A system determining whether the feed shafts are normal or abnormal, the system including: a command generation unit that moves the feed shafts in a forward direction at a predetermined speed from a lower limit value to an upper limit value of a range of feeding movement by the numerical controller; and a feed shaft abnormality determination unit that monitors a drive torque command during the movement of the feed shafts in the forward direction by the command generation unit, compares a monitoring result during the movement in the forward direction with a normal value of the drive torque command, determines that abnormality occurs when the drive torque command deviates from the normal value, and outputs the determination result.

A system determining whether the feed shafts are normal or abnormal, the system including: a command generation unit that moves the feed shafts in a forward direction at a predetermined speed from a lower limit value to an upper limit value of a range of feeding movement by the numerical controller; and a feed shaft abnormality determination unit that monitors a drive torque command during the movement of the feed shafts in the forward direction by the command generation unit, compares a monitoring result during the movement in the forward direction with a normal value of the drive torque command, determines that abnormality occurs when the drive torque command deviates from the normal value, and outputs the determination result.

An abnormality diagnostic method executes causing the feed axis to perform an axis operation in a predetermined diagnosis condition to obtain servo information according to a control of the servomotor, performing a frequency analysis on the obtained servo information, obtaining a damage frequency generated while the feed axis whose bearing is damaged performs the axis operation, from a result of the frequency analysis, and comparing the obtained damage frequency with a predetermined threshold to determine a presence/absence of an abnormality. In the determining, before the damage frequency is compared with the threshold, a determination whether a vibration frequency of the bearing interferes with a vibration frequency generated while a rolling element passes through a nut of the ball screw or not is performed, and the comparison is performed by setting the respective thresholds that are different in a case of the interference and a case of no interference.

A failure detection device includes a formaldehyde sensor that detects the generation of formaldehyde, a vibration sensor that detects vibration of a spindle head, and a machine controller that detects the occurrence of an abnormality of a spindle bearing. The machine controller determines the occurrence of the abnormality of the spindle bearing and a cause of the abnormality based on a change in the output value of the formaldehyde sensor over time and a change in the output value of the vibration sensor over time.

An abnormality diagnostic method executes causing the feed axis to perform an axis operation in a predetermined diagnosis condition to obtain servo information according to a control of the servomotor, performing a frequency analysis on the obtained servo information, obtaining a damage frequency generated while the feed axis whose bearing is damaged performs the axis operation, from a result of the frequency analysis, and comparing the obtained damage frequency with a predetermined threshold to determine a presence/absence of an abnormality. In the determining, before the damage frequency is compared with the threshold, a determination whether a vibration frequency of the bearing interferes with a vibration frequency generated while a rolling element passes through a nut of the ball screw or not is performed, and the comparison is performed by setting the respective thresholds that are different in a case of the interference and a case of no interference.

A failure detection device includes a formaldehyde sensor that detects the generation of formaldehyde, a vibration sensor that detects vibration of a spindle head, and a machine controller that detects the occurrence of an abnormality of a spindle bearing. The machine controller determines the occurrence of the abnormality of the spindle bearing and a cause of the abnormality based on a change in the output value of the formaldehyde sensor over time and a change in the output value of the vibration sensor over time.

Provided is an abnormality diagnosis device for a machine tool, and an abnormality diagnosis method, whereby it is possible to diagnose the degree of damage to a spindle system due to a collision. An abnormality diagnosis device (40) for a machine tool (1) has: a displacement sensor (36) for detecting the amount of displacement of a spindle bearing (30); an acceleration sensor (38) for detecting the acceleration of a ram (28); a collision determination unit (46) for determining whether the ram or a spindle (32) has collided with a work piece, on the basis of at least the amount of displacement of the spindle bearing detected by the displacement sensor or the acceleration of the ram detected by the acceleration sensor; and a damage determination unit (50) for determining the degree of damage to the spindle bearing on the basis of at least the amount of displacement of the spindle bearing, the acceleration of the ram, or a frequency characteristic of vibration of the ram due to rotation of the spindle obtained from the acceleration of the ram, when the collision determination unit determines that the ram or the spindle has collided with the work piece.

A method for anomaly detection in a cutting machine with a spindle that is driven by an electric motor, wherein the method includes determining an electric power consumption of the motor during a working cycle of the machine, dividing the working cycle into time windows, determining, for each time window, whether the spindle was cutting and/or idling based on associated electric power values, determining median and expected deviation of electric power values for cutting and idling operation over the sequence of time windows, and determining an anomaly if electric power values during cutting or idling exceed a predetermined relationship to the corresponding median and expected deviation values.