Accesso libero

Research on the fault diagnosis method of offshore oil and gas field equipment combined with deep reinforcement learning

 e   
26 mar 2025
INFORMAZIONI SU QUESTO ARTICOLO

Cita
Scarica la copertina

Figure 1.

Multisource heterogeneous data model
Multisource heterogeneous data model

Figure 2.

Fault diagnosis process based on DDPG-SDAE
Fault diagnosis process based on DDPG-SDAE

Figure 3.

Nose-free pulse signal
Nose-free pulse signal

Figure 4.

The noise extraction effect of different algorithms
The noise extraction effect of different algorithms

Figure 5.

MAE of various algorithms under SNR
MAE of various algorithms under SNR

Figure 6.

Simulation signal time domain waveform
Simulation signal time domain waveform

Figure 7.

The upper and lower envelope of different algorithms
The upper and lower envelope of different algorithms

Figure 8.

Fault diagnosis of different models
Fault diagnosis of different models

Figure 9.

Fault diagnosis migration results of different models
Fault diagnosis migration results of different models

Different migration task descriptions

Describe Source domain Target domain Migration task
The single-transmitter migration task Sensor 1 Sensor 3 1→3
Sensor 2 Sensor 3 2→3
Sensor 1 Sensor 2 1→2
Sensor 3 Sensor 2 3→2
Sensor 2 Sensor 1 2→1
Sensor 3 Sensor 1 3→1
Multi-sensor migration task Sensor 1+2 Sensor 3 1+2→3
Sensor 1+3 Sensor 2 1+3→2
Sensor 2+3 Sensor 1 2+3→1
Lingua:
Inglese
Frequenza di pubblicazione:
1 volte all'anno
Argomenti della rivista:
Scienze biologiche, Scienze della vita, altro, Matematica, Matematica applicata, Matematica generale, Fisica, Fisica, altro