Order Spectra Research Articles

Automatic Modulation Recognition for Secondary Modulated Signals

Automatic modulation recognition (AMR) for secondary modulated signals, remains as a bottleneck, since both analog and digital modulation are adopted in one signal. To address this issue, we focus on the original signal spectrum and the 2nd order spectrum of the pre-demodulated signal, which imply modulation features. Based on this idea, a novel statistic for discrimination is proposed and the feature vector is formed. Finally, the support vector machine (SVM) is adopted to implement the classification work.

Order spectrum analysis enhanced by surrogate test and Vold-Kalman filtering for rotating machinery fault diagnosis under time-varying speed conditions

Rotating machinery signals are usually dominated by rotating frequency harmonics, and the presence of these frequency components or change in their magnitudes indicate health condition. Order spectrum is widely applied in rotating machinery fault feature extraction, because of its capability in intuitive spectral representation of rotating frequency harmonics in order domain. However, some speed non-synchronous components are often present. They show wide-band features in order spectra, and hinder accurate identification of rotating frequency harmonic orders. To address this issue, a scheme is proposed to identify and remove speed non-synchronous components of either constant or time-varying frequency. To this end, surrogate test is generalized through new candidate construction method and nonstationarity based indicator for test criterion, to identify true nonstationary signal components adaptively and eliminate subjective influences. Vold-Kalman filter is used to separate signal components by exploiting its capability in mono-component decomposition of complex nonstationary signals. The proposed method is validated through analyses of both induction motor stator current signals and hydraulic turbine rotor vibration signal. The results demonstrate its advantages over conventional computed order spectrum analysis.

Intelligent robot chair with communication aid using TEP responses and higher order spectra band features

In recent years, electroencephalography-based navigation and communication systems for differentially enabled communities have been progressively receiving more attention. To provide a navigation system with a communication aid, a customized protocol using thought evoked potentials has been proposed in this research work to aid the differentially enabled communities. This study presents the higher order spectra based features to categorize seven basic tasks that include Forward, Left, Right, Yes, NO, Help and Relax; that can be used for navigating a robot chair and also for communications using an oddball paradigm. The proposed system records the eight-channel wireless electroencephalography signal from ten subjects while the subject was perceiving seven different tasks. The recorded brain wave signals are pre-processed to remove the interference waveforms and segmented into six frequency band signals, i. e. Delta, Theta, Alpha, Beta, Gamma 1-1 and Gamma 2. The frequency band signals are segmented into frame samples of equal length and are used to extract the features using bispectrum estimation. Further, statistical features such as the average value of bispectral magnitude and entropy using the bispectrum field are extracted and formed as a feature set. The extracted feature sets are tenfold cross validated using multilayer neural network classifier. From the results, it is observed that the entropy of bispectral magnitude feature based classifier model has the maximum classification accuracy of 84.71 % and the value of the bispectral magnitude feature based classifier model has the minimum classification accuracy of 68.52 %.

Circular dichroism and its uses in biomolecular research - A Review

The higher-order structure of proteins as well as their thermal stability can be determined using the circular dichroism (CD). CD is a common approach for swiftly assessing binding, secondary structure, and folding properties of proteins. In a nutshell, circular dichroism is an absorption spectroscopy technique that employs circularly polarized light to explore structural properties of optically active chiral compounds. Biological molecules, as well as their interactions with metals and other compounds, are studied extensively. Circular dichroism is becoming more widely acknowledged as a useful technique for studying the various conformations taken by proteins and nucleic acids in solution. Because CD is a quantitative approach, it can be used to track protein denaturation and protein-ligand interaction. These CD measures will have two key advantages: they can be performed on small amounts of material in a physiological buffer, and they will provide one of the greatest methods for monitoring any structural changes that occur as a result of changes in environmental conditions. It has proven possible to generate proteins on a big scale for therapeutic reasons utilizing recombinant DNA technology. Circular dichroism is also well-known as a useful method which is used for determining the folding characteristics of proteins. CD is used to see if a purified, produced peptide is either bended or if it has a mutation that impacts its strength and confirmation. The basic steps in getting this CD data, as well as the methodologies for interpreting the spectra in order to predict the protein structure, are summarized in this article. However, many researchers’ value is harmed when they use circular dichroism, either because of poor experimental design or because of insufficient data. The essential steps in getting this CD data, as well as the methodologies for interpreting the spectra in order to predict the protein structure, will be summarized in this article. However, the value of many investigations using circular dichroism is harmed due to insufficient attention to critical components of instrument calibration or sample characterization.

VZ Sex: X-Ray Confirmation of Its Intermediate Polar Nature

Abstract Intermediate polars are members of the cataclysmic variable binary stars. They are characterized by a moderately magnetized white dwarf accreting matter from a cool main-sequence companion star. In many cases, this accretion gives rise to a detectable X-ray emission. VZ Sex is an interesting X-ray source whose nature needs a robust confirmation. Here, we used archived XMM-Newton observations to assign the source to the intermediate polar class. We applied the Lomb–Scargle periodogram method to detect any relevant periodic feature in the 0.1–10 keV light curve and performed a spectral fitting of the X-ray spectrum in order to get information on the on-going accretion mechanism. By inspecting the periodogram, we detected a clear periodic feature at ≃20.3 minutes that we interpret as the spin period of the white dwarf. We additionally found the typical side bands expected as the consequence of the beat between the spin and the orbital period of ≃3.581 hr. The source is characterized by an unabsorbed flux of ≃2.98 × 10−12 erg cm−2 s−1 corresponding to an intrinsic luminosity of ≃7 × 1031 erg s−1 for a distance of ≃433 pc. The existence of such features allows us to classify VZ Sex as a clear member of the intermediate polar class. Furthermore, with the estimated WD spin, the ratio P spin/P orb is ≃0.09, i.e., consistent with that expected for a typical IP system above the period gap. In addition, the estimated intrinsic luminosity opens the possibility that a bridge linking the normally bright IPs to the faint population of sources does exist.

Spectrophotometric Determination of Carbimazole and Its Major Impurity, Degradation Product and Metabolite: Methimazole -=SUP=-*-=/SUP=-

The present research work was carried out in order to develop simple, accurate and precise UV sprctrophotometric methods having comparable sensitivity as that of sophisticated chromatographic techniques. Two methods were developed namely first derivative spectrophotometry and ratio spectra derivative spectrophotometry for accurate determination of specified impurity methimazole (imp A) in presence of drug carbimazole. First derivative spectrophotometric method involves recording of zero order spectra of both the drugs carbimazole and methimazole and its mixture in the range of 200-400 nm and subsequent conversion of these spectra into first derivative spectra. The drugs carbimazole and methimazole were determined by using zero crossing wavelengths of 227 and 260 nm respectively. In the second approach, ratio spectra were recorded for carbimazole and methimazole by selecting appropriate divisor concentration and converted into first derivative spectra. The determination of carbimazole and methimazole were carried out at wavelength 226.2 and 257 nm, respectively. Both the methods were validated as per ICH guideline. The drugs carbimazole and methimazole showed linear response with good correlation coefficient and exhibited specificity, accuracy and precision within acceptable range. The second method of ratio spectra derivative spectrophotometry was found more sensitive as compare to first derivative spectrophotometry in detecting level of impurity methimazole up to 0.5% as per official specification. Hence, these developed methods can be used as alternative to sophisticated chromatographic technique for determination of assay and related impurity in bulk drug and formulation. Keywords: carbimazole, methimazole, first derivative spectrophotometry, ratio spectra derivative spectrophotometry.

An Improved Viterbi Algorithm for Adaptive Instantaneous Angular Speed Estimation and Its Application Into the Machine Fault Diagnosis

It is a very challenging task to diagnose the fault of rotating machinery under variable speed condition. The traditional tacholess order tracking (TLOT) method still has the problems of high computation complexity and low adaptability. Aiming at these problems, a new adaptive instantaneous angular speed (IAS) estimation method based on the improved Viterbi algorithm (VA) and the energy centrobaric correction method is developed. Since the traditional VA cannot process the long time series and find the fundamental order automatically, an improved penalty function for ridge search is proposed. Meanwhile, the search band of IAS is adaptively optimized to accelerate the speed of ridge search. Furthermore, an energy centrobaric correction approach is used for improving the accuracy of instantaneous frequency estimation and the antinoise performance. With the obtained IAS, the nonstationary time-domain vibration signal is resampled as the stationary angle-domain vibration signal by the Vold–Kalman filtering and the Hilbert transform. Finally, the envelope order spectrum is used to diagnose the mechanical faults of a civil aircraft engine. With the datasets of aircraft engine, rolling bearing, and wind turbine, the experimental results show that the improved VA can adaptively estimate IAS faster and achieve higher accuracy of fault detection than the typical IAS estimation methods. Meanwhile, its antinoise ability is verified.

A Methodology to Handle Spectral Smearing in Gearboxes Using Adaptive Mode Decomposition and Dynamic Time Warping

Tacho-less order tracking is an effective tool for fault detection in gearboxes operating under speed fluctuations. This technique's performance depends on extracting instantaneous shaft speed information from a complex multicomponent gearbox signal, which is first preprocessed by a bandpass filter. However, spectral overlap resulting from the time-varying frequency components makes it challenging to isolate the shaft speed harmonic mono-component using this approach. In order to overcome such issues, an adaptive tacho-less order-tracking (OT) method combining the variational mode decomposition (VMD) and the fast dynamic time warping (FDTW) is proposed in this article. The proposed method first decomposes the measured gearbox vibration signal using VMD to estimate the instantaneous shaft speed profile to construct the shaft vibration signal. The gearbox vibration signal is then resampled based on the optimal warping path obtained by FDTW, which performs an “elastic” stretching and compression along the time axis of the extracted shaft vibration signal with respect to a sinusoidal reference signal with a constant shaft rotational frequency. Finally, the presence of gear fault is detected by constructing the order spectrum of the resampled vibration signal. The effectiveness of the proposed algorithm is demonstrated using both simulation analysis and experimental validation using measurements from two different wind-turbine gearboxes collected under test and field conditions, respectively.

Validated spectral manipulations for determination of an anti-neoplastic drug and its related impurities including its hazardous degradation product.

Innovative and specific double dual wavelength, dual ratio subtraction spectrophotometric methods were carried out along with a successive ratio subtraction spectrophotometric method for determination of dacarbazine and its related impurities including toxic and hazardous ones. For determination of dacarbazine by the double dual wavelength method, the absorbance differences between 323 and 350 nm of the zero order absorption spectra of dacarbazine were used. The values of absorbance difference between 267.2 and 286.2 nm of the zero order spectra of 5-amino-imidazole-4 carboxamide were used for its determination by the dual ratio subtraction method. The zero order absorption spectrum of 2-azahypoxanthine at 235 nm was used for its determination after applying the successive ratio subtraction method. ICH guidelines were followed for validation of the developed methods, where linear relationships were obtained in the range of 4–20, 1–16, and 2–20 μg mL−1 for dacarbazine, 5-amino imidazole-4-carboxamide and 2-azahypoxanthine, respectively. Accurate, precise, and specific results were obtained upon applying the proposed methods according to ICH guidelines. Furthermore, the developed methods were successfully applied for determination of dacarbazine in its pharmaceutical formulation. Comparing the results of the developed methods with those of the official USP spectrophotometric method statistically showed no significant difference. The developed methods don't need any sophisticated techniques so they are considered cost effective methods. Moreover, the introduced methods have the advantages of being green where water was used as a solvent. The methods proved to be more economic, fast and simple than other reported HPLC methods.

A TEO‐based modified Laplacian of Gaussian filter to detect faults in rolling element bearing for variable rotational speed machine

Conventional signal processing techniques for fault detection are usually aimed at constant speed conditions. Nowadays, order tracking, especially tacho-less order tracking is regarded as a valuable tool for extracting fault features under variable rotational speed conditions. Therefore, a teager energy operator (TEO)-based modified Laplacian of Gaussian filter is proposed to enhance the fault detection behaviour of tacho-less order tracking. This method consists of four steps: First, multi-synchrosqueezing transform is employed to estimate and then extract the instantaneous rotation frequency of a shaft. Second, based on the extracted curve, the non-stationary domain signal is converted into a quasi-stationary domain by the re-sampling technique. Third, the obtained quasi-stationary domain signal is de-noise by the novel method. Finally, fault characteristic orders are extracted via envelope order spectrum analysis method and the performance is significantly improved. The results of numerical simulation and experimental investigations are performed to validate the superiority of the novel method for fault extraction under variable rotational speed conditions.

Raman Spectroscopy Discloses Altered Molecular Profile in Thyroid Adenomas.

Follicular patterned nodules are sometimes complex to be classified due to ambiguous nuclear features and/or questionable capsular or vascular invasion. In this setting, there is a poor inter-observer concordance even among expert pathologists. Raman spectroscopy was recently used to separate benign and malignant thyroid nodules based on their molecular fingerprint; anyway, some histologically proved follicular adenomas were clustered as having a characteristic profile of malignant lesions. In this study, we analyzed five follicular thyroid adenomas with a malignant spectroscopic profile compared to five follicular adenomas with a benign Raman spectrum in order to assess possible molecular differences between the two groups. Morphological, immunohistochemical, and molecular analyses evidenced expression of malignancy-associated proteins in four out of five malignant clustered adenomas. The remaining malignant clustered adenoma showed a TSHR mutation previously associated with autonomously functioning follicular carcinomas. In conclusion, thyroid follicular adenomas are a group of morphologically benign neoplasms that may have altered the mutational or expression profile; cases of adenomas with altered immunophenotype are recognized as showing a profile associated with malignancy by Raman spectroscopy. This correlation warrants a more extensive evaluation and suggests a potential predictive value of spectroscopic assessment in recognizing characteristics associated with tumor progression in follicular thyroid neoplasms.

Design and Assessment of a Polyurethane Carrier Used for the Transmembrane Transfer of Acyclovir

The Herpes simplex viruses (HSV-1, HSV-2) are responsible for a wide variety of conditions, from cutaneous-mucosal to central nervous system (CNS) infections and occasional infections of the visceral organs, some of them with a lethal end. Acyclovir is often used intravenously, orally, or locally to treat herpetic infections but it must be administered with caution to patients with kidney disease and to children of early age. The main objectives of this study were to synthesize and evaluate new polyurethane nanoparticles that might be used as proper transmembrane carriers for acyclovir. Polyurethane particles were obtained by a polyaddition process: a mixture of two aliphatic diisocyanates used as organic phase was added to a mixture of butanediol and polyethylene glycol used as aqueous phase. Two different samples (with and without acyclovir, respectively) were synthesized and characterized by UV-Vis spectra in order to assess the encapsulation efficacy and the release profile, FT-IR, DSC, SEM, and SANS for structural characterization, as well as skin irritation tests. Nearly homogeneous samples with particle sizes between 78 and 91 nm have been prepared and characterized revealing a medium tendency to form clusters and a high resistance to heat up to 300 °C. The release profile of these nanoparticles is characteristic to a drug delivery system with a late discharge of the loaded active agents. Very slight increases in the level of transepidermal water loss and erythema were found in a 15-day evaluation on human skin. The results suggest the synthesis of a non-irritative carrier with a high encapsulation efficacy that can be successfully used for the transmembrane transfer of acyclovir.

Simulation and investigation of perovskite/nano-pyramidal GeSe solar cell: Realizing high efficiency by controllable light trapping

Perovskite Solar Cells (PSC) have been elicited much interest within the photovoltaic industry due to their many performance advantages. One of the effective ways to enhance the Power Conversion Efficiency (PCE) of PSCs is to minimize light and electrical losses. To this end, we have focused on the use of nanostructured light absorbers in PSCs and have simulated these structures to understand their effects on the light absorption and electrical output of the cells. Given that perovskites do not absorb light of wavelengths higher than 800 nm, we used an extra absorption material - GeSe – which has a narrower bandgap and a wider absorption spectrum in order to increase the amount of light absorbed. GeSe Nano-pyramids (GSNPs) were also used in the active layer (perovskite) to manage input light. The use of such structures improved the short-current density (Jsc) of the cell. The effects of changing the height of GeSe NPs were also investigated to determine the best height of NPs that produced the highest PCE. The optimal structure had NP height of 100 nm and resulted in Jsc and PCE values of 24.83 mA/cm2 and 18.49%, respectively, which were 25.65% and 21.80%, improvements over the planar design, respectively.

Intelligent cross-condition fault recognition of rolling bearings based on normalized resampled characteristic power and self-organizing map

Intelligent bearing fault recognition under nonstationary conditions is still a challenge. This paper presents a novel intelligent cross-condition bearing fault recognition scheme. In this scheme, we propose a normalized resampled characteristic power (NRCP) feature, which is constructed based on the pulse-based order spectrums. Based on NRCP feature, the whole fault recognition strategy is developed. First, the resampled signals are obtained by pulse-based order tracking technique, and the order spectrums are produced by the joint application of Hilbert transform and fast Fourier transform. Second, the NRCP feature space is constructed based on the order spectrums. Then, the Laplacian score (LS) algorithm is applied to refine the NRCP features. Finally, the new features are fed into self-organizing map (SOM) to identify the health conditions of rolling bearings. The proposed method is experimentally validated to be able to differentiate health, outer race fault, inner race fault, and multiple fault bearings.

A note on spectral velocity approximation at shorter intermediate periods

It is common to use the design pseudo spectral acceleration (PSA) spectrum together with a modal combination rule to estimate the peak linear seismic response of a structural system. Some of the modal combination rules proposed so far require an accurate estimation of spectral velocity (SV) spectrum consistent with the given design PSA spectrum in order to account for modal correlations in a simple manner. The traditional pseudo spectral velocity (PSV) approximation of SV ordinates is reliable only for the velocity-sensitive region of the spectrum. More reliable approximations have therefore been developed in the recent years for the acceleration-sensitive and displacement-sensitive regions. In this work, the approximation developed for the acceleration-sensitive region is proposed to be applied on a greater range of periods, involving the shorter periods of the velocity-sensitive region, for a more accurate estimation of the SV spectrum. Regression equations are developed to predict the limiting period of the extended range by using the information available from the given PSA spectrum. A correction factor is also proposed to be applied to the SV estimates in order for those to have a smooth transition near the limiting period.

Compressed Sensing-Based Order Analysis for Blade Tip Timing Signals Measured at Varying Rotational Speed

Monitoring the vibrations of high-speed rotating blades is significant to the security of turbomachineries. Blade tip timing (BTT) is considered as a promising technique for detecting blade vibrations without contact online. However, extracting blade vibration characteristics accurately from undersampled BTT signals measured at varying rotational speed (VRS) has become a big challenge. The existing two methods for this issue are restricted within the order bandwidth limitation and require prior information and precise sensor installation angles, which is often unpractical. To overcome these difficulties, a compressed sensing-based order analysis (CSOA) method was proposed. Its feasibility comes from the sparsity of BTT vibration signals in the order domain. The mathematical model for the proposed method was built, and the optimizing principles for sensor number and sensor arrangement were given. Simulated and experimental results verified the feasibility and advantages of the proposed method that it could extract order spectrum accurately from BTT vibration signals measured at VRS without the drawbacks in the existing two methods.

Estimating charge-transport properties of fuel-cell and electrolyzer catalyst layers via electrochemical impedance spectroscopy

Electrochemical impedance spectroscopy is the most common experimental technique for measuring the charge-transport properties of catalyst layers. Such a measurement relies on fitting the impedance spectrum with analytical impedance expressions. To date, a study that examines the suitability of the available analytical models for such analysis does not exist. In this work, a numerical one-dimensional catalyst-layer model is used to assess the appropriateness of the analytical models for estimating catalyst-layer charge-transport properties. An ohmic-heating-based approach to computing ohmic resistance is used to examine the relationship between conductivity, resistance, and impedance of various catalyst layers representative of those used in proton-exchange-membrane fuel cells and water electrolyzers. The ohmic-heating analysis indicates that the most commonly used impedance expressions (Eikerling and Kornyshev, 1999; Makharia et al., 2005) result in a threefold overestimation of protonic resistance and may not be applicable to the proton-conductivity estimation for electrolyzer catalyst layers that exhibit low electronic conductivity. A more recent analytical model (Kulikovsky, 2017) is shown to produce protonic- and electronic-transport properties that agree with numerical simulations. The results of this work are used to provide recommendations for the selection of analytical impedance expressions for a given operating regime (H2/O2 or H2/N2) and an observed shape of the measured spectrum in order to achieve an accurate charge-transport characterization of a catalyst layer. A novel graphical approach to analyzing H2/N2 spectra is also proposed. Although the considered analytical models are not applicable to heterogeneous catalyst layers and no general algebraic conductivity-resistance relationship exists in that case, it is shown that the H2/N2 impedance measurement of heterogeneous catalyst layers provides the total ohmic resistance. A two-dimensional fuel-cell model is used to show that the anode catalyst layer may cause a distortion of the impedance spectrum at frequencies above 5 Hz that obstructs the charge-transport characterization with analytical models.

Wind Turbine Bearing Fault Detection Using Adaptive Resampling and Order Tracking

Wind energy is growing increasingly popular in the United States, so it is imperative to make it as cost competitive as possible. Operations and Maintenance (O&M) make up 20-25% of the total cost of onshore wind projects. Unplanned maintenance contributes approximately 75% of the total maintenance costs (WWEA, 2012). Condition-based maintenance strategies intend to maximize the uptime by reducing to the amounts of unplanned maintenance. This should result in an overall decrease in the cost of maintenance. Wind turbines produce an interesting challenge, because their main shaft rotation is both slow and nonstationary. Through the use of adaptive resampling and order tracking, both of these challenges were combated as the bearing fault was identified in the order spectrum then tracked as it progressed. The fault was identified as an outer race defect on the main bearing that initiated sometime during or before installation. The total energy in the order spectrum around the bearing fault rate was identified as a potential front-runner for a prognostic parameter. This paper presents a case study application to operational wind turbine bearing data to demonstrate the ease and intuitiveness of combining adaptive resampling and order tracking to diagnose faults for slow, nonstationary bearings. Prognosis of remaining useful life is proposed with features extracted from the order spectrum, but additional data are needed to develop and demonstrate this analysis.

Rolling Bearing Diagnosis Based on the Higher Order Spectra

Bearing defect diagnosis is traditionally done using the demodulation/enveloping technology. Diagnosis is mostly based on the spectrum of the squared envelope signal. In literature, the use of the higher order spectra (HOS) has shown to have a tremendous potential for vibration based diagnostics. In this paper we implemented and experimentally validated the higher order spectra based on the envelope analysis for the diagnosis of ball bearing defects. The implemented technology employs the spectral kurtosis to obtain a frequency band for the demodulation and the third order normalized spectra, i.e. the bicoherence for diagnosis of bearing fault. The high effectiveness of the diagnostics of the implemented technology has been experimentally revealed and compared with that of well-known demodulation/enveloping technology.

The New Second and Higher Order Spectral Technique for Damage Monitoring of Structures and Machinery

The new second and higher order spectral technique, the cross-covariance of complex spectral components, is proposed for monitoring damage of structure and machinery Normalization of the proposed technique is also developed. It is shown by simulation that the proposed technique provides effectiveness gain for detecting of damage compared to the higher order spectra.