A novel wavelet threshold denoising and deep belief network fault detection algorithm

For oil pipeline leakage fault detection problems, a novel negative pressure wave (NPW) leak detection method based on wavelet threshold denoising and deep belief network (Wavelet-DBN) is proposed. Firstly, the wavelet threshold denoising method is used to deal with the sample pressure signal, and the results of wavelet denoising with different wavelet basis functions and different decomposition levels are compared. The optimal parameters are selected for wavelet denoising and the characteristic information of a pipeline pressure signal is extracted. Secondly, in order to improve the accuracy of the pipeline leakage monitoring method based on NPW, the deep belief network algorithms are proposed to classify and identify the NPW sample signals. Finally, the sample data are collected from the industrial oil pipeline leakage experiment. The simulation experimental results show that the proposed method has a higher accuracy rate than other traditional machine learning methods, such as support vector machines, and reduces the false alarm rate of oil pipeline leakage monitoring.

Fluctuating Characteristics of the Stilling Basin with a Negative Step Based on Hilbert-Huang Transform

The violent fluctuation of hydrodynamic pressure in stilling basins is an important factor threatening the safety of the bottom plates of stilling basins, and plays an important role in the safe operation of stilling basins. In order to deeply understand the fluctuating characteristics of stilling basins, the fluctuating pressure signal of a stilling basin bottom plate is processed by the Hilbert-Huang transform method through a hydraulic model test. In this paper, three signal decomposition methods are used to decompose the pulsating pressure signal. A Hilbert transform is used to select the component with the best decomposition effect. The time-frequency-amplitude diagram of the pulsating pressure signal is obtained by Hilbert transform, and its time-frequency characteristics are discussed in depth. The analysis results are as follows: (a) the decomposition results from the CEEMD method are orthogonal and complete. The HHT method is suitable for processing fluctuating pressure signals. (b) With an increase in IMF decomposition order, the signal frequency band becomes narrow, the Hilbert spectrum amplitude decreases and the pulsating pressure energy decreases. The decomposition of the fluctuating pressure signal into components of different scales shows that the turbulence is composed of multiple scales of vortices, reflecting the vortex structure in the turbulence. (c) The jet impingement zone of the drop bucket stilling basin is near x/L = 0.075. The dominant frequency and marginal spectrum energy of the jet impingement zone are very prominent, and the marginal spectrum energy is mostly concentrated within 5.0 Hz. (d) At different drop height and different flow energy ratio, the fluctuation in the dominant frequency of fluctuating pressure decreases, the dominant frequency of the head of the stilling basin is larger, the dominant frequency of the middle and rear parts tends to be stable, and the dominant frequency is finally stabilized at about 1.0 Hz. This paper attempts to use the HHT method to process the fluctuating pressure signal, and the results provide a new discussion method for exploring the fluctuating pressure characteristics of hydraulic structures.

Time-Frequency Characteristics of Fluctuating Pressure on the Bottom of the Stilling Basin with Step-Down Floor Based on Hilbert–Huang Transform

Fluctuating pressure is an important feature of the bottom of a stilling basin with step-down floor. To analyze the frequency domain characteristics and energy distribution of this fluctuating pressure, the Hilbert–Huang transform (HHT) method is used. First, empirical mode decomposition is performed on the pressure fluctuation signal to obtain a number of intrinsic mode functions (IMFs), and then the Hilbert transformation is performed on each IMF to obtain the Hilbert spectrum and marginal spectrum for characterizing the pressure fluctuation signal. The results show that the fluctuating pressure signal of the stilling basin with step-down floor has obvious characteristics of low frequency and large amplitude. The dominant frequencies of the head and tail of the stilling basin are very prominent, and most of the energy is concentrated below 5.0 Hz; with the increase in the relative position of the measuring point, the energy distribution in stilling basin with step-down floor changes from high-frequency component to low-frequency component. The fluctuating pressure signal of the stilling basin with step-down floor has random amplitude modulation and frequency modulation. The marginal spectrum obtained by the HHT method can obtain the local characteristics of the signal more accurately and is more suitable for processing nonlinear and nonstationary signals.

The pressure characteristics analysis of oil pulsation flow based on VMD

The pressure signal of oil pulsating flow is a kind of multi-component signal; in order to realise the effective separation of the multi-component pressure signal and extract its vibration characteristics, the pressure signal was decomposed by Variational Mode Decomposition (VMD). The slope criterion of the centre frequency is proposed to determine the number of components of VMD decomposition, and the method to judge the main components of the signal by energy value is proposed. The Hilbert envelope demodulation analysis was performed on the main components obtained. The results show that the proposed center frequency slope criterion method is effective in the VMD decomposition of the pressure signal of oil pulsating flow, which is used to decompose the pressure signal into 9 components. Four major components of the pressure signal are obtained by the correlation between each component and the pressure signal, and the energy value calculation of each component. The main component frequency of the pressure signal is one time, 6 times, 11 times and 14 times the frequency of the system spindle rotation; these are the sum of two cosine signals of close frequency and have the characteristic of beat vibration.

Multistage Digital-to-Analogue Chip Based on a Weighted Flow Resistance Network for Soft Actuators

A control chip with a multistage flow-rate regulation function based on the correlation between the flow resistance and flow rate has been developed in this article. Compared with the traditional proportional solenoid valve, this kind of flow valve based on microfluidic technology has the characteristics of being light-weight and having no electric drive. It solves such technical problems as how the current digital microfluidic chip can only adjust the flow switch, and the adjustment of the flow rate is difficult. To linearize the output signal, we propose a design method of weighted resistance. The output flow is controlled by a 4-bit binary pressure signal. According to the binary value of the 4-bit pressure signal at the input, the output can achieve 16-stage flow adjustment. Furthermore, we integrate the three-dimensional flow resistance network, multilayer structure microvalve, and parallel fluid network into a single chip by using 3D printing to obtain a modular flow control unit. This structure enables the microflow control signal to be converted from a digital signal to an analogue signal (DA conversion), and is suitable for microflow driving components, such as in microfluidic chip sampling systems and proportional mixing systems. In the future, we expect this device to even be used in the automatic control system of a miniature pneumatic soft actuator.

Adevelopment of an Advanced Pressure Signal Acquisition Card for a Modular Turbojet Fadec System

Gas turbine engines are very important in aviation. Pressure is one of the key thermodynamic parameters which, first of all, suffers radical change within the flow passage of a gas turbine, on the other hand, there are several accessories like fuel and oil supply, in which the pressure of the working medium is essential. The measurement of this variable is therefore inevitable in data acquisition or engine control systems. The author shows the process of development of an advanced pressure signal acquisition card that fits into a modular electronic control system of a turbojet engine. The unit incorporates numerous experiences gathered with the previous generation of this module regarding power supply and integrated sensors as well. Furthermore, there are several innovations that enable a more efficient installation, data acquisition and built-in test possibilities. The most important difference is the 32-bit ARM Cortex-M0+ microcontroller which allows faster operation which allows the acquisition of more signals, including additional functions as thrust measurement, digital input/output handling and many others. The unit operation was thoroughly assessed using simulated and real operating conditions as well.