IntelliSense of operation state for power equipment is a key technology underpinning the safe and reliable operation of new-type power systems

and it provides core information to enable real-time health-state assessment and preventive maintenance. This paper reviews the development and current status of IntelliSense technologies from three perspectives

i.e.

advanced sensing techniques

collective sensing methods

and artificial intelligence learning paradigms

and then their applications in typical engineering scenarios are also outlined. Finally

the limitations of existing technologies are analyzed in terms of sensing performance

multimodal fusion

and general operating-condition adaptability

in response to the strong stochasticity

wide dynamic range

and high time variability exhibited by new-type power systems. On this basis

key technical pathways for large-model-enabled IntelliSense of operation state for power equipment are discussed. This work aims to provide technical references for enabling self-assessment

self-diagnosis

and operating-condition adaptation of power equipment.