Abstract: A method and system for inspecting deviation in dynamic characteristics of a feeding system are provided, and the method includes: exciting the feeding system and detecting vibrations of a subcomponent of a component to be inspected of the feeding system to generate a monitoring excitation signal in a monitoring mode; calculating, by a modal analysis method, monitoring eigenvalues and monitoring eigenvectors of the monitoring excitation signal; determining, by a modal verification method, similarity between the monitoring eigenvalues and standard eigenvalues of a digital twin model and similarity between the monitoring eigenvectors and standard eigenvectors of the digital twin model; determining that the dynamic characteristics of the subcomponent are deviated, when the monitoring eigenvalues and monitoring eigenvectors are not similar to the standard eigenvalues and standard eigenvectors. Therefore, the subcomponent whose dynamic characteristics are deviated can be sensed remotely and precisely.

Abstract: A sensor placement optimization device is provided, which may include a preprocessing circuit and an operational circuit. The preprocessing circuit may perform a pre-process for the sensing signals of a plurality of temperature sensors, installed on a machine tool, to generate a pre-processed data. The operational circuit may execute a normalization for the pre-processed data to generate a normalized data, perform a principal component analysis for the normalized data to generate a dimensionality-reduced data and implement a principal component regression for the dimensionality-reduced data to obtain the contributions of the temperature sensors. Then, the operational circuit may rank the temperature sensors according to the contributions thereof to generate a ranking result and execute a screening process according to the ranking result to select at least one redundant sensor from the temperature sensors; afterward, the operational circuit may remove the redundant sensor from the temperature sensors.

Abstract: A method and system for inspecting deviation in dynamic characteristics of a feeding system are provided, and the method includes: exciting the feeding system and detecting vibrations of a subcomponent of a component to be inspected of the feeding system to generate a monitoring excitation signal in a monitoring mode; calculating, by a modal analysis method, monitoring eigenvalues and monitoring eigenvectors of the monitoring excitation signal; determining, by a modal verification method, similarity between the monitoring eigenvalues and standard eigenvalues of a digital twin model and similarity between the monitoring eigenvectors and standard eigenvectors of the digital twin model; determining that the dynamic characteristics of the subcomponent are deviated, when the monitoring eigenvalues and monitoring eigenvectors are not similar to the standard eigenvalues and standard eigenvectors. Therefore, the subcomponent whose dynamic characteristics are deviated can be sensed remotely and precisely.

Abstract: A method and a system for building digital twin models allow the setting of a shape and dimensions of a simplified geometric solid corresponding to a component of a feeding system; after sampling the solid to obtain second position data, calculates a set of model eigenvalues and a set of model eigenvectors by a modal analysis method according to a material data of the component, the second position data and second size data of the solid; and defines the solid as a digital twin model of the component when it is determined by a modal verification method that a set of actual eigenvectors of the component is similar to the set of model eigenvectors. Data amounts of the second position and size data are far less than data amounts of first position and size data of an image of the component.

Abstract: A sensor placement optimization device is provided, which may include a preprocessing circuit and an operational circuit. The preprocessing circuit may perform a pre-process for the sensing signals of a plurality of temperature sensors, installed on a machine tool, to generate a pre-processed data. The operational circuit may execute a normalization for the pre-processed data to generate a normalized data, perform a principal component analysis for the normalized data to generate a dimensionality-reduced data and implement a principal component regression for the dimensionality-reduced data to obtain the contributions of the temperature sensors. Then, the operational circuit may rank the temperature sensors according to the contributions thereof to generate a ranking result and execute a screening process according to the ranking result to select at least one redundant sensor from the temperature sensors; afterward, the operational circuit may remove the redundant sensor from the temperature sensors.

Abstract: A machine tool health monitoring method which is to use a predetermined plurality of vibration sensors on a plurality of components of a machine tool and to drive motors of the machine tool to excite the machine tool using an electronic device while the health status of the machine tool is good, and then to perform a diagnostic process to obtain a characteristic cluster consisting of a plurality of modals, and then to define the characteristic cluster as a sample health characteristic cluster. The diagnostic process includes the procedures of vibration transmissibility obtaining, singular value decomposition, curve fitting and modal establishing. In addition, excite the machine tool and proceed the diagnosis process to obtain a current health characteristic cluster. Finally, the current health characteristic cluster is compared with the sample health characteristic cluster to judge whether the machine tool is healthy or not.

Abstract: A machine tool health monitoring method which is to use a predetermined plurality of vibration sensors on a plurality of components of a machine tool and to drive motors of the machine tool to excite the machine tool using an electronic device while the health status of the machine tool is good, and then to perform a diagnostic process to obtain a characteristic cluster consisting of a plurality of modals, and then to define the characteristic cluster as a sample health characteristic cluster. The diagnostic process includes the procedures of vibration transmissibility obtaining, singular value decomposition, curve fitting and modal establishing. In addition, excite the machine tool and proceed the diagnosis process to obtain a current health characteristic cluster. Finally, the current health characteristic cluster is compared with the sample health characteristic cluster to judge whether the machine tool is healthy or not.

Abstract: A device for monitoring healthy status of machinery mounts is provided, which may include a plurality of vibration detectors, a signal acquisition device and a signal processor. The vibration detectors may detect the vibration signals from of a machine device, where the machine device may include a plurality of machinery mounts. The signal acquisition device may receive the vibration signals of the vibration detectors. The signal processor may execute a modal frequency analysis process to analyze the vibration signals of the vibration detectors, and calculate a vibration mode corresponding to the natural frequency of the machinery mounts in current status to serve as the test mode; then, the signal processor may compare the test mode with a reference mode to determine the healthy status of the machinery mounts, where the reference mode is corresponding to the natural frequency of the machinery mounts in the optimized status.

Abstract: A method for estimating a variation in a preload applied to a linear guideway of a machine tool includes steps of: a) obtaining, via each of vibration sensors, first and second vibration signals that are generated according to detection of vibration of a table disposed on the linear guideway respectively at first and second time instants; b) determining, via the computation module, first and second natural frequencies based on a theoretical mode shape and respectively on the first and second vibration signals; and c) determining, via the computation module, the variation in the preload based on the first and second natural frequencies.

Abstract: A device for monitoring healthy status of machinery mounts is provided, which may include a plurality of vibration detectors, a signal acquisition device and a signal processor. The vibration detectors may detect the vibration signals from of a machine device, where the machine device may include a plurality of machinery mounts. The signal acquisition device may receive the vibration signals of the vibration detectors. The signal processor may execute a modal frequency analysis process to analyze the vibration signals of the vibration detectors, and calculate a vibration mode corresponding to the natural frequency of the machinery mounts in current status to serve as the test mode; then, the signal processor may compare the test mode with a reference mode to determine the healthy status of the machinery mounts, where the reference mode is corresponding to the natural frequency of the machinery mounts in the optimized status.

Abstract: A spindle speed adjusting device in machining is provided, which may include a plurality of signal detection modules, a signal capturing module and a signal processing module. Each of the signal detection modules may keep measuring the vibration signals in machining. The signal capturing module may capture the vibration signals. The signal processing module may execute a transmissibility analysis to obtain the transmissibility between the signal detection modules, and execute a frequency response fitting according to the transmissibility to obtain a plurality of system dynamic parameters, and then execute a stability lobe diagram analysis to calculate the optimized spindle speed of the machining tool so as to make the machining tool operate at the optimized spindle speed. The signal processing module may repeatedly execute the transmissibility analysis, the frequency response fitting and the stability lobe diagram analysis to keep updating the optimized spindle speed until the machining process ends.

Abstract: A method for estimating a variation in a preload applied to a linear guideway of a machine tool includes steps of: a) obtaining, via each of vibration sensors, first and second vibration signals that are generated according to detection of vibration of a table disposed on the linear guideway respectively at first and second time instants; b) determining, via the computation module, first and second natural frequencies based on a theoretical mode shape and respectively on the first and second vibration signals; and c) determining, via the computation module, the variation in the preload based on the first and second natural frequencies.

Abstract: A spindle speed adjusting device in machining is provided, which may include a plurality of signal detection modules, a signal capturing module and a signal processing module. Each of the signal detection modules may keep measuring the vibration signals in machining. The signal capturing module may capture the vibration signals. The signal processing module may execute a transmissibility analysis to obtain the transmissibility between the signal detection modules, and execute a frequency response fitting according to the transmissibility to obtain a plurality of system dynamic parameters, and then execute a stability lobe diagram analysis to calculate the optimized spindle speed of the machining tool so as to make the machining tool operate at the optimized spindle speed. The signal processing module may repeatedly execute the transmissibility analysis, the frequency response fitting and the stability lobe diagram analysis to keep updating the optimized spindle speed until the machining process ends.

Abstract: A system for the monitoring a preload in a ball screw includes a ball screw, a detecting device, a capturing device and a processing device. The ball screw has a preload. The detecting device detects an operating signal of the ball screw. The operating signal contains information about the ball screw's rotating speed and status. The status refers to a vibration or a sound generated by the operating ball screw. The capturing device is connected to the detecting device and acquires the operating signal. The processing device is connected to the capturing device, and has a threshold. The processing device processes and converts the operating signal into a ball-passing signal. When the ball-passing signal surpasses the threshold, the processing device determines that the ball screw's preload has vanished. Thereby, the system is enabled to determine the current state of the ball screw's preload reliably.

Abstract: A method of detecting a preload of a ball screw is to acquire an operational signal of the ball screw, to process the operational signal via a theoretical ball pass order and an order tracking analysis procedure to acquire an actual ball pass order, to compare and judge the relationship between the actual ball pass order and the theoretical ball pass order via a preload judgment procedure, and finally to observe the proportion of occurrence of side band of the actual ball pass order to determine the preload status of the ball screw.

Abstract: A mechanism for suppressing grinding-cutting vibration comprises a C-shaped base, a fixed support seat, a clamp device and a vibration absorber. Based on vibration absorbing principle of the vibration theory, the clamp device is connected to the movable cutting machine, so as to move along with the cutting machine during the machining operation, and the clamp force applied to clamp the workpiece is adjustable. By such arrangements, the vibration energy produced at the time of cutting the workpiece can be transferred to the vibration absorber through the clamp device, and then a part of the vibration energy will be absorbed by the vibration absorber, thus achieving the objective of reducing vibration of the cut position.

Abstract: A mechanism for suppressing grinding-cutting vibration comprises a C-shaped base, a fixed support seat, a clamp device and a vibration absorber. Based on vibration absorbing principle of the vibration theory, the clamp device is connected to the movable cutting machine, so as to move along with the cutting machine during the machining operation, and the clamp force applied to clamp the workpiece is adjustable. By such arrangements, the vibration energy produced at the time of cutting the workpiece can be transferred to the vibration absorber through the clamp device, and then a part of the vibration energy will be absorbed by the vibration absorber, thus achieving the objective of reducing vibration of the cut position.