Key Engineering Materials Vol. 693

Abstract: A small automated enzyme immunoassay analyzer system based on immunoenzymatic techniques is designed and implemented in this paper. The working instrument process is determined according to immunoenzymatic techniques, and then enzyme analysis system is designed. Institutional innovation is implemented. Several forms institutions of absorbing and discharging and mobile are designed, according working principle instrument and the forms of the analyzer at home and abroad. A new photoelectric detection institution based on micro spectrometer is designed. Using fuzzy adaptive algorithm controls constant temperature. This paper offers a new viewpoint and direction of small automated enzyme linked immunosorbent assay analyzer system design.

Abstract: The Automatic Test System (ATS) is being increasingly used in the business and professional test. However, there are some potential problems emerged in the application of the distributed test. So we intend to solve the problems by adopting the idea of the Cloud Computing to solve the two challenges: improve the efficient use of the limited and heterogeneous hardware test resources and shorten the test cycle which is defined as the whole time of the test. The paper proposes several structures of the Cloud Test System (CTS): the overall structure, the software and hardware architecture. Theoretically,the study overcomes the challenges of the existing test system, then the foundation of the further study is laid.

Abstract: The traditional first-order differential operator is under the influence of the Gaussian noise, therefore, it often implement boundary extraction after average filtering. But the filtering process would often smooth the details of some directions of image too much, so that the edge cannot be extracted correctly. To solve this problem, this paper puts forward the edge detection algorithm based on edges keep, to determine the keeping direction of the edge through matching different directions’ edge template. Instead of average filtering process, it can improve the performance of traditional operator, and provide the simulation results. Experimental results show that the algorithm can eliminate noise, and at the same time, keep more edge information of the image.

Abstract: With the development of Internet industry, equipment data is increasing. The traditional method is not suitable for processing large data. Aiming at inefficient problem of Apriori algorithm when mining very large database, an efficient parallel association rules mining algorithm (Advanced Pruning Parallel Apriori Algorithm) based on a cluster is presented. APPAA algorithm can enhance the mining efficiency, as well as the system’s extension. Experimental results show that APPAA algorithm cuts down 85% mining time of Apriori, and it has good characteristics of parallel and expandable.so it is suitable for mining very large size database of fault diagnosis.

Abstract: In order to reduce the false alarm rate in coal mine fire warning system, we apply information fusion technology to the system and propose a fire forecast algorithm based on Rough Set Support Vector Machine ( RS-SVM ). Firstly, we map the feature description of coal mine fires to the knowledge representation system described by rough set; Secondly, we discrete the continuous attributes and eliminate the redundant information for attribute reduction to form a rule set of this knowledge representation system; At last, we use the above rule set as the training sample to optimize the parameters for the fire warning support vector machine. The experimental results show that the accuracy of the algorithm is very high. It can make timely and accurate prediction of coal mine fire.

Abstract: In this paper, the dynamometer for measuring the forces of the tool in FSW process was designed. The design principle of the dynamometer was adopted octagonal ring deformation to get the forces in FSW process. The design dynamometer was calibrated, the result showed the linearity and cross sensitivity of the dynamometer in allowed range, the worked reliable of the dynamometer was good. It can be used to measure the forces in FSW process.

Abstract: Rough set theory is a useful tool for attribute reduction of fault diagnosis for rotating machinery, but cannot be efficiently used to sample increased areas. Aiming at the problem of incremental attribute reduction, a novel attribute reduction algorithm was put forward based on the binary resolution matrix for the two updating situations and the algorithm had a low space complex. Finally, with the fault diagnosis experiments of the bearing, the attribute reduction method was proved to be correct.

Abstract: Blind source separation (BSS) is an effective method for the fault diagnosis and classification of mixture signals with multiple vibration sources. The traditional BSS algorithm is applicable to the number of observed signals is no less to the source signals. But BSS performance is limit for the under-determined condition that the number of observed signals is less than source signals. In this research, we provide an under-determined BSS method based on the advantage of time-frequency analysis and empirical mode decomposition (EMD). It is suitable for weak feature extraction and pattern recognition. Firstly, vibration signal is decomposed by using EMD. The number of source signals are estimated and the optimal observed signals are selected according to the EMD. Then, the vibration signal and the optimal observed signals are used to construct the multi-channel observed signals. In the end, BSS based on time-frequency analysis are used to the constructed signals. Gearbox signals are used to verify the effectiveness of this method.

Abstract: For composite fault is difficult to diagnose, the characteristics of the large amount of data. This paper presents a method of The Prediction method of Composite Fault Based on data driven to establish intelligence unit Based on a collection of virtual individuals associated with the virtual failure associated collection and virtual behavior associated collection. Composite fault warning engine modeling is proposed, and give the warning value of composite fault finally. This method is fully assessing the future "dominant state" on the basis of the fully aware of current "hidden state". The impact of factors such as disturbance of hidden failures on composite fault prediction are fully considered, to some extent, the long-span composite failure prediction problem is solved, and the experiments show that the method effectively increases the accuracy of composite fault prediction.

Abstract: When dealing with the vibration analysis of the rolling element bearing under gear noise and time-varying speed condition, order tracking is always utilized to convert the time signal to angular domain. In this way, the smearing effect in the spectrum is avoided and the noise cancellation methods based on the periodicity of the gear signal can be reapplied. In this paper, the resonance frequency variation of the resampled signal is analyzed and its influence on the kurtogram algorithm based bandpass filtering procedure is studied through a simulation experiment and a fault feature extraction method of the rolling bearing based on reverse order tracking is proposed. Effectiveness of the proposed method is verified through the analysis of the signal measured from the test-rig.