高炉交流探尺西门子S120功能组态

高炉探尺调节的工作稳定性直接影响高炉的正常生产,对稳定高炉炉况和原燃料的正常下料起着至关重要的作用。探尺好比高炉操作人员的眼睛一旦出现故障将严重影响高炉生产,因此必须选用安全可靠维护方便的电控设备来保证探尺的可靠运行。本文选用西门子公司的S120变频器对高炉探尺进行传动控制,介绍了探尺提尺、放尺、跟随料面三种工作状态变频器的内部组态方案,以及硬件组态和工艺原理。

SINAMICS S120变频器在高炉探尺控制系统中的应用

为满足高炉生产工艺日益精细化的需求;探尺控制系统必须实现精准捕捉生产料面。结合西门子SINAMICS;S120变频器的独特性能;探尺控制系统可实现在速度控制方式和转矩控制方式之间快速切换;根据下降的速度变化精确判断生产中料面的异常变化;保证系统平稳、可靠、安全的运行。

Underwater Image Enhancement Based on Multi-scale Adversarial Network

In this study,an underwater image enhancement method based on multi-scale adversarial network was proposed to solve the problem of detail blur and color distortion in underwater images.Firstly,the local features of each layer were enhanced into the global features by the proposed residual dense block,which ensured that the generated images retain more details.Secondly,a multi-scale structure was adopted to extract multi-scale semantic features of the original images.Finally,the features obtained from the dual channels were fused by an adaptive fusion module to further optimize the features.The discriminant network adopted the structure of the Markov discriminator.In addition,by constructing mean square error,structural similarity,and perceived color loss function,the generated image is consistent with the reference image in structure,color,and content.The experimental results showed that the enhanced underwater image deblurring effect of the proposed algorithm was good and the problem of underwater image color bias was effectively improved.In both subjective and objective evaluation indexes,the experimental results of the proposed algorithm are better than those of the comparison algorithm.

Riser VIV and its numerical simulation

This paper summarizes some of the typical riser vortex-induced vibration （VIV） problems in subsea oil and gas developments, and presents the corresponding computational fluid dynamics （CFD） time domain simula- tion results to address these problems. First, the CFD time domain simulation approach was applied to analyze the wake field behind a stationary cylinder and a vibrating cylinder. Then a vertical riser VIV response under uniform current was studied. The VIV response time histories revealed some valuable clues that could lead to explanation of the higher harmonics. After that, a vertical riser VIV response under shear current was investigated. A 3 000 ft （1 ft=-0.304 8 m） water depth top tensioned riser was sized, and its VIV responses under uniform and shear current were studied. Then this paper continues to discuss one catenary flexible riser VIV response during normal lay. Last, the time domain simulation approach was applied to a partially submerged flexible jumper, to study the jumper VIV behavior, and dynamic motion envelopes. It was demonstrated that the time domain simulation ap- proach is able to disclose details of the flow field, vortex shedding pattern, and riser dynamic behavior, and han- dle different tvoes of risers under different Woe of currents.

Method for Detecting Weld Feature Size Based on Line Structured Light

With the rapid development of the machining and manufacturing industry,welding has been widely used in forming connections of structural parts.At present,manual methods are often used for welding and quality inspection,with low efficiency and unstable product quality.Due to the requirements of visual inspection of weld feature size,a visual inspection system for weld feature size based on line structured light(LSL)is designed and built in this paper.An adaptive light stripe sub-pixel center extraction algorithm and a feature point extraction algorithm for welding light stripe are proposed.The experiment results show that the detection error of the weld width is 0.216 mm,the detection error of the remaining height is 0.035 mm,the single measurement costs 109 ms,and the inspection stability and repeatability of the system is 1%.Our approach can meet the online detection requirements of practical applications.

Radar emitter signal recognition based on multi-scale wavelet entropy and feature weighting

In modern electromagnetic environment, radar emitter signal recognition is an important research topic. On the basis of multi-resolution wavelet analysis, an adaptive radar emitter signal recognition method based on multi-scale wavelet entropy feature extraction and feature weighting was proposed. With the only priori knowledge of signal to noise ratio(SNR), the method of extracting multi-scale wavelet entropy features of wavelet coefficients from different received signals were combined with calculating uneven weight factor and stability weight factor of the extracted multi-dimensional characteristics. Radar emitter signals of different modulation types and different parameters modulated were recognized through feature weighting and feature fusion. Theoretical analysis and simulation results show that the presented algorithm has a high recognition rate. Additionally, when the SNR is greater than-4 d B, the correct recognition rate is higher than 93%. Hence, the proposed algorithm has great application value.

A multi-scale convolutional auto-encoder and its application in fault diagnosis of rolling bearings

Aiming at the difficulty of fault identification caused by manual extraction of fault features of rotating machinery,a one-dimensional multi-scale convolutional auto-encoder fault diagnosis model is proposed,based on the standard convolutional auto-encoder.In this model,the parallel convolutional and deconvolutional kernels of different scales are used to extract the features from the input signal and reconstruct the input signal;then the feature map extracted by multi-scale convolutional kernels is used as the input of the classifier;and finally the parameters of the whole model are fine-tuned using labeled data.Experiments on one set of simulation fault data and two sets of rolling bearing fault data are conducted to validate the proposed method.The results show that the model can achieve 99.75%,99.3%and 100%diagnostic accuracy,respectively.In addition,the diagnostic accuracy and reconstruction error of the one-dimensional multi-scale convolutional auto-encoder are compared with traditional machine learning,convolutional neural networks and a traditional convolutional auto-encoder.The final results show that the proposed model has a better recognition effect for rolling bearing fault data.

Experimental evaluation and modeling of liquid jet penetration to estimate droplet size in a three-phase riser reactor

In this work, the effects of injecting an evaporating liquid jet into solid-gas flow are experimentally investigated. A new model （SHED model） and a supplementary model （spray model） have also been proposed to investigate some flow-field characteristics in three-phase fluidized bed with the mean relative error 4.3% between model and measured results. Some experiments were conducted to study the influences of flow-field parameters such as liquid volumetric flow rate, injection velocity, jet angle and gas superficial velocity as well as solid mass flux on the jet penetration depth （JPD）. In addition, independent variables were experimentally employed to propose two empirical correlations for JPD by using multiple regression method and spray cone angle （SCA） by using dimensional analysis technique. The mean relative errors between the JPD and SCA correlations versus ex- perimental data were 7.5% and 3.9%, respectively. In addition, in order to identify the variable effect, a parametric study was carried out. Applying the proposed model can avoid direct use of expensive devices to measureJPD and to nredict dronlet size.

Dot Size Thermal Objects Detection in Atmosphere of Infrared Range

The article deals with the experimental studies of atmosphere indistinct radiation structure. The information extraction background of dot size thermal object presence in atmosphere is reasonable. Indistinct generalization of experimental study regularities technique of space-time irregularity radiation structure in infrared wave range is offered. The approach to dot size thermal object detection in atmosphere is proved with a help of threshold method in the thermodynamic and turbulent process conditions, based on the indistinct statement return task solution.

Intrinsic mode characteristic analysis and extraction in underwater cylindrical shell acoustic radiation

Target dimension is important information in underwater target classification. An intrinsic mode characteristic extraction method in underwater cylindrical shell acoustic radiation was studied in this paper based on the mechanism of shell vibration to gain the information about its dimension instead of accurate inversion processing. The underwater cylindrical shell vibration and acoustic radiation were first analyzed using mode decomposition to solve the wave equation. The characteristic of acoustic radiation was studied with different cylindrical shell lengths, radii, thickness, excitation points and fine structures. Simulation results show that the intrinsic mode in acoustic radiation spectrum correlates closely with the geometry dimensions of cylindrical shells. Through multifaceted analysis, the strongest intrinsic mode characteristic extracted from underwater shell acoustic radiated signal was most likely relevant to the radiated source radius. Then, partial information about unknown source dimension could be gained from intrinsic mode characteristic in passive sonar applications for underwater target classification. Experimental data processing results verified the effectiveness of the method in this paper.

An adaptive tensor voting algorithm combined with texture spectrum

An adaptive tensor voting algorithm combined with texture spectrum is proposed. The image texture spectrum is used to get the adaptive scale parameter of voting field. Then the texture information modifies both the attenuation coefficient and the attenuation field so that we can use this algorithm to create more significant and correct structures in the original image according to the human visual perception. At the same time, the proposed method can improve the edge extraction quality, which includes decreasing the flocculent region efficiently and making image clear. In the experiment for extracting pavement cracks, the original pavement image is processed by the proposed method which is combined with the significant curve feature threshold procedure, and the resulted image displays the faint crack signals submerged in the complicated background efficiently and clearly.

Maximal-overlap adaptive multiwavelet for detecting transient vibration responses from dynastic signal of rotating machineries

Vibration signal is an important prerequisite for mechanical fault detection. However, early stage defect of rotating machiner- ies is difficult to identify because their incipient energy is interfered with background noises. Multiwavelet is a powerful tool used to conduct non-stationary fault feature extraction. However, the existing predetermined multiwavelet bases are independ- ent of the dynamic response signals. In this paper, a constructing technique of vibration data-driven maximal-overlap adaptive multiwavelet （MOAMW） is proposed for enhancing the extracting performance of fault symptom. It is able to derive an opti- mal multiwavelet basis that best matches the critical non-stationary and transient fault signatures via genetic algorithm. In this technique, two-scale similarity transform （TST） and symmetric lifting （SymLift） scheme are combined to gain high designing freedom for matching the critical faulty vibration contents in vibration signals based on the maximal fitness objective. TST and SymLift can add modifications to the initial multiwavelet by changing the approximation order and vanishing moment of mul- tiwavelet, respectively. Moreover, the beneficial feature of the MOAWM lies in that the maximal-overlap filterbank structure can enhance the periodic and transient characteristics of the sensor signals and preserve the time and frequency analyzing res- olution during the decomposition process. The effectiveness of the proposed technique is validated via a numerical simulation as well as a rolling element beating with an outer race scrape and a gearbox with rub fault.