Fault diagnosis of rotating machinery based on fuzzy clusteringoptimized by chaos embedded particle swarm optimization

A method of weighted fuzzy clustering optimized by chaos embedded particle swarm algorithm(CPSO) is put forward and applied in vibration fault diagnosis of rotating machinery. In the method, CPSO is used to displace the traditional stochastic-gradient algorithm to optimize parameters of weighted fuzzy C-means (WFCM). The best clustering num and clustering centers are automatically attained according to clustering validity function. The experimental results show that the method effectively increases the convergence velocity and precision of WFCM and so does the correctness rate of fault diagnosis for rotating machinery.     

State and Prospects of Diesel Engine Fault Diagnosis Technique

As a kind of complex power machinery, diesel engine is being paid more and more attention to its condition monitoring and fault diagnosis technology. In the fault diagnosis field of diesel engine, the technique of signal process, character abstraction and identification method have formed a system, but there is a certain distance away from practical. This paper analyzes the common faults and influencing factor of diesel engine. The principle, characteristic and disadvantage of modern fault diagnosis technology, such as various time-frequency methods based on vibration signal, speed fluctuation method, iron content and spectrometry, grey system theoretical diagnosis method, artificial neural network and expert system fault diagnosis method, were reviewed. The difficulties and the development direction of diesel engine fault diagnosis were put forward in the end.     

Real time monitoring for multivariate statistical process with on line multiscale filtering

By analyzing shortages of current MSPCA model, an on line multi variable statistical process monitoring method is proposed, which uses some concepts from online multi scale filtering and can be applied to sensor fault diagnosis. In the method, wavelet decomposition is employed to the signals using edge correction filter in a fixed length data window, and then wavelet denoising is conducted with wavelet threshold filtering. Next, an on line multi scale model is constructed for data combining wavelet transformation and adaptive PCA in the previous data window. This model avoids time waste in direct signal denoising and reduces time cost in multi scale data with conventional PCA, which eventually increases accuracy in fault diagnosis. Experiments on eight vibration signals of 6135D diesel engine under severe leak condition prove the practicability and feasibility of the proposed method.     

Cotton Image Segmentation Algorithm Based on Fusion Method of Markov Random Field and Quantum Particle Swarm Cluster

[Objective] The aim of this study was to improve the cotton image segmentation accuracy in a picking robot image processing system. [Method] An image segmentation algorithm based on a fusion method of Markov random field and quantum particle swarm optimization clustering was proposed. The process of the proposed algorithm is as follows: first, transform the RGB (red, green, blue) images into grayscale; second, use it to segment these images; finally, the threshold of the connected area is set on the basis of the segmented image to obtain the target area. Then, the cotton front image and the cotton side image are selected from the images collected from different angles. The segmentation experiment was carried out by using this algorithm, and compared with the Otsu algorithm, the fuzzy C-means algorithm, the quantum particle swarm image segmentation algorithm and the Markov random field image segmentation algorithm. [Result] The results showed that the segmentation accuracy and peak signal to noise ratio of the proposed algorithm were 98.94% and 77.48 dB. When compared with the Otsu algorithm, fuzzy C-means algorithm, quantum particle swarm optimization algorithm and Markov random field algorithm, the average segmentation accuracy and peak signal to noise ratio of the proposed algorithm increased by 2.47%–4.56%, and 9.81–13.11 dB, respectively. [Conclusion] The proposed algorithm had higher segmentation accuracy and higher peak signal to noise ratio than the other algorithms tested.     

Fuzzy c-means Cluster Over Gentic Algorithm

Fuzzy c-means (FCM) algorithm is dynamic cluster algorithm whose result often is local optimal decision. There often exists insignificant clustering in the result of Fuzzy c-means algorithm when traditional union, Intersection and inclusion work in fuzzy set. Our research indicates there are no insignificant clustering in the result of Fuzzy c-means algorithm over genetic algorithm and partial optimal solution can be avoided with this algorithm to a certain extent. The coding, select, corresponding crossover and mutation operators are designed. Finally we compared the performance of GFCM and FCM with testing data. Results show that the performance of GFCM is far better than FCM.     

Research of the Ignition Timing System for Compressed Natural Gas Vehicle

Compared to bi-fuel engine,it uses completely CNG(Compressed nature gas) to replace diesel which can save more oil fuel than bi-fuel engine that reffited diesel engine into CNG engine. A 4102 diesel engine is refitted into CNG engine and a mechanical ignition timing system is designed by the method of gear and belt. The principles and the construction of the system is introduced and the characteristics of the design is analyzed. The system performed well and had good liability when run in a platform. Compared with the previous one, it kept higher dynamic character and emitted lower. It is a cheap one and can be use to reform the diesel engines.     

Application of higher density wavelet transform to composite fault diagnosis of rolling bearing

Aiming at the difficulties in accurate reorganization of several weak faults currently, a composite fault diagnosis method based on higher density discrete wavelet transform and envelope spectrum is proposed. Firstly, the higher density discrete wavelet transform is used to decompose acquired vibration signals of rolling bearings. Then, the single-subband reconstruction is performed on the wavelet coefficients and scaling coefficients at each scale in order to solve frequency aliasing. Finally, the envelope spectra of all subband signals are calculated, and all faults can be recognized according to the characteristic frequencies of the typical faults. The proposed method is applied to the diagnosis of the rolling bearings with composite faults, and is compared with other common fault diagnosis method. The results show that the proposed method can be effectively used for the early composite fault diagnosis of rolling bearings.     

基于台架试验的渔船柴油机履行新排放标准探讨

环保部2016年发布了GB 15097—2016《船舶发动机排气污染物排放限值及测量方法（中国第一、二阶段）》,该标准相较于《渔业船舶法定检验技术规则（船长大于或等于12 m国内海洋渔业船舶2017）》的要求增加了一氧化碳、碳氢化合物、颗粒物3个控制项目,氮氧化物的排放限值也明显提高。为获知当前中国主流渔船柴油机排放的技术现状、了解履行新标准的差距,对2种典型的渔船柴油机进行了排放污染物测试试验和劣化试验验证。试验结果显示：典型渔船柴油机可满足新标准一阶段的要求,但距离二阶段要求有较大差距。其中颗粒物的排放超出二阶段限值25%~53%。通过两型柴油机试验数据的对比分析发现,燃油喷射方式是改善颗粒物排放和有效降低柴油机劣化程度的关键因素。针对渔船柴油机如何更好的履行二阶段排放要求给出建议：推迟新标准二阶段生效;鼓励研发新产品,促进先进技术引进;控制实船使用燃油质量,提高渔民的环保意识;加强实船监管力度。     

Bottom-up Clustering Algorithm of High Dimension

Clustering algorithm based on wavelet transform is efficient, and which can detect clusters of arbitrary shape. It is insensitive to the outliers and the order of input data. However, efficiency of the algorithm would be degraded, and computation complexity of the algorithm would be considerable with increase of clustering dimensions. A bottom-u Pmethod is put forward to make the original algorithm fit to clustering in high dimension, and the scalability of the improved algorithm is enhanced by parallelization. The experiment demonstrates that the improved algorithm has no impact on quality of clustering and has a good efficient in high dimension clustering and in decrease of comnutation comnlexity.     

The Signals Analysis System Based on Fast Wavelet Transform

The fast wavelet transform (FWT) algorithm in wavelet analysis was introduced in the paper. With quadrature mirror filters (QMF) associated with popular wavelet bases, the fast wavelet decomposition and reconstruction for signals were implemented. Combined with virtual instrument technique, the FWT analysis system for signals was successfully developed. The system can break up signal not only into approximations, which are the high-scale and low-frequency components of the signal, but also into details which are the low-scale and high-frequency components. Especially it can identify singularity signal, which contain some important message of equipment condition and fault, and refine signal from noisy signal, which is corrupted by noise.     

Time-frequency Characteristic of Wavelet Base and Its Application Transient Signal Detection

The application of wavelet analysis in fault diagnosis is growing rapidly.There are many different wavelet base to use but no accepted procedure for choosing among them, the analysis results by using them have great difference. This paper describes the significant properties of wavelet base, and analysis behavior of transient signal in wavelet transform, result on some methods for how to choose wavelet base in analysis transient signal.     

插电式混合动力汽车纯电动行进间启动发动机的平顺性控制

针对单电机插电式混合动力汽车在纯电动行进间电动机启动发动机时由于系统输出转矩变化进而引起整车冲击的问题,分析得到发动机点火时刻的不同及离合器接合状态的不同是造成转矩波动的原因。在此基础上,提出了基于离合器主、从动盘转速差和电机角加速度为输入量的离合器压力模糊控制的混合动力汽车模式切换动态协调控制策略,并对比了发动机目标转速点火和怠速转速点火的控制效果。最后通过台架试验以及实车道路试验对提出的控制策略进行了验证。结果表明,基于目标转速点火的协调控制策略能减小整车的冲击度。     

Wavelet Packet Decomposition Based on Entropy Threshold for White-noise Rejection in PD Signal

This paper analyzes the different characteristics of white-noise interference in the signals of partial discharge (PD) after wavelet transform. There is high value in lots of scales for PD and white-noise interference is to zero with increasing scale. The threshold is set for wavelet coefficient in all scales. If the coefficient of signal is higher than the threshold, it is PD signal. Otherwise it is noise interference. A threshold-based wavelet packet transform (WPT) algorithm is put forward to suppress white noise interference in PD signals. The results testifies that it has a favorable adaptability to extract PD signals using WPT.     

A Virtual Wavelet Transform Analyzer for the Signal Analysis Based on the Direct Algorithm

A virtual wavelet transform analyzer for the signal analysis based on the direct algorithm is introduced so that the discrete wavelet transform and continuous wavelet transform is maken to signal in the direct algorithm. The authors first introduce the direct algorithm of the WT, which is numerical algorithm obtained from the original formula of the wavelet transform by directly numericalizing. Then some conclusions are drawn on the direct algorithm. The examples are the sampling principle and technology for the wavelets, the limitation of the scale range of the wavelets and the measures to solve the edge phenomenal in the direct algorithm of the discrete wavelet transform, and some conclusions in the direct algorithm of the continuous wavelet transform. The virtual wavelet transform analyzer for the signal analysis based on the direct algorithm explored based on these studies and combined with virtual instrument technique can make the discrete wavelet transform and continuous wavelet transform to signal with any basic wavelet. It can be applied in studying the property of any basic wavelet and learning the theory on the wavelet transform, and also in making some engineering signal analysis. In the end, the authors give some typical examples for the application of the virtual analyzer. These examples show that the analyzer can be applied in many situations.     

Denoise Based On Translation Invariance Wavelet TransformAnd Its Applications

De_noising algorithm based on traditional wavelet transform may produce artifacts on discontinuities of the signal. The reason is that the de_noising algorithm lacks of wavelet translation invariant. This paper proposes a de_noising method based on translation invariant. The method performs the cycle_spinning for the signal to be analyzed. And then, the soft (hard) thresholding is used to shrink the wavelet coefficient of the signal and reconstruct the signal. Consequently, the shift dependence of wavelet basis is eliminated. This method can suppress the artifacts effectively so that de_noised signal is more smooth and has better approximation to original signal.     

A high pressure fuel injection system of a 4JB1 diesel engine

A fuel system evaluation method was introduced to select the proper high pressure injection system for diesel engines. Using this method, the second generation common rail system of BOSCH Company was selected for use in the 4JB1 diesel engine. Based on this common rail system, a fuel supplying model was built using AMESim. The model included a high pressure pump sub module, a pressure control valve sub module, an injectors sub module, and a connecting pipes sub module. Through model simulation, the influences of parameters (e.g., rail volume, high pressure pipe length and diameter) on pressure fluctuations and pressure building were studied. Rail pipe system parameters were selected based on simulation results. Experimental results show the rail pipe parameters could satisfy the needs of rapid pressure response and low pressure fluctuations for common rail diesel engines.     

Computation of the Wavelet and Scaling Functions Using Coefficients of Wavelet Filter

To associate the discrete wavelet transform with the continuous wavelet transform, an iterative convolution algorithm is given by analyzing the and scaling function using coefficients of wavelet filter. usually used methods of the computation The way of judging the convergence of improved algorithm on of the wavelet function iterative convolution is given. The advantages of improved algorithm is analyzed. The experimental result shows that the modified algorithm is effective.     

Calculation on Natural Frequency and Main Vibration Mode of Double-lined Type Mounting System

The vibration characteristic of engine mounting system is analyzed, the vibration model of engine mounting system is established, and calculation method of natural frequency and main vibration mode of mounting system is put forward. Then an engine mounting system with double - lined type isolator is presented. Isolation performance of engine mounting system is improved greatly by selecting elastic coefficient of isolator reasonably.     

Kinetic characteristics of ignition process of diesel surrogate fuel

The purpose of this paper is to identify the effects of toluene and the toluene content which is at different initial temperatures on the ignition delay time of diesel surrogate fuel under homogeneous charge compression ignition (HCCI) engine condition. The CHEMKIN4.1 module (closed homogeneous batch reactor) is used with the constructed diesel surrogate fuel chemical kinetics model to simulate the constant volume. The results show that the ignition property is mainly characterized by n-heptane. The presence of the slowly oxidizing toluene in the surrogate fuel does not affect the auto-ignition time considerably. In addition,the influence of toluene content on the ignition delay time is significant only at low initial temperature. More ignition delayed combustion processes have been found when toluene content is increasing.