Toshniwal Industries Pvt. Ltd.
 
 
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+ 91 145 2695171
 

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Industrial Area, Mahukupura,
AJMER - 305 002,
INDIA
info@tipl.com
+ 91-145-2695171 / 72 / 73

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PiT PREDICTOR
SOFT SENSOR

 
Online characteristics via Digital Image Processing:
  • Flame variation.
  • Clinker preheating impact (positive/Negative).
  • Heat Exchange impact with meal quantity.
  • Coating.
  • Plum and fuels combustion properties.
  • Secondary air.
 
Unique information source
  • Features
  • Functional Overview
  • Advantages
  • Brochures/Documents

  • Based on Neural Net Technology.
  • Continuous online-prediction of main process parameter.
  • Soft sensor to accurate quality parameter prediction.
  • Self learning adaptive software, basing on neural nets.
  • Integration of digital optical information.
  • High availability.
  • PiT Predictor includes features of PiT Indicator.
  • Upgradeable to PiT Navigator.
The on-line prediction of free-lime is based on an impact analysis. The image obtained characteristics (moments) and conventional PLC measurements as well as the laboratory free-lime values are used to train a process model based on a neural nets. The display of the forecasted free-lime content is done within the visualization software of the PiT Indicator as a trend indicator. The correlation of the data from the optical sensor with the process control system data also allows for an on-line prediction of NOx, CO, C3S and as well for the calorific value of the currently used fuel. This enables the operator to correct the fuel quantities.


  • Fuel savings through precise control of the optimum free lime.
  • Lower energy costs for milling through optimized free lime content.
  • Very exact prediction (i.e. Freelime, NOx, C3S etc)
  • Permanent on-line information on clinker quality
  • Superior correlation coefficient of 0.9 between laboratory values and prediction of free lime
  • Stabile kiln operation and clinker quality.
  • Increased clinker production volume (up to 5%)
  • Reduced primary fuel consumption (up to 5%)
  • Increased alternative fuel usage (up to 100%)
  • Reduced emissions (NOx and CO2)
  • Increased kiln reliability and availability.
  • Quicker reaction to process changes.
  • Save energy costs.
  • Match quality and energy.
  • Quick Adaptation to fuel variation.
  • Stable Signal for Expert Optimizers.
 
 

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