Two or more data values are received from one or more sensors of a hard disk drive. The two or more data values are indicative of a fly height of a recording head of the hard disk drive. The two or more data values are input into a machine-learning processor during operation of the hard disk drive. A fly height of the recording head during the operation of the hard drive head is adjusted based on an output of the machine learning processor

Two or more data values are received from one or more sensors of a hard disk drive. The two or more data values are indicative of a fly height of a recording head of the hard disk drive. The two or more data values are input into a machine-learning processor during operation of the hard disk drive. A fly height of the recording head during the operation of the hard drive head is adjusted based on an output of the machine learning processor.

The present disclosure describes aspects of health management for magnetic storage media. In some aspects, a media health manager determines, with a read channel, read metrics for a sector of magnetic storage media that resides in a zone of magnetic storage media. The media health manager accesses read metrics of the zone and updates the read metrics of the zone based on the read metrics determined for the sector to provide updated read metrics for the zone of magnetic storage media. A health score for the zone of magnetic storage media is then determined with a neural network based on the updated read metrics of the zone of magnetic storage media. By so doing, gradual wear of the magnetic storage media may be predicted using the health score, enabling replacement of a magnetic storage media device before failure to improve reliability or availability of data stored to the device.

The present disclosure describes aspects of health management for magnetic storage media. In some aspects, a media health manager determines, with a read channel, read metrics for a sector of magnetic storage media that resides in a zone of magnetic storage media. The media health manager accesses read metrics of the zone and updates the read metrics of the zone based on the read metrics determined for the sector to provide updated read metrics for the zone of magnetic storage media. A health score for the zone of magnetic storage media is then determined with a neural network based on the updated read metrics of the zone of magnetic storage media. By so doing, gradual wear of the magnetic storage media may be predicted using the health score, enabling replacement of a magnetic storage media device before failure to improve reliability or availability of data stored to the device.

According to one embodiment, an information processing device includes an acquisitor and a processor. The acquisitor is configured to acquire a reproduced signal based on a signal obtained from a magnetic recording medium. The reproduced signal includes first input data, second input data, and third input data. The processor is configured to perform a first process and a second process. In the first process, the processor is configured to derive a first derived feature value from a first inner product of a first feature value based on the first input data and a second feature value based on the second input data. In the second process, the processor is configured to derive a second derived feature value from a second inner product of a third feature value based on the third input data and the first derived feature value.

According to one embodiment of a magnetic disk device, a controller determines, by using a determination model, whether or not a distance in a radial direction from a target position related to a first track to a position of a magnetic head exceeds a threshold. The position of the magnetic head fluctuates from the target position toward a second track during execution of writing to the first track. The controller performs writing to the first track when the distance does not exceed the threshold, and performs no writing to the first track when the distance exceeds the threshold. The determination model is a learned model configured to receive pieces of position error information obtained by reading servo information from servo areas and output a value representing whether or not the distance exceeds the threshold while the magnetic head moves above the servo areas.

According to one embodiment, an information processing device includes an acquisitor and a processor. The acquisitor is configured to acquire a reproduced signal based on a signal obtained from a magnetic recording medium. The reproduced signal includes first input data, second input data, and third input data. The processor is configured to perform a first process and a second process. In the first process, the processor is configured to derive a first derived feature value from a first inner product of a first feature value based on the first input data and a second feature value based on the second input data. In the second process, the processor is configured to derive a second derived feature value from a second inner product of a third feature value based on the third input data and the first derived feature value.