Low-pass Research Articles

A primary wideband calibration method for noise hydrophones based on three-transducer spherical wave reciprocity in the frequency domain.

A primary wideband calibration method for noise hydrophones is developed, which can be applied to obtain noise acoustic spectral density sensitivity in the free-field. In this method, a wideband three-transducer spherical wave reciprocity calibration method is proposed in the frequency domain. A lowpass spatial domain filter is utilized to eliminate the reflecting acoustic waves from boundaries and water surface, and the wideband frequency responses of the transducer pair are calculated. Wideband calibrations are performed in a laboratory anechoic water tank, and two hydrophones with different reference sensitivities are calibrated in the frequency range of 250 Hz to 20 kHz using noise signals. The decidecade band sensitivities are obtained by the primary wideband calibration, which is in agreement with the single frequency sensitivities. The expended uncertainty of the primary wideband calibration is analyzed and estimated to be 8.9% (k = 2).

Evolution characteristics of an induced electric charge signal and identification method of charge for instability failure in loaded coal

A coal-loaded charge induction monitoring system is developed to effectively forecast the dynamic disasters caused by coal failure. Specifically, a digital finite impulse response (FIR) filter is designed to denoise and filter the signal, and the time-frequency domain evolution of induced charge signals is analyzed during coal failure experiments. The quantitative relationships between the induced electric charge and stress-strain energy, and ultimately, between induced electric charge and coal deformation/failure, are revealed. Ultimately, the electric charge sensor exhibits high signal collection frequency and high sensitivity, and the FIR low-pass filter constructed in MATLAB effectively denoises and filters induced charge signals. The main frequency range of the white noise is 50–500 Hz, and the main frequency of the charge signal induced by coal deformation and failure is concentrated in the range of 0–50 Hz. The optimal distances for monitoring cubic and cylindrical raw coal samples using this sensor are 9 mm and 11 mm, respectively. Notably, strain energy is released faster when it can dissipate more readily, and induced charge pulses become denser when more intense signals produce large fluctuations. A method is proposed to identify coal deformation and failure based on changes in the induced electric charge. This study provides a new means of monitoring the early warning signs of dynamic coal mine disasters. Based on our experimental results and conclusions, a new method is proposed to identify coal deformation and failure based on changes in the induced electric charge. The precursor to the moment of coal failure can be identified by monitoring the amplitude of the induced charge, the dynamic trend of fluctuation, and the cumulative number of induced electric charge pulses during the process of coal deformation.

Grid-connected virtual synchronous generator transient suppression based on proportional differential control and frequency low-pass filtering

Abstract The virtual synchronous generator (VSG) technology has a wide range of applications in various distributed generation units. However, sudden changes in power command at grid connection can lead to severe oscillations in the output power and frequency of virtual synchronous generators. In addition, existing oscillation suppression methods are either based on complex parameter designs or change the original inertial support characteristics and power frequency drop characteristics. In this paper, a new transient suppression method is proposed, i.e., a proportional differential controller is added behind the power error and an additional low-pass filter is placed behind the output frequency. Finally, by establishing a simulation platform, it is verified that the proposed scheme can greatly reduce the overshoot, regulation time and frequency offset of the active power.

Near-infrared spectroscopy for glucose detection in aqueous solution

This work presents a near-infrared spectroscopy-based technique to measure the glucose concentration in an aqueous solution. A near-infrared light source sends optical energy through a glucose-water solution. The energy transmitted through the aqueous solution is received by a photodetector and a conditioning circuit that includes an operational amplifier and a low-pass filter to remove high-frequency noise. The received light intensity converted to DC voltage is found to be inversely proportional to the glucose concentration in the aqueous solution. The experimental results for glucose concentration in the range of 0–4000 mg/dL confirm the expected theoretical behavior. The sensitivity of the system is 26.25 μV/mgdL-1. The proposed glucose detection system is a promising tool for monitoring glucose levels in various industries, including food and beverage quality and healthcare.

A robust optimization strategy for brushless DC motor repetitive controller based on H-infinity

The control of Brushless DC (BLDC) motor has many challenges. A large number of harmonics are generated during motor operation, while it is susceptible to external disturbances such as noise. The large torque ripple is also a constraint to the large-scale popularity of BLDC motors in some high-end industries. Taking the BLDC motor control system as the research object, this paper proposes a control method of H-infinity repetitive control. First, the state space expression is derived from the mathematical model of the BLDC motor. Then, the parameters of the low-pass filter in the internal mode link are obtained for the design of the internal mode link in the repetitive control. In addition, the H-infinity repetitive control system for the BLDC motor is constructed and converted into the standard form of the H-infinity system. Finally, bringing the generalized controlled object in the standard form of the H-infinity into MATLAB to derive the compliant compensator. The simulation results show that the proposed method can not only suppress harmonics but also improve the robustness of the BLDC motor control system.

Adaptive Fuzzy Filter-based L 1 Adaptive Controller Design for Electromechanical Actuator Containing Uncertainties and Disturbances

Conventional L 1 adaptive controller utilizes high adaptation gain to quickly adapt time varying uncertainties and disturbances. However, it contaminates the control signal with high frequency components. To eliminate this high frequency signal, it uses a low pass filter with fixed structure. Yet, the main problem with this fixed structured filter is that it may cancel the estimated values of uncertainties and disturbances along with the high frequencies. To overcome this problem, in this research work, an adaptive fuzzy low pass filter is proposed in place of the fixed structured filter of the L 1 adaptive controller. In this proposed research work, the filter changes its structure according to the time varying uncertainties and disturbances. Hence, the contributory part of this work is that the proposed adaptive fuzzy filter efficiently cancels out high frequency components without nullifying the estimated values of uncertainties and disturbances from the control signal. The stability of the proposed adaptive fuzzy filter-based L 1 adaptive controller is guaranteed analytically. The proposed method is employed on an electromechanical actuator, viz., DC motor experimental setup to validate its effectiveness. Adequate cancellation of high frequency signal incurs smooth control signal which in turn provides lower control energy.

An Ultra-Low-Voltage Transconductance Stable and Enhanced OTA for ECG Signal Processing.

In this paper, a rail-to-rail transconductance stable and enhanced ultra-low-voltage operational transconductance amplifier (OTA) is proposed for electrocardiogram (ECG) signal processing. The variation regularity of the bulk transconductance of pMOS and nMOS transistors and the cancellation mechanism of two types of transconductance variations are revealed. On this basis, a transconductance stabilization and enhancement technique is proposed. By using the "current-reused and transconductance-boosted complementary bulk-driven pseudo-differential pairs" structure, the bulk-driven pseudo-differential pair during the input common-mode range (ICMR) is stabilized and enhanced. The proposed OTA based on this technology is simulated using the TSMC 0.18 μm process in a Cadence environment. The proposed OTA consumes a power below 30 nW at a 0.4 V voltage supply with a DC gain of 54.9 dB and a gain-bandwidth product (GBW) of 14.4 kHz under a 15 pF capacitance load. The OTA has a high small signal figure-of-merit (FoM) of 7410 and excellent common-mode voltage (VCM) stability, with a transconductance variation of about 1.35%. Based on a current-scaling version of the proposed OTA, an OTA-C low-pass filter (LPF) for ECG signal processing with VCM stability is built and simulated. With a -3 dB bandwidth of 250 Hz and a power consumption of 20.23 nW, the filter achieves a FoM of 3.41 × 10-13, demonstrating good performance.

A robust proportional filtered integral controller based on backpropagation neural network

This paper introduces a novel design of a proportional filtered-integral (P-FI) controller whose parameters are auto-tuned using the backpropagation neural networks (BPNN) algorithm. The proposed controller is designed to address the main challenges posed by a class of complex systems characterized by uncertain high-gain and pure integrator dynamics, including high-frequency noise amplification and poor robustness against parameter variations. Designing such a controller involves three main steps: First, a proportional–integral–derivative (PID) controller is designed, with its parameters auto-tuned online using the BPNN algorithm, resulting in the primary (BPNN-PID) controller. Second, the obtained parameters of the previous controller are utilized to compute those of a low-pass filter offline. This filter is then cascaded with the integral parts of a PID controller, forming a P-FI controller structure. This configuration introduces a phase lead within a specific frequency range without amplifying high-frequency noise, overcoming the primary disadvantage of the derivative term. Finally, the parameters of the resulting P-FI controller are again auto-tuned online using the BPNN algorithm, resulting in the final robust (BPNN-P-FI) controller. This novel controller structure and its parameters tuning procedure, based on a two-stage BPNN learning approach, constitute the main contributions of this paper. Simulation results demonstrate the superiority of the proposed controller in terms of time-domain performance, sensor noise attenuation, and closed-loop robustness compared to those obtained with the BPNN-PID and optimally tuned PID controllers.

Implementation of Raspberry Pi As A2dp Module On The Quality of Song Reception of Humanoid Robot

This research discusses comparing the performance of Bluetooth communication on Raspberry Pi in controlling dance humanoid robots using external modules and direct communication. This research aims to understand the difference in performance between the two methods, by analyzing data transmission speed, signal stability, and communication latency that affect the quality of robot movement. In addition, this research also aims to evaluate the effectiveness of using simple filters such as low-pass filter circuits to improve the stability of Bluetooth communication on Raspberry Pi. It is hoped that this research can lead to a better understanding of the influence of both communication methods on the quality of dance humanoid robot movements.

A combined denoising method for Q-factor compensation of poststack seismic data

Attenuation is a main factor limiting the resolution of seismic data. Earth works as a low-pass filter, which has strong attenuation of the high-frequency data. The loss of high-frequency energy can be compensated by the inverse Q filtering strategy. However, this method will also increase the energy of random noise which limits its application. The inverse Q filtering algorithm also needs the Q-factor as the input parameter, which is not easy to obtain. In this paper, we proposed a three-stage process to correct the attenuation of poststack data. In the first stage, a robust structure-oriented filtering is applied to remove random noise while protecting the structure information to avoid high-frequency noise burst. In the second stage, the local centroid frequency shift (LCFS) method is used to estimate the Q factor along the seismic trace. This method combined shaping regularization and centroid frequency shift (CFS) method to improve the robustness and accuracy of Q estimation to some extent. The final stage is to apply a stable inverse Q-filtering. Synthetic and field data examples demonstrate that time-varying Q-value can be accurately estimated by using the local centroid frequency shift (LCFS) method, and the proposed workflow can compensate the attenuation without bursting of high-frequency random noise.

Online Mechanical Resonance Frequency Identification Method Based on an Improved Second-Order Generalized Integrator—Frequency-Locked Loop

To address the issue of mechanical resonance frequency detection in dual-inertia servo systems, this paper proposes an online identification method for mechanical resonance frequency using a low-pass filter and cascaded second-order generalized integrator—frequency-locked loop (LPF-CSOGI-FLL). Initially, the cascaded second-order generalized integrator—frequency-locked loop (CSOGI-FLL) is employed to eliminate the interference of direct current (DC) bias in resonance frequency identification. From a dual-stage structural perspective, the first second-order generalized integrator (SOGI-FLL) acts as a band-pass pre-filter to extract the mechanical resonance signal from the signal to be tested. The second SOGI-FLL generates a signal with equal amplitude and frequency to the mechanical resonance and obtains the frequency of the resonance signal through the frequency-locked loop. Subsequently, a low-pass filter (LPF) is applied to the frequency feedback loop of the second-stage SOGI-FLL, effectively reducing the oscillation of the estimated frequency. Finally, combining the CSOGI-FLL with an LPF forms a novel structure, namely, LPF-CSOGI-FLL. The results demonstrate that the proposed method significantly improves the detection accuracy of mechanical resonance frequency under various conditions. Compared to traditional offline techniques, this method overcomes the impact of resonance frequency drift and enhances system stability.

Single EX-CCCII-Based First-Order Versatile Active Filter

This paper presents a new current-mode first-order versatile active filter employing one extra-x second-generation current controlled current conveyor (EX-CCCII) and one grounded capacitor. The proposed filter can realize first-order filtering functions of a low-pass filter (LPF), high-pass filter (HPF), and all-pass filter (APF) within the same topology with low-input and high-output impedances required for current-mode circuits. This multiple-output EX-CCCII-based filter can provide six transfer functions as both non-inverting and inverting filtering functions of the LPF, HPF, and APF are obtained. The filter also offers electronic control of the pole frequency of all filtering. The proposed current-mode filter can be applied to work as a mixed-mode active filter, namely in the transadmittance-mode (TAM), transimpedance-mode (TIM), and voltage-mode (VM). Each operation mode can provide six transfer functions. The proposed filter was simulated and designed using SPICE and 0.18 µm CMOS technology. Experimental results using the commercially available integrated circuit AD844 were used to confirm the functionality of the new circuits.

Fuzzy logic-based coordinated operation strategy for an off-grid photovoltaic hydrogen production system with battery/supercapacitor hybrid energy storage

The coupling of photovoltaic power generation with water electrolyzer is advantageous for enhancing solar energy utilization and generating green hydrogen. In this work, an off-grid photovoltaic-based hydrogen production system consisting of photovoltaic, electrolyzer, battery energy storage system and supercapacitor was developed. A coordinated operation strategy is designed to manage the power of each unit in the system to avoid significant fluctuations in working power and frequent start-stop operations of the electrolyzer unit. Firstly, the coordinated operation strategy sets five operation modes for the photovoltaic-based hydrogen production system, and the fuzzy logic control algorithm is used to choose the operation mode to determine the reference power of each unit. On this basis, the state of charge feedback-based first-order low-pass filter algorithm is used to achieve the power allocation to mitigate deep charging and discharging of the supercapacitor. The proposed solution is extensively assessed through comparative simulation experiments based on three typical test days. The numerical results confirm its effectiveness and demonstrate the potential for achieving high system efficiency.

An efficient low-delay polyphase implementation method for active noise control systems

When implementing active noise control systems on signal processing hardware, the time delay introduced by electronic components (especially components requiring additional lowpass filters or introducing fixed-sample-size delays) may adversely affect the noise control performance. One common approach to reducing this delay is to use a high sampling rate, but this increases the computation significantly when implementing the ANC filters in real time. In the current work, a polyphase-structure-based filter design method is developed for active noise control systems that can reduce the computation load for real-time filter implementation but do not introduce an additional time delay. Although the computation reduction capability of a polyphase filter structure is well known for multi-rate systems, the traditional use of such multi-rate systems requires additional anti-aliasing and reconstruction filters which introduces an additional time delay. Thus, in delay-sensitive applications, such as active noise control, this method was previously applied only on the filter adaption phase, instead of directly on the real-time filtering process. In this article, a filter decomposition method using the minimum-phase technique is proposed to decompose an ANC filter into two multiplicative causal filters both of which have lowpass frequency response shapes at high frequencies such that the polyphase structure can be applied directly to the two multiplicative causal control filters without introducing additional anti-aliasing and reconstruction filters. Results show that, compared with various traditional low sampling rate implementations, the proposed method can significantly improve the noise control performance. Compared with the non-polyphase high-sampling rate method, the real-time computations that increase with the sampling rate are improved from quadratically to linearly.

Human hand gesture recognition using fast Fourier transform with coot optimization based on deep neural network

ABSTRACT Hand motion detection is particularly important for managing the movement of individuals who have limbs amputated. The existing algorithm is complex, time-consuming and difficult to achieve better accuracy. A DNN is suggested to recognize human hand movements in order to get over these problems.Initially, the raw input EMG signal is captured then the signal is pre-processed using high-pass Butterworth filter and low-pass filter which is utilized to eliminate the noise present in the signal. After that pre-processed EMG signal is segmented using sliding window which is used for solving the issue of overlapping. Then the features are extracted from the segmented signal using Fast Fourier Transform. Then selected the appropriate and optimal number of features from the feature subset using coot optimization algorithm. After that selected features are given as input for deep neural network classifier for recognizing the hand movements of human. The simulation analysis shows that the proposed method obtain 95% accuracy, 0.05% error, precision is 94%, and specificity is 92%.The simulation analysis shows that the developed approach attain better performance compared to other existing approaches. This prediction model helps in controlling the movement of amputee patients suffering from disable hand motion and improve their living standard.

Analysis, design, and optimization based on genetic algorithms of a highly efficient dual-band rectenna system for radiofrequency energy-harvesting applications

This paper gives an enhanced Rectenna design that operates at dual-band [2.45 and 5.8] GHz in the ISM (Industrial, Scientific, and Medical) band and is printed on an FR4-Epoxy substrate. This Rectenna design includes two proposed sub-designs for the receiving antenna and rectifier circuit based on the microstrip technology. The first sub-design concerns the microstrip patch antenna (MPA) described by its radiating element as a pentagonal, its ground being affected by a defective ground structure technique, and its polarization manner as circular polarization. This MPA design is analyzed, designed, optimized using genetic algorithms (GAs), simulated under CST MWS (i.e., computer simulation technology microwave studio), and confirmed by another software named HFSS (high-frequency structure simulator). The second sub-design concerns the microstrip rectifier circuit (MRC) that contains an input matching network based on a coupled-line impedance transformer strategy to achieve good adaptation between MPA and MRC, voltage doubler converter using an SMS7630 Schottky diode thanks to its high sensitivity, microstrip interdigital capacitor to mitigate the intrinsic losses due to the lumped elements, harmonic rejection filter based on a stepped-impedance low-pass filter to reject the unwanted harmonics generated by the non-linear behavior of SMS7630, and the resistive load that models the consumption of the system to be fed. This MRC is analyzed, designed, optimized using GAs, and simulated under ADS (Advanced Design System). The effectiveness of the proposed MPA is proven in terms of gain equals 3.06 dBi and 4.683 dBi at 2.45 GHz and 5.8 GHz respectively, and efficiency equals 95.13 % and 96.552 % at 2.45 GHz and 5.8 GHz respectively. The proposed MRC is effective in terms of efficiency at a lower input power value of about 97.18 % and 67.93 % at 2.45 GHz and 5.8 GHz respectively.

Filter cable design with defected conductor transmission structures

Electrical cables, as the industry’s blood vessels and nervous system, require evolving distributed filtering for complex electromagnetic environment adaptability. This article introduces a filter cable design featuring an insulated cylinder coated with a defected conductor transmission structure (DCTS). The DCTS, with a well-designed etched pattern, functions as a boundary condition for transmitting specific frequency electromagnetic waves, similar to a lumped filter circuit. To validate this method, a low-pass filter cable is proposed with six-slot-ring defected structures, utilizing polytetrafluoroethylene as the inner dielectric, encased within a flexible printed circuit board (FPCB)-manufactured DCTS. The proposed cable, with precise dimensions (2.4 mm diameter, 340 mm length), demonstrates minimal insertion loss ( < 0.38 dB below 6 GHz) in the passband and rejection exceeding 23 dB at 7.7-25 GHz in the stopband. Further enhancements achieve attenuation exceeding 50 dB in the stopband (7.1 GHz to 20 GHz). Compared to traditional cables, this filter cable addresses electromagnetic compatibility (EMC) by cutting off the interference coupling path.

ЦИФРОВА СИСТЕМА КЕРУВАННЯ РЕЗОНАНСНОГО ІНВЕРТОРА НАПРУГИ З САМОЗБУДЖЕННЯМ

Phase-locked loop systems (PLL) are widely used in control circuits of transistor resonant voltage inverters of induction heating installations. One of disadvantages of PLL systems is low speed, which is caused by the presence of a low-pass filter. This disadvantage is absent in self-oscillating systems, when the switching moment of the transistors is determined on each of half periods. At the same time, an asymmetry of half periods is possible, which is a significant disadvantage if there is a transformer at the output of the inverter. A self-oscillating digital control system for a resonant voltage inverter and equal half periods durations of the inverter output voltage has been developed. It can work with different methods of regulating the output current and allows to provide switching modes of transistors with minimal power losses. References 7, figures 5.

Discovering manganese-based blacks in the grave goods of Kha and Merit (Egypt, 1450-1400 BCE): Multidisciplinary investigation on use and nature

As part of the “TT8 Project”, several research groups examined the grave goods from the Theban Tomb No. 8 of Kha and his wife Merit who lived during the second half of 18th dynasty and were discovered by the Italian Archaeological Mission led by Ernesto Schiaparelli. Thanks to the collaboration of Egyptologists, conservators, and scientists, numerous state-of-the-art, non-invasive methods were used to examine and characterize the objects found in the tomb.During this comprehensive investigation, for which a fully non-invasive approach was designed, the preliminary results for three polychrome wooden caskets showed the unexpected presence of manganese in the black areas in combination with the carbon black ink also present in the black decorations.In addition to MA-XRF analysis, which allowed for the discovery, an innovative imaging method was applied for faster discrimination of black pigments. This method is based on the optical spectral differences between manganese-based blacks and carbon black in the short-wave infrared – with a maximum difference in the range of 1400–1700 nm – and is comparable to a photograph in terms of acquisition time. By using an InGaAs camera with an interferential long-pass filter of 1400 nm, the images were acquired first on a series of mock-ups and then on the wooden caskets. Using false color imaging representation, the areas painted with manganese black showed a clear red false color, in contrast to the black false color of the areas painted with carbon black. The results are fundamental to understanding whether the use of manganese black could be more widespread than reported in the literature so far.

43 Epigenomic profiling of translocation renal cell carcinoma via liquid biopsy

Abstract Background Translocation renal cell carcinoma (tRCC) is an aggressive subtype of kidney cancer usually driven by a fusion involving the TFE3 gene. Due to histologic overlap with other subtypes of RCC, tRCC is frequently misclassified. Methods for accurate diagnosis and detection of this molecularly distinct entity are therefore a pressing need. Epigenomic profiling of ctDNA via plasma chromatin immunoprecipitation and sequencing (ChIP-seq) has recently emerged as a powerful tool to detect and molecularly subtype cancers and may offer a more sensitive and specific detection of molecular fusions. We aimed to detect tRCC in plasma and to discriminate tRCC from ccRCC based on epigenomic profiling of cfDNA. Methods We first identified differentially expressed gene, methylated regions (DMRs) and regulatory elements (REs) specific to tRCC vs. ccRCC via RNA-seq, methylated DNA immunoprecipitation sequencing (MeDIP-seq) and ChIP-Seq, of 4 tRCC and 5 ccRCC cell lines. We collected 16 plasma samples from metastatic patients with tRCC, 11 with ccRCC and 9 healthy patients (HP). Ultra low pass whole genome sequencing (ulpWGS) was performed to infer ctDNA fraction (TF), and cfMeDIP-seq, H3K4me3/H3K27ac cfChIP-seq for epigenomic profiling. Signal at tRCC-specific regions derived from cell lines profiling was aggregated for each mark and normalized to common active REs and DMRs, then compared between classes using a Wilcoxon rank-sum test. Classification performance was evaluated using the area under the receiver operating characteristic (AUROC) curve. Results Overall 8/16 tRCC and 5/12 ccRCC samples had &amp;gt;3% TF by ulpWGS. H3K4me3 and H3K27ac cfChIP-seq signal was significantly higher in all tRCC samples compared to healthy patients (p&amp;lt;10-6, AUROC =1), at tRCC-specific promoters and tRCC-specific REs respectively. Furthermore, H3K27ac signal in plasma was also significantly higher at tRCC-specific REs in tRCC samples compared to ccRCC (p&amp;lt;10-4, AUROC=0.95). MeDIP-seq could not discriminate between tRCC and ccRCC. Conclusions Although a majority of tRCC plasma samples profiled had TF &amp;lt; 3%, all could be distinguished from healthy samples on the basis of cfChIP. H3K27ac cfChIP-Seq was also discriminatory for tRCC vs. ccRCC. Epigenomic profiling of cfDNA appears as a powerful tool for both detection of tRCC and discrimination from ccRCC/healthy plasma, with potential implications for diagnosis and guiding therapy.