Resonant Frequency Band Research Articles

Iterative singular value decomposition-based in-band denoising approach with envelope order analysis for sun gear fault diagnosis of planetary system under varying speed

The vibration signal of the planetary gear train is easily disturbed by the background noise, so the measured signal is complicated. In order to accurately extract the fault features, the resonance method has been widely used. However, even if the optimal resonance frequency band is found, the in-band noise still exists, so it is necessary to study an effective in-band denoising method. In this paper, an in-band denoising method based on Iterative Singular Value Decomposition (ISVD) is proposed for the fault diagnosis of the secondary sun gear of a planetary gear train, combined with the envelope order spectrum analysis. This method uses the enhanced Wavelet Packet Transform Spectral Kurtosis (WPTSK) to determine the best frequency band for the signal, and uses the ISVD method to realize the signal denoising. It sets a threshold to avoid the destruction of the useful information caused by the excessive iteration, and uses the relationship between the singular values and frequency components to reconstruct the denoised signal. Finally, the signal is converted to the fault characteristic order domain by resampling to identify the fault type of the sun gear from the envelope order spectrum. The simulation and experimental results show that compared with the Empirical Mode Decomposition (EMD) and Variational Mode Decomposition (VMD), the ISVD can effectively suppress the in-band noise and more accurately extract the fault characteristic order of the secondary sun gear under varying speed.

Terahertz metamaterial-induced multiple transparency windows through bright-bright mode couplings

Metamaterials that offer optical control over multiple transparency windows have paved the way for advancements in terahertz (THz) modulation technology. In this paper, we have conducted a systematic investigation into the interaction between THz waves and “bright” split-ring resonators (SRRs). Through manipulation of the quantity and spatial arrangement of SRRs within metamaterial structures, we have successfully induced multiple transparency windows within the THz spectrum. Furthermore, we have explored the transmitted switching ratio of both the designed single transparency window and double resonance frequency bands as a function of the azimuthal angle of the THz wave. This work offers a general strategy for designing the number of electromagnetically induced transparency windows and holds the potential for realizing multichannel memories.

Изучение принципов построения широкополосной колебательной СВЧ системы на примере резонатора Фабри-Перо

In telecommunications and radar systems of the centimeter and millimeter wave ranges, span klystrons are widely used as medium and high power amplifiers. The use of high-quality resonators makes it possible to realize high efficiency and amplification factors. However, typical designs of 2 - 4 resonator klystrons have a bandwidth of 0.1 - 0.5 % due to the need to use resonators with a high Q – factor. The well-known method of expanding the amplified frequency band in the centimeter range up to 7 – 12 % and in the millimeter range up to 1 - 2 % consists in tuning the frequency of the intermediate klystron resonators by several percent of the central amplification frequency. But in this case, it is required to use 10 - 12 resonators. The authors of the work discovered that when a millimeter range electromagnetic wave is reflected from an electrodynamics system in the form of a metal film on the surface of a semiconductor layer, the input resistance phase-frequency characteristic of this system consists of a chain of frequency intervals with turnings from a positive phase-frequency characteristic to a negative one and vice versa. The possibility of constructing a phase shifter with a negative phase frequency response based on this phenomenon is demonstrated and its application for expanding the resonant frequency band is considered on the example of the Fabry - Perot interferometer model. This resonator contains a phase shifter in the form of a semiconductor layer F with a thickness DF, a conductivity σF, a relative dielectric eF and a magnetic mF permeability. The outer surface of the layer F contains a metal mirror, and the inner surface is adjacent to the layer W. The layer W which has the thickness of DW, eW, mW forms the internal space of the resonator. The external environment I with mI and eI. adjoins the layer W. A plane electromagnetic wave propagates in I media so that it excites the resonator at a wavelength of l0. The use of a phase shifter makes it possible to increase the resonant wavelength band Δl/l0 by 2 - 4 times and with an electromagnetic field amplification coefficient |G(l)| in the W layer by 10 - 20 times (the value of Dl/l0 corresponds to 0.707 max |G(l0)|). An increase of σF leads to an amplitude-frequency characteristic transforming of the field gain function G(l0) from two maxima to one maximum form with a transition through a flat top. In this case max |G(l0)| decreases and Dl/l0 increases. For the case, when the function |G(l)| has a flat top, an increase in the wave resistance ρW of the layer W with a corresponding decrease in sF and optimal values of DW leads to an increase in |G(l0)|. When this occurs, Dl/l0 becomes lower.

Miniaturized and high gain circularly slotted 4×4 MIMO antenna with diversity performance analysis for 5G/Wi-Fi/WLAN wireless communication applications

A miniaturized with a high gain four port Multiple-Input Multiple-Output (MIMO) is presented in the manuscript. The presented design contains four radiating patch elements with a Defected Ground Structure (DGS). The shape of the radiating element is identified after the analysis of three stages. The design optimization is performed by changing the diameter of the circle loaded in the patch region and changing the length of the ground layer. The design is investigated for L, S, C, and X frequency band regions. The structure is designed using flame-retardant glass-reinforced epoxy laminate material (FR4) substrate material. The physical size of the four-port structure is 78x50 mm2. Three resonating frequency bands are observed at 2.02 GHz, 5.87 GHz and 11.19 GHz. The structure provides minimum return loss of −10.27 dB, −18.51 dB and −18.59 dB. The proposed design achieves a peak bandwidth of 3.94 GHz, and a maximum gain of 10.03 dBi, Various diversity parameters, including Total active reflection coefficient (TARC), Envelope Correlation Coefficient (ECC), mean effective gain (MEG), Diversity Gain (DG), and channel capacity loss (CCL), have been thoroughly analyzed. The measured and simulated outcomes are compared and analyzed. All performance indicators meet the allowed limits, demonstrating the suitability of the design for 5G, Wi-Fi and WLAN wireless communication applications.

A triboelectric nanogenerator based on bionic design for harvesting energy from low-frequency vibration

With the development of Internet of Things and the increase of wearable devices, the infinite self-power supply of small devices such as wireless sensors and portable devices has been widely concerned. Considering that the vibration energy in the environment is not affected by day and night, season and climate, and widely distributed, its mechanical energy can be collected. If the low-frequency and small amplitude vibration energy in the environment can be collected and converted into electric energy, it will provide a reliable solution for the self-power supply of these small devices. In this study, we designed a miniaturized energy harvester inspired by bionics. The resonance mechanism improved by nonlinearity is used to realize the amplification of vibration in low width frequency band. And triboelectric nanogenerator (TENG) is used to convert mechanical energy into electrical energy. Through the modeling and dynamic analysis of the system, we find a low resonance frequency band as the working range of the system. Subsequently, a prototype of the bird legs-type TENG was fabricated and tested to verify the design concept. We verify the ability of the prototype to amplify low-frequency vibration and optimized the structural parameters. Moreover, we demonstrate the excellent electrical output performance of the prototype in low-frequency and small external excitation environment and give two application prospects of wearable prototype and vehicle-mounted prototype.

A 28/32/38 GHz Circularly Polarized DRA Micro-strip Antenna for 5G mm-Wave Applications

In modern communication system, mobile communication spectrum, below 3 GHz bands, faces more shortage and is not able to serve people with more efficient device connectivity and required data speed. Upon this background, 5G wireless communication – the 5th generation mobile technology standards are able to deliver high data rates, low latency communications, and massive device connectivity. For the efficient deployment of the 5G systems, and in order to support higher bandwidth, there is a dire need to design a compact and efficient antenna at mm wave frequencies (26/28 and 38). The resulting antenna, as the outcome, has been established to possess a compact size of 10 × 12 × 0.254 mm3 that covers three bands from the frequency spectra. The lower band resonant frequency is located at 26.74 GHz, the range between 25.44 GHz and 28.37 GHz, the middle band resonant frequency is located at 32 GHz, the range between of 31.08 GHz and 32.48 GHz, and the higher resonant frequency is located at 38.76 GHz, the range between 36.04 GHz and 40.34 GHz. In this article a modified novel structure of partial ground plane and DRA are used to get the better radiation enhancement and circular polarization. In this, the circularly polarized bands consist of the axial ratios <3 dB which are 27.95 GHz to 28.37 GHz, 31.08 GHz to 31.67 GHz, and 36.04 GHz to 38.73 GHz. The gain achieved is greater than 6.5 dBi and the efficiency is greater than 96% over the three bands. Ultimately, it is proved to the right option for 5G mm wave applications.

An electrical impedance matching method of dual-frequency transducers for ultrasound internal imaging

A micro single transducer with two resonant frequencies can solve the inherent contradiction between detection depth and resolution by simultaneously emitting two frequency bands of ultrasonic waves. But the difference of impedance values in the two resonant frequency bands seriously affects dual-frequency echo signal efficiency. In order to improve the quality of transducer sensitivity, a dual-frequency electrical impedance matching method is proposed in the study. By selecting a specific matching structure to match one frequency without messing up the impedance of another frequency, the two frequencies can be designed independently to achieve preliminary impedance matching. The matching networks for single frequency are combined to form a complete dual-frequency matching circuit, and adjust the initial matching value to obtain a suitable matching state. The performances of the matching network have been tested and verified by experiments. After matching, the low-frequency and high-frequency sensitivities of the transducer increased 1.86 times and 2.26 times, respectively. In addition, system noise was also reduced by 29.6% after adding the matching network. The results demonstrate that this dual-frequency matching network can simultaneously increase the amplitude of high-frequency and low-frequency echoes to obtain better quality images.

Resampling Technique-Based Demodulation Analysis for Planet Bearing Cage Fault Diagnosis Under Nonstationary Conditions

Vibration signals of the planetary transmission system usually contain excitation responses from different structures. The fault characteristic of the planet bearing cage is weak, which is often overwhelmed by strong noise and other irrelevant vibration components. Therefore, fault feature extraction of the planet bearing cage is a challenging topic. In this paper, a novel fault feature extraction method is proposed to extract weak fault features of the planet bearing cage. The general parameterized time-frequency transform is employed to accurately extract instantaneous rotational speed information from the planet bearing vibration signal for resampling. It can obtain the accurate rotational speed result even though under power frequency interference conditions. The influence of the deterministic components excited by the gear can be reduced by using the spectral pre-whitening and the interference of noise and random impact can be reduced in the selection of the optimal resonance frequency band by using autogram analysis. The fault characteristic components of the planet bearing cage can be extracted from the square envelop spectrum. The neighborhood power density ratio index is further constructed to distinguish the health bearing state from the cage fault bearing state and evaluate the degree of faults. Experiments designed in a planetary transmission system test rig of an armored vehicle have verified the potential and effectiveness of the proposed fault feature extraction method in exhibiting planet bearing cage fault features.

Design and validation of frequency reconfigurable multiband antenna using varied current distribution method

Modern communication technologies require systems that can function at a wide range of frequencies, with diversity of radiation patterns, and with different types of polarization. In communication systems, the antenna serves as a filter; hence the ability to reconfigure the antenna is essential. The performance and design of a frequency band reconfigurable antenna are discussed in the paper, along with a comparison of the outputs of simulated and the fabricated design. Three PIN diodes are utilized to switch between various frequency bands. To increase selectivity, two ring resonators were added to the antenna's ground structure. As the current distribution changes in various switching instances, it is seen that the antenna operates at various resonant frequency bands. Connecting the diodes would change the current and field distribution in the chip design and thus change the resonant frequency. The antenna structure was designed and obtained results using High Frequency Simulation Structure (HFSS) software. The simulated and fabricated antenna is found to be operating in S band (2–4 GHz) and C (4–8 GHz) band of IEEE frequency bands with a gain in the range of 2.59 dB–9.54 dB. Typically the antenna resonates at various frequencies specifically, 2.38 GHz, 2.48 GHz, 3.98 GHz, 4 GHz, 4.45 GHz, 6.99 GHz, 7.2 GHz, 8.25 GHz. Under different switching cases of the diodes, the antenna is found to be radiating in different frequency ranges. By switching the PIN diodes under different cases, the current distribution path can be altered and as result of it, the antenna operates at variable frequencies.

Validating a Physics-Based Automatic Classification Scheme for Impact Echo Signals on Data Using a Concrete Slab with Known Defects

Impact echo (IE) is capable of locating subsurface defects in concrete slabs from the vibrational response of the slab to a mechanical impact. For an intact slab (“good” condition), the frequency spectrum of the IE is dominated by a single peak corresponding to the slab’s “thickness resonance frequency,” whereas the presence of subsurface defects (“fair” or “poor” conditions) could manifest in various ways such as multiple distinct peaks at frequencies higher, or lower, than the thickness resonance. In previous research, the authors have proposed a frequency partitioning of the spectrum for IE signal classification. Firstly, the thickness resonance frequency band is identified using a data-driven approach and then the IE signals are represented by their energy distribution in three bands—frequencies less than, within, and greater than the thickness resonance. Following this feature extraction, an unsupervised clustering approach is used to identify the centroids for each signal class—good, fair, and poor—which are further used to classify any test signal into one of the three aforementioned classes. The classification is developed by training on unlabeled IE signals from real bridge deck data (the Federal Highway Administration’s [FHWA’s] InfoBridge dataset) without making use of any labeled data. This study aims to validate the proposed methodology on a labeled dataset of eight reinforced concrete specimens constructed at the FHWA Advanced Sensing Technology Nondestructive Evaluation laboratory having known artificial defects. Our findings indicate that the physics-based feature definition and the method developed on real bridge data are robust and can classify IE signals in the labeled data with moderate accuracy.

Adaptive linear quadratic regulator for optimal structural control based on wavelet transform and genetic algorithm

PurposeIn real life, excitations are highly non-stationary in frequency and amplitude, which easily induces resonant vibration to structural responses. Conventional control algorithms in this case cannot guarantee cost-effective control effort and efficient structural response alleviation. To this end, this paper proposes a novel adaptive linear quadratic regulator (LQR) by integrating wavelet transform and genetic algorithm (GA).Design/methodology/approachIn each time interval, multiresolution analysis of real-time structural responses returns filtered time signals dominated by different frequency bands. Minimization of cost function in each frequency band obtains control law and gain matrix that depend on temporal-frequency band, so suppressing resonance-induced filtered response signal can be directly achieved by regulating gain matrix in the temporal-frequency band, leading to emphasizing cost-function weights on control and state. To efficiently subdivide gain matrices in resonant and normal frequency bands, the cost-function weights are optimized by a developed procedure associated to genetic algorithm. Single-degree-of-freedom (SDOF) and multi-degree-of-freedom (MDOF) structures subjected to near- and far-fault ground motions are studied.FindingsResonant band requires a larger control force than non-resonant band to decay resonance-induced peak responses. The time-varying cost-function weights generate control force more cost-effective than time-invariant ones. The scheme outperforms existing control algorithms and attains the trade-off between response suppression and control force under non-stationary excitations.Originality/valueProposed control law allocates control force amounts depending upon resonant or non-resonant band in each time interval. Cost-function weights and wavelet decomposition level are formulated in an elegant manner. Genetic algorithm-based optimization cost-efficiently results in minimizing structural responses.

An Equivalent Differential Method for Active Damping of LCL Type Grid-Connected Inverters With Grid-Side Inductor Voltage Feedback

The differential feedback of grid-side inductor voltage can effectively increase the damping of grid-connected inverters. Compared with proportional feedback of filter capacitor current, it can increase the output impedance of the grid-connected inverters, which is more conducive to reducing the impact of grid background harmonics on the grid-in current. However, there is a differential link in its damping branch, and existing differential implementation methods were pursuing to be ideal differential in wide frequency band, as a consequence, high frequency components of the grid-side inductor voltage are amplified, which affects the quality of grid-in current. For this reason, this paper proposes a band-pass filter in series with a lead compensation unit to replace the ideal differential. The major advantage different from the conventional methods is that the proposed strategy is only equivalent to the ideal differential around the resonance frequency band. Specifically, it features lower gain at low and high frequency bands. Finally, theoretical analysis and experiment results show that the proposed strategy can reduce the influence of the added damping path on the fundamental component of grid-in current and features better suppression effect on the harmonics.

Rolling Bearing Composite Fault Diagnosis Method Based on Enhanced Harmonic Vector Analysis.

Composite fault diagnosis of rolling bearings is very challenging work, especially when the characteristic frequency ranges of different fault types overlap. To solve this problem, an enhanced harmonic vector analysis (EHVA) method was proposed. Firstly, the wavelet threshold (WT) denoising method is used to denoise the collected vibration signals to reduce the influence of noise. Next, harmonic vector analysis (HVA) is used to remove the convolution effect of the signal transmission path, and blind separation of fault signals is carried out. The cepstrum threshold is used in HVA to enhance the harmonic structure of the signal, and a Wiener-like mask will be constructed to make the separated signals more independent in each iteration. Then, the backward projection technique is used to align the frequency scale of the separated signals, and each fault signal can be obtained from composite fault diagnosis signals. Finally, to make the fault characteristics more prominent, a kurtogram was used to find the resonant frequency band of the separated signals by calculating its spectral kurtosis. Semi-physical simulation experiments are conducted using the rolling bearing fault experiment data to verify the effectiveness of the proposed method. The results show that the proposed method, EHVA, can effectively extract the composite faults of rolling bearings. Compared to fast independent component analysis (FICA) and traditional HVA, EHVA improves separation accuracy, enhances fault characteristics, and has higher accuracy and efficiency compared to fast multichannel blind deconvolution (FMBD).

Automated Bayesian operational modal analysis of the long-span bridge using machine-learning algorithms

The Bayesian Operational Modal Analysis (OMA) approach can both estimate the most probable value (MPV) of modal parameters and swiftly give identification uncertainty. However, the determination of certain parameters shall still require the expertise of professionals and process is labor-intensive. In light of the massively available data from the in-situ structural health monitoring (SHM) system of the long-span bridge, the proposal and development of an automated strategy for identifying and tracking varying bridge modal parameters are much desired. A novel machine-learning-based framework is proposed to automatically estimate the parameters required for the Bayesian OMA. The major contributions of the proposed method are: (i) The cross-modal assurance criterion (CMAC) matrix is proposed and adopted to obtain the correlation between the target modes from a global perspective. It is reconstructed using the convolutional autoencoder (CAE) to remove the embedded noise information and the modal resonant frequency band can be detected, and (ii) The Kohonen network is used to automatically determine the number of target modes by clustering the normalized singular value (SV) sequence. Collected data from numerical simulation and a full-scale long-span suspension bridge are adopted to validate the proposed framework. Results show that the proposed framework can successfully estimate the required parameters from the raw data in an automated manner. This feature transforms the conventional Bayesian OMA into an automated strategy for identifying and tracking the modal parameters of the long-span bridge.

A fault diagnosis method for variable speed gearbox bearing based on SET improved multi-source ridge line

Due to the noise interference and frequency ambiguity of gearbox vibration signal under variable speed, the traditional instantaneous frequency estimation method is prone to frequency mutation and low ridge line fusion accuracy. This paper proposes an improved method of extracting multi-source time–frequency ridge lines based on time–frequency analysis by exploring the relationship between the vibration signal of the gearbox without a tachometer and the fluctuation law of the bearing rotation frequency. In the proposed method, the Variable Mode Decomposition (VMD) filter and Synchroextracting Transform (SET) are first used to analyze the time frequency of the gearbox vibration signal. Secondly, the local peak search algorithm obtains multiple time–frequency ridge lines from low-frequency and high-frequency resonance frequency bands. Thirdly, the synchronization process is carried out based on the maximum energy spectrum in the time spectrum. The multi-source ridge line extraction algorithm is improved with reduced frequency mutation and optimized ridge line fusion accuracy. Finally, the optimized speed curve is used to track the vibration signal order of the gearbox. The bearing fault characteristic order is obtained from the angular order spectrum, and the effectiveness of the proposed method is verified by the simulation and the experiment.

DESIGN AND ANALYSIS OF MULTI-BAND COMPACT MICROSTRIP ANTENNA IN GSM1900/WLAN/WiMAX/DSRC/X-BAND FREQUENCY BANDS FOR VEHICLE APPLICATIONS

This study focuses the design and analysis of a compact, multi-band microstrip patch antenna for wireless communications operations. The design antenna exhibits distinct quad resonance frequency bands I from 1.879 GHz to 1.986 GHz, II from 3.1 GHz to 3.87 GHz, and III from 4.97 GHz to 6.515 GHz, IV from 7.26 GHz to 8.6 GHz, which covers GSM 1.900 GHz, WLAN (5.2/5.8 GHz), DSRC 5.9 GHz and WiMAX (3.5/5.5 GHz) bands. In addition, it can also support the X-band from 7.26 to 8.6 GHz. The antenna is designed on an inexpensive substrate of FR4 with dimensions of 36(L) × 25(W) mm2 and consists of two branches of curved strips for a quad-band response. The antenna is designed and analyzed using electromagnetic 3D computer simulation software. The designed antenna can provide advantages in GSM/WLAN/WiMAX/DSRC/X-band satellite applications for vehicle communication with four resonant frequency bands, nearly omnidirectional radiation characteristics, and acceptable gain.

Fault tracing of gear systems: An in-situ measurement-based transfer path analysis method

A transfer path analysis method based on the in-situ measurement is proposed for the fault tracing of parallel axis gear systems. A virtual decoupling technique is used to achieve the in-situ measurement of the decoupled frequency response function (FRF) between bearing positions and measuring points on housing, avoiding the tedious test procedure and non-representative assembly conditions caused by the physical decoupling. Based on the decoupled FRF and the responses of the gearbox housing, the bearing force is identified using the Tikhonov regularization theory. Then the frequency-dependent path contribution, which will be used to perform the transfer path analysis, is obtained by multiplying the decoupled FRF and the bearing force. Finally, the fault-specific path rank order is determined using the path contribution within the resonant frequency band. This band is located by the spectral kurtosis algorithm. Based on the proposed in-situ path analysis, fault tracing is conducted by determining the dominant transfer path. The effectiveness of the proposed path analysis method is verified both numerically and experimentally. A two-stage parallel axis gear test rig with localized defects is utilized to demonstrate the efficacy of the proposed fault tracing strategy. Moreover, based on the path analysis, a physically-interpretable signal decomposition method is proposed to enhance the fault feature. Through this decomposition method, the fault indicator of the weakest fault type (chipped tooth) can be magnified by 204%. The proposed transfer path analysis method provides a feasible strategy for fault tracing, feature enhancement and incipient fault diagnosis of parallel axis gear systems.

Design and Modeling of Piezoelectric-AlN-based Acoustic Sensor for Sound Pressure Level Measurements

This paper illustrates the design of a piezoelectric acoustic sensor based on AlN to be used for aero-acoustic measurements. A significant prerequisite for such sensors is a large sound pressure level (SPL) and flat frequency response in the auditory band (20 Hz to 20 kHz). That is why this sensor has been designed to measure upto an SPL of 180 dB. The design of the device has been achieved through the MEMS-CAD tool Coventorware. The Si-diaphragm thickness has been optimized for the desired SPL range using Coventorware for three different sizes of the device, namely 1.5 mm × 1.5 mm, 1.75 mm × 1.75 mm and 2 mm × 2 mm. The cavity developed after the diaphragm formation is connected to the exterior environment through a microchannel. The microchannel was designed for low cut-off frequency. The complete frequency response of all the three sensor structures has been determined. Moreover, a comparison has been drawn among the three devices in terms of parameters such as low cut-off frequency, resonance frequency, and sensitivity to find the optimized device size. The low cut-off frequency, resonance frequency, and flat band sensitivity of the optimized device are 35 Hz, 83 kHz, and 170 µV/Pa, respectively. In addition to this, a proposed fabrication process flow of the device has been presented.

Polynomial fitting detrended autocorrelation kurtosis of 1.5D spectrum and its application in bearing fault feature extraction

Kurtogram is a typical fault diagnosis algorithm, and its derivative methods are widely used in bearing fault signal processing. The key to such methods is to select the indexes that are specifically sensitive to periodic fault characteristics. The traditional time domain kurtosis index is too sensitive to non-periodic transient impulses, and the frequency domain index is too sensitive to harmonic components, which seriously affects the selection of resonance frequency band and the extraction of fault features. In view of this, a polynomial detrended autocorrelation kurtosis of 1.5D spectrum is proposed in this paper. Firstly, the original signal is decomposed by wavelet packet decomposition, and the 1.5D spectrum of each subband signal is calculated. Then, the 1.5D spectral autocorrelation coefficient of each subband is calculated, and the trend term is removed from the specific interval of autocorrelation coefficient by polynomial fitting. Finally, the kurtosis of the autocorrelation coefficient after removing the trend term is calculated to select the optimal resonance frequency band for analysis, so as to extract the fault feature information. The experimental data show that this method is sensitive to the fault characteristic frequency and frequency doubling with coupling relationship, and can suppress non-periodic transient impulse and harmonic interference.

Fault feature extraction method of pump data sample under strong impact and strong noise environment

The condition monitoring and fault diagnosis of pump stations are essential to ensure the normal operation of pump stations. This work monitors the vibration, swing, pressure pulsation, noise, speed of the pump unit in the steady and transient operation process and diagnoses the equipment state to judge the safety and health of the unit. The fault feature extraction method suitable for the environment of strong impact and strong noise is studied. The frequency band segmentation, accuracy chart to determine the resonance frequency band and the maximum correlation kurtosis deconvolution method are used to enhance the fault feature. Finally, the data measured are sampled and selected, and the kurtosis of the system software is measured the skewness and other indicators are compared with the indicators of handheld analysis and measurement data. The total accuracy rate of data collected by the system software reaches 98.22%.