A numerical control system according to the present invention controls machine drive systems included in a machine tool that performs machining using a tool, according to a numerical control program, and includes a coordinate transformation unit that acquires a disturbance force or a disturbance torque applied to each machine drive system, and coordinate-transforms the disturbance force or the disturbance torque into a tool reference coordinate system for output, and an identification unit that calculates cutting process parameters that determine characteristics of a cutting process model and dynamic characteristic parameters that determine characteristics of a dynamics model of the machine tool, using the disturbance force or the disturbance torque output from the coordinate transformation unit, states of the machine drive systems, predetermined equation models, and cutting conditions. The equation models define relationships between the cutting process parameters, the dynamic characteristic parameters, and the disturbance force or the disturbance torque.

The present invention relates to an apparatus and a method of automatically converting thermal displacement compensation parameters of a machine tool, which automatically convert a compensation parameter of a thermal displacement compensation equation of a machine tool so that the compensation parameter is optimized to a current thermal displacement state of the machine tool in real time based on Z-directional or Y-directional displacement data of a tool tip end of a reference tool measured by a tool measuring unit according to an operation state of the machine tool or various kinds of machine tools or thermal displacement data of the machine tool calculated by measuring a processed portion of a processed material, and temperature data measured by a temperature measuring unit, to minimize a processing error according to thermal displacement and improve processing accuracy of the machine tool.

A cooling arrangement for an electronic device comprises a primary cooling device and a secondary cooling device. The primary cooling device includes a fluidic input line receiving a cooling fluid from a cooling fluid source and a fluidic output line returning the cooling fluid toward a drain. The primary cooling device is thermally connected to the electronic device, receives the cooling fluid from the fluidic input line and transfers heat from the electronic device to the cooling fluid before returning the cooling fluid via the fluidic output line. A flow detection device monitors a flow of the cooling fluid in the primary cooling device. The secondary cooling device is thermally connected to the electronic device. A processor activates the secondary cooling device to absorb and dissipate heat from the electronic device when the flow detection device detects a lack of flow of the cooling fluid in the primary cooling device.

A method includes four steps, (1) setting an initial tool temperature, (2) estimating a temperature of a tool or a position measurement sensor based on the initial tool temperature and a temperature of a spindle, (3) estimating an amount of thermal displacement of the tool or the position measurement sensor with a preliminarily set tool thermal displacement estimation formula based on the estimated temperature, and (4) moving a feed shaft of the machine tool based on the estimated amount of thermal displacement to perform a correction. In the second step, the temperature of the spindle is measured, then a tool-mounted portion temperature of the spindle from the measured temperature is estimated. Further, the temperature of the tool or the position measurement sensor is estimated with the tool-mounted portion temperature, the initial tool temperature of the tool or the position measurement sensor, and the preliminarily set tool temperature estimation formula.

An information handling system includes a chassis and a payload. The chassis directs an airflow along the payload. The payload includes a heatsink for cooling a first component using a first portion of the airflow and an airflow directing heatsink for cooling a second component. The airflow directing heatsink uses both of the first portion of the airflow and a second portion of the airflow for cooling the second component.

A method for detecting thermal events in an electrical system includes: synchronizing, via a controller, measurements of power consumed by each of a plurality of load elements during an interval with one another and with measurements of power supplied by each of a plurality of power sources to the plurality of load elements during the interval; determining a differential between a sum of the power consumed by the load elements during the interval and a sum of the power supplied by the power sources to the plurality of load elements during the interval; comparing the differential to a predetermined threshold; and determining whether a thermal event has occurred based on the comparison of the differential to the predetermined threshold.

A method for detecting thermal events in an electrical system includes: synchronizing, via a controller, measurements of power consumed by each of a plurality of load elements during an interval with one another and with measurements of power supplied by each of a plurality of power sources to the plurality of load elements during the interval; determining a differential between a sum of the power consumed by the load elements during the interval and a sum of the power supplied by the power sources to the plurality of load elements during the interval; comparing the differential to a predetermined threshold; and determining whether a thermal event has occurred based on the comparison of the differential to the predetermined threshold.

A calculation formula learning unit sets a coefficient relating to a time lag element in a thermal displacement estimation calculation formula by machine learning while fixing a coefficient relating to measured data except the coefficient relating to the time lag element at a predetermined value based on a difference between a thermal displacement estimated value about a machine element calculated by substituting a measured data group into the thermal displacement estimation calculation formula and a thermal displacement actual measured value about the machine element; sets the coefficient relating to the measured data except the coefficient relating to the time lag element in the thermal displacement estimation calculation formula by machine learning based on the difference while fixing the coefficient relating to the time lag element at a predetermined value; and repeats the machine learning.

The invention provides a method for modeling and compensating for the spindle's radial thermal drift error in a horizontal CNC lathe, which belongs to the field of error compensation technology of CNC machine tools. Firstly, the thermal drift error of two points in the radial direction of the spindle and the corresponding temperature of the key points are tested; then the thermal inclination angle of the spindle is obtained based on the thermal tilt deformation mechanism of the spindle, and the correlation between the thermal inclination angle and the temperature difference between the left and right sides of the spindle box is analyzed. According to the positive or negative thermal drift error of the two points that have been measured and the elongation or shortening of the spindle box on the left and right sides, the thermal deformation of the spindle is then classified and the thermal drift error model under various thermal deformation attitudes is then established. Then the influence of the size of the machine tool's structure on the prediction results of the model is analyzed. In real-time compensation, the thermal deformation attitude of the spindle is automatically judged according to the temperature of the key points, and the corresponding thermal drift error model is automatically selected to apply the compensation to the spindle. The method is used to distinguish the thermal deformation attitude of the spindle in a CNC lathe, and the thermal deformation mechanism is used to predict the radial thermal drift error of the spindle.

The present disclosure concerns machine tools and more specifically compensation of variations which may occur within a multi-axis machine tool during a cutting process. An example embodiment includes a method of machining a workpiece using a machine tool comprising a machining head and a workpiece holder moveable relative to each another the method comprising: performing a first machining operation on a workpiece mounted to the workpiece holder according to a first programmed series of movements of the machining head relative to the workpiece holder, the first machining operation having a first maximum machining tolerance; performing a second machining operation on the workpiece according to a second programmed series of movements of the machining head relative to the workpiece holder, the second machining operation having a second maximum machining tolerance; performing a measurement operation to determine a position of an artefact on the machine tool; calculating an offset relative to a corresponding previously stored position of the artefact; and applying the offset to the second programmed series of movements prior to performing the second machining operation, wherein the second maximum machining tolerance is smaller than the first maximum machining tolerance.