This study proposes a fault diagnosis method (FD) for multistage centrifugal pumps (MCP) using informative ratio principal component analysis (Ir-PCA). To overcome the interference and background ...noise in the vibration signatures (VS) of the centrifugal pump, the fault diagnosis method selects the fault-specific frequency band (FSFB) in the first step. Statistical features in time, frequency, and wavelet domains were extracted from the fault-specific frequency band. In the second step, all of the extracted features were combined into a single feature vector called a multi-domain feature pool (MDFP). The multi-domain feature pool results in a larger dimension; furthermore, not all of the features are best for representing the centrifugal pump condition and can affect the condition classification accuracy of the classifier. To obtain discriminant features with low dimensions, this paper introduces a novel informative ratio principal component analysis in the third step. The technique first assesses the feature informativeness towards the fault by calculating the informative ratio between the feature within the class scatteredness and between-class distance. To obtain a discriminant set of features with reduced dimensions, principal component analysis was applied to the features with a high informative ratio. The combination of informative ratio-based feature assessment and principal component analysis forms the novel informative ratio principal component analysis. The new set of discriminant features obtained from the novel technique are then provided to the K-nearest neighbor (K-NN) condition classifier for multistage centrifugal pump condition classification. The proposed method outperformed existing state-of-the-art methods in terms of fault classification accuracy.
Nanofiber‐based products are widely used in the fields of public health, air/water filtration, energy storage, etc. The demand for nonwoven products is rapidly increasing especially after COVID‐19 ...pandemic. Electrospinning is the most popular technology to produce nanofiber‐based products from various kinds of materials in bench and commercial scales. While centrifugal spinning and electro‐centrifugal spinning are considered to be the other two well‐known technologies to fabricate nanofibers. However, their developments are restricted mainly due to the unnormalized spinning devices and spinning principles. High solution concentration and high production efficiency are the two main strengths of centrifugal spinning, but beaded fibers can be formed easily due to air perturbation or device vibration. Electro‐centrifugal spinning is formed by introducing a high voltage electrostatic field into the centrifugal spinning system, which suppresses the formation of beaded fibers and results in producing elegant nanofibers. It is believed that electrospinning can be replaced by electro‐centrifugal spinning in some specific application areas. This article gives an overview on the existing devices and the crucial processing parameters of these nanofiber technologies, also constructive suggestions are proposed to facilitate the development of centrifugal and electro‐centrifugal spinning.
This review article forces on discussing the differences and relationships of three nanofiber technologies—electrospinning, centrifugal spinning, and electro‐centrifugal spinning. It mainly summarizes the existing devices and crucial processing parameters. The electro‐centrifugal spinning combines the strengths of electrospinning and centrifugal spinning, showing potentials in processing elegant nanofibers in large scale.
This paper presents a novel framework for classifying ongoing conditions in centrifugal pumps based on signal processing and deep learning techniques. First, vibration signals are acquired from the ...centrifugal pump. The acquired vibration signals are heavily affected by macrostructural vibration noise. To overcome the influence of noise, pre-processing techniques are employed on the vibration signal, and a fault-specific frequency band is chosen. The Stockwell transform (S-transform) is then applied to this band, yielding S-transform scalograms that depict energy fluctuations across different frequencies and time scales, represented by color intensity variations. Nevertheless, the accuracy of these scalograms can be compromised by the presence of interference noise. To address this concern, an additional step involving the Sobel filter is applied to the S-transform scalograms, resulting in the generation of novel SobelEdge scalograms. These SobelEdge scalograms aim to enhance the clarity and discriminative features of fault-related information while minimizing the impact of interference noise. The novel scalograms heighten energy variation in the S-transform scalograms by detecting the edges where color intensities change. These new scalograms are then provided to a convolutional neural network (CNN) for the fault classification of centrifugal pumps. The centrifugal pump fault classification capability of the proposed method outperformed state-of-the-art reference methods.
•A unified analytical model for centrifugal softening and stiffening harvesters is proposed.•The influence mechanism of centrifugal effects is analytically analyzed.•The analytical model is ...experimentally validated.•Case studies are conducted to comprehensively compare two types of harvesters.
Depending on its mounting orientation, the rotational piezoelectric harvester can be subjected to the centrifugal softening or stiffening effects, which may pose a positive or negative influence on the energy harvesting performance. This paper firstly presents the comprehensive comparison of the centrifugal softening and stiffening harvesters with a unified dimensionless analytical model. The analytical expressions of the optimum short-circuit and open-circuit rotational frequencies, the optimum resistances and the optimum centrifugal coefficients are derived to reveal the influence mechanism of the centrifugal effects. The proposed model is validated experimentally and used for case studies to compare the centrifugal softening and stiffening harvesters. Results illustrate that the centrifugal softening harvester has a superior energy harvesting performance at low rotational frequencies while the centrifugal stiffening harvester is better at high rotational frequencies. Furthermore, the peak power of the centrifugal softening harvester is higher while the frequency bandwidth of the centrifugal stiffening harvester is wider. In addition, it is found that the centrifugal stiffening harvester is more sensitive to the centrifugal coefficient. Based on the centrifugal stiffening effect, the self-tuning harvester can be achieved with a wide frequency bandwidth. Meanwhile, this requires that the centrifugal coefficient is precisely determined, and the fundamental natural frequency of the harvester without the centrifugal force should be low enough when operating at low rotational frequencies. Compared with the centrifugal stiffening effect, the centrifugal softening effect may be more suitable to be used in MEMS/NEMS applications since it can reduce the fundamental resonant frequency of the harvester during the rotation.
Ultrathin, lightweight, high‐strength, and thermally conductive electromagnetic interference (EMI) shielding materials with high shielding effectiveness (SE) are highly desired for next‐generation ...portable and wearable electronics. Pristine graphene (PG) has a great potential to meet all the above requirements, but the poor processability of PG nanosheets hinders its applications. Here, efficient synthesis of highly aligned laminated PG films and nacre‐like PG/polymer composites with a superhigh PG loading up to 90 wt% by a scanning centrifugal casting method is reported. Due to the PG‐nanosheets‐alignment‐induced high electrical conductivity and multiple internal reflections, such films show superhigh EMI SE comparable to the reported best synthetic material, MXene films, at an ultralow thickness. An EMI SE of 93 dB is obtained for the PG film at a thickness of ≈100 µm, and 63 dB is achieved for the PG/polyimide composite film at a thickness of ≈60 µm. Furthermore, such PG‐nanosheets‐based films show much higher mechanical strength (up to 145 MPa) and thermal conductivity (up to 190 W m−1 K−1) than those of their MXene counterparts. These excellent comprehensive properties, along with ease of mass production, pave the way for practical applications of PG nanosheets in EMI shielding.
Highly aligned freestanding laminated graphene films and nacre‐like graphene/polymer composite films are synthesized by scanning centrifugal casting. Due to the graphene‐alignment‐induced high electrical conductivity and multiple internal reflections, the films show superhigh electromagnetic‐interference‐shielding performance, comparable to the reported best synthetic material, MXene films, at ultralow thickness, along with much better mechanical strength and thermal conductivity.
•A SCO2 simple regenerative Brayton cycle used in SLFR is proposed.•One-dimensional analysis code is developed to design SCO2 compressor.•Optimization is implemented to improve isentropic efficiency ...using 1D code.•Optimization is conducted on impeller blade through three-dimensional CFD.
This paper dedicates to develop a systematic approach of design and multi-dimensional performance optimization of the Supercritical carbon dioxide (SCO2) compressor. A 5 MW SCO2 simple regenerative cycle used in small scale lead-cooled fast reactor (SLFR) was firstly proposed and simulated to define the operation condition of SCO2 compressor. Under the inlet and outlet condition of 305.15 K/7.56 MPa and 22 MPa, isentropic efficiency and mass flow rate of 80% and 69.88 kg·s−1 respectively was obtained. Secondly, a single stage centrifugal compressor was applied as the SCO2 compressor and one-dimensional (1D) design based on self-developed code was conducted to determine the basic geometry of the compressor, the code was verified with experiments and shows satisfactory accuracy. Additionally, CFD analysis was carried out to validate the results of 1D design and also shows good agreement. Then, three one-dimensional optimizations, two single objective optimizations using Particle Swarm Optimization (PSO) and one multi-objective optimization using Genetic Algorithm (GA), on aerodynamic efficiency of the SCO2 centrifugal compressor were performed based on 1D design code, five crucial parameters with ± 5% variation range were optimized. The 1D optimization results show that the isentropic efficiency received an improvement of about 5 percentage points compared to that of 1D design. Lastly, three-dimensional optimization concentrated on the blade profile of impeller were conducted on a fully automatic optimization platform to further improve the isentropic efficiency of SCO2 centrifugal compressor. Wrap angle and the leading and trailing edge of the main blade were optimized. Two optimal impellers with wrap angle in the range of + 5% and −5% were obtained respectively, the former impeller got the highest pressure ratio, while the latter one gained a higher isentropic efficiency but the lowest pressure ratio over the whole operation range.
The effects of polyvinylidene fluoride (PVDF) wt. % and electric fields on the production of PVDF fibers using a novel centrifugal electrospinning design were investigated. High-quality, bead-free ...fibers with diameter of (0.55 ± 0.04) μm were successfully produced. Fibers with exceptionally high β-phase content of 96.1 % and piezoelectric coefficient, d33 of (−157 ± 5) pC N−1 were obtained using PVDF amount and electric field of 14.0 wt % and 400 V cm−1, respectively. Under 3.0 N repetitive vertical forces, the fabricated piezoelectric nanogenerator (PENG) exhibited impressive open-circuit voltage, short-circuit current and power density of (32.6 ± 0.7) V, (3.26 ± 0.07) μA and (15.4 ± 0.6) μW cm⁻2, respectively. The production of high and well aligned β-phase in the fibers indicated by good d33 values are the likely reasons for the excellent performance of the PENG. Ultimately, potential of the fabricated PENG as a self-power supply for low-energy electronic devices was demonstrated.
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•A novel design for centrifugal electrospinning to efficiently produce PVDF fibres.•The success of using a low electrical field to enhance the beta-phase content in PVDF fibres.•High Voc signal generated using a PVDF fibre-based PENG.•The potential for replacing lead-based PENGs with fibre-based PENGs as a power supply for low-energy electronics.
Air pollution containing microorganisms poses a major hazard to human health. It is critical to develop air filters that are both highly efficient for indoor use and suitable for use in industrial ...settings. Developing long‐lasting electrostatic force‐assisted filtration while keeping high‐temperature resistance and antibacterial qualities is still challenging. Here, centrifugal spinning is used to fabricate fiber mats consisting of polyimide with silver incorporation (PI/Ag). The electrostatic force remained over –700 V after 330 days. The strong electrostatic effect improves the filtration efficiency, resulting in a high PM0.3 removal efficiency of 99.1% with a low‐pressure drop of 103.67 Pa. The high filtration efficiency remains above 91.3% for PM0.3 after placing it for 330 days and heating it at 280 °C. The PI/Ag fiber mats also show antimicrobial properties against the E. coli (Gram‐negative) and S. aureus (Gram‐positive) with prominent bacteriostatic zones >1.2 mm. The PI/Ag fiber mat filters are expected to have great potential for multi‐scenario air filtration.
A heat‐resistant, self‐sustained electrostatic, and antibacterial polyimide/silver fiber mat is developed for both indoor and industrial outdoor air filtration. The network structure and the strong and self‐sustained electrostatic effect formed during centrifugal spinning ensure high filtration efficiency. The high‐temperature resistance of polyimide enables to filtration of high‐temperature outdoor PM resources.
•A novel method is proposed to diagnose faults in a pump based on vibration data.•A stochastic realization algorithm is used to extract features to diagnose faults.•Two different classification ...algorithms are proposed to diagnose the faults.•Incipient faults could be diagnosed with the proposed method.•The data is obtained with a low-cost accelerometer developed by the authors.
One of the strategies to detect and classify faults in mechanical systems is to use a time domain family of techniques known as output-only methods. Those methods are based on the analysis of sample covariance matrices, which are estimated from vibration data extracted from mechanical systems under unmeasured natural excitation. Using the stochastic realization theory, it is possible to derive Markov parameters from sample covariance matrices. Those parameters contain only the significant spectral components from data. In this paper, a novel output-only method based on the Markov parameters is proposed to diagnose faults. The idea is to use the Markov parameters estimated from vibration data as features in classification algorithms based on convex optimization. The method was applied to diagnose incipient cavitation failures in a water supply network centrifugal pump. A low-cost triaxial vibration sensor developed by one of the authors was used to register the vibration data. The proposed method was compared to the analysis based on sample covariance matrices demonstrating the advantages related to the use of the Markov parameters.
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