal Software Radio Peripheral. The ultrawideband antenna is able to sense the various frequencies transmitted by the arbitrary waveform generator. These transmitted signals from the arbitrary waveform generator are treated as busy spectrum channels in the cognitive radio environment. The narrowband antennas are able to perform communication by transmitting the signals at identified spectrum holes. The sensed signals are observed on a real‐time signal analyzer, and the communication signals are viewed in LabVIEW software for which a real‐time signal reception algorithm is used. This signal reception is performed using Universal Software Radio Peripheral.

A smartphone-integrated ratiometric fluorescence sensing platform for visual and quantitative point-of-care testing of tetracycline

A smartphone-integrated ratiometric fluorescent sensing system (DPA-Ce-GMP-Eu) for visual and point-of-care testing (POCT) of tetracycline with high sensitivity and accuracy was developed. The blue fluorescence of DPA-Ce-GMP was changed into red by doping with Eu3+ duo to the energy transfer from Ce3+ to Eu3+. Upon exposure to tetracycline, coordination between Eu3+ and tetracycline blocks energy transfer from Ce3+ to Eu3+, converting the fluorescent color from red to blue. The tetracycline detection can be realized within a wide concentration range from 0.01 μM to 45 μM. The limit of detection (LOD) reaches as low as 6.6 nM. To realize quantitative point-of-care detection in real samples, a portable device with smartphone as signal reader and analyzer is further designed to integrate with the DPA-Ce-GMP-Eu sensing platform. The Color Picker APP installed in the smartphone can convert the Red, Green and Blue (RGB) channels of the fluorescence images into digital values. With milk as real sample, tetracycline can be on-site detected with LOD of 10.8 nM. This developed platform presents a great promise for POCT in practical application with merits of low cost, easy carry, simple operation, and excellent selectivity and repeatability.

Automated measuring system for studies of microwave filters in a wide frequency range

The structure of an automated measuring system for the study of the frequency characteristics of microwave filters in a wide frequency range is given. It is based on a handheld probe station, a vector network analyzer, a vector signal analyzer and a signal generator. It provides automation of research and determination of the main parameters of microwave filters – amplitude-frequency characteristics, phase-frequency response, group delay differences, level signal attenuation in stop band. The function of documenting the results of measuring the parameters of microwave filters allows not only in real time, but also in post-processing to analyze and compare the characteristics of microwave filters in the frequency range from 10 MHz to 24 GHz.

Error correction and uncertainty measurement of short-open-load calibration standards on a new concept of software defined instrumentation for microwave network analysis

Software-Defined Radio (SDR) has appeared as a sufficient framework for the development and testing of the measurement systems such as a signal generator, signal analyzer, and network analysis used in the network analyzer. However, most of researchers or scientists still rely on commercial analyzers were larger benchtop instruments, highly cost investment and minimum software intervention. In this paper, a new concepts measurement revolution called as Software Defined Instrumentation (SDI) on network analysis is presented, which is based on reconfigurable SDR, a low-cost implementation, ability to access RF chain and utilizing open source signal processing framework. As a result, a Vector Network Analyzer (VNA) has been successful implemented by deploying an SDR platform, test sets, and data acquisition from the GNU Radio software in host PC. The known calibration process on SHORT-OPEN-LOAD (SOL) technique is validated to ensure measurement data from this SDI free from systematic error. Two types of SOL calibration standards used for a comparison study to validate the SDI measurement system which is capable of generating the response on the differential of standard quality and accuracy of standards kits. Finally, calibration uncertainty analysis is also presented in this work by utilizing RF open source package without any cost addition.

Dynamic and thermal characterization of additively manufactured pressure-fed flexures with internal fluidic channels

This paper presents the dynamic and thermal characteristics of pressure-fed flexures with the additively manufactured internal fluidic channels under various pressure and fluidic conditions. Additive manufacturing technology makes use of the mechanical design flexibility that can effectively control the material distribution in terms of stiffness and damping of the flexures. Five different fluidic channel geometries (circular, semicircular, inverse-semicircular, triangular, and inverse-triangular) with the same cross-sectional area were designed and fabricated inside of one-dimensional cantilever beams (10 × 24 × 100 mm3). Stiffness, damping ratio and natural frequency of each cantilever according to varying air pressure condition from 14.7 psi (unpressurized) to 75 psi and water-filled condition were characterized, and at the same time, dynamic behaviors of each cantilever were identified by using dynamic signal analyzer. Furthermore, the thermal behavior of the channel with respect to unpressurized air, 40 psi air, and water-flowing condition was analyzed. As a result, the internal channel geometry and filled-in media in the channel have significant influences to determine the dynamic and thermal characteristics of flexures. These results can be applied to the design of flexure mechanisms that can adaptively control or compensate for their dynamic behaviors in an easy, convenient and low-cost manner.

Drilling Condition Identification Based on Sound Pressure Signal in Anterior Cervical Discectomy Surgery

BackgroundIn anterior cervical discectomy and fusion (ACDF) surgery, drilling operation causes a high risk of tissue injury. This study aimed to present a novel feedback system based on sound pressure signals to identify drilling condition during ACDF.Material/MethodsACDF surgery was performed on the C4/5 segments of 6 porcine cervical specimens. The annulus fibrosus, endplate cartilage, sub-endplate cortical bone, and posterior longitudinal ligament (PLL) were drilled until penetration using a 2-mm high-speed burr. Sound pressure signals were collected using a microphone and dynamic signal analyzer. The recorded signals of different tissues were proceeded with lifting wavelet transform for extracting harmonic components. The frequencies of harmonic components are 1, 2, 3, 4, and 5 times higher than the motor frequency. The magnitude of harmonic components was calculated to identify different drilling conditions, along a broad spectrum of frequencies (1–5 kHz). For statistical analysis, one-way ANOVA (analysis of variance) and post hoc test (Dunnett’s T3) were performed.ResultsVery good demarcation was found among the signal magnitudes of different drilling conditions. Different drilling conditions do not present the same rate of variation of frequency. Differences in magnitude among all drilling conditions were statistically significant at certain frequency points (p<0.05). In 3 cases, one tissue could not be identified with respect to another (annulus fibrosus and endplate cartilage at 2 kHz, PLL and penetration at 3 kHz, annulus fibrosus and sub-endplate cortical bone at 5 kHz, p>0.05).ConclusionsSound pressure signals may provide an auxiliary feedback system for enhancing drilling operation in ACDF surgery, especially in minimally invasive surgery.

Practical Prediction of CFO-Made OFDM Symbol Distortion

The Carrier Frequency Offset (CFO) is considered to be a major drawback of the Orthogonal Frequency-Division Multiplexing (OFDM) signal. So, in many practical situations, specifically with LTE-Advanced downlink introducing carrier aggregation, estimation of the CFO-induced OFDM symbol phase deviation, is of interest. However, this demands complex test equipment, such as e.g. a Vector Signal Analyzer (VSA), which might not be always and everywhere available. Therefore, we applied the link abstraction principle on the Bit Error Rate (BER) that is considered to be determined just by the CFO-caused phase deviation, i.e. as if the channel was noiseless and time-dispersion-free (so that evident bit errors occur just due to the actual CFO). Furthermore, as the CFO-caused squared phase deviation is linear with the instantaneous (per-OFDM-symbol) Peak-to-Average Power Ratio (PAPR), which is related to the Error Vector Magnitude (EVM) and so with BER, we develop a simple model for analytical BER-based estimating of CFO. In this sense, we considered the easy-to-measure BER degradation as resulting just from the according additive white Gaussian noise (AWGN) source, which abstracts the CFO distortion. The proposed analytical model is validated by according Monte-Carlo simulations.

Analysis of electromagnetic behaviors induced by contact failure in electrical connectors

AbstractElectrical connectors are widely used in electrical devices as an interconnect element and their reliability is a critical factor in device performance. However, there are multiple factors that may lead to poor reliability. These include contact failure induced by temperature and humidity, vibration, and atmospheric contamination, which may induce deterioration of the transmitted signal and leakage of electromagnetic energy. In the current work, the contact failure characteristics of a specific connector are investigated through measurement and analysis of high frequency parameters and spectrums. Based on transmission line theory and electrical contact theory, an equivalent model was developed to explore the effect of contact failure on high frequency parameters. Experiments were conducted using a network analyzer, signal generator, signal analyzer, and H‐field probe. The high frequency parameters were measured and compared with the calculated values, with consistent results. The leakage spectrums were measured with an H‐field probe for a variety of input signal amplitudes and frequencies and loose contact conditions. The results indicate that leakage increases with higher frequency and greater input signal amplitude.

WmA-MiFN: A Weighted Majority and Auction Game Based Green Ultra-Dense Micro-Femtocell Network System

Power optimization and interference management in ultra-dense small cell based fifth-generation mobile networks are critical issues. This paper proposes a two-tier micro-femtocell based heterogeneous ultra-dense cellular network system, where femtocell allocation takes place inside the microcell based on user density. The femtocells form groups according to the adjacency and the leader selection of each group is performed using weighted majority game. Dedicated frequency allocation is performed for micro- and femtocell users though the leader of each femtocell group allocates frequencies to its follower femtocells based on auction game. Agilent EXG vector signal generator N5172B, EXA vector signal analyzer 9010A, and Agilent signal studio software are used for experimental purpose for performance evaluation of the proposed network. According to the simulation results, the proposed network decreases power transmission by 23%–41%, improves signal-to-interference-plus-noise ratio by 12%–39% and spectral efficiency by 10%–37% than the existing competing heterogeneous cellular network systems.

Embedded Ceramic-Based Passive Wireless Sensors for Harsh-Environment Applications

Recent advancements in high temperature systems such as gasifiers, molten slag furnaces, super-heated steam turbines, and energy harvesting systems require in-situ temperature monitoring. Conventional temperature sensors such as thermocouples, thermistors, and resistance temperature devices (RTDs) are limited to such applications due to poor reliability. Additionally, these sensors require one end of the device to be maintained in a relatively cold junction which limits the integration with the sophisticated modern high temperature systems. To mitigate these issues, research has been focused on adapting wireless technology for measuring temperature in harsh environments where a conventional temperature sensor cannot be integrated with the system. Initially, research was focused heavily on fiber optics sensor systems, surface acoustic wave (SAW) sensors, laser interferometers, and infra-red sensors. However, these sensor systems have limited lifespan, poor reliability due to reactions taking place at the hot junction, and integration of the sensor with the high temperature system is challenging due to sophisticated design of the furnaces, gasifiers, or turbine blades. In order to mitigate these issues, research has been focused on adapting radio-frequency (RF) technology for high temperature systems. The objective of this work was to design and fabricate inductor-capacitor (LC) resonator based wireless sensors to monitor temperature systems above 500oC.The two-dimensional (planar) LC resonator sensors were designed using the ANSYS Maxwell simulation package. The inductor design was based upon a fifteen-turn coil. The coil geometry was based on a width of 0.15 mm and a spacing of 0.15 mm spacing between the turns. The outer diameter was ~20 mm and the inner diameter was near ~10 mm. The capacitor was based on an interdigitated capacitor (IDC) which could be easily printed onto a ceramic substrate, which would act as the dielectric. The common substrate used in this work was alumina (Al2O3) or yttrium-stabilized zirconia (YSZ). The LC circuit patterns were printed onto alumina or zirconia substrates using inks containing semi-conducting ceramic particles. A few different semi-conducting ceramic compositions were evaluated in this work. One example composition was the La2NiO4 (LN) composition, which displays relatively good high-temperature stability and high electrical conductivity in the range from >40 S/cm at temperatures above 450⁰C. The ceramic powder compositions were synthesized using a conventional solid-state reaction route by mixed the stoichiometric constituents by attrition-milling using zirconia media in ethanol. The resultant slurry was dried and calcined >1000°C for 4 h. X-ray diffraction (XRD) analysis was performed using Panalytical X-ray diffractometer to confirm single phase formation. The circuit patterns were fabricated by using a micro-casting process. Conventional photolithography was used to pattern the photoresist onto the ceramic substrates. The patterned photoresist acted as the molds to deposit the ceramic inks to form the desired LC patterns. The micro-casted patterns were dried and then fired in a muffle furnace to ~1200oC to densify the patterns and bond them to the ceramic substrates. During the firing process, the photoresist would be removed in situ through a basic pyrolysis mechanism. For initial testing in this work, platinum (Pt) interconnects connected to the contact pads were made using Pt ink and further connected to Pt wires to connect to the electrical analysis equipment. Figure 1 shows a magnified optical microscopy picture of a section of the inductor pattern, which shows the level of resolution of the ceramic pattern. The sensors were tested within a high temperature muffle furnace in air. Initial tests used matching sensors placed parallel to each other within the furnace. One sensor was attached using the Pt wires to a signal generator (HP E4433B, USA) to act as the interrogator. The second sensor was hard-wired to a signal analyzer (Tektronix RSA306B, USA). The sensors were characterized at 500 – 1000oC in an ambient atmosphere with an RF signal ranging from 10 – 80 MHz at 2 MHz/sec sweep rate. The sensors showed a sensitivity of 0.2 kHz/oC. Two signal processing methods were implemented in algorithm form (within MATLAB) to estimate the temperature given the frequency response of the sensor. The methods evaluated were the cross-correlation and minimization of absolute error methods. In addition to these two signal processing methods, a split window technique for analyzing the temperature/frequency correlation was used. The cross-correlation signal processing method showed the best fitting for the initial sensor testing. The first set of sensors based on the LN compositions demonstrated sensitivities ~0.2 kHz/oC up to 1000°C. The work will further discuss the results from all sensor compositions and geometries. In addition, the investigation of cyclic stability and repeatability analysis will also be discussed in the presentation. Figure 1

A Decoupling Design with T-Shape Structure for the Aluminum Nitride Gyroscope.

This paper reports a novel design for the decoupling of microelectromechanical systems (MEMS) gyroscopes. The MEMS gyroscope is based on piezoelectric aluminum nitride (AlN) film, and the main structure is a mass hung by T-shape beams. A pair of parallel drive electrodes are symmetrically placed on the surface of the vertical bar for driving the oscillating mass. A serpentine sense electrode is placed on the lateral bar. When the gyroscope is oscillating in drive mode, charges with equal quantity and opposite sign will be polarized and distributed symmetrically along the lateral bar. These charges neutralize each other at the sense electrode. Therefore, no coupling signals can be detected from the sense electrode. This design can realize the decoupling between the drive mode and sense mode. In this work, the T-shape decoupled structure was designed as the key component of an AlN piezoelectric gyroscope and the whole structure was simulated by COMSOL Multiphysics 5.2a. The working principle of the decoupling is described in detail. Electrical properties were characterized by the dynamic signal analyzer. According to the test results, the drive mode and the sense mode are decoupled. The coefficient of orthogonal coupling is 1.55%.

Analysis on the Definition Consistency Problem of EVM Measurement and its Solution

The definition consistency problem of error vector magnitude (EVM) measurement is analyzed, and a solution using the peak-to-average ratio of the constellation diagram as a correction factor is proposed. Using different vector signal analyzers, the EVM values for 16-quadratic-amplitude modulation (QAM) and 64-QAM digitally modulated signals with certain distortions are measured. Furthermore, the corresponding theoretical EVM values are obtained through numerical simulation and analytical calculation. Comparing these results, it could be found that the definitions of EVM in different instruments are different. The essential reason is the different definition of EVM in the radio broadcast television technical standards and the wireless communication technology standards. This difference will lead to measurement errors and cognitive confusion. In order to solve this problem, a method using the peak-to-average ratio of the constellation diagram as a correction factor is proposed, and the experimental results proved that this solution is effective. At the same time, we strongly recommend the adoption of a unified EVM definition.

Deep learning based EVM correction for RF receiver of vector signal analyser

This Letter presents a novel deep learning approach for optimising the receiver performance with respect to the error vector magnitude (EVM) metric, which was verified and evaluated by applying it to a self-developed proprietary vector signal analyser (VSA). A four-layer neural network was built and trained to estimate and correct the systematic error of the VSA receiver by using a calibrated commercially available vector signal generator as the training source. Experimental results show that the EVM performance of the self-developed VSA is improved and approaches that of a state-of-the-art VSA.

Performance comparison of automatic peak detection for signal analyser

The aim of this paper is to propose a new peak detection method for a portable device, which know as modified automatic threshold peak detection (M-ATPD). M-ATPD evolves out of ATPD with a focus on reducing computational time. The proposed method replaces the clustering threshold calculation in ATPD with a standard deviation threshold calculation. M-ATPD reduces computational time by 2 times faster compared to ATPD for control signal and 8.65 times faster compared to ATPD for raw biosignals. Modified ATPD also shows a slight improvement in terms of detection error, with a decrease of about 6.66% to 13.33% in peak detection of noise signals. Modified ATPD successfully fixes the error of peak detection on pulse control signals associated with ATPD. For raw biosignals, in total M-ATPD achieved 19.41% lower detection error compare to ATPD.

In-Service BER Based Estimation of OFDM PAPR and CFO-induced Peak Phase Deviation

High Peak-to-Average Power Ratio (PAPR) of the transmitted OFDM signal is a well-known major drawback of the Orthogonal Frequency-Division Multiplexing (OFDM), so the High-Power Amplifier (HPA) is therefore necessary to operate in its linear region, i.e. with large back-off between the operating input power and its saturation region, so introducing not only in-band distortion, but also the adjacent channel interference. Specifically with the Long-Term Evolution (LTE) systems downlink, some sort of PAPR reduction, such as e.g. clipping, must be utilized. Considering that in many practical situations, determining PAPR demands complex test equipment, such as e.g. Vector Signal Analyzer (VSA), which might not be available, in this paper, we develop a simple Bit-Error-Rate (BER) based model for the (residual) PAPR estimation, by applying link abstraction, i.e. considering the easy measurable BER degradation due to HPA non-linearity, as if it were the consequence of the according level of additive white Gaussian noise (AWGN) abstracting the HPA distortion, while considering high Signal-to-Noise Ratio (SNR) and long enough cyclic prefix (CP), thus neglecting (real) additive noise and time dispersion (i.e. multipath fading). Moreover, the out-of-service BER testing, which requires network operator to interrupt its revenue-generating traffic, can be substituted by in-service BER estimation from in-phase and quadrature-phase eye diagram closures, measured on live traffic, by means of a simple oscilloscope. The analytical model is verified by the appropriate Monte-Carlo simulations.

КОНТРОЛЬ І МОДЕЛЮВАННЯ ПАРАМЕТРІВ ДЛЯ ТЕПЛОВОЇ ДІАГНОСТИКИ ПОРУШЕНЬ СИЛОВОГО ЕЛЕКТРООБЛАДНАННЯ

It has been considered the heat processes of traction electric engines parts in the maintenance and possible ways of heat generation modeling, which intensity is interconnected with operating physical quantities and possible components failure of traction electric drives in urban electric transport. The reasonable choice of input parameters, which control is possible with the help of remote techniques, located outside the mobile vehicle, was used in the development of pilot plant. By means of experimental equipment set containing electromechanical device in the form of a traction drive and brake, means for setting, regulation and control of technological input values and experimental device for measuring heating temperature electric engine with a given accuracy, it was realized the prepared experiment plan, implemented the variation of thermal processes in possible duty cycles of traction power equipment occurring on real urban routes. By means of differential electronic transducer “temperature-frequency” (T–F), the results of changing output ordinate were recorded and used in polynomial modeling of heating process in electric engine. The regression second order model, describing the thermal process, a spectral analyzer for record and visual control of output ordinate, were used for studying heat generation in laboratory-like environments and for evaluating the possibility of using standard and experimental control device for real traction substations of urban electric transport during remote technical diagnostics equipment according to its heating temperature. Using experimental differential electronic transducer T–F with a modulator and short mathematical description of heating process of traction electric drive allow to identify thermal processes with using of computing tools, which are different in few resources. It has been considered hardware-based ways to achieve the desired measuring set accuracy of the output ordinate and a program solution variant of the spectral low-frequency signal analyzer, which realization is possible by means of popular microcontrollers. The results have confirmed the appropriateness of studying thermal processes in electrical equipment and devices for synthesis of local compact remote equipment, which allows to create technical diagnostics devices and neural networks for possible failures evaluation, determined by the heat gradient in parts of power equipment of urban electric vehicles, operated on various routes and in different conditions.

Inspection Technology Using Helmholtz Resonance for Small Holes

In this paper, we present an inspection technology using Helmholtz resonance for small holes. As for the Helmholtz resonator, resonance frequency changes depending on the shape of the opening of the resonance container. The opening part is replaced with small hole parts and the hole diameter is inspected by measuring the resonance frequency of the inspection container. Small hole parts processed into a metal plate by press stamping or electric discharge method are the subject of examination. The prototype inspection system is constructed of a cylindrical container, a signal generator,and a sound signal analyzer. The container has a built-in standard microphone and speaker and resonance frequency is measured with respect to the container volume and sample hole diameter. The test sample of about 0.05 mm-2.0 mm in diameter had a hole formed by precision drill processing using planer-type jig borer and the electric discharge method. Test sample hole diameter inspection is enabled by measuring the resonance frequency and first fourier transform of measurement data.

Multifunction Radio Frequency Photonic Array With Beam-Space Down-Converting Receiver

A multifunction photonic beam-space array processor is shown to generate the beam space of an X -band array. Subsequent down-conversion of desired beams is performed via introduction of an optical local oscillator and high-speed photodetectors at the processor output. A separate optical path is used to “image” the full field of view of the input array for real-time angle-of-arrival estimation. Finally, experimental results showing simultaneous processing of output beams for a radar waveform and an in-band communications signal are presented. The recovery of a 10-MHz bandwidth, quaternary phase-shift keying communications signal with a nominal error vector magnitude of 15.5% is performed via a vector signal analyzer, whereas a custom digital beam-space beam-forming processor is shown to process the same beam data to recover a 100-MHz chirp radar waveform while simultaneously canceling the in-band communications signal by approximately 20 dB via an adaptive spatial null.

Seizure episodes detection via smart medical sensing system

Cyber-physical systems (CPS) consist of seamless network of sensors and actuators integrated with physical processes related to human activities. The CPS exploits sensors and actuators to monitor and control different physical process that can affect the computations of the devices. This paper presents the monitoring of physical activities exploiting wireless devices as sensors used in medical cyber-physical systems. Patients undergoing epileptic seizures experience involuntary body movements such as jerking, muscle twitching, falling, and convulsions. The proposed method exploits S-Band sensing used in medical CPS that leverage wireless devices such as omni-directional antenna at the transmitter side, four-beam patch antenna at the receiver side, RF signal generator and vector signal analyzer that perform signal conditioning by providing amplitude and raw phase data. The method uses wireless monitoring and recording system for measurement and classification of a clinical condition (epileptic seizures) versus normal daily routine activities. The data acquired that are perturbations of the radio signal is analyzed as amplitude, phase information, and statistical models. Extracting the statistical features, we leverage various machine learning algorithms such as support vector machine, random forest, and K-nearest neighbor that classify the data to differentiate patient’s various activities such as press-ups, walking, sitting, squatting, and seizure episodes. The performance parameters used in three machine learning algorithms are accuracy, precision, recall, Cohen’s Kappa coefficient, and F-measure. The values obtained using five performance parameters provide the accuracy of more than 90%.

Real-time solid flow velocity measurement based on a microwave sensor

Measurement and control of bulk solid flows become increasingly important in industries, such as large-scale production, coal transportation and food processing, although rapid and accurate velocity measurement is still a challenging task in these applications. This paper presents a new velocity measurement method based on a microwave sensor operated at 10.525 GHz and investigates the factors that affect velocity of bulk solid flows and the velocity of the solid particles in order to quantify the flow and improve the efficiency of transportation. In this method, a microwave Doppler Signal Analyser is adopted to calculate the average velocity of bulk solid flows and obtain the instantaneous velocity of a single solid flow. The influence of air friction, pipe collision and particle interactions is also analysed with experiments. The measurement results show that the average velocities of bulk solid flows range from 0.6 to 1.6 m/s, and the interaction between solids play a major effect on solid movements. The effect of pipe wall friction should also be considered. Besides, the mass flow rate and the total mass of bulk solid flow can be calculated. The mass flow rate ranges from 0 kg/s to 0.21 kg/s in the entire experiment.