Abstract:
The machine learning apparatus includes: a state data observing unit which observes state data of the laser apparatus, including data output from a reflected light detecting unit for measuring a reflected light amount; an operation result acquiring unit which acquires a success/failure result indicating whether the machining has been started successfully by the laser beam output from a laser oscillator; a learning unit which learns light output command data by associating the light output command data with the state data of the laser apparatus and the success/failure result of the machining start; and a decision making unit which determines the light output command data by referring to the light output command data learned by the learning unit.
Abstract:
A laser apparatus includes laser diode module groups (LDMGs) and power supply units and provides a laser light source by collecting laser beam from the LDMGs, and comprises: a driving current supply circuit network for injecting the driving currents into the respective LDMGs, independently; a control unit which controls the driving currents independently; a first recording unit in which are recorded data representing a relationship between the driving current and optical output power, and data representing a relationship between the driving current and drive voltage; and a first calculating unit which calculates the driving currents to be allocated to the LDMGs so as to achieve maximum electrical to optical conversion efficiency, wherein the control unit allocates the driving currents to the LDMGs in accordance with the results calculated by the first calculating unit so that the LDMGs as a whole can achieve maximum electrical to optical conversion efficiency under conditions.
Abstract:
An optical power monitoring device detects an optical power propagating through an optical fiber including at least a core and a cladding. The optical power monitoring device includes: a first optical fiber; a second optical fiber having a larger core diameter than the first optical fiber; a connection part where an end surface of the first optical fiber and an end surface of the second optical fiber are spliced; a first leakage part for leakage of a beam from the first optical fiber to the outside; a second leakage part for leakage of a beam from the second optical fiber to the outside; a first photodetector that detects an optical power leaking from the first leakage part; and a second photodetector that detects an optical power leaking from the second leakage part.
Abstract:
A laser device provided with the function of predicting occurrence of condensation and preventing occurrence of condensation in advance. The laser device is provided with a controlling part calculating a reference temperature for judging whether a cooling water feed device may feed cooling water based on a temperature measured by a thermometer and a humidity measured by a hygrometer, and a comparing part comparing a reference temperature and a cooling water temperature. The cooling water feed device is configured to stop the feed of cooling water after a command for starting up the laser oscillator has been output and the cooling water temperature is lower than the reference temperature and to start or continue the feed of cooling water when the cooling water temperature is the reference temperature or more.
Abstract:
A fiber laser apparatus includes a fiber laser oscillator that performs laser oscillation with laser light from at least one laser diode module, and includes a loop-shaped optical fiber formed with: a combiner in which at least two input side optical fibers are connected to one output side optical fiber that includes one output end; and an optical fiber for connection of both ends in which the output end of the output side optical fiber is connected to the input end of any one of the input side optical fibers, the optical fiber for connection of both ends including a light leakage means formed such that at least one of values among a numerical aperture, a core diameter and a mode field diameter of the optical fiber for connection of both ends is gradually reduced from a side which is connected to the output end toward a side which is connected to the input end.
Abstract:
A machine learning device is connected to a fiber laser device. The machine learning device observes, as a state variable representing a driving state of the fiber laser device, a state quantity including time-series data on output light detection results obtained by detecting a light output of laser light emitted from the fiber laser device and time-series data on reflected light detection results obtained by detecting reflected light of the laser light, and acquires determination data representing a failure occurrence situation in the fiber laser device as determined from a difference between the output light detection results and a light output instruction of the fiber laser device. The machine learning device learns a boundary condition for failure occurrence caused by the reflected light by using the state variable and the determination data.
Abstract:
A laser system having an automatic diagnosis function enabling a plurality of laser diodes to be diagnosed for faults in a short time.The laser system includes a judging part judging the presence of a fault or deterioration of a component of the laser system. The judging part is configured to judge the presence of a fault or deterioration of a component of the laser system based on the results of detection of a first photodetection part and second photodetection part when successively driving a plurality of laser diode module groups included in an individual laser oscillation unit so that the mutual drive times do not overlap simultaneously for at least two laser oscillation units among a plurality of laser oscillation units.
Abstract:
A machine learning device is connected to a fiber laser device. The machine learning device observes, as a state variable representing a driving state of the fiber laser device, a state quantity including time-series data on output light detection results obtained by detecting a light output of laser light emitted from the fiber laser device and time-series data on reflected light detection results obtained by detecting reflected light of the laser light, and acquires determination data representing a failure occurrence situation in the fiber laser device as determined from a difference between the output light detection results and a light output instruction of the fiber laser device. The machine learning device learns a boundary condition for failure occurrence caused by the reflected light by using the state variable and the determination data.
Abstract:
A laser system having an automatic diagnosis function enabling a plurality of laser diodes to be diagnosed for faults in a short time.The laser system includes a judging part judging the presence of a fault or deterioration of a component of the laser system. The judging part is configured to judge the presence of a fault or deterioration of a component of the laser system based on the results of detection of a first photodetection part and second photodetection part when successively driving a plurality of laser diode module groups included in an individual laser oscillation unit so that the mutual drive times do not overlap simultaneously for at least two laser oscillation units among a plurality of laser oscillation units.
Abstract:
The laser machining system includes a laser device configured to output a laser beam, and a machining head configured to emit the laser beam emitted by a laser oscillator of the laser device and propagated through an optical fiber, to a workpiece in order to perform laser machining. The machining head includes at least one wavelength selective mirror having wavelength selectivity with various values of reflectivity and transmittance according to wavelengths, and at least one image capturing device. The laser machining system monitors abnormality in a laser optical system leading from the laser oscillator to the machining head, during the laser machining, by reflecting light propagated from a side of introduction of the laser beam into the machining head by the wavelength selective mirror, making the light incident on an image capturing surface of the image capturing device, and detecting incident light illuminance distribution appearing on the image capturing surface of the image capturing device.