PF Component Research Articles

A Double Interpolation and Mutation Interval Reconstruction LMD and Its Application in Fault Diagnosis of Reciprocating Compressor

The accuracy and stability of the envelope estimation function are enduring issues throughout the research process of LMD. This paper presents double interpolation and mutation interval reconstruction local mean decomposition (DIMIRLMD) to improve the stability of the demodulation process and the accuracy of PF components. DIMIRLMD first proposes a mutation interval reconstruction envelope algorithm using extreme symmetry points to suppress the demodulation mutation phenomenon, which disturbs the stability of the demodulation process, and then selects the optimal PF component from a double interpolation PF component library based on the index of orthogonality (IO) for a better hierarchical property. DIMIRLMD was employed to analyze the simulation signal and vibration signal of a reciprocating compressor in an oversized bearing clearance state, and the results illustrate its performances are more excellent than those of three other LMD methods. Furthermore, the envelope frequency spectrum obtained from the proposed LMD presents a clear double rotation fault frequency and lower noise disturbance.

Research on the composite fault diagnosis of gearbox based on local mean decomposition and Hilbert demodulation

For the sake of deriving the signature frequencies of the composite malfunctions of broken and worn teeth of gearbox, the essay raised a method on account of local mean decomposition and Hilbert demodulation to diagnose gearbox composite fault. The local mean decomposition translates a complicated multi-component AM-FM signal into several PF elements with certain physical significance. Every PF component can be approximately regarded as a simplex component AM-FM signal. Using correlation coefficient method, the Hilbert envelope demodulation spectrum is analyzed by selecting the PF component which is strongly relevant to the incipient composite malfunction signal, and the malfunction signature frequency is identified from the demodulation spectrum. Through analyzing the emulation signal and the vibration signal of the actual gear box broken-wear complex fault, and compared with EMD, it is shown that the means can effectually discern the malfunction characteristic frequency in the composite fault signal.

Fault feature extraction and recognition of vibration signal based on CWD-SK and HMM

Aiming at the problem of rolling bearing fault diagnosis caused by interference information in the process of vibration transmission, this paper puts forward the theory and method of vibration signal fault diagnosis based on Choi Williams distribution spectral kurtosis (SK) combined with hidden Markov model (HMM). The fault location method of local mean decomposition (LMD) is used to screen the PF component with obvious fault characteristic information, CWD-SK is calculated and set as the characteristic parameter to realize the feature extraction of the initial fault of the vibration signal. CWD-SK is input into HMM as the feature vector to classify and identify the fault features of the vibration signal. Finally, the effectiveness of the algorithm is verified by the simulation of the actual data. It provides a robust theoretical and methodological basis for the establishment of fault diagnosis and classification recognition technology suitable for initial rolling mechanical vibration signals.

Study on modal parameter identification of engineering structures based on nonlinear characteristics

AbstractTo study the nonlinear characteristics of the modal recognition of civil engineering parameters, a method of nonlinear recognition of the parameters of characteristics based on LMD is proposed. The LMD method is applied to decompose the acceleration response signals of the disturbing structure of the building, to obtain the PF components, the instantaneous frequency, and the instantaneous amplitude of each PF component, to determine the modal natural frequency and damping coefficient. To determine the modal parameter based on the LMD, the calculation and analysis results are presented as follows: the frequency of the components fluctuates between the fifth and sixth models, which shows that the components contain the reaction of the fifth and sixth design modes. This is because these two modes (3.101 Hz and 3.147 Hz) are very close to each other, which makes it difficult to distinguish between the responses of these two modes by the LMD method. The frequency of the components is always stable (the first 2.5 s), which indicates that during this period the responses of modes 5e and 6e do not dampen, and the ratio between them in the PF1 components does not differ much. The component frequency curve shows an interesting phenomenon. Starting from about 3.8 s, the frequency curve gradually approaches the first mode, and only the frequency of the first mode is about 6 s, which indicates that the response of the first mode still exists and makes up a significant proportion. Modular response, caused by the damping, is only detected in the first half of the 10 s response, after which it is verified from the nonlinear characteristics of the LMD parameter recognition method that half of the third-order modal response on the scale is very low and almost equal to zero, and despite problems with dense frequency separation mode in the LMD method, the frequency responses of its PF components may reflect the mode combination phenomenon and reflect the duration of each mode throughout the response.

The Syntax of Answers to Positive Polar Questions in Jordanian Arabic

Responses to a polar question have recently received much attention in the syntactic literature (e.g., Yaisomanag, 2012 on Thi; Wu, 2016 on Taiwanese, Servidio et al., 2018 on Italian; among others). However, the syntax of yes-no questions in Arabic has been undermined in the literature. The present study provides a syntactic analysis of answers to positive/neutral polar questions in Jordanian Arabic. Jordanian Arabic is particularly relevant here because its system allows for a variety of answer expressions. For example,an answer to a polar question could be in the form of a particle (a: ‘yes’ and laʔ ‘no’) or a finite verb echoing the verb of the question. Following Holmberg (2016), we demonstrate that these expressions are full sentences derived by ellipses. We assume that a yes-no question has an unvalued, free polarity variable [±Pol] that needs to be assigned a value. Deriving the answer would provide a value for this variable. This involves copying the TP of the question and merging an answer particle or an abstract polarity feature (affirmative or negative) in spec-Foc to value the unvalued feature of Pol; then the TP of the answer gets deleted at the PF component under identity with the TP of the question. Keywords: Polarity questions, Answers, Ellipsis, Jordanian Arabic.

A method of fault detection of casing lead based on CEEMDAN-LMD

The existing regular inspection tests for the deformation faults of the bushing lead have the problem of offline detection and poor sensitivity. In order to effectively extract the high frequency components of vibration for diagnosis and analysis, a new fault diagnosis method for the transformer bushing lead is proposed. This method decomposes the time-domain waveform of the collected ultrasonic echo signal through CEEMDAN, and reconstructs its high-frequency components according to the entropy weight method to obtain a denoising signal, and then performs LMD decomposition of the denoised signal, and decomposes the denoised signal. The PF component is analyzed as the input feature component. The method of ultrasonic inspection of casing lead in this article has good adaptability, can obtain lead fault location results with high precision and good reliability, low hardware cost, and good application prospects.

A novel 3D cellular automata-phase field model for computationally efficient dendrite evolution during bulk solidification

Large-domain 3D microstructure prediction that balances both efficiency and accuracy remains a challenging task of materials science and engineering communities. This paper presents a novel 3D Cellular Automata-Phase Field (CA-PF) model that can accurately predict the dendrite formation in a large domain, which combines a 3D CA model with a 1D PF component. In this integrated model, the PF component reformulated in a spherical coordinate is employed to accurately calculate the local growth kinetics including the growth velocity and solute partition at the solidification front while the 3D CA component uses the growth kinetics as inputs to update the dendritic morphology variation and composition redistribution throughout the entire domain. Taking advantage of the high efficiency of the CA model and the high fidelity of the PF model, the 3D CA-PF model saves the computational cost more than five orders of magnitude compared to the 3D PF models without losing much accuracy. By coupling the thermodynamic and kinetic calculations into the PF component, the CA-PF model is capable of handling the microstructure evolution of any complex multi-component alloys. A 2D and a 3D phase-field benchmark problems were first adopted to validate the single dendrites predicted by the 3D CA-PF model. Then, the 3D CA-PF model is applied to predicting the dendrite growth during large-scale solidification processes of directional solidification of Al-30wt.%Cu and laser welding of Al-Cu-Mg and Al-Si-Mg alloys.

Research on Adaptive Reclosing Discriminant Method Based on LMD Sample Entropy

Based on the adaptive time-frequency analysis characteristics of local mean decomposition and the nonlinear quantization ability of sample entropy, an adaptive reclosing discriminant method based on LMD sample entropy is proposed. Firstly, the local mean decomposition method is applied to decompose the original signal of the transmission line fault into several product function components (PF component). Then calculate the sample entropy of the first three PF components to achieve feature quantization of the PF component. Finally, the sum of the sample entropy of first three PF components is used as the eigenvalue to distinguish the fault type of the transmission line. Obtained from the simulation results, the method can identify the type of fault.

Research on the Mechanical Fault Diagnosis Method for Circuit Breakers Based on KFCM

According to the characteristics of non-stationary vibration signals of circuit breakers, a new fault diagnosis method for circuit breakers is proposed in this paper. In this method, the time domain waveform of the collected vibration signal is decomposed by CEEMDAN, and its high-frequency component is reconstructed according to the entropy weight method to obtain the denoised signal. The denoised signal is decomposed by LMD, and the multi-scale permutation entropy is calculated for the decomposed PF component as the input characteristic component of KFCM recognition algorithm. The results of KFCM identification show that this method has a high recognition rate for typical faults such as circuit breaker shaft jam, loose base and refusing action.

Leak Detection and Location Based on ISLMD and CNN in a Pipeline

The key to leak detection and location in water supply pipelines is signal denoising and feature extraction. First, in this paper, an improved spline-local mean decomposition (ISLMD) is proposed to eliminate noise interference. Based on the ISLMD decomposition of a signal, the cross-correlation function between the reference signal and the product functions component can be obtained. And then the PF component containing the leak information can be extracted reasonably. Compared with improved local mean decomposition, the ISLMD has higher accuracy in leak location. Second, an image recognition method using a convolutional neural network for leak detection is proposed, which can better address the problem that the features of different leak apertures or locations are highly similar to each other. The images from the conversion of the reconstructed signals are used as the input of the AlexNet model, which is capable of adaptive extraction of leak signal features. The trained AlexNet model can effectively detect different leak apertures. Finally, the signal time-delay between the upstream and downstream pressure transmitters caused by the leak and propagation of negative pressure wave is determined according to generalized cross-correlation analysis, and thereby, the leak location is obtained. The experimental results show that the proposed method is effective for leak detection and location.

Word Formation at the Syntax-Morphology Interface: Denominal Adjectives in Bulgarian

A major goal in the study of the interface between syntax and morphology (understood as part of the PF component) is to understand mismatches between syntactic representations and the corresponding morphological representations. Denominal adjectives in Bulgarian provide one such mismatch. In morphology, they are composed of a nominal component D adjoined to an adjectivizing head F. In syntax, however, the nominal component D behaves like a nominal phrase occupying the specifier of F. Denominal adjectives in Bulgarian thus present both a structural mismatch whereby a syntactic specifier-head relation is mapped to head adjunction at PF and a mismatch between the syntactic and morphological category of denominal adjectives. I analyze these mismatches as the result of a morphological (postsyntactic) operation, which converts nominal phrases into denominal adjectives postsyntactically, as part of the word formation process that combines the nominal phrases with adjectivizing morphology. The proposal is an extension of the theory of the syntax-morphology mapping developed within Distributed Morphology ( Embick and Noyer 2001 , et seq.) on the basis of Marantz’s (1984) Morphological Merger and relies on the implementation of Morphological Merger developed by Harizanov (2014a) in the context of cliticization, itself an elaboration of Matushansky’s (2006) and Nevins’s (2011) proposals.

A New Incipient Fault Diagnosis Method Combining Improved RLS and LMD Algorithm for Rolling Bearings With Strong Background Noise

Aiming at the difficulty of extracting information for incipient fault symptoms from rolling bearings with strong background noise, an improved incipient fault detection method based on modified recursive least squares (RLS) adaptive equalization, and a local mean decomposition (LMD) algorithm is proposed. First, an efficient RLS de-noising model is established by introducing a momentum factor together with a forgotten factor to de-noise the incipient fault signal of the bearings. Then, the LMD algorithm is used to decompose the pre-processed signal to obtain an effective PF component, and complete the envelope demodulation to extract information from the incipient fault. Based on the above algorithm, an improved RLS and LMD identifying algorithm for incipient faults can thus be achieved. Finally, some actual fault signals of a large unit rolling bearing are used to simulate and verify the accuracy and efficiency of the proposed algorithm. The experimental comparison indicated that our algorithm can not only improve the de-noising effect, but also correctly extract the features of the incipient fault and identify them with good engineering operability and expansibility.

Fault Feature Detection of Rolling Bearing Based on LMD and Third-Order Cumulant Diagonal Slice Spectrum

Bearing fault signal presents obvious nonlinear and non-stationary characteristics, and local mean decomposition (LMD) method can adaptively process nonlinear and non-stationary signal. Quadratic phase coupling is one of the commonest nonlinear phenomena, and three-order cumulant diagonal slice spectrum is suitable for the extraction of the frequency components involved in quadratic phase coupling. In order to effectively detect the fault features of rolling bearing, a fault feature detection method of rolling bearing based on LMD and diagonal slice spectrum was proposed in the paper. Diagonal slice spectrum was applied in the extraction of the frequency components involved in quadratic phase coupling from the simulation signal, and it successfully extracted the quadratic phase coupling frequency components of the , and . The method was finally used in the detection of the bearing inner race fault features, and the results demonstrated that compared with diagonal slice spectrum of the PF component signals, the diagonal slice spectrum of the PF component envelope signals can identify fault characteristics much clearer and brighter. Meanwhile, the effective extraction of the inner race fault features verified the effectiveness and practicability of the method proposed in this paper.

Determinant factors of physical fitness in European children.

This study was designed to explore the determinants of physical fitness in European children aged 6-11years, cross-sectionally and longitudinally. There were sufficient data on 4903 children (50.6% girls) on measured physical fitness (cardio-respiratory, muscular strength, flexibility, balance, and speed) and possible determinants related to child characteristics, child lifestyle and parental factors. Multivariate and mixed linear regression models were conducted. Age, sex, children's BMI and physical activity were independent and strong determinants of children's fitness. Significant but small effects were found for low maternal BMI, high psychosocial well-being and fruit and vegetable intake as protective determinants. Sleep duration, breakfast intake, parental age and education and paternal BMI did not have a consistently significant effect on physical fitness. The role of determinants depended on children's sex and the specific PF component. Longitudinal analyses especially highlighted the importance of child's BMI as physical fitness determinant, independent of physical activity. BMI together with physical activity, diet and psychosocial factors are modifiable targets to enhance physical fitness. This calls for policy approaches that combine these factors in a systematic way.

Fault Diagnosis of Wind Turbine Based on ELMD and FCM

In view of failure characteristics of wind turbine gear box, this paper put forward a method for fault diagnosis based on the ensemble local means decomposition (ELMD) and fuzzy C-means clustering (FCM) method. By resolving the vibration signal of different fault state of high speed gear box by ELMD, the PF component was obtained with its singular value, which was composed of known sample followed by a test sample as the feature vector. The known sample was clustered by using the FCM clustering, and the test sample was recognized and classified . The experimental results show that the method for fault diagnosis based on ELMD and FCM clustering has good diagnosis results.

Revisiting the Phonology and Morphosyntax of Chechen and Ingush Verb Doubling

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On Swiping in English

This paper examines the syntax of clauses in which prepositions undergo Swiping/Sluice-Stranding in elliptical questions like Who with? (e.g. in response to ‘She’s having an affair’). We begin by outlining characteristic properties of Swiping, noting that this involves an interrogative wh-constituent positioned in front of a focused preposition, and that the clause remnant following the preposition obligatorily undergoes a type of ellipsis traditionally termed Sluicing. We outline the recent CP shell analysis of Swiping developed by van Craenenbroeck (2010), under which a PP containing a wh-word is moved into the specifier position of an inner CP, the wh-word is moved into the specifier position of an outer CP (stranding the preposition on the edge of the inner CP), and the residual TP is deleted at PF. We discuss a range of problems with his analysis, and argue that it can be substantially improved if we adopt a more richly articulated cartographic structure for the clause periphery under which Swiped clauses contain ForceP, FocP, and FinP projections. More specifically, we argue that the wh-PP moves to the edge of FinP (with the auxiliary moving to Fino in structures involving auxiliary inversion), the preposition moves into Foco to mark it as focused, and the wh-constituent moves into Spec-ForceP to type the clause as interrogative. We claim that the obligatory Sluicing component of Swiping involves ellipsis of FinP in the PF component, and that this is required in order to repair violations of PF constraints which would otherwise arise. We show how our analysis accounts for a range of phenomena not captured under van Craenenbroeck’s original analysis.

Opaque and transparent datives, and how they behave in passives

In this paper, we provide evidence based on case alternations in passives in favor of the view that dative is a mixed case. Dative, but also other cases, has the property of being either inherent/lexical or structural. We propose an analysis of datives aiming to account for their mixed status within and across languages. Building on Řezáč’s (2008) theory of opacity vs. transparency of theta-related case to Agree, combined with a (modified) theory of case alternations in terms of m(orphological)-case (Marantz 1991), we propose that dative arguments are PPs, unlike accusatives which are DPs. Being complements of the phasal head P, dative DPs are invisible to an outside probe, Voice or T, for Agree. Under certain conditions, however, they become visible: either when a φ-probe is present on P probing and transmitting the features of the DP embedded below it or when P incorporates into the Voice-v complex lifting the phase-hood of the PP. We argue that the actual distribution of m-cases in actives and passives of languages with alternating datives is determined at the PF component, subject to the case-realization disjunctive hierarchy proposed by Marantz (1991). A dative argument entering Agree qualifies as having ‘dependent case’ in the sense of Marantz (1991) and not as having lexically governed case. Finally, we propose that cross-linguistic differences concerning the environments where dative alternations happen (passives vs. middles) depend on the head where the φ-probe entering Agree with dative DPs is located: Voice or v.

Research on Fault Diagnosis Theory and Key Technology for Power Machinery

Based on the disadvantages of the original LMD algorithm in terms of smoothing method and end effect, this paper puts forward to a method of diagnosis of rotor system faults based on the improved LMD and singular value decomposition. The PF component obtained after applying the improved LMD method is able to separate the aliasing modes while maintaining the natures and features of the original PF component. Thus, the systems real information can be grasped more effectively. According to the experimental analysis, this method can be applied to diagnosis of rotor system faults effectively.

Locatum Structures and the Acquisition of Telicity

This article presents a study of a between-subjects design experiment on the comprehension of telicity in simple telic predicates (e.g., John filled the bucket) and locatum predicates (e.g., the water filled the bucket) in L1 Spanish. Weist, Wysocka, and Lyytinen (1991) for English and Finnish, and Van Hout (1997, 1998b) for English and Dutch have shown that children up to age 6;06 allow simple telic predicates to have both telic and atelic interpretations. The main objective of this article is to show that children aged 3;09 allow locatum structures to be interpreted as telic, like adults, but allow simple telic predicates to have telic and atelic interpretations. The central claim is that in simple telic predicates, telicity is checked by covert movement, while in locatum predicates, telicity is checked by overt movement. Children misinterpret simple telic predicates because covert movement is an operation that takes place after the branching off to the PF component, but perform like adults when overt movement is involved.