Wireless Self-Powered Vibration Sensor System for Intelligent Spindle Monitoring

In recent years,high-end equipment is widely used in industry and the accuracy requirements of the equipment have been risen year by year.During the machining process,the high-end equipment failure may have a great impact on the product quality.It is necessary to monitor the status of equipment and to predict fault diagnosis.At present,most of the condition monitoring devices for mechanical equipment have problems of large size,low precision and low energy utilization.A wireless self-powered intelligent spindle vibration acceleration sensor system based on piezoelectric energy harvesting is proposed.Based on rotor sensing technology,a sensor is made to mount on the tool holder and build the related circuit.Firstly,the energy management module collects the mechanical energy in the environment and converts the piezoelectric vibration energy into electric energy to provide 3.3 Vfor the subsequent circuit.The lithium battery supplies the system with additional power and monitors’the power of the energy storage circuit in real-time.Secondly,a three-axis acceleration sensor is used to collect,analyze and filter a series of signal processing operations of the vibration signal in the environment.The signal is sent to the upper computer by wireless transmission.The host computer outputs the corresponding X,Y,and Z channel waveforms and data under the condition of the spindle speed of 50∼2500 r/min with real-time monitoring.The KEIL5 platform is used to develop the system software.The small-size piezoelectric vibration sensor with high-speed,high-energy utilization,high accuracy,and easy installation is used for spindle monitoring.The experiment results show that the sensor system is available and practical.

Vibration analysis of a new polymer quartz piezoelectric crystal sensor for detecting characteristic materials of volatility liquid

We present a new polymer quartz piezoelectric crystal sensor that takes a quartz piezoelectric crystal as the basal material and a nanometer nonmetallic polymer thin film as the surface coating based on the principle of quartz crystal microbalance （QCM）. The new sensor can be used to detect the characteristic materials of a volatile liquid. A mechanical model of the new sensor was built, whose structure was a thin circle plate composing of polytef/quartz piezoelectric/polytef. The mechanical model had a diameter of 8 mm and a thickness of 170 ~tm. The vibration state of the model was simulated by software ANSYS after the physical parameters and the boundary condition of the new sensor were set. According to the results of experiments, we set up a frequency range from 9.995850 MHz to 9.997225 MHz, 17 kinds of frequencies and modes of vibration were obtained within this range. We found a special frequency fsp of 9.996358 MHz. When the resonant frequency of the new sensor＇s mechanical model reached the special frequency, a special phenomenon occurred. In this case, the amplitude of the center point O on the mechanical model reached the maximum value. At the same time, the minimum absolute difference between the simulated frequency based on the ANSYS software and the experimental measured stable frequency was reached. The research showed that the design of the new polymer quartz piezoelectric crystal sensor perfectly conforms to the principle of QCM. A special frequency value fsp was found and subsequently became one of the most important parameters in the new sensor design.

Low-frequency characteristics extension for vibration sensors

Traditional magneto-electric vibration sensors and servo accelerometers have severe shortcomings when used to measure vibration where low frequency components predominate.A low frequency characteristic extension for velocity vibration sensors is presented in this paper.The passive circuit technology,active compensation technology and the closed- cycle pole compensation technology are used to extend the measurable range and to improve low frequency characteristics of sensors.Thses three types of low frequency velocity vibration sensors have been developed and widely adopted in China.

Analytical Solution of Vibration Analysis on Fixed-Free Single-Walled Carbon Nanotube-Based Mass Sensor

Fixed-free single-walled carbon nanotubes (SWCNTs) have attracted a lot of interest in recent years due to their suitability for a wide range of applications, such as field emission and vacuum microelectronic devices, nanosensors, and nanoactuators. Based on a cantilever beam-bending model with a rigid mass at the free end and mode analysis, an analytical solution is developed in the present study to deal with the resonant frequency and mode shapes of a SWCNT- based mass sensor. The resonant frequency shift and mode shape of the fixed-free SWCNTs caused by the addition of a nanoscale particle to the beam tip are examined in order to explore the suitability of SWCNTs as a mass detector device. The simulation results reveal that the volume of the added particle has little effect on the first resonant frequency. In contrast, the second resonant frequency decreases with increasing the volume of the added particle. Furthermore, the resonant frequency shift of the first mode is very obvious for the amount of added mass, and the second resonant frequency decreases rapidly with increasing volume of added particle. Therefore, the first and second resonant frequencies can be used in the measurement of the mass of added particle and its volume, respectively.

SVD Approach for Actuator and Sensor Placement in Active Vibration Control of Large Cable Net Structures

The actuator and sensor placement problem for active vibration control of large cable net structures is investigated in this paper.Since the structures exhibit closely spaced modes in the range of low frequencies,the number of modes to be considered is quite large after modal truncation,while only a limited number of actuators and sensors are to be placed.This makes it hard to determine the actuator and sensor locations with the existing placement methods in the literature such as the methods based on the controllability/observability grammian.To deal with this issue,an actuator and sensor placement method based on singular value decompositions(SVD)of the input and output matrices is proposed,which guarantees the modal controllability and observability of the system.The effectiveness of the SVD based method is verified through numerical simulations in which comparisons are conducted between randomly-chosen locations and the optimal ones obtained by a genetic algorithm.

Interrogating a Fiber Bragg Grating Vibration Sensor by Narrow Line Width Light

A method to interrogate fiber Bragg grating vibration sensor by narrow line width light is demonstrated. The interrogation scheme takes advantage of the intensity modulation of narrow spectral bandwidth light, such as distributed feedback laser, when a reflection or transmission spectrum curve of an fiber Bragg grating （FBG） moves due to the strain which is applied on the sensor. The sensor＇s response to accelerating frequency and amplitude is measured by experiment. The factors which have impacts on the sensitivity of the interrogation system are also discussed.

ACTIVE VIBRATION CONTROL OF A CANTILEVER BEAM USING PIEZOELECTRIC SENSORS AND ACTUATORS

讨论了利用压电片作为传感器和驱动器对悬臂梁进行主动振动控制问题，针对模态频率差距较大的系统，提出了分组建模和控制的方法。使用滤波器消除观测溢出。文中还讨论了传感器／驱动器配置问题。实验结果验证了所述方法的有效性。

DPCM-based vibration sensor data compression and its effect on structural system identification

Due to the large scale and complexity of civil infrastructures, structural health monitoring typically requires a substantial number of sensors, which consequently generate huge volumes of sensor data. Innovative sensor data compression techniques are highly desired to facilitate efficient data storage and remote retrieval of sensor data. This paper presents a vibration sensor data compression algorithm based on the Differential Pulse Code Modulation (DPCM) method and the consideration of effects of signal distortion due to lossy data compression on structural system identification. The DPCM system concerned consists of two primary components: linear predictor and quantizer. For the DPCM system considered in this study, the Least Square method is used to derive the linear predictor coefficients and Jayant quantizer is used for scalar quantization. A 5-DOF model structure is used as the prototype structure in numerical study. Numerical simulation was carried out to study the performance of the proposed DPCM-based data compression algorithm as well as its effect on the accuracy of structural identification including modal parameters and second order structural parameters such as stiffness and damping coefficients. It is found that the DPCM-based sensor data compression method is capable of reducing the raw sensor data size to a significant extent while having a minor effect on the modal parameters as well as second order structural parameters identified from reconstructed sensor data.

Weighted Multi-sensor Data Level Fusion Method of Vibration Signal Based on Correlation Function

As the differences of sensor＇s precision and some random factors are difficult to control,the actual measurement signals are far from the target signals that affect the reliability and precision of rotating machinery fault diagnosis.The traditional signal processing methods,such as classical inference and weighted averaging algorithm usually lack dynamic adaptability that is easy for trends to cause the faults to be misjudged or left out.To enhance the measuring veracity and precision of vibration signal in rotary machine multi-sensor vibration signal fault diagnosis,a novel data level fusion approach is presented on the basis of correlation function analysis to fast determine the weighted value of multi-sensor vibration signals.The approach doesn＇t require knowing the prior information about sensors,and the weighted value of sensors can be confirmed depending on the correlation measure of real-time data tested in the data level fusion process.It gives greater weighted value to the greater correlation measure of sensor signals,and vice versa.The approach can effectively suppress large errors and even can still fuse data in the case of sensor failures because it takes full advantage of sensor＇s own-information to determine the weighted value.Moreover,it has good performance of anti-jamming due to the correlation measures between noise and effective signals are usually small.Through the simulation of typical signal collected from multi-sensors,the comparative analysis of dynamic adaptability and fault tolerance between the proposed approach and traditional weighted averaging approach is taken.Finally,the rotor dynamics and integrated fault simulator is taken as an example to verify the feasibility and advantages of the proposed approach,it is shown that the multi-sensor data level fusion based on correlation function weighted approach is better than the traditional weighted average approach with respect to fusion precision and dynamic adaptability.Meantime,the approach is adaptable and easy to use,can be applied to other areas of vibration measurement.

Comparison of enhancement techniques based on neural networks for attenuated voice signal captured by flexible vibration sensors on throats

Wearable flexible sensors attached on the neck have been developed to measure the vibration of vocal cords during speech.However,highfrequency attenuation caused by the frequency response of the flexible sensors and absorption of high-frequency sound by the skin are obstacles to the practical application of these sensors in speech capture based on bone conduction.In this paper,speech enhancement techniques for enhancing the intelligibility of sensor signals are developed and compared.Four kinds of speech enhancement algorithms based on a fully connected neural network(FCNN),a long short-term memory(LSTM),a bidirectional long short-term memory(BLSTM),and a convolutional-recurrent neural network(CRNN)are adopted to enhance the sensor signals,and their performance after deployment on four kinds of edge and cloud platforms is also investigated.Experimental results show that the BLSTM performs best in improving speech quality,but is poorest with regard to hardware deployment.It improves short-time objective intelligibility(STOI)by 0.18 to nearly 0.80,which corresponds to a good intelligibility level,but it introduces latency as well as being a large model.The CRNN,which improves STOI to about 0.75,ranks second among the four neural networks.It is also the only model that is able to achieves real-time processing with all four hardware platforms,demonstrating its great potential for deployment on mobile platforms.To the best of our knowledge,this is one of the first trials to systematically and specifically develop processing techniques for bone-conduction speed signals captured by flexible sensors.The results demonstrate the possibility of realizing a wearable lightweight speech collection system based on flexible vibration sensors and real-time speech enhancement to compensate for high-frequency attenuation.

Sensor Layout of Hoisting Machinery Vibration Monitoring Based on Harmony Genetic Search Algorithm

With the construction of automated docks,health monitoring technology as a parallel safety assurance technology for unmanned hoisting machinery has become a hot spot in the development of the industry.Hoisting machinery has a huge structure and numerous welded joints.The complexity and nonlinearity of the welded structure itself makes the structural failure parts random and difficult to arrange for monitoring sensors.In order to solve the problem of effectiveness and stability of the sensor arrangement method for monitoring the structure of hoisting machinery.Using the global and local search capabilities enhanced by the complementary search mechanism,a structural vibration monitoring sensor placement algorithm based on the harmony genetic algorithm is proposed.Firstly,the model is established for modal analysis to obtain the displacement matrix of each mode.Secondly,the optimal parameter combination is established through parameter comparison,and the random search mechanism is used to quickly search in the modal matrix to obtain the preliminary solution,and then the preliminary solution is genetically summed The mutation operation obtains the optimized solution,and the optimal solution is retained through repeated iterations to realize the decision of the vibration sensor layout of the crane structure monitoring.Combining the comparison test of harmony genetic algorithm,harmony search algorithm and genet-ic algorithm,the fitness of harmony genetic algorithm in X,Y and Z directions were 0.0045,0.0084 and 0.0058,respectively,which were all optimal.And the average probability of deviating from the optimal path is 1.10%,19.34%,and 54.43%,which are also optimal.Harmony genetic algorithm has the advantages of simplicity,fastness and strong global search ability,and can obtain better fitness value and better search stability.

Frequency Features Based Fuzzy System for Rotating Machinery Vibration Analysis Using Smartphones Low-Cost MEMS Sensors

Smart devices have become an important entity for many applications in daily life activities. These devices have witnessed a rapid improvement in its technology to fulfill the increasingly diverse usage demands. In the meanwhile, rotating machinery vibration analysis based on low-cost sensors has gained a considerable attraction over the last few years. For a long time, the vibration analysis of machines has been accepted as an effective solution to detect and prevent failures in complex systems to avoid the sudden malfunction. The objective of this work is to use MEMS accelerometer measurements to monitor the different level of vibration of a machine. This work presents a new technique for rotating machinery vibration analysis. It uses Fast Fourier Transformation as a feature extraction algorithm and Fuzzy Logic System (FLS) as the classifier algorithm. A smartphone accelerometer is used to collect the data from the vibrating machine. The performance of the proposed technique is tested using data from different vibration resources at a different speed of operations. The results are discussed to illustrate the various vibration levels.

Distance Estimation and Material Classification of a Compliant Tactile Sensor Using Vibration Modes and Support Vector Machine

Many animals possess actively movable tactile sensors in their heads,to explore the near-range space.During locomotion,an antenna is used in near range orientation,for example,in detecting,localizing,probing,and negotiating obstacles.A bionic tactile sensor used in the present work was inspired by the antenna of the stick insects.The sensor is able to detect an obstacle and its location in 3 D(Three dimensional) space.The vibration signals are analyzed in the frequency domain using Fast Fourier Transform(FFT) to estimate the distances.Signal processing algorithms,Artificial Neural Network(ANN) and Support Vector Machine(SVM) are used for the analysis and prediction processes.These three prediction techniques are compared for both distance estimation and material classification processes.When estimating the distances,the accuracy of estimation is deteriorated towards the tip of the probe due to the change in the vibration modes.Since the vibration data within that region have high a variance,the accuracy in distance estimation and material classification are lower towards the tip.The change in vibration mode is mathematically analyzed and a solution is proposed to estimate the distance along the full range of the probe.

ACTIVE VIBRATION CONTROL AND SUPPRESSION FOR INTEGRATED STRUCTURES

The finite element dynamic model for integrated structures containing distributed piezoelectric sensors and actuators ( S/As ) is formulated with a new piezoelectric plate bending element in this paper. The problem of active vibration control and suppression of integrated structures is investigated under constant gain negative velocity feedback control law. A general method for active vibration control and suppression of integrated structures is presented. Finally, numerical example is given to illustrate the validity of the method proposed in this paper.

Research on A Checking Method of Vibration Characteristics for Test System

To ensure the accuracy and precision of vibration test,a universal checking method is proposed.The use of the method is discussed and an actual example is given.First,the calibration of the 7703A-500 type sensor is analyzed on the basis of frequency response method.The frequency range of normal working can be determined by the exact calibration of sensitivity,frequency response and linearity.For the basic problem of abnormal signals appearing in test system,the method of zero check and loading vibration source are developed.The frequency spectrum of output signals is employed to distinguish the noise signal,unknown source signal and useful signal effectively.Finally,the experimental results reveal the importance to improve the accuracy of the results of practical vibration test.

The Anti-Vibrating-Impact Research of the Piezoelectric Resonator Force Sensor

Based on the analysis of one-dimension inertial accelerometer movement model,from which the resolution of the accelerometer inertial mass displacement equation was derived,the response of the sensor sensing element to vibration and impact of various frequencies was studied.The theoretical and experimental results show that a reasonable configuration among the sensing element inherent frequency,environmental exciting frequency and the damp factors of the sensor is the key to prevent the sensor from damage.The sensor has good anti-vibrating impact ability when the relative damp factor is 0.7,and the environmental interferential vibrating frequency is less than 0.35 times of the inherent frequency of the sensing element.

ACTIVE CONTROL OF THE PIEZOELASTIC LAMINATED CYLINDRICAL SHELL'S VIBRATION UNDER HYDROSTATIC PRESSURE

The control of the piezoelastic laminated cylindrical shell's vibration under hydrostatic pressure was discussed. From Hamilton's principle nonlinear dynamic equations of the piezoelastic laminated cylindrical shell were derived. Based on which, the dynamic equations of a closed piezoelastic cylindrical shell under hydrostatic pressure are obtained. An analytical solution was presented for the case of vibration of a simply supported piezoelastic laminated cylindrical shell under hydrostatic pressure. Using veloctity feedback control, a model for active vibration control of the laminated cylindrical shell with piezoelastic sensor/actuator is established. Numerical results show that, the static deflection of the cylindrical shell can be changed when voltages with suitable value and direction are applied on the piezoelectric layers. For the dynamic response problem of the system, the larger the gain is, the more the vibration of the system is suppressed in the vicinity of the resonant zone. This presents a potential way to actively reduce the harmful effect of the resonance on the system and verify the feasibility of the active vibration control model.

Vibration Compensation for Scanning Tunneling Microscope

The influence of vibration is already one of main obstacles for improving the nano measuring accuracy.The techniques of anti-vibration,vibration isolation and vibration compensation become an important branch in nano measuring field.Starting with the research of sensitivity to vibration of scanning tunneling microscope(STM),the theory,techniques and realization methods of nano vibration sensor based on tunnel effect are initially investigated,followed by developing the experimental devices.The experiments of the vibration detection and vibration compensation are carried out.The experimental results show that vibration sensor based on tunnel effect is characterized by high sensitivity,good frequency characteristic and the same vibratory response characteristic consistent with STM.