De Aller-Bedste Bøger - over 12 mio. danske og engelske bøger
Levering: 1 - 2 hverdage

Failure Prediction of Temperature Sensor Using Hybrid Neural Fuzzy

Failure Prediction of Temperature Sensor Using Hybrid Neural Fuzzyaf Cherry Bhargava
Bag om Failure Prediction of Temperature Sensor Using Hybrid Neural Fuzzy

The growth of Electronic products becomes more complex due to a major requirement of high reliability, high speed and low cost. In today¿s world, reliability becomes a great need of any electronic equipment for active as well as passive components such as a temperature sensor. Failure prediction is the major constraints to predict the remaining useful life of the component in order to anticipate the costly failures or system unavailability. In the modern competitive market, low cost and high performance are the key factors to attract the customers towards their products. Growing system complexity demands robust control to reduce system control and to reduce the successive failures. Reliability prediction of passive components especially temperature sensor is of great concern as these are required in almost every system. As these components are mounted on a board to form a complete system, the probability of damage is increased, as the different components have different characteristics and different operating conditions. So artificial intelligence techniques are used which adopt knowledge of failure mechanism of an individual part of the system and check the health condition of it.

Vis mere
  • Sprog:
  • Engelsk
  • ISBN:
  • 9786139847181
  • Indbinding:
  • Paperback
  • Sideantal:
  • 92
  • Udgivet:
  • 26. juli 2018
  • Størrelse:
  • 150x6x220 mm.
  • Vægt:
  • 155 g.
  • 2-3 uger.
  • 2. december 2024
På lager

Normalpris

Abonnementspris

- Rabat på køb af fysiske bøger
- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding

Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.

Beskrivelse af Failure Prediction of Temperature Sensor Using Hybrid Neural Fuzzy

The growth of Electronic products becomes more complex due to a major requirement of high reliability, high speed and low cost. In today¿s world, reliability becomes a great need of any electronic equipment for active as well as passive components such as a temperature sensor. Failure prediction is the major constraints to predict the remaining useful life of the component in order to anticipate the costly failures or system unavailability. In the modern competitive market, low cost and high performance are the key factors to attract the customers towards their products. Growing system complexity demands robust control to reduce system control and to reduce the successive failures. Reliability prediction of passive components especially temperature sensor is of great concern as these are required in almost every system. As these components are mounted on a board to form a complete system, the probability of damage is increased, as the different components have different characteristics and different operating conditions. So artificial intelligence techniques are used which adopt knowledge of failure mechanism of an individual part of the system and check the health condition of it.

Brugerbedømmelser af Failure Prediction of Temperature Sensor Using Hybrid Neural Fuzzy



Find lignende bøger
Bogen Failure Prediction of Temperature Sensor Using Hybrid Neural Fuzzy findes i følgende kategorier: