• 分析了切削硬岩时的刀具磨损和破损特征。

    The wear and rupture of cutting tool are investigated.

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  • 盾构刀具磨损原因探析。

    Causes of tool wear shield.

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  • 它生成很差的表面光洁性且刀具磨损非常大。

    It produces a poor surface finish; tool wear is high.

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  • 研究了钻削过程中刀具磨损特征信号的提取。

    The problem of extracting drilling tool wears character signal is studied.

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  • 介绍了一种螺杆铣削过程刀具磨损建模的方法。

    Tool wear modeling method for spiral rod milling is presented.

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  • 可听阈内的切削声信号包含着丰富的刀具磨损信息。

    The cutting sound signal in audible range includes a plenty of tool-wear information.

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  • 刀具磨损、破损的在线监控是FMS的基本功能之一。

    The on-line monitoring of tool wear and breakage is one of the basic functions of FMS.

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  • 刀具磨损状态自动识别系统能够显著地降低制造成本。

    Systems for automatic tool wear monitoring contribute to measures to reduce manufacturing costs considerably.

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  • 刀具磨损在生产实践中和在理论上都是十分重要的课题。

    In practical machining operations and in theory the tool-wear is an important problem.

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  • 良好的极压、抗磨损性能,减少刀具磨损,延长刀具寿命。

    Good extreme pressure, abrasion resistance, reduce the tool wear, extending the service life of cutter.

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  • 本文详细地分析了刀具磨损的形貌后,提出了相应的建议。

    In this paper the wear morphology of tool is analysed in detail and then concerned Suggestions are hereupon recommended.

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  • 为了更好地研究现代刀具,将分形理论引入刀具磨损研究。

    The fractal theory is introduced into the wear investigation of cutting tool for studying the modern tool.

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  • 研究木工刀具磨损特性的目的就在于优化木材切削加工技术。

    The aim to investigate the tools wear characteristics is to optimize the processing technology in Machining wood and wood based materials.

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  • 提出采用切削力信号的奇异性指数作为衡量刀具磨损的参量。

    The singular index of cutting force signal is proposed as a parameter for detecting cutter's wear.

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  • 随着刀具磨损的增加,振动信号的振幅增大,振动能量亦相应增加。

    With the increment of tool wear, the signal magnitude increases and the vibration energy increases correspondingly.

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  • 刀具磨损、破损自动检测技术,在现代制造行业具有广泛的应用前景。

    The automatic measuring technique of tool breakage and wear will be more and more important in production.

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  • 介绍一种以PC机为后台,以双单片机为前台的刀具磨损状态识别系统。

    An application of PC and microcontroller in the system for tool wear detection is introduced.

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  • 针对异型螺杆铣削加工,采用振动信号特征值作为检测刀具磨损的参量。

    The characteristic values of vibration signals were used as testing parameters of tool wear for milling special shaped spiral rods.

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  • 本文结合实际工程对运用掘进参数检测刀具磨损的方法进行了探索研究。

    The method estimating the cutter wear by analyzing the tunneling parameters is presented in this paper.

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  • 本文以图像分析理论为基础,针对切屑形态识别和刀具磨损检测进行了研究。

    In this paper based on image analysis theory the chip shape recognition and tool wear inspecting were analyzed and studied.

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  • 硬质相颗粒的脱落是干式高速车铣D60钢时金属陶瓷刀具磨损的主要原因。

    The main reason of ceramic tool Wearing is coming off the hard grain during the dry cutting of steel D60.

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  • 在研究刀具磨损时,必须准确方便地确定出刀具磨损的测量部位和测量基准。

    And it is necessary to specify accurately and conveniently the locations and the base of measuring toolwear when the toolwear is studied.

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  • 在切削实验中,可对切屑厚度、刀具磨损及螺纹等的形貌进行观察并测量其尺寸。

    In cutting experiments, it can be observed and measured that the chip thickness, the tool wear, the screw thread teeth, and so on.

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  • 介绍了基于突变论的方法建立刀具磨损与破损失效寿命模型的可行性的研究结果。

    The Paper Presents a feasible study of modeling on tool life for the failure modes of tool wear and fracture based on methods of catastrophe theory.

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  • 针对传统刀具磨损检测的缺点,设计了一套结合图像处理的方法来检测磨损的方案。

    A method combined with image manipulation is contrived to detect the project of wear, which aim at the shortage of inspection of conventional tools wear.

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  • 导电加热切削时,由于强烈的电热效应,刀具磨损形态与传统切削加工方法有所不同。

    The wear form of cutting tools in electric hot machining (EHM) is different from that of conventional cutting due to strong electric and thermal effects.

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  • 找出刀具磨损信息在可听阈内的主要集中频段能提高切削声信号的信噪比,改善识别结果。

    Finding out the major concentrated frequency band of tool-wear information can enhance SNR (Signal Noise Ratio) and improve tool-wear degree recognition result.

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  • 找出刀具磨损信息在可听阈内的主要集中频段能提高切削声信号的信噪比,改善识别结果。

    Finding out the major concentrated frequency band of tool-wear information can enhance SNR (Signal Noise Ratio) and improve tool-wear degree recognition result.

    youdao

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