Sallen Key Research Articles

A Fault Diagnosis Method for Analog Circuits Based on Improved TQWT and Inception Model

A soft fault in an analog circuit is a symptom where the parameter range of a component exists symmetrically to the left and right of its nominal value and exceeds a specific range. The proposed method uses the Grey Wolf Optimization (GWO) optimized tunable Q-factor wavelet transform (TQWT) algorithm for feature refinement, the Inception model for feature extraction, and an SVM for fault diagnosis. First, the Q-factor is optimized to make it more compatible with the signal. Second, the signal is decomposed, and a single-branch reconstruction is performed using the TQWT to extract features adequately. Then, fault feature extraction is conducted using the Inception model to obtain multiscale features. Finally, a Support Vector Machine (SVM) is used to complete the entire fault diagnosis process. The proposed method is comprehensively evaluated using the Sallen–Key bandpass filter circuit and the four-op-amp biquad high-pass filter circuit widely used in electronic systems. The experimental results prove that the proposed method outperforms the existing methods in terms of diagnosis accuracy and reliability.

Application and characterization of digital Sallen–Key filter in nuclear spectrum smoothing

In the nuclear spectrum analysis processing, spectrum smoothing can remove the statistical fluctuation in the spectrum, which is beneficial for peak detection and peak area calculation. In this work, a spectrum smoothing algorithm is proposed based on digital Sallen–Key filter, which contains four parameters (m, n, k, D). The amplitude–frequency response curve of Sallen–Key filter is deduced and the filtering performance is analyzed. Meanwhile, the effects of the four parameters on the shape of the smoothed spectrum are explored: D affects the counts and peak areas of the spectrum, and the peak area can be corrected by the peak area correction function S’. The parameters of m, n and k affect the peak position after smoothing, making the peak position shift to the right, and the peak position correction function P’ can be used to correct the peak position, when n¿2, the spectrum data appear negative after smoothing, when k¿2, the smoothed spectrum broadening degree is greater than 20%. Smoothness (R), noise smoothing factor (NSF), spectrum count ratio before and after smoothing (PER), and comprehensive evaluation factor (Q) are used to evaluate the smoothing effect of the algorithm. The parameters of the algorithm are optimally selected: about the gamma spectrum of 137Cs and 60Co, the optimal parameters are m=1.5 n=2 k=2 D=1, about the characteristic X-ray spectrum of Fe and quasi-geological sample (TiMnFeNiCuZn), the optimal parameters are m=1.1 n=1.1 k=1.3 D=1. Based on Sallen–Key smoothing method, Fourier transform method, Gaussian function method, wavelet transformation method, center of gravity method and least squares method, the gamma spectrum of 137Cs is smoothed and denoised in this paper. The results show that the Sallen–Key method has better spectrum denoising effect (R=0.6056) and comprehensive performance indicators (Q=0.6104), which can be further applied for the smoothing of nuclear spectrum data.

A 17 GHz inductorless low‐pass filter based on a quasi‐Sallen–Key approach

SummaryIn this paper, an evolution of the Sallen–Key biquad architecture is presented, suitable for applications at very high frequency. The pole of the buffer amplifier is exploited as one of the poles of the biquad, therefore overcoming the constraints it poses on the maximum resonance frequency that can be achieved. This allows designing low‐pass filters with cutoff frequencies above 10 GHz without using bulky inductors and with good linearity performance provided by the use of feedback. This approach has been exploited to design a biquad in a commercial SiGe BiCMOS technology with maximum of about 320 GHz. The biquad has been designed to provide a resonance frequency of 12 GHz and a quality factor Q of 1.9; postlayout simulations show a cutoff frequency in excess of 17 GHz, 15.75 mW of power consumption, an equivalent input noise below 1 Vrms, and −52 dB of total harmonic distortion (THD) for a 640 mVpp input signal, with a very limited area consumption.

An effective approach based on nonlinear spectrum and improved convolution neural network for analog circuit fault diagnosis.

In this work, an effective approach based on a nonlinear output frequency response function (NOFRF) and improved convolution neural network is proposed for analog circuit fault diagnosis. First, the NOFRF spectra, rather than the output of the system, are adopted as the fault information of the analog circuit. Furthermore, to further improve the accuracy and efficiency of analog circuit fault diagnosis, the batch normalization layer and the convolutional block attention module (CBAM) are introduced into the convolution neural network (CNN) to propose a CBAM-CNN, which can automatically extract the fault features from NOFRF spectra, to realize the accurate diagnosis of the analog circuit. The fault diagnosis experiments are carried out on the simulated circuit of Sallen-Key. The results demonstrate that the proposed method can not only improve the accuracy of analog circuit fault diagnosis, but also has strong anti-noise ability.

Rich Dynamical Behavior in a Simple Chaotic Oscillator Based on Sallen Key High-Pass Filter

Rich Dynamical Behavior in a Simple Chaotic Oscillator Based on Sallen Key High-Pass Filter

An incipient fault diagnosis method based on Att-GCN for analogue circuits

Incipient faults for analogue circuits in modern electronic systems are difficult to diagnose due to poor fault features. To address this issue, a method based on the attention weighted graph convolution network (Att-GCN) is proposed in this paper. The structural and data features of samples are jointly extracted to mine the effective characteristics from incipient faults. First, a wavelet packet energy transform and a probabilistic principal component analysis (ProbPCA) are employed to enhance the sample fault information. Then, the distance clustering method is deployed to construct the sample set into a non-European structure sample graph, where the structural features of fault samples are preserved. Second, an Att-GCN, which combines the spatial-domain graph convolution network and improved self-attention mechanism, is constructed to extract the structural features and data features to obtain more effective fault information. Additionally, the multisample dropout method is introduced to reduce network overfitting in the training process. To assess the method’s actual performance for fault diagnosis, experiments are carried out in the Sallen–Key bandpass filter circuit, the four-op-amp biquadratic filter circuit and the amplifier board circuit. The outcomes indicate that this method improves the incipient fault diagnosis accuracy for analogue circuits.

Performance of real-time neutron/gamma discrimination methods

Nuclear security usually requires the simultaneous detection of neutrons and gamma rays. With the development of crystalline materials in recent years, Cs2LiLaBr6 (CLLB) dual-readout detectors have attracted extensive attention from researchers, where real-time neutron/gamma pulse discrimination is the critical factor among detector performance parameters. This study investigated the discrimination performance of the charge comparison, amplitude comparison, time comparison, and pulse gradient methods and the effects of a Sallen–Key filter on their performance. Experimental results show that the figure of merit (FOM) of all four methods is improved by proper filtering. Among them, the charge comparison method exhibits excellent noise resistance; moreover, it is the most suitable method of real-time discrimination for CLLB detectors. However, its discrimination performance depends on the parameters {t}_text{s}, {t}_text{m}, and {t}_text{e}. When {t}_text{s} corresponds to the moment at which the pulse is at 10% of its peak value, {t}_text{e} requires a delay of only 640–740 ns compared to {t}_text{s}, at which time the potentially optimal FOM of the charge comparison method at 3.1–3.3 MeV is greater than 1.46. The FOM obtained using the {t}_text{m} value calculated by a proposed maximized discrimination difference model (MDDM) and the potentially optimal FOM differ by less than 3.9%, indicating that the model can provide good guidance for parameter selection in the charge comparison method.

Optimized fractional-order Butterworth filter design in complex F-plane

This paper introduces a new technique to optimally design the fractional-order Butterworth low-pass filter in the complex F-plane. Design stability is assured by incorporating the critical phase angle as an inequality constraint. The poles of the proposed approximants reside on the unit circle in the stable region of the F-plane. The improved accuracy of the suggested scheme as compared to the recently published literature is demonstrated. A mixed-integer genetic algorithm which considers the parallel combinations of resistors and capacitors for the Valsa network is used to optimize the frequency responses of the fractional-order capacitor emulators as part of the experimental verification using the Sallen–Key filter topology. The total harmonic distortion and spurious-free dynamic range of the practical 1.5th-order Butterwoth filter are measured as 0.13% and 62.18 dBc, respectively; the maximum and mean absolute relative magnitude errors are 0.03929 and 0.02051, respectively.

A Reconfigurable Balun-LNA and Tunable Filter With Frequency-Optimized Harmonic Rejection for Sub-GHz and 2.4 GHz IoT Receivers

A CMOS reconfigurable balun-LNA and tunable filter is proposed for sub-GHz and 2.4 GHz IoT applications. The core of the LNA gain stage is composed of two cascaded inverters for the single-to-differential conversion, and the additional inverter is placed in the feedback path for the implementation of the active feedback. In the sub-GHz band, it operates as an active feedback LNA by enabling all inverter stages. At the narrow 2.4 GHz band, it operates as an inductive source degenerated LNA (ISDLNA) with a minimum noise figure (NF) by disabling the inverter in the feedback path. In order to suppress the unwanted local oscillator (LO) harmonic mixing in the sub-GHz band and provide the frequency-optimized harmonic rejection ratio (HRR), a reconfigurable Sallen-Key (SK) filter-based <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$4^{\mathbf {th}}$ </tex-math></inline-formula> -order tunable filter is proposed on the basis of the modified super source follower (SSF) with enhanced loop gain. It covers the entire VHF band with a smaller capacitance tuning ratio by switching the polarity of the output of the modified SSF. Compared to previous works, this work provides the largest tuning range from 50 MHz to 700 MHz without splitting individually optimized circuits corresponding to each frequency band and using no external board components. This is the first suggestion of a fully integrated SK filter-based tunable filter to cover VHF/UHF bands through a hardware re-configurability without increasing the tuning ratio of the switched capacitor array, while providing an optimum HRR performance for corresponding operating frequencies in conjunction with harmonic rejection mixer (HRM). In addition, it proposes a hardware efficient re-configurable balun-LNA to operate as a wideband feedback LNA at sub-GHz and a narrowband ISDLNA at 2.4 GHz without the use of external input matching circuits. In the measurement, the proposed front-end achieves an average power gain ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{S}_{{21}}$ </tex-math></inline-formula> ) of 25.9 dB, NF of < 4.25 dB, and in-band input-referred third-order intercept point (IIP3) of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$&gt;\!\!\!-12.8$ </tex-math></inline-formula> dBm over the tuning range from 50 MHz to 700MHz. The proposed tunable filter shows the frequency-optimized HRR from 10 dBc to 26 dBc over the tuning range while greatly reducing a silicon area. At 2.4 GHz band, it shows <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{S}_{{21}}$ </tex-math></inline-formula> of 14.7 dB, NF of 3.2 dB, and in-band IIP3 of −4.5 dBm. The die area of the proposed circuit, excluding I/O PADs and the measurement output buffer, is less than 2.0 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . The power consumption of the front-end working at sub-GHz and 2.4 GHz bands is 33.6 mW and 5.1 mW respectively.

Design and characterization of third-order Sallen–Key digital filter in nuclear signal processing

The Gaussian filter shaping circuit is widely used in the nuclear pulse signal processing due to its good performance in amplitude extraction and pulse counting. A third-order Sallen–Key (3rd S–K) filter shaping circuit is designed based on a RC integrator and a second-order Sallen–Key (2nd S–K) circuit. According to the digital 3rd S–K, the transfer functions is derived in the Laplacian domain, and the numerical recurrence model is analyzed and researched, the purpose is to obtain its transfer function and amplitude–frequency response curve in the z-domain. For the simulation and actual sampling of the nuclear signal, digital shaping processing is performed at different parameters, three parameters (d, SNR, δ) are defined to compare and analyze the amplitude extraction, noise suppression and symmetry of the digital shaping method, which shows that as the shaping parameters increases, the digital shaping output noise suppression performance is better, the SNR increased from 49.25 to 64.21, the waveform is more symmetrical, the δ reduced from 34.05 to 0.22. At the same parameters, it is compared and analyzed with CR-RC3 and 2nd S–K shaping methods, according to the digital Gaussian shaping results, the 3rd S–K digital shaping method has better pulse amplitude extraction(d = 36.06%), noise suppression performance (SNR = 64.21) and waveform symmetry (δ = 0.22). Under different shaping methods, the energy resolution and pulse counting rate of the Fe characteristic X-ray energy spectrum are compared based on a Si-PIN detector. The results show that the 3rd S–K digital shaping method has better energy resolution performance and comprehensive performance indicators, which can be further applied for digital shaping of nuclear pulse signals.

TLSCA-SVM Fault Diagnosis Optimization Method Based on Transfer Learning

In fault-diagnosis classification, a pressing issue is the lack of target-fault samples. Obtaining fault data requires a great amount of time, energy and financial resources. These factors affect the accuracy of diagnosis. To address this problem, a novel fault-diagnosis-classification optimization method, namely TLSCA-SVM, which combines the sine cosine algorithm and support vector machine (SCA-SVM) with transfer learning, is proposed here. Considering the availability of fault data, this thesis uses the data generated by analog circuits from different faults for analysis. Firstly, the data signal is collected from different faults of the analog circuit, and then the characteristic data are extracted from the data signals by the wavelet packets. Secondly, to employ the principal component analysis (PCA) reduces the feature-value dimension. Lastly, as an auxiliary condition, the error-penalty item is added to the objective function of the SCA-SVM classifier to construct an innovative fault-diagnosis model namely TLSCA-SVM. Among them, the Sallen–Key bandpass filter circuit and the CSTV filter circuit are used to provide the data for horizontal- and vertical-contrast classification results. Comparing the SCA with the five optimization algorithms, it is concluded that the performance of SCA optimization parameters has certain advantages in the classification accuracy and speed. Additionally, to prove the superiority of the SCA-SVM classification algorithm, the five classification algorithms are compared with the SCA-SVM algorithm. Simulation results showed that the SCA-SVM classification has higher precision and a faster response time compared to the others. After adding the error penalty term to SCA-SVM, TLSCA-SVM requires fewer fault samples to process fault diagnosis. Ultimately, the method which is proposed could not only perform fault diagnosis effectively and quickly, but also could run effectively to achieve the effect of transfer learning in the case of less failure data.

Comparative Analysis of Multiple Feedback and Sallen Key Band-Pass Filters for Development of Ferrite Based High Sensitive Fluxgate Sensor

Comparative Analysis of Multiple Feedback and Sallen Key Band-Pass Filters for Development of Ferrite Based High Sensitive Fluxgate Sensor

Application of DBN and GWO-SVM in analog circuit fault diagnosis

For large-scale integrated electronic equipment, the complex operating mechanisms make fault detection very difficult. Therefore, it is important to accurately identify analog circuit faults in a timely manner. To overcome this problem, this paper proposes a novel fault diagnosis method based on the deep belief network (DBN) and restricted Boltzmann machine (RBM) optimized by the gray wolf optimization (GWO) algorithm. First, DBN is used to extract the deep features of the analog circuit output signal. Then, GWO is used to optimize the penalty factor c and kernel parameter g of support vector machine (SVM). Finally, GWO-SVM is used to diagnose the signal features extracted by the DBN. Fault diagnosis simulation was conducted for the Sallen–Key band-pass filter and a four-opamp biquad highpass filter. The experimental results show that compared with the existing algorithms, the algorithm proposed in this paper improves the accuracy of Sallen–Key bandpass filter circuit to 100% and shortens the fault diagnosis time by about 90%; for four-opamp biquad highpass filter, the accuracy rate has increased to 99.68%, and the fault diagnosis time has been shortened by approximately 75%, and reduce hundreds of iterations. Moreover, the experimental results reveal that the proposed fault diagnosis method greatly improves the accuracy of analog circuit fault diagnosis, which solves a major problem in analog circuitry and has great significance for the future development of relevant applications.

Polydimethylsiloxane‐based capacitive motion sensor and its read‐out circuit

SummaryA capacitive motion sensor that can detect human walking and motions up to a certain distance was designed using polydimethylsiloxane (PDMS) as the primary sensor material. A read‐out circuit was designed to detect capacitive coupling with the sensor material caused by the motion in the surrounding. The read‐out circuit consists of sensing, filtering, and amplifying stages. A high‐pass filter was used to avoid DC components, and to eliminate adverse impacts of 50Hz noise in the sensing signal, a sixth‐order low‐pass filter consisting of active Sallen–Key and passive RC filters was utilized. The signals obtained from the complete read‐out circuit revealed that the sensor system could accurately detect human movements up to 2 m away. Also, different signal patterns were obtained from the output of the sensor system for various human motions.

A Statistical Approach of Analog Circuit Fault Detection Utilizing Kolmogorov–Smirnov Test Method

This work presents a testing technique based on ‘Kolmogorov–Smirnov’ (K–S) test for detection of parametric faults in analog circuits. The proposed method is a time-domain signal processing technique that compares the statistical similarity in terms of ‘Empirical Cumulative Distribution Function’ (ECDF) of the outputs of the circuit when the input of the circuit is a random analog signal. ‘Multivariate Adaptive Regression Splines’ (MARS) technique is used to map the tolerances of functional metrics to the components of the circuit under test (CUT). Two benchmark circuits, i.e., second-order Sallen–Key band-pass filter and weakly nonlinear cascade amplifier are tested to validate the proposed fault detection technique. The proposed statistical approach with the use of random analog signal as input excitation results reduction of complexity for designing input test signal and increases fault coverage in the analog circuit testing. The proposed method is testified experimentally for Sallen–Key band-pass filter. The experimental results are in good agreement with the simulated results.

Robust stability analysis of incommensurate fractional-order systems with time-varying interval uncertainties

This paper focuses on the stability analysis of the incommensurate fractional-order systems describing by the pseudo-state-space form in the presence of interval uncertainties. By using the generalized small-gain theorem and the properties of M-matrices, a condition is achieved for robust finite-gain L2 stability of these systems. In addition, satisfying this condition ensures the asymptotic stability of uncertain fractional-order systems, based on the Caputo definition. Unlike the methods which are based on the eigenvalue argument checking, the proposed robust stability analysis method can be used for systems with irrational fractional orders and time-varying uncertainties. Compared with the Lyapunov based methods, the conservatism due to the lack of relation between stability condition and fractional-order of the system does not occur in the proposed method. An illustrative example is presented to confirm this method does not lead to conservatism generated by reformulation of the interval uncertainty, which is the basis of the commonly used methods in the literature. Finally, the suggested method is employed for robust stability checking of the Sallen–Key filter including fractional capacitors with irrational orders.

Fault Diagnosis of Nonlinear Analog Circuit Based on Generalized Frequency Response Function and LSSVM Classifier Fusion

For fault diagnosis of nonlinear analog circuit, a novel method based on generalized frequency response function (GFRF) and least square support vector machine (LSSVM) classifier fusion is presented. The sinusoidal signal is used as the input of analog circuit, and then, the generalized frequency response functions are estimated directly by the time-domain formulations. The discrete Fourier transform of measurement data is avoided. After obtaining the generalized frequency response functions, the amplitudes of the GFRFs are chosen as the fault feature parameters. A classifier fusion algorithm based on least square support vector machine (LSSVM) is used for fault identification. Two LSSVM multifault classifiers with different kernel functions are constructed as subclassifiers. Fault diagnosis experiments of resistor-capacitance (RC) circuit and Sallen Key filter are carried out, respectively. The results show that the estimated GFRFs of the circuit are accurate, and the fault diagnosis method can get high recognition rate.

10-GHz Fully Differential Sallen–Key Lowpass Biquad Filters in 55nm SiGe BiCMOS Technology

Multi-GHz lowpass filters are key components for many RF applications and are required for the implementation of integrated high-speed analog-to-digital and digital-to-analog converters and optical communication systems. In the last two decades, integrated filters in the Multi-GHz range have been implemented using III-V or SiGe technologies. In all cases in which the size of passive components is a concern, inductorless designs are preferred. Furthermore, due to the recent development of high-speed and high-resolution data converters, highly linear multi-GHz filters are required more and more. Classical open loop topologies are not able to achieve high linearity, and closed loop filters are preferred in all applications where linearity is a key requirement. In this work, we present a fully differential BiCMOS implementation of the classical Sallen Key filter, which is able to operate up to about 10 GHz by exploiting both the bipolar and MOS transistors of a commercial 55-nm BiCMOS technology. The layout of the biquad filter has been implemented, and the results of post-layout simulations are reported. The biquad stage exhibits excellent SFDR (64 dB) and dynamic range (about 50 dB) due to the closed loop operation, and good power efficiency (0.94 pW/Hz/pole) with respect to comparable active inductorless lowpass filters reported in the literature. Moreover, unlike other filters, it exploits the different active devices offered by commercial SiGe BiCMOS technologies. Parametric and Monte Carlo simulations are also included to assess the robustness of the proposed biquad filter against PVT and mismatch variations.

A chaotic circuit under a new classification framework of inductorless Chua’s circuits

PurposeThis paper aims to classify the inductorless Chua’s circuits into two types from the topological structures and construct a chaotic circuit under this new classification framework.Design/methodology/approachIn this paper, two types of inductorless Chua’s circuit models are presented from topological structure, among which the first type of inductorless Chua’s circuit (FTICC) model is much closer to the original Chua’s circuit. Under this classification framework, a new inductorless Chua’s circuit that belongs to the FTICC model is built by replacing LC parallel resonance of the original Chua’s circuit with a second order Sallen–Key band pass filter.FindingsCompared with a paradigm of a reported inductorless Chua’s circuit that belongs to the second type of inductorless Chua’s circuit (STICC) model, the newly proposed circuit can present the attractors which are much more closely to the original Chua’s attractors. The dynamical behaviors of coexisting period-doubling bifurcation patterns and boundary crisis are discovered in the newly proposed circuit from both numerical simulations and experimental measurements. Moreover, a crisis scenario is observed that unmixed pairs of symmetric coexisting limit cycles with period-3 traverse through the entire parameter interval between coexisting single-scroll chaotic attractors and double-scroll chaotic attractor.Originality/valueThe newly constructed circuit enriches the family of inductorless Chua’s circuits, and its simple topology with small printed circuit board size facilitates the various types of engineering applications based on chaos.

NCRC to improve linearity and sensitivity for RuO 2 urea biosensor sensing measurement

A novel noise-cancelling readout circuit (NCRC) is proposed to improve the linearity and sensitivity of traditional voltage–time (V–T) measurement system for ruthenium dioxide (RuO2) urea biosensor. To reduce the non-ideal effect related to traditional V–T measurement system that negatively threatened by the impact of power line noise, this NCRC adopts a new power line noise elimination scheme. Moreover, by employing the Twin-T notch filter and the Sallen–Key low-pass filter, the proposed NCRC can increase the linearity by 161% while retaining the sensitivity at an average level than V–T measurement system. A new NCRC for measuring the linearity and sensitivity of RuO2 urea biosensor is implemented by a real circuit board. The experimental results show that the proposed NCRC can achieve 0.956 linearity and 1.22 mV/(mg/dl) average sensitivity.