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公开(公告)号:US12030152B2
公开(公告)日:2024-07-09
申请号:US17269904
申请日:2019-08-19
申请人: Blum-Novotest GmbH
发明人: Steffen Stauber , Bruno Riedter
IPC分类号: G05B19/4065 , B23Q17/24 , B23Q17/00 , B23Q17/22 , G01B11/02 , G01B11/08 , G01B11/24 , G05B19/18
CPC分类号: B23Q17/2485 , G05B19/4065 , B23Q17/00 , B23Q17/22 , B23Q17/24 , G01B11/02 , G01B11/08 , G01B11/2433 , G05B19/18 , G05B2219/37415
摘要: A method for checking a tool uses a device with a light emitter for beam emission for tool scanning and with a beam receiver for beam reception and for outputting a shadow signal; and an evaluation unit for processing the shadow signal; rotation of the tool; moving the tool until it reaches a starting position in which the blade dips into the beam and shades this such that a threshold of a range of the evaluation unit is reached or undershot; moving the tool, starting from the starting position, out of the beam and registering the shadow signal; ascertaining that the shadow signal for a cutting edge does not fall below the lower switching threshold or exceed the upper switching threshold such that a shadow signal lies above the lower and below the upper switching threshold; wherein the feed is determined in proportion to a measurement range.
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公开(公告)号:US12030149B2
公开(公告)日:2024-07-09
申请号:US17303545
申请日:2021-06-02
申请人: FRANZ KESSLER GMBH
发明人: Joachim Van Sprang , Harald Weing , Daniel Weiß
IPC分类号: B23Q17/09 , G01L5/00 , G05B19/4065 , B23B49/00
CPC分类号: B23Q17/0966 , G01L5/0076 , G05B19/4065 , B23B49/00 , G05B2219/37355
摘要: A method for sensing a cutting-edge load in a motor-driven machine-tool unit having a stator unit and a rotor unit that is rotatable at least about an axis of rotation. The rotor unit includes a tool receiving unit that is adjustable along the axis of rotation and to which a clamping force can be applied, for fixing and clamping a releasably fixable tool shank of a tool. A tool head of the tool includes at least one individual cutting edge. A tool sensor is provided for sensing the load on the tool, the tool sensor being realized as an individual-cutting-edge sensor for sensing a cutting-edge load on the individual cutting edge.
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3.
公开(公告)号:US20240118673A1
公开(公告)日:2024-04-11
申请号:US18463351
申请日:2023-09-08
申请人: SORALINK SOLUTIONS
发明人: Hsin-Yun YAO , Jean-Samuel CHENARD
IPC分类号: G05B19/4065
CPC分类号: G05B19/4065 , G05B2219/34477
摘要: Sensor and method for performing industrial machinery monitoring based on sensor data processing by a machine learning algorithm. The sensor stores a predictive model of the machine learning algorithm and receives measurements generated by at least one sensing component of the sensor. For example, the measurements comprise one or more of the following: a temperature of an industrial machine, a measurement of a vibration of the industrial machine, and a sound intensity of the industrial machine. The sensor executes the machine learning algorithm, which uses the predictive model for inferring output(s) based on inputs. The output(s) comprise at least one predicted operating condition of the industrial machine (e.g. a predicted failure). The inputs comprise at least some of the measurements. The machine learning algorithm may implement a neural network. The predictive model may be updated based on feedback generated by the sensor or received from another device.
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公开(公告)号:US20240077846A1
公开(公告)日:2024-03-07
申请号:US18241415
申请日:2023-09-01
发明人: Christoph Wüstner
IPC分类号: G05B19/4065
CPC分类号: G05B19/4065 , G05B2219/37252 , G05B2219/50276
摘要: A method for predicting a service state of a printing machine at a defined point in time includes:
measuring a plurality of successive process values of a process parameter which is an indicator of the functionality of the printing machine;
determining a plurality of successive scatter values which describe the spread of the measured process values within a predetermined time range;
determining a local scatter minimum of the scatter values;
determining a baseline, in that a baseline value is established that correlates with the value of the process parameter at the point in time of the local minimum and that does not change up until a new determination of a baseline; and
determining a health value at a specific point in time, with a predetermined relation of the process value to the baseline value at this point in time. A service state is assessed
upon the health value exceeding a predetermined threshold.-
5.
公开(公告)号:US20240061396A1
公开(公告)日:2024-02-22
申请号:US18498974
申请日:2023-10-31
发明人: Qingqing Huang , Yan Han , Zhen Kang , Yan Zhang , Ping Wang
IPC分类号: G05B19/4065
CPC分类号: G05B19/4065 , G05B2219/37252 , G05B2219/32335 , G05B2219/37434
摘要: Disclosed is a prediction method for tool remaining life of a numerical control machine tool based on a hybrid neural model, including: constructing a hybrid neural network model, specifically including the following steps: constructing sample data according to the sampling frequency of tool data; obtaining a first feature vector representing the tool life by utilizing a convolutional neural network and a long short-term memory network; generating working condition signals of sampling points into a second feature vector representing the tool life by utilizing an NFM neural network; and inputting a current working time of a tool and the acquired feature vectors into a multi-layer perceptron for fusion to predict the tool life.
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公开(公告)号:US11892816B2
公开(公告)日:2024-02-06
申请号:US17449261
申请日:2021-09-29
发明人: Cheng-Sung Lai
IPC分类号: G05B19/4065
CPC分类号: G05B19/4065 , G05B2219/14071
摘要: A method of operating a testing system comprising a plurality of testing slots. The method comprising: testing the testing slots; obtaining a current testing data from the testing slots; determining whether one of the testing slots is abnormal by comparing the current testing data with a former testing data; shutting down the one of the testing slots and sending a repairing notification if the one of the testing slots is determined to be abnormal; performing a confirmation procedure to determine whether the one of the testing slots is repaired to be normal; and restarting the one of the testing slots if the one of the testing slots passes the confirmation procedure.
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公开(公告)号:US11883920B2
公开(公告)日:2024-01-30
申请号:US17304001
申请日:2021-06-11
发明人: Ya-Chen Hsu , Yu-Ming Huang , Yei-Gei Chen , Kuan-Ting Kuo , Shiang-Chi Chen , Po-Hsiu Ko
IPC分类号: B24B11/04 , B24B49/18 , G05B19/4065
CPC分类号: B24B11/04 , B24B49/18 , G05B19/4065 , G05B2219/32201
摘要: A prognostic and health management system for precision ball grinding machines includes: a detector connected to a first and a second grinding discs; and a central processing module including a determining unit, a historical data recording unit, a timing unit, and an alarm unit. The detector is connected to the determining unit, detects data of the two grinding discs, and sends the data to the determining unit, the determining unit compares data in the historical data recording unit to determine whether the first and second grinding discs are abnormal, if there is an abnormality, the alarm unit releases a warning signal, if the determining unit determines that there is no abnormality, the timing unit records a grinding time of the first and second grinding discs, and based on a comparison of the past records, the alarm unit releases a warning signal after a predetermined time has elapsed.
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公开(公告)号:US20230384758A1
公开(公告)日:2023-11-30
申请号:US17845139
申请日:2022-06-21
申请人: TECOM CO., LTD.
发明人: Kuo-Chuan HUNG
IPC分类号: G05B19/4065
CPC分类号: G05B19/4065 , G05B2219/35519
摘要: An integrated system for customized machine tool detection is disclosed in the present invention. The integrated system includes a communication module, a database, a display module, an operation interface, and an integrated module. The integrated system for customized machine tool detection is utilized to save a plurality of machine tool detection sub-systems with a first protocol, make a user choose at least one machine tool detection sub-systems to be a customized machine tool detection system to detect a working machine tool.
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公开(公告)号:US20230341829A1
公开(公告)日:2023-10-26
申请号:US18210700
申请日:2023-06-16
发明人: Brian E. Brooks , Gilles J. Benoit , Peter O. Olson , Tyler W. Olson , Himanshu Nayar , Frederick J. Arsenault , Nicholas A. Johnson
IPC分类号: G05B13/04 , G05B13/02 , G06N5/043 , G05B23/02 , G06N5/046 , G05B19/4065 , G05B19/418 , G06Q10/0631 , G06Q10/0639 , G06Q30/0202 , B60W40/064 , B60W40/08 , B60W40/105 , G06F18/21 , G06N7/01
CPC分类号: G05B13/042 , G05B13/0265 , G06N5/043 , G05B13/024 , G05B23/0229 , G06N5/046 , G05B19/4065 , G05B19/41835 , G05B13/041 , G06Q10/06315 , G06Q10/06395 , G06Q30/0202 , B60W40/064 , B60W40/08 , B60W40/105 , G05B13/021 , G06F18/2193 , G06N7/01 , G05B2219/36301 , G06Q10/087
摘要: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining causal models for controlling environments. One of the methods includes obtaining data specifying baseline probability distributions for each of a plurality of controllable elements; maintaining a causal model; repeatedly performing the following: selecting control settings for the environment based on the causal model and values for a particular internal parameter of the control system that are sampled from a range of possible values; selecting control settings for the environment based on the baseline probability distributions; monitoring environment responses to the control settings selected based on the causal model and the control settings selected based on the baseline probability distributions; determining, for each of the possible values, a measure of a difference between a current system performance and a baseline system performance; and updating how frequently each of the possible values is sampled.
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公开(公告)号:US11790700B2
公开(公告)日:2023-10-17
申请号:US16927354
申请日:2020-07-13
申请人: OKUMA CORPORATION
发明人: Hiroshi Ueno
IPC分类号: G07C3/08 , G06N20/00 , G05B19/18 , G05B19/4065
CPC分类号: G07C3/08 , G05B19/182 , G05B19/4065 , G06N20/00
摘要: A relearning necessity determination method is provided for determining a necessity of relearning of a learned diagnostic model in a machine tool including a machining abnormality diagnosing unit. The machining abnormality diagnosing unit determines normal or abnormality of machining using the diagnostic model generated through machine learning. The method includes storing a cumulative cutting time or a cumulative cutting distance of a tool mounted to the machine tool as a tool usage, storing the tool usage when the machining abnormality diagnosing unit diagnoses the machining as machining abnormality, and determining the necessity of the relearning of the diagnostic model based on a frequency distribution of the tool usage stored in the storing of the tool usage.
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