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An accurate energy prediction and optimization model plays a very important role in the petrochemical industries. Due to the imbalanced and uncompleted characteristics of complex petrochemical small data, it is a big challenge to build accurate prediction and optimization models for energy analysis. In order to solve this problem, a nonlinear interpolation virtual sample generation method integrated with extreme learning machine is proposed. Well virtual input and output variables can be generated through interpolation of the hidden layer outputs of extreme learning machine. The generated virtual samples are put together with the original samples to train models for enhancing accuracy performance. To validate the effectiveness of the proposed nonlinear interpolation virtual sample generation method, a standard function is firstly selected, and then the proposed nonlinear interpolation virtual sample generation method is applied to developing a model of energy analysis for ethylene production systems. Simulation results showed that the prediction accuracy could be significantly improved, which provided helpful guidance for production departments and government to achieve the goal of energy management of petrochemical industries.

With the increasing development of modern industries, ensuring the safety and reliability of production processes becomes a more and more urgent task. Alarm root cause analysis plays a very significant role in preventing faults of complex industrial processes. Causal network modeling is an important part of alarm root cause analysis. For building a good causal network model, transfer entropy is usually adopted as an effective method. However, there are some problems in determining prediction horizons of transfer entropy. In order to solve these problems and further enhance the performance of the original transfer entropy method, a modified transfer entropy method taking the prediction horizon from one variable to another and to itself simultaneously into consideration is proposed. Moreover, based on data-driven and process knowledge based modeling methods, an approach integrating transfer entropy with superficial process knowledge is designed to correct the false calculation of transfer entropy and then o...

Aimed at the goal of improving the quality and the efficiency of welding for T-type welding seam, This paper put forward a method to track the seam by using the vision sensor. Machine tool main motion trajectory is generated from the numerical model of the parts. The position of two welding torches are adjusted independently based on the machine tool main motion trajectory to ensure the welding precision. Two sets of adjusting mechanism are needed for T-type welding seam. The vision sensor measure the seam and pass the deviation signal to the CNC system. The CNC system adjust the position of the welding torch installed on the cross slide table to reach the goal of seam tracking and dual-beam laser welding for T-type welding seam. Practice shows that this system for T-type welding seam dual-beam laser welding is easy to operate and can improve the quality and the efficiency.

Aimed at the goal of digital capture function for CNC profiling lathe, it has conducted researches on the key technologies of CNC system development, including automatic profiling measurement, profiling data collection methods and G-code program automatically generation. Before process, use an on-off-type laser sensor along the planned path close to the sample workpiece point by point to get series of coordinate points of the contour through the CNC system position latch function and the switch of senors state; through subsequent processing methods: contour segmentation, curve filtering, etc. And generate the G-code program for process. Practice shows that this special CNC system for profiling lathe, not only integrates automatic profiling data acquisition, automatic generation of process G code program, and has the characteristics of simple structure, easy operation and high efficiency.

As an important part of an engine, piston is working for a long time in the environment of high temperature, high pressure and pulse-pounding. Its working state and life directly affect the life of the engine. Piston fatigue failure plays an important factor of piston failure. Piston hydro-pulse test machine has important significance for studying the life of piston mechanical fatigue. The paper is about the design and use effect of domestic piston hydro-pulse test machine. Practice shows that the control technology of Piston hydro-pulse test machine, fulfills various indicators of piston fatigue tests, and has important significance for improving domestic piston design, production and usage.

Aimed at solving the problem of mold damage caused by a foreign body in the mold before mold clamping, this paper proposes a solution, which applies image processing technology such as background updating and the difference image algorithm to solve it. Not only can it judge whether there is a foreign body in the mold but it can also detect whether the product is perfect by comparing the foreground image with the background image at the appropriate time (before mold clamping or after mold opening) and by calculating the qualified rate of pixel in all ROIs (Region of Interest). To eliminate the influence of vibration and of changes in brightness in the surrounding environment on the detecting results, this paper utilizes near infrared illumination technology and the background updating algorithm. In addition, the ROI is set to improve the detecting speed and accuracy.

For the seam feature measurement of the tight butt joint without misalignment in laser welding, current vision sensor cannot obtain the seam gap width and seam position stably and reliably. In this paper, a seam measurement method based on the micro depth of field is proposed. A four times optical magnification lens, a CCD/CMOS camera and an external LED lighting unit are used to constitute the measure system, which can be used for the tight butt joint for laser welding. Experiment indicated that it can obtain the seam gap width and seam position stably and correctly. With the method, seam surface normal vector also can be measured. The measurement accuracy for the seam gap width and seam position is 5 µm and 6 µm, respectively. Furthermore, the narrowest welding seam gap that can be measured by this method is 0.02 mm, which is fully satisfied the demand of the seam measurement in laser welding.

Background and objective: It has been shown that macrophages play an important role in the development of severe acute pancreatitis (SAP), and eventually lead to multiple organ failure (MOF). Clodronate-liposome selectively depleted macrophages. This study was to investigate the role of renal macrophage infiltration in acute renal injury in rats with SAP and to evaluate the potential of superparamagnetic iron oxide (SPIO)-enhanced magnetic resonance imaging (MRI) for diagnosis. Methods: Superparamagnetic Fe3O4 nanoparticles were prepared by chemical coprecipitation. SPIO-liposomes and SPIO-clodronate-liposomes were prepared by the thin film method. SAP models were prepared by injection of sodium taurocholate into the subcapsular space of rat pancreas. Sprague-Dawley rats were randomly divided into a control group, SAP plus SPIO-liposome (P) group, and SAP plus SPIO-clodronate-containing liposome (T) group. Kidney injury was evaluated by T2-weighted MRI scan. The levels of serum amylase (SAM), blood urea nitrogen (BUN), and serum creatinine (SCr) were measured by an automated enzymatic method. Serum tumor necrosis factor-α (TNF-α) was measured by enzyme-linked immunosorbent assay (ELISA). Pathological changes in the pancreas and kidney were observed using hematoxylin and eosin (H&E) staining, while cell apoptosis was detected with terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining. In addition, the macrophage markers (CD68) of the renal tissue were detected with immunohistochemistry. Results: The pathological changes in the pancreas and kidneys of rats in the T group were milder than those in the P group. The MRI signal intensity of the kidneys in the P and T groups was significantly lower than that in the control group. There were significant changes in the two experimental groups (P