JRF33铁路车号识别装置在矿车计数系统的应用

针对采厂矿车翻卸人工计数可靠性低、安全风险大等问题，提出一种矿车翻卸自动计数系统设计方案，以JRF33铁路车号识别装置为载体，以RS485为通讯协议，对采集数据进行统计分析。结果显示，计数系统运行良好，翻卸数据采集及时、准确、完整。系统对采矿原料运输数据统计、分析应用和生产指导有一定的指导意义。     

无浮标式自动排渣放水器的设计

现有浮标式自动排渣放水器在使用过程中,煤渣含量较高时,自动排渣放水器内部为多相混合介质,影响浮标动作,严重时会使自动排渣放水器失效。针对所存在的问题,设计了一种无浮标式自动排渣放水器。对这一自动排渣放水器的结构和工作原理进行了介绍,对自动排渣放水器状态和移动容器受力进行了分析,并进行了试验验证。     

Learning and revision in cognitive robotics disassembly automation

Disassembly is a key step for an efficient treatment of end-of-life (EOL) products. A principle of cognitive robotics is implemented to address the problem regarding uncertainties and variations in the automatic disassembly process. In this article, advanced behaviour control based on two cognitive abilities, namely learning and revision, are proposed. The knowledge related to the disassembly process of a particular model of product is learned by the cognitive robotic agent (CRA) and will be implemented when the same model has been seen again. This knowledge is able to be used as a disassembly sequence plan (DSP) and disassembly process plan (DPP). The agent autonomously learns by reasoning throughout the process. In case of an unresolved condition, human assistance is given and the corresponding knowledge will be learned by demonstration. The process can be performed more efficiently by applying a revision strategy that optimises the operation plans. As a result, the performance of the process regarding time and level of autonomy are improved. The validation was done on various models of a case-study product, Liquid Crystal Display (LCD) screen.     

汽车路况网的进一步研究

汽车路况网的概念源于数字城市的概念,通过研究网络、实时数据库和汽车智能,实现安全的交通网络。研究的语言一般应用Lisp语言,数据库为实时数据库。     

A probabilistic load shedding concept considering highly volatile local generation

Automatic load shedding is the ultimate countermeasure against imbalance in a power system and can effectively help preventing large blackouts. Taking into account a high penetration of renewable energy sources (RES) in the distribution grid, a clear distinction between load and generation at the PCC becomes increasingly more difficult. For that reason an adaptation of frequency relay parameters and their locations of installation are necessary. In Europe this is rest on a multi-step plan based on values such as the yearly peak load. In this paper a novel probabilistic method for automatic load shedding is presented that uses the average values instead of peak values for load shedding. Its applicability is verified by a dynamic power system model that was developed to compare the classical and novel probabilistic load shedding principle. The method is verified using data from a German TSO.     

How to predict the global instantaneous feeling induced by a facial picture?

Picture selection is a time-consuming task for humans and a real challenge for machines, which have to retrieve complex and subjective information from image pixels. An automated system that infers human feelings from digital portraits would be of great help for profile picture selection, photo album creation or photo editing. In this work, two models of facial pictures evaluation are defined. The first one predicts the overall aesthetic quality of a facial image, and the second one answers the question “Among a set of facial pictures of a given person, on which picture does the person look like the most friendly?”. Aesthetic quality is evaluated by the computation of 15 features that encode low-level statistics in different image regions (face, eyes, and mouth). Relevant features are automatically selected by a feature ranking technique, and the outputs of 4 learning algorithms are fused in order to make a robust and accurate prediction of the image quality. Results are compared with recent works and the proposed algorithm obtains the best performance. The same pipeline is considered to evaluate the likability of a facial picture, with the difference that the estimation is based on high-level attributes such as gender, age, and smile. Performance of these attributes is compared with previous techniques that mostly rely on facial keypoint positions, and it is shown that it is possible to obtain likability predictions that are close to human perception. Finally, a combination of both models that selects a likable facial image of good quality for a given person is described.     

Condition assessment for automatic tool changer based on sparsity-enabled signal decomposition method

Automatic tool changer (ATC) is one of the key basic parts in CNC machining centers, and the globoidal indexing cam and the groove cam are the functional units for tool changing. Thus the condition monitoring is important for highly efficient and precision machining. In this paper, a condition monitoring system is constructed for the ATC, especially for the globoidal indexing cam, including vibration signal acquisition, fault feature extraction and localization, and condition assessment. In the constructed system, sparsity-enabled signal decomposition method is introduced to extract transient component and reduce noises in the complex vibration signals, and the transient component is always a key feature for fault localization. Simulation study shows that the sparsity-enabled signal decomposition method is effective in transient feature extraction. The experimental application in condition assessment for the ATC demonstrates that the constructed condition monitoring system has the potential to assess the working condition of the ATC in practical application.     

Kinetic parameter estimation for cooling crystallization process based on cell average technique and automatic differentiation

In this paper, a cell average technique(CAT) based parameter estimation method is proposed for cooling crystallization involved with particle growth, aggregation and breakage, by establishing a more efficient and accurate solution in terms of the automatic differentiation(AD) algorithm. To overcome the deficiency of CAT that demands high computation cost for implementation, a set of ordinary differential equations(ODEs) entailed from CAT based discretized population balance equation(PBE) are solved by using the AD based high-order Taylor expansion. Moreover, an AD based trust-region reflective(TRR) algorithm and another interior-point(IP) algorithm are established for estimating the kinetic parameters associated with particle growth, aggregation and breakage. As a result, the estimation accuracy can be further improved while the computation cost can be significantly reduced, compared to the existing algorithms. Benchmark examples from the literature are used to illustrate the accuracy and efficiency of the AD-based CAT, TRR and IP algorithms in comparison with the existing algorithms. Moreover, seeded batch cooling crystallization experiments of β form L-glutamic acid are performed to validate the proposed method.     

自动电位滴定仪示值误差测量不确定度评定

按照JJG 814-2015规定,自动电位滴定仪需进行电计示值误差和仪器示值误差检定,本文例举对这两项检定结果进行不确定度评定,供相关人员参考。     

全自动凯氏定氮仪测定蛋白质(以N计)不确定度分析与探讨

目的:用全自动凯氏定氮仪测定蛋白质(以N计)不确定度进行分析与探讨。方法 :采用GB 5009.5-2016第一法凯氏定氮法测定蛋白质(以N计)含量,建立数学模型,通过对各个不确定度分量的计算合成,找出影响测量不确定度的因素,最终得出样品中蛋白质(以N计)含量的扩展不确定度与合成标准不确定度。结果:蛋白质(以N计)含量测定的扩展不确定度为(20.93±0.25)%,k=2。结论:采用JJF 1059.1-2012《测量不确定度评定与表示》,对不确定度进行评定,确保蛋白质(以N计)含量结果的准确性。