Explore the vast range of titles available.

CE-OFDM technology is used to modulate the phase of OFDM signal, and it ensures the range of signal envelope to be constant and overcomes the disadvantage of high OFDM signal peak-to-average ratio. This essay puts forward a kind of phase demodulation mode based on Costas loop for CE-OFDM system, and makes a comparison with the original demodulation modes by MATLAB simulation.

The combination of reversible angular dispersion-induced microbunching (ADM) and the rapid damping storage ring provides a storage-ring-based light source with the capability to produce longitudinal coherent radiation with a high repetition rate. This paper presents a prototype design for a test facility based on the study by Jiang et al. [ Sci. Rep. (2022), 12 , 3325]. The modulation–demodulation section is inserted into a long straight section of the storage ring instead of a bypass line, which poses great challenges for the optimization of the nonlinear dynamics of the storage ring. However, this design avoids the challenging injection and extraction system connecting to the bypass line. To utilize mature laser technology and reduce the difficulty of the reversible ADM lattice design, we use a long-wavelength 1030 nm seed laser. In the simulation, we achieved 20th harmonic radiation with a bunching factor of about 7.2%. The growth rate of vertical emittance and energy spread of the electron beam for a single pass are about 11% and 0.02%, respectively. When the energy of the electron beam is 800 MeV and two sets of damping wigglers are employed, the damping time in the vertical plane is reduced to 8.31 ms. This results in a 438 kHz repetition rate of the coherent radiation at the new equilibrium state.

Envelope analysis, one of the most widely used methods in the field of rotating machinery fault diagnosis, aims to approximate fault impact characteristics by analyzing the envelope of the filtered signal in the demodulation band. The demodulation band is essentially the carrier frequency band and the resonant frequency band of the mechanical system. However, since the resonant frequencies of different mechanical components vary and are often unknown, accurately identifying the carrier frequency band becomes the most significant challenge in the envelope analysis process. Currently, the mainstream research approach involves the use of various metrics to evaluate the band with the most fault information and then performing envelope analysis on this band. Although these methods have shown effectiveness in practical applications, they still have notable limitations. For example, when faults occur simultaneously in different bearings and gears, existing methods can identify only one carrier frequency band, and the identified bands often lack consistency across the same set of test data. To address these issues, this paper proposes a novel demodulation band selection method that can efficiently and accurately identify all faults when signals from multiple faulty components coexist. This method has been evaluated through bearing fault simulations and case studies, and its performance outperforms traditional methods such as spectral kurtosis and Autogram. It can effectively extract the characteristic spectra of all faulty components under multi-resonance conditions, demonstrating excellent anti-interference capability and efficiency advantages. Therefore, it holds significant engineering value in improving the accuracy of fault diagnosis.

Demodulation is a key technology for the enhanced Loran (eLoran) system to achieve positioning and timing, and it affects the final performance of the system. Based on the traditional matched correlation algorithm, this paper proposes a new matched correlation demodulation method with notch processing. Furthermore, by combining it with the pattern modulation of the eLoran system, the matched correlation integrate notch demodulation method is further modified to improve demodulation performance. Firstly, the data link of the eLoran system is introduced in detail, including the encoding and modulation processes, the influencing factors of received signals, and the evaluation methods in the demodulation process. Secondly, on the basis of the principle of the matched correlation (MC) demodulation algorithm, a matched correlation demodulation algorithm integrating notch processing (MC-NF) and a demodulation correlation algorithm combined with modulation patterns (PMC-NF) are proposed. And, an analysis of the key factors affecting demodulation performance is given. Next, the demodulation performance of the mentioned algorithms under the conditions of random noise, skywave, and in-band continuous wave interference is calculated in detail. A large number of experimental results show that notch processing performs excellently in suppressing random noise and in-band continuous wave interference, and it can greatly improve the demodulation performance of the traditional matched correlation algorithm. Moreover, PMC-NF is superior to MC-NF; approximately 2.8 dB at decoding the critical point.

Conventional eddy-current sensors have the advantages of being contactless and having high bandwidth and high sensitivity. They are widely used in micro-displacement measurement, micro-angle measurement, and rotational speed measurement. However, they are based on the principle of impedance measurement, so the influence of temperature drift on sensor accuracy is difficult to overcome. A differential digital demodulation eddy current sensor system was designed to reduce the influence of temperature drift on the output accuracy of the eddy current sensor. The differential sensor probe was used to eliminate common-mode interference caused by temperature, and the differential analog carrier signal was digitized by a high-speed ADC. In the FPGA, the amplitude information is resolved using the double correlation demodulation method. The main sources of system errors were determined, and a test device was designed using a laser autocollimator. Tests were conducted to measure various aspects of sensor performance. Testing showed the following metrics for the differential digital demodulation eddy current sensor: nonlinearity 0.68% in the range of ±2.5 mm, resolution 760 nm, maximum bandwidth 25 kHz, and significant suppression in the temperature drift compared to analog demodulation methods. The tests show that the sensor has high precision, low temperature drift and great flexibility, and it can instead of conventional sensors in applications with large temperature variability.

A low-complexity vital sign detection system is proposed. The system uses a phase discriminator as the demodulation module and a phase shifter to solve the null problem in CW radar. This design significantly reduces the complexity. In the subsequent processing of this system, variational pattern decomposition (VMD) is used to analyze vital sign signals. Experiments using this system show that VMD is efficient and accurate in extracting human target respiration and heartbeat frequencies.

Cannabis is an ancient plant that has been used for therapeutic and recreational purposes. Nowadays, industrial hemp, a variety with low concentration of the psychoactive cannabinoid Δ9-tetrahydrocannabinol (THC) and high concentration of non-psychoactive cannabinoids, is getting more and more interest in the food, pharmaceutical, and cosmetic industry. However, cannabis not only contains cannabinoids as bioactive components but also other metabolites like terpenes and phenolic compounds, and the content of these interesting secondary metabolites greatly differs with the genetic variety of the plant. Due to the huge complexity of composition of the cannabis matrix, in this work, a comprehensive two-dimensional liquid chromatography (LC × LC) method has been developed as a very power separation technique coupling a pentafluorophenyl (PFP) and a C18 in the first and second dimensions. Two industrial hemp strains (cookie and gelato) were analyzed to determine the difference in their content of cannabinoids and phenolic compounds. To do this, a new demodulation process was applied for the first time to transform 2D raw data into 1D data which allowed carrying out the chemometric analysis needed to determine the statistical differences between the hemp strains. The cookie strain presented a total of 41 cannabinoid markers, while the gelato strain presented more representative phenolic compounds, in total 24 phenolic compounds were detected as potential markers of this sample. These differences in the chemical composition could determine the industrial destiny of the different hemp strains.

To address the non-stationary characteristics of gear vibration signals under fault conditions, a noise-assisted multivariate empirical mode decomposition (NA-MEMD) approach is employed for gear fault detection. This study presents a fault diagnosis methodology combining NA-MEMD with envelope demodulation analysis. The NA-MEMD technique adaptively decomposes vibration signals into multiple mono-component intrinsic mode functions. Fault-related components are subsequently subjected to envelope demodulation processing to extract characteristic fault signatures from gear vibration data. Experimental validation using actual gearbox fault cases demonstrates that the developed approach successfully identifies gear defect features through effective signal decomposition and demodulation analysis. Results confirm the method’s capability to enhance fault feature extraction for mechanical transmission systems.

Nowadays, the problem of synthesizing demodulation algorithms with good noise immunity and acceptable computational complexity is a particularly pressing issue. The application of a non-Gaussian approximation of the prior distribution of the estimated parameters for demodulation in Massive MIMO systems using Newton’s method is proposed. The demodulation problem is presented in the form of a problem of solving a system of nonlinear equations. A study of the new algorithm was conducted under the conditions of a different number of antennas and different orders of QAM modulation. The results of modeling a new demodulation algorithm using Newton’s method are presented, as well as a comparison with the well-known MMSE algorithm, Monte Carlo, and K-best methods, which confirm the effectiveness of the proposed approach of non-Gaussian approximation for demodulation in Massive MIMO systems.

In doubly dispersive delay-Doppler channels, orthogonal frequency division multiplexing (OFDM)-based navigation signals suffer from degraded performance due to subcarrier orthogonality loss. To address the reduced energy concentration of orthogonal frequency division multiplexing with binary offset carriers (OFDM-BOC) signals under such conditions, this paper proposes a novel orthogonal time frequency space with binary offset carriers (OTFS-BOC) system that combines OTFS modulation with spread-spectrum BOC signaling, leveraging the superior robustness of orthogonal time frequency space (OTFS) against channel dispersion. A unified modulation and demodulation model is developed, along with practical implementation strategies for different application scenarios. Simulation results demonstrate improved ranging accuracy and transmission performance over OFDM-BOC, confirming the proposed system’s advantages in challenging environments.