Frequency Estimation Research Articles

Radial Vibration Measurement of Rotating Shaft using Constant Density Fringe Pattern and Line Scan Camera

Abstract The radial vibration signals of the rotor can provide abundant information about the health condition of the machine. In this paper, a simple vision-based measurement system is proposed to simultaneously measure two-dimensional displacements in radial directions for the rotating shaft, where the system consists of a constant density fringe pattern (CDFP), a line scan camera (LSC), and a lens. The CDFP should be installed around the surface of the rotating shaft to make the density of the fringe constant along the shaft axis, while the shaft axis is vertical to the optical axis of the LSC but not parallel to the line-array sensor of the LSC. Therefore, the density of the fringe imaged on the LSC is not constant because of the modulation of the circular surface of the shaft, and the distribution of the fringe density on the LSC is a U-shaped curve. Thus, the shaft centreline orbit can be tracked by the lowest point of the density distribution curve (DDC) of the fringe. Then, an efficient and accurate parameterized instantaneous frequency estimation method (PIFEM) is employed to estimate the DDC of the fringe, because the variable density fringe can be regarded as an amplitude-modulated and frequency-modulated nonstationary signal whose instantaneous frequency function is equivalent to the DDC. Experimental results verify the feasibility and effectiveness of the proposed method by comparing it to the eddy current sensors.

Population prevalence of hypospadias according to monitoring of congenital malformations in the regions of the Russian Federation

Hypospadias is a common congenital malformation, and its incidence varies widely between countries and geographic regions, making it necessary to obtain proprietary frequency estimates. In addition, a number of studies have noted a trend toward increased hypospadias.Purpose. The study aims at assessing the incidence and dynamics of hypospadias in the regions of the Russian Federation for the period 2011–2021.Material and methods. The study included 22 regions of the Russian Federation. The study sample included cases of hypospadias among live births, stillbirths, and fetuses. The number of cases of hypospadias is 7071, the total number of births during the study period is 4,677,892. IBM SPSS Statistics 21 was used to process the research materials. Poisson regression was used to assess the incidence and risk factors for hypospadias.Results. The overall incidence of hypospadias in all regions was 15.12 cases per 10,000 births. The incidence of all cases of hypospadias by region ranged from 2.12 to 34.76 per 10,000 births. There were no significant trends in changes in the frequency of the defect during the study period. Among all cases of hypospadias, the majority is represented by hypospadias of the glans penis (Q54.0) — 5666 cases or 80.13%. In 99.41% of cases, hypospadias occurred in live-born children. The incidence of hypospadias in children increased with maternal age (over 35 years).Discussion. For the first time, estimates of the incidence of hypospadias have been obtained based on monitoring data for congenital malformations. Since hypospadias is a common defect, it can be assumed that in regions of the Russian Federation with low frequencies of hypospadias, the defect is most likely underreported. The incidence of the defect has remained stable over time, although many studies have found an increase in the incidence of hypospadias. Continued research is needed to clarify the epidemiological characteristics of hypospadias.

Complex-Valued Noisy Sinewaves Frequency Estimator Based on DTFT Linearization and Interpolation

AbstractThis paper proposes an Interpolated Discrete-Time Fourier Transform (LIpDTFT) estimator for complex-valued noisy sinewave frequency based on the Linearization of the DTFT module behavior around the spectrum peak. It belongs to a class of LIpDTFT estimators that compensate the poor Discrete Fourier Transform (DFT) frequency resolution by interpolating two DTFT samples located very close to an initial frequency estimate. As compared with other DTFT-based frequency estimators recently proposed in the literature, the proposed LIpDTFT estimator ensures a smaller interpolation error and a lower processing effort. Moreover, if the rectangular window is adopted, it almost attains the unbiased Cramér-Rao Lower Bound (CRLB) even if a very small number of samples is analyzed. The accuracies ensured in different operating conditions by the proposed frequency estimator and other state-of-the-art DTFT-based algorithms are compared to each other through computer simulations.

Phenomic landscape and pharmacogenomic implications for HLA region in a Taiwan Han Chinese population

BackgroundThe human leukocyte antigen (HLA) genes, exhibiting significant genetic diversity, are associated with susceptibility to various clinical diseases and diverse in drug responses. High costs of HLA sequencing and the population-specific architecture of this genetic region necessitate the establishment of a population-specific HLA imputation reference panel. Moreover, there is a lack of understanding about the genetic and phenotypic landscape of HLA variations within the Taiwanese population.MethodsWe created models for a Taiwanese-specific HLA imputation reference panel. These models were trained with the array genotype data and HLA sequencing data from 845 Taiwanese subjects. HLA imputation was applied for 59,448 Taiwanese subjects to characterize the HLA allele and haplotype frequencies. Additionally, a phenome-wide association study (PheWAS) was conducted to identify the phenotypes associated with HLA variations. The association of the biallelic HLA variants with the binary and quantitative traits were evaluated with additive logistic and linear regression models, respectively. Furthermore, an omnibus test with likelihood-ratio test was applied for each HLA amino acid position in the multiallelic HLA amino acid polymorphisms to compare the difference between a fitted model and a null model following a χ2 distribution of n-1 degree of freedom at a position with n residues. Finally, we estimated the prevalence of adverse drug reactions (ADR)-related HLA alleles in the Taiwanese population.ResultsIn this study, the reference panel models displayed remarkable accuracy, with averages of 99.3%, 98.9%, and 99.1% for 2-, 4-, 6-digit alleles of the eight classical HLA genes, respectively. For PheWAS, a total of 18,136 significant associations with HLA variants across 26 phenotypes are identified (p < 5×10-8), highlighting the pleiotropy feature of the HLA region. Among the independent signals, 15 are novel, including the association of HLA-B pos 138 variation with ankylosing spondylitis (AS), and rs9266290 and rs9266292 with allergy. Through an analysis spanning the entire HLA region, we identified clusters of phenotype correlations. Finally, the carriers of pharmacogenomic related HLA alleles, including HLA-C*01:02 (35.86%), HLA-B*58:01 (20.9%), and HLA-B*15:02 (8.38%), were characterized in the Taiwanese general population.ConclusionsWe successfully delivered the HLA imputation for 59,448 Taiwanese subjects and characterized the genetic and phenotypic landscapes of the HLA variations. In addition, we quantified the estimated prevalence of the ADR-related HLA alleles in the Taiwanese population. The developed HLA imputation reference panel could be used for estimation of population HLA allele frequencies, which can facilitate further studies in the role of HLA variants in a wider range of phenotypes in the population.

Frequency Offset Estimation for UWB-OFDM System using Weight and Exhaustiveness based Monarch Butterfly Optimization Approach

The performance of an OFDM system has limitation because the carrier frequency offset (CFO) and sampling frequency offset (SFO) is not estimated correctly. Current methods propose the way of obtaining frequency estimation by using the evolutionary algorithm, but the evolution algorithm suffers from the premature convergence problem. In order to provide efficient frequency offset estimation, this paper proposed weight and exhaustiveness based monarch butterfly optimization approach. First, on the transmitter block, for modulating an input symbol, the Hybrid-Quadrature Phase-Shift Keying modulation scheme is used. Brunn’s IFFT is done at each transmitter for symbol mapping and then in each transmitter block cyclic prefix is inserted. After that, WE-MBO algorithm estimates the frequency offset. On receiver side, the inverse operation of the transmitter is performed. After comparison of proposed system with the existing system, the proposed system gave better performance.

HeavySeparation: A Generic Framework for Stream Processing Faster and More Accurate

Sketch as a probability data structure has been widely used in high volume, fast data streams. At the cost of a tiny accuracy in frequency estimation, it achieves a high speed with small memory usage. However, skewed data streams pose a significant challenge for existing sketches in terms of accuracy and speed using limited memory. To address this issue, we proposed a framework, called HeavySeparation, to enhance existing sketches by filtering elephant flow efficiently and accurately. We adopt a power-weakening increment strategy to allow sufficient competition in the early stages of identifying elephant flows and amplifying relative advantage when the frequency of candidate flow is large. To verify the effectiveness and efficiency of our framework, we apply the framework to two typical sketches and two common stream processing tasks. Results show that HeavySeparation framework reduces the error by around 1∼2 orders of magnitude on average compared to the state-of-the-art in frequency estimation.

Pseudo-Eulerian model formulation for the determination of breakage frequency and daughter size distribution: single droplet breakup experiments in turbulent flow

The study of breakage of single oil droplet in a turbulent flow is experimentally performed by means of direct visualization using high-speed imaging. A comparison of two different approaches for estimation of the breakage frequency is presented using the same set of experimental data. The first approach, estimate the breakage frequency based on the estimation of the averaged breakage time and breakage probability calculation based on single oil breakage experiments. The second approach consist in combining and superposing the different measurements into one population of droplets, to investigate the evolution of the size distribution of droplets emulating a pseudo-Eulerian representation. Using this approach, the breakage frequency can be estimated by following the evolution of the number of droplets of a particular size. We found that the pseudo-Eulerian approach is more accurate for construction of closure model for the implementation of population balance equation.

Perceived misdiagnosis of psychiatric conditions in autistic adults

Many autistic people, particularly women, do not receive an autism diagnosis until adulthood, delaying their access to timely support and clinical care. One possible explanation is that autistic traits may initially be misinterpreted as symptoms of other psychiatric conditions, leading some individuals to experience misdiagnosis of other psychiatric conditions prior to their autism diagnosis. However, little is currently known about the frequency and nature of psychiatric misdiagnoses in autistic adults. Using data collected in the first half of 2019 from an ongoing longitudinal register of autistic adults in the Netherlands, this study explored the frequency of perceived psychiatric misdiagnoses before receiving an autism diagnosis. Gender differences were also explored. A sample of 1211 autistic adults (52.6% women, mean age 42.3 years), the majority of whom were Dutch and relatively highly educated, was evaluated. Results showed that 24.6% (n=298) of participants reported at least one previous psychiatric diagnosis that was perceived as a misdiagnosis. Personality disorders were the most frequent perceived misdiagnoses, followed by anxiety disorders, mood disorders, chronic fatigue syndrome/burnout-related disorders, and attention-deficit/hyperactivity disorder. Autistic women (31.7%) reported perceived misdiagnoses more frequently than men (16.7%). Women were specifically more likely than men to report perceived misdiagnoses of personality disorders, anxiety disorders, and mood disorders. Women also reported prior psychiatric diagnoses more often in general (65.8% versus 34.2% in men). Within the group of individuals with a prior diagnosis, perceived misdiagnoses were equally likely for men and women. One in four autistic adults, and one in three autistic women, reported at least one psychiatric diagnosis, obtained prior to being diagnosed with autism, that was perceived as a misdiagnosis. Inaccurate diagnoses are linked to long diagnostic pathways and delayed recognition of autism. These findings highlight the need for improved training of mental health practitioners, in order to improve their awareness of the presentation of autism in adulthood and of the complex relationship between autism and co-occurring conditions. The current study constitutes a first step towards showing that autistic adults, and particularly women, may be at greater risk of experiencing misdiagnoses. Future studies based on larger, more representative samples are required, to replicate current findings and provide more reliable estimates of the overall frequency of misdiagnoses as well as the frequency of misdiagnoses for specific psychiatric conditions. This study was made possible by funding from the Netherlands Organisation for Health Research and Development (ZonMW), project number 60-63600-98-834.

Reduced-complexity multiple parameters estimation via toeplitz matrix triple iteration reconstruction with bistatic MIMO radar

In this advanced exploration, we focus on multiple parameters estimation in bistatic Multiple-Input Multiple-Output (MIMO) radar systems, a crucial technique for target localization and imaging. Our research innovatively addresses the joint estimation of the Direction of Departure (DOD), Direction of Arrival (DOA), and Doppler frequency for incoherent targets. We propose a novel approach that significantly reduces computational complexity by utilizing the Temporal-Spatial Nested Sampling Model (TSNSM). Our methodology begins with a multi-linear mapping mechanism to efficiently eliminate unnecessary virtual Degrees of Freedom (DOFs) and reorganize the remaining ones. We then employ the Toeplitz matrix triple iteration reconstruction method, surpassing the traditional Temporal-Spatial Smoothing Window (TSSW) approach, to mitigate the single snapshot effect and reduce computational demands. We further refine the high-dimensional ESPRIT algorithm for joint estimation of DOD, DOA, and Doppler frequency, eliminating the need for additional parameter pairing. Moreover, we meticulously derive the Cramér-Rao Bound (CRB) for the TSNSM. This signal model allows for a second expansion of DOFs in time and space domains, achieving high precision in target angle and Doppler frequency estimation with low computational complexity. Our adaptable algorithm is validated through simulations and is suitable for sparse array MIMO radars with various structures, ensuring higher precision in parameter estimation with less complexity burden.

Identifying Buffet Oscillations Using Sliding-Window Dynamic Mode Decomposition

Buffet is a self-sustaining oscillation that can endanger an aircraft in transonic flight. Early automatic detection of the onset of buffet from simulation data is a necessary step in optimization algorithms used to design new aircraft geometries. We use the Dynamic Mode Decomposition (DMD) eigenvalues to detect the onset of buffet from transient simulations of the OAT15A airfoil across a range of angles of attack. During transients, different eigenvalues may be expressed at different times, and we process shorter segments of the data (sliding windows) in order to obtain robust, time-varying estimates of frequency of oscillation and decay/growth rates. We demonstrate that the onset of oscillation can be identified by analyzing DMD eigenvalues, and that physically different mechanisms of oscillation can additionally be identified from spatial profiles associated with DMD modes. The dominant buffeting modes can be detected through DMD before they become apparent in the physically relevant quantities, such as the coefficient of lift. We expect that such early detection of the onset of buffet could reduce the computational burden of aircraft design and expand the feasible design space.

Vital Sign Monitoring in Dynamic Environment via mmWave Radar and Camera Fusion

Contact-free vital sign monitoring, which uses wireless signals for recognizing human vital signs (i.e, breath and heartbeat), is an attractive solution to health and security. However, the subject's body movement and the change in actual environments can result in inaccurate frequency estimation of heartbeat and respiratory. In this paper, we propose a robust mmWave radar and camera fusion system for monitoring vital signs, which can perform consistently well in dynamic scenarios, e.g., when some people move around the subject to be tracked, or a subject waves his/her arms and marches on the spot. Three major processing modules are developed in the system, to enable robust sensing. Firstly, we utilize a camera to assist a mmWave radar to accurately localize the subjects of interest. Secondly, we exploit the calculated subject position to form transmitting and receiving beamformers, which can improve the reflected power from the targets and weaken the impact of dynamic interference. Thirdly, we propose a weighted multi-channel Variational Mode Decomposition (WMC-VMD) algorithm to separate the weak vital sign signals from the dynamic ones due to subject's body movement. Experimental results show that, the 90 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${^{th}}$</tex-math></inline-formula> percentile errors in respiration rate (RR) and heartbeat rate (HR) are less than 0.5 RPM (respirations per minute) and 6 BPM (beats per minute), respectively.

Indirect frequency estimation by time-shifted accelerations subtraction: generalization of the methodology and numerical application on a Warren truss bridge

In the context of Structural Health Monitoring (SHM) of transportation infrastructures, bridge eigen frequencies are commonly adopted as diagnostic indices. Under this regard, as a cost-effective identification methodology, indirect SHM, which consists in the use of sensors installed on running vehicles, is attracting attention. In particular, methods relying on the use of two or more on-board sensors may suppress the influence of track irregularity, which is a remarkable drawback for indirect SHM, and improve the identification accuracy. However, the combination characteristics of the two on-board sensors is still an open issue to be addressed. Also, in many studies, test bridges consist of simple girders, and there are few verifications on complex structures, such as truss bridges. The first contribution of this study is the analytical and generalized expression of the operational range defining the use of time-shifted signals subtraction operation for indirect frequency estimation. After the outcomes provided by this formulation were confirmed by the results obtained from a 2D explanatory example, the proposed procedure was further validated through three-dimensional train-track-bridge dynamic simulations. For this purpose, 3D FE model of a real existing Warren truss bridge, dynamically validated through experimental tests, and a 3D multi-body rail vehicle were adopted. From an engineering standpoint, a relevant result of this study found is that the coexistence of proper sensors onboard positioning and sufficient target bridge component excitation revealed to be crucial for the success of an indirect frequency identification procedure which is based on time-shifted accelerations subtraction.

Molecular detection of intestinal parasites in a rural community of Colombia: A one health approach to explore potential environmental-zoonotic transmission.

Protozoan and helminth parasitic infections pose significant public health challenges, especially in developing countries with rural populations marked by suboptimal hygiene practices and socio-economic constraints. The parasites are the etiological agents of these infections and have a notably elevated global prevalence. Therefore, this study focuses on estimating the frequency and transmission dynamics of several parasitic species, including Blastocystis, Giardia, Cryptosporidium spp., Entamoeba histolytica, Ascaris lumbricoides, Trichuris trichiura, Taenia spp. and hookworms, within a rural community in southwest Colombia with a particular emphasis on the One Health framework, considering environmental and zoonotic transmission potentials. This study involved the analysis of 125 samples, encompassing human participants (n = 99), their domestic pets (dogs) (n = 24) and water sources (n = 2). Parasite detection was carried out utilizing a combination of microscopy and molecular techniques. Furthermore, the characterization of Blastocystis subtypes (STs) was achieved through Oxford Nanopore sequencing of the rRNA-18S gene. The investigation also entailed the examination of potential associations between intestinal parasitism and various sociodemographic factors. Results revealed a high frequency of parasitic infections when employing molecular methods, with Blastocystis (n = 109/87%), Giardia (n = 20/16%), Ancylostoma duodenale (n = 28/22%), Ancylostoma ceylanicum (n = 7/5.6%), E. histolytica (n = 6/4.8%), Cryptosporidium spp. (n = 12/9.6%) and even Taenia (n = 1/0.8%) detected. Cryptosporidium spp. was also identified in water samples. Coinfections were prevalent, with 57% (n = 70) of samples exhibiting single-parasite infections and 43% (n = 53) showing various degrees of polyparasitism, emphasizing the complexity of transmission dynamics. Blastocystis subtyping, conducted via Oxford Nanopore sequencing, revealed a diversity of subtypes and coexistence patterns, with ST2 being the most prevalent. This research underscores the importance of using molecular techniques for frequency estimation, particularly emphasizing the relevance of zoonotic transmission in parasitic infections. It highlights the significance of the One Health approach in comprehending the circulation of parasites among animals, humans and environmental sources, thereby directly impacting public health and epidemiological surveillance.

Optimizing Bangkaew dog breed identification using DNA technology.

The Bangkaew dog is an indigenous dog breed in the Phitsanulok province of Thailand. This breed is recognized by the Fédération Cynologique Internationale (FCI), a global canine organization. The unique traits of the Bangkaew breed lead to purebred selection for breeding, while only their traits and pedigree from parental history are recorded. Determination of the risk of inbreeding depression and the origin of unknown DNA profiles is essential due to the challenges in predicting puppy characteristics, which are crucial for breed management and conservation. This study aimed to emphasize that current allelic frequency data for the Bangkaew dog breed must be considered for precise individual identification. Approximately 82 Bangkaew dogs from various Thai localities were studied using 15 microsatellite markers for genotypic monitoring and individual identification. Maternal genetic inheritance was assessed via mtDNA D-loop analysis. The results revealed high genetic diversity in the Bangkaew breed, indicating low potential for inbreeding. We also found that using a 15 loci microsatellite panel was effective for the identification of Bangkaew dogs. The optimized 10 loci microsatellite genotyping panel developed in this study presents improved identification testing efficiency, promoting both time- and cost-effectiveness. Analysis of microsatellite DNA markers in Bangkaew dogs using an optimized panel of 10 loci selected from 15 loci effectively facilitated individual identification. This approach not only enhances time and cost efficiency, but also provides accurate allelic frequency estimates, which are crucial for the realistic evaluation of DNA evidence.

Advancements in genetic techniques and functional genomics for enhancing crop traits and agricultural sustainability.

Genetic variability is essential for the development of new crop varieties with economically beneficial traits. The traits can be inherited from wild relatives or induced through mutagenesis. Novel genetic elements can then be identified and new gene functions can be predicted. In this study, forward and reverse genetics approaches were described, in addition to their applications in modern crop improvement programs and functional genomics. By using heritable phenotypes and linked genetic markers, forward genetics searches for genes by using traditional genetic mapping and allele frequency estimation. Despite recent advances in sequencing technology, omics and computation, genetic redundancy remains a major challenge in forward genetics. By analyzing close-related genes, we will be able to dissect their functional redundancy and predict possible traits and gene activity patterns. In addition to these predictions, sophisticated reverse gene editing tools can be used to verify them, including TILLING, targeted insertional mutagenesis, gene silencing, gene targeting and genome editing. By using gene knock-down, knock-up and knock-out strategies, these tools are able to detect genetic changes in cells. In addition, epigenome analysis and editing enable the development of novel traits in existing crop cultivars without affecting their genetic makeup by increasing epiallelic variants. Our understanding of gene functions and molecular dynamics of various biological phenomena has been revised by all of these findings. The study also identifies novel genetic targets in crop species to improve yields and stress tolerances through conventional and non-conventional methods. In this article, genetic techniques and functional genomics are specifically discussed and assessed for their potential in crop improvement.

A supervised approach for improving the dimensionless frequency estimation for time‐domain simulations of building structures on embedded foundations

AbstractThe analysis of soil–structure interaction (SSI) problems has been established successfully in recent decades. In particular, the solution in the frequency domain provides an exact and efficient method for computing the response of the coupled system. Despite this, the state of practice as a first attempt to incentivize time domain analyses compatible with standard finite element packages introduces the so‐called dimensionless flexible‐base frequency. This frequency, which depends solely on the structure‐to‐soil‐period ratio, allows transforming the frequency domain analyses into time domain analyses using frequency‐independent soil impedance values. However, if such frequency exists for the combined system, it must depend on several physical variables. In this work, we propose a supervised approach to obtain the flexible‐base dimensionless frequency at which the frequency‐independent soil impedance should be used. The analysis is carried out using five dimensionless parameters, and the importance of each one to the estimation of the dimensionless flexible‐base frequency is investigated. We use an inverse problem based on ensemble Kalman inversion (EnKI) to obtain the optimal frequency of the interaction. The data obtained are then employed in a machine‐learning framework to map a set of dimensionless parameters to such a frequency. The generated mapping is finally verified, and a significant improvement in time‐domain simulations is shown compared to the state of practice.

Reconstructing the Spectrum of a Polyharmonic Signal under Slow Fluctuations in the Sampling Period

Reconstructing the Spectrum of a Polyharmonic Signal under Slow Fluctuations in the Sampling Period

Experimental validation of a short-term damping estimation method for wind turbines in nonstationary operating conditions

Abstract. Modal properties and especially damping of operational wind turbines can vary over short time periods as a consequence of environmental and operational variability. This study seeks to experimentally test and validate a recently proposed method for short-term damping and natural frequency estimation of structures under the influence of varying environmental and operational conditions from measured vibration responses. The method is based on Gaussian process time-dependent auto-regressive moving average (GP-TARMA) modelling and is tested via two applications: a laboratory three-storey shear frame structure with controllable, time-varying damping and a flutter test of a full-scale 7 MW wind turbine prototype, in which two edgewise modes become unstable. Damping estimates for the shear frame compare well with estimates obtained with stochastic subspace identification (SSI) and standard impact hammer tests. The efficacy of the GP-TARMA approach for short-term damping estimation is illustrated through comparison to short-term SSI estimates. For the full-scale flutter test, GP-TARMA model residuals imply that the model cannot be expected to be entirely accurate. However, the damping estimates are physically meaningful and compare well with a previous study. The study shows that the GP-TARMA approach is an effective method for short-term damping estimation from vibration response measurements, given that there are enough training data and that there is a representative model structure.

Kernel density estimation of allele frequency including undetected alleles.

Whereas undetected species contribute to estimation of species diversity, undetected alleles have not been used to estimated genetic diversity. Although random sampling guarantees unbiased estimation of allele frequency and genetic diversity measures, using undetected alleles may provide biased but more precise estimators useful for conservation. We newly devised kernel density estimation (KDE) for allele frequency including undetected alleles and tested it in estimation of allele frequency and nucleotide diversity using population generated by coalescent simulation as well as well as real population data. Contrary to expectations, nucleotide diversity estimated by KDE had worse bias and accuracy. Allele frequency estimated by KDE was also worse except when the sample size was small. These might be due to finity of population and/or the curse of dimensionality. In conclusion, KDE of allele frequency does not contribute to genetic diversity estimation.

Research on targeted modulation of elastic wave bandgap in cantilever-structured piezoelectric Phononic crystals

Piezoelectric phononic crystals (PPCs) have the advantages of simplicity and efficiency in controlling elastic wave bandgaps, which can be utilized to solve NVH problems with varying frequency features, such as the low-frequency vibrations caused by the time-varying power source (i.e., motor) in the subframe and underbody of new energy vehicles. However, most of the previous studies on PPCs bandgap control are qualitative, lacking the knowledge of bandgap targeted modulation. This paper analyzes the locally resonant (LR) bandgap characteristics of PPCs with shunting circuits, and aims to achieve precise control of bandgap position by circuit parameters. A theoretical research model of cantilever-structured PPCs is established firstly, and its accuracy is verified through finite element analysis and experiments. Subsequently, the formation mechanism of the LR bandgap is analyzed, and a bandgap characteristic frequency estimation method is proposed, along with an analysis of the influence of electrical parameters using this method. Finally, from the perspective of bandgap practicality, the variable capacitance method is proposed, which can quickly calculate the capacitance value through an estimation formula under the arbitrary designation of target bandgap in the low-frequency range of 200 Hz∼500 Hz. The results show that the actual bandgap position is very close to the target bandgap position, and the bandgap always keeps enough bandwidth and attenuation amount. This method has broad prospects in the field of vibration attenuation where frequency characteristics are variable.