CHAPTER 1.2 allen bradley DL3500-DH+/DH485 CABLE WIRING
.bmp)
Tuesday, August 2, 2022
Tuesday, June 8, 2021
Friday, December 29, 2017
WEIGHT CALCULATOR :
WEIGHT CALCULATOR :
Standard conversion factors
INCH * 25.4 = MILLIMETRE
FOOT * 0.3048 = METRE
YARD * 0.9144 = METRE
MILE * 1.6093 = KILOMETER
ACRE * 0.4047 = HECTARE
POUND * 0.4536 = KILOGRAM
DEGREE FARENHEIT * 5/9 - 32 = DEGREE CELSIUS
MILLIMETRE * 0.394 = INCH
METRE * 3.2808 = FOOT
METRE * 1.0936 = YARD
SHEET
WEIGHT (KGS) = LENGTH (MM) * WIDTH (MM) *
0. 00000785 * THICKNESS
EXAMPLE
= THE WEIGHT OF MS SHEET OF THICKNESS 1 MM
AND SIZE 1250 MM * 2500 MM SHALL BE
2500MM
* 1250
MM * 0.00000785 *
1 = 24=53 KGS/ SHEET
2.ROLLED STEEL CHANNELS
Designation
Weight / Metre Depth of Section Width of
Flange
Kg
mm
mm
ISMC
75
7.14
75
40
ISMC
100
9.56
100
50
ISMC
125
13.1
125
65
ISMC
150
16.8
150
75
ISMC
175
19.6
175
75
ISMC
200
22.3
200
75
ISMC
225
26.1
225
80
ISMC
250
34.2
250
80
ISMC
300
36.3
300
90
ISMC
350
42.7
350
100
ISMC
400
50.1
400
100
DESIGNATION
WEIGHT / METRE DEPTH OF
SECTION WIDTH OF FLANGE
ISMB
100
11.5
100
75
ISMB
125
13.2
125
75
ISMB
150
15.0
150
80
ISMB
175
19.5
175
90
ISMB
200
25.9
200
100
ISMB
225
38.1
225
110
ISMB
250
37.3
250
125
ISMB
300
45.1
300
140
ISMB
350
52.9
350
140
ISMB
400 62.6
400
140
ISMB
500
87.7
500
180
WEIGHT (KGS ) = WIDTH * WIDTH * 0.00000785 * LENGTH.
Example : A Square of size 25mm and length 1 metre then the
weight shall be.
25
* 25
* .00000785 * 1000mm = 4.90 kgs /
metre
WEIGHT (KGS ) = 3.14 * 0.00000785 * ((diameter / 2)*( diameter /
2)) * LENGTH.
Example : A Round of 20mm diameter and length 1
metre then the weight shall be.
3.14 * 0.00000785
* ((20/2) * ( 20/2)) * 1000 mm = 2.46 kgs / metre
DIA (mm) * DIA (mm) * 0.00623 = WEIGHT PER
METRE
7. SS / MS Pipe
OD ( mm) - W.Tthick(mm) * W.Thick (mm) * 0.0248
= Weight Per Metre
OD ( mm) - W.Tthick(mm) * W.Thick (mm) * 0.00756 =
Weight Per Foot
8.SS / MS CIRCLE
DIA(mm) * DIA (mm) * THICK(mm) * 0.0000063 = Kg Per Piece
Length (Mtr) * Width (Mtr) * Thick(mm) * 8 = Weight Per Piece
Length (ft) * Width (ft) * Thick(inch) * 3 /4 = Weight Per Piece
DIA (mm) * DIA (mm) * 0.00680 = WT. PER Mtr
Dia (mm) * Dia (mm) * 0.002072 = Wt. Per foot.
WEIGHT (KGS) = LENGTH (MM) * BREADTH (MM)
* 0. 0000085 * THICKNESS
EXAMPLE = THE WEIGHT
OF BRASS SHEET OF THICKNESS 1 MM , LENGTH 1220 MM AND BREADTH 355
MM SHALL BE
1220
*
355 *
0.0000085 * 1 = 3.68 Kgs / Sheet
WEIGHT (KGS) = LENGTH (MM) * BREADTH (MM)
* 0. 0000087 * THICKNESS
EXAMPLE = THE WEIGHT
OF BRASS SHEET OF THICKNESS 1 MM , LENGTH 1220 MM AND BREADTH 355
MM SHALL BE
1220
*
355 *
0.0000087 * 1 = 3.76 Kgs / Sheet
OD (mm) - THICK (mm) * THICK(mm) * 0.0260 = WEIGHT PER METRE
WEIGHT (KGS) = LENGTH (MM) * BREADTH (MM)
* 0. 00000026 * THICKNESS
EXAMPLE = THE WEIGHT
OF ALUMINIUM SHEET OF THICKNESS 1 MM , LENGTH 2500 MM AND BREADTH
1250 MM SHALL BE
2500
*
1250 * 0.0000026
* 1 = 8.12 Kgs / Sheet
OD (mm) - THICK(mm) * THICK(mm) *0.0083 = WEIGHT PER METRE
Wednesday, January 18, 2017
Monday, August 17, 2015
Allen Bradley plc analog scaling
SCL INSTRUCTION
FOR ANALOG INPUT:-
In case of
Micrologix -1000 A for current signal (4 to 20 mA),
Max Value for
i/p = 31230 (Approx.)
So min value
at 4 mA = 31230*4/20 = 6246 (Approx.)
Let the range
of RTD is 0 to 400 degree C.
To calculate
the value of rate & offset please use following formula.
1). Rate = (scaled
max. - scaled min.) * 10000 / (input max. - input min.)
= (400 – 0) * 10000 / (31230-6246)
Rate
= 160
2). Offset = scaled
minimum - (input minimum x rate)
= 0 – (6246 * .0160)
Offset = -100
FOR ANALOG OUTPUT
In case of
Micrologix -1000 A for current signal (4 to 20 mA),
To use the AI
double click on I/O Configuration & then I/O Setup.
Select the
o/p mode (may be current or voltage, which you want to use).
If you want
to provide 0 to 10 V signal on o/p then the value at O:0.4 should be 0 to 31230
(Approx.).
Remote IOS of Allen-Bradley
change the ip address of local and remote IOS of Allen-Bradley
start stop logic in rs logix 5000 by using emote IOS of Allen-Bradley
Allen-Bradley plc remote ios communication with intouch ad rs view scada
Allen-Bradley compact logic 1769 BY using Ethernet adopter
connected to remote ios and communication to Review32 and
Intouch scada
Intouch scada
Saturday, August 15, 2015
abb positioner (tzidc) for control valve calibration procedure
Abb positioner manual checking and opening of control
valve:
A.Press Mode key for 3 sec untill parameter
1.3 MAN_SENS
then release the Mode key
B.now showing
SENS_POS which is -25 degree or any
other reading.this is zero or 0 % close
postion of the control valve.
C.For 100% opening press
both keys: 1st up errow key
with 2nd errow dowen key untill valve not open 100 %.then release the
both key.
Note: alwayes keep the
control valve at zero position befor exit SENS_POS parameter.
Abb positioner Auto caliberation of control valve:
A.Press Mode key for 5 sec
untill parameter
ADJ_LIN
3
2
1
0
then release the Mode key
B.auto caliberation
working 10 to 100 % Run
c. end of caliberation .
Tuesday, May 5, 2015
PID Control
PID ControlOverall Course Objectives
•
Develop the skills necessary to function as an
industrial process control engineer.
– Skills
•
Tuning loops
•
Control loop design
•
Control loop troubleshooting
•
Command of the terminology
– Fundamental
understanding
•
Process dynamics
•
Feedback control
PID Controls
•
Most common
controller in the CPI.
•
Came into use in
1930’s with the introduction of pneumatic controllers.
• Extremely flexible and powerful control algorithm when applied properly.
General Feedback Control Loop Closed Loop Transfer Functions
•
From the general feedback control loop and using
the properties of transfer functions, the following expressions can be derived:
Characteristic Equation
•
Since setpoint tracking and disturbance
rejection have the same denominator for their closed loop transfer functions,
this indicates that both setpoint tracking and disturbance rejection have the
same general dynamic behavior.
•
The roots of the denominator determine the
dynamic characteristics of the closed loop process.
•
The characteristic equation is given by:
Feedback Control Analysis
•
The loop gain (KcKaKpKs)
should be positive for stable feedback control.
•
An open-loop
unstable process can be made stable by applying the proper level of feedback
control.
Characteristic Equation Example
•
Consider the dynamic behavior of a P-only
controller applied to a CST thermal mixer (Kp=1; tp=60
sec) where the temperature sensor has a ts=20 sec and ta
is assumed small. Note that Gc(s)=Kc.
Example Continued- Analysis of the Closed Loop Poles
•
When Kc
=0, poles are -0.05 and -0.0167 which correspond to the inverse of tp and ts.
•
As Kc
is increased from zero, the values of the poles begin to approach one another.
•
Critically damped
behavior occurs when the poles are equal.
•
Underdamped
behavior results when Kc is increased further due to the
imaginary components in the poles.
In-Class Exercise
•
Determine the
dynamic behavior of a P-only controller with Kc equal to 1 applied
to a first-order process in which the process gain is equal to 2 and the time
constant is equal to 22. Assume that Gs(s)
is equal to one and Ga(s) behaves as a first-order process with a
time constant of 5.
PID Control Algorithm
Definition of Terms
•
e(t)- the
error from setpoint [e(t)=ysp-ys].
•
Kc- the controller gain is a tuning parameter and
largely determines the controller aggressiveness.
•
tI- the
reset time is a tuning parameter and determines the amount of integral action.
•
tD- the
derivative time is a tuning parameter and determines the amount of derivative
action.
Transfer Function for a PID Controller
Example for a First Order Process with a PI Controller
Example of a PI Controller Applied to a Second Order
Process
Properties of Proportional Action
•
Closed loop transfer function base on a P-only
controller applied to a first order process.
•
Properties of P control
– Does
not change order of process
–
Closed loop time constant is smaller
than open loop tp
–
Does not eliminate offset.
Offset Resulting from P-only Control Proportional Action for the Response of a PI
ControllerProportional Action
• The primary benefit of proportional action is that it speedup the response of the process. Properties of Integral Action
•
Based on applying an I-only controller to a
first order process
•
Properties of I control
–
Offset is eliminated
– Increases
the order by 1
– As integral action is increased, the process becomes faster, but at the expense of more sustained oscillations
Integral Action for the Response of a PI Controller Integral Action
•
The primary
benefit of integral action is that it removes offset from setpoint.
•
In addition, for
a PI controller all the steady-state change in the controller output results
from integral action.
Properties of Derivative Action
•
Closed loop transfer function for
derivative-only control applied to a second order process.
•
Properties of derivative control:
–
Does not change
the order of the process
–
Does not
eliminate offset
–
Reduces the
oscillatory nature of the feedback response
Derivative Action for the Response of a PID Controller Derivative Action
• The primary benefit of derivative action is that it reduces the oscillatory nature of the closed-loop response.
Position Form of the PID AlgorithmProportional Band
•
Another way to express the controller gain.
•
Kc in this formula is
dimensionless. That is, the controller
output is scaled 0-100% and the error from setpoint is scaled 0-100%.
• In more frequent use 10-15 years ago, but it still appears as an option on DCS’s Conversion from PB to Kc
•
Proportional band is equal to 200%.
•
The range of the error from setpoint is 200 psi.
•
The controller output range is 0 to 100%.
Conversion from Kc to PB
•
Controller gain is equal to 15 %/ºF
•
The range of the error from setpoint is 25 ºF.
• The controller output range is 0 to 100%.\
Digital Equivalent of PID Controller
•
The trapezoidal approximation of the integral.
• Backward difference approximation of the first derivative
Digital Version of PID Control Algorithm Velocity Form of PID Controller
•
Note the difference in proportional, integral,
and derivative terms from the position form.
•
Velocity form is the form implemented on DCSs.
Correction for Derivative Kick
•
Derivative kick occurs when a setpoint change is
applied that causes a spike in the derivative of the error from setpoint.
•
Derivative kick can be eliminated by replacing
the approximation of the derivative based on the error from setpoint with the
negative of the approximation of the derivative based on the measured value of
the controlled variable, i.e.,
Correction for Aggressive Setpoint Tracking
•
For certain process, tuning the controller for
good disturbance rejection performance results in excessively aggressive action
for setpoint changes.
•
This problem can be corrected by removing the
setpoint from the proportional term.
Then setpoint tracking is accomplished by integral action only.
The Three Versions of the PID Algorithm Offered on
DCS’s
•
(1) The original
form in which the proportional, integral, and derivative terms are based on the
error from setpoint
Guidelines for Selecting Direct and Reverse Acting
PID’s
•
Consider a direct acting final control element
to be positive and reverse to be negative.
•
If the sign of the product of the final control
element and the process gain is positive, use the reverse acting PID algorithm.
•
If the sign of the product is negative, use the
direct acting PID algorithm
•
If control signal goes to a control valve with a
valve positioner, the actuator is considered direct acting.
Level Control Example
•
Process gain is negative because when flow out
is increased, the level decreases.
•
If the final control element is direct acting,
use direct acting PID.
•
For reverse acting final control element, use
reverse acting PID.
In-Class Exercise
•
Write the position
form of the PID algorithm for Example 3.4, and assume that the control valve on
the feed line to the mixer has an air-to-close actuator. Use the form that is not susceptible to
derivative kick. Specify whether the
controller is a direct-acting or reverse-acting controller.
In-Class Exercise
•
Write the
velocity form of the PID algorithm for Example 3.1, and assume that the control
valve on the feed line to the mixer has an air-to-open actuator. Use the form that is not susceptible to
derivative kick or proportional kick. Specify whether the controller is a
direct-acting or reverse-acting controller.
Filtering the Process Measurement
•
Filtering reduces
the effect of sensor noise by approximating a running average.
•
Filtering adds
lag when the filtered measurement is used for control.
•
Normally, use the
minimum amount of filtering necessary.
•
f- filter factor (0-1)
Feedback Loop with Sensor Filtering
Effect of Filtering on Closed Loop Dynamics
Analysis of Example
•
tf is equal to
Dt (1/f-1) as f
becomes small, tf becomes
large.
•
As tf is increased, tp’ will increase.
•
Critical issue is
relative magnitude of tf compare to tp.
Effect of the Amount of Filtering on the Open Loop
Response
Effect of a Noisy Sensor on Controlled Variable
without Filtering
Effect of a Noisy Sensor on Controlled Variable with
Filtering
An Example of Too Much and Too Little Filtering
Relationship between Filter Factor (f), the
Resulting Repeatability Reduction Ratio (R) and the Filter Time Constant
(tf)
Key Issues for Sensor Filtering
•
To reduce the
effect of noise (i.e., R is increased), f must be reduced, which
increases the value of tf. Filtering
slows the closed-loop response significantly as tf becomes larger than 10% of tp.
•
The effect of
filtering on the closed-loop response can be reduced by increasing the
frequency with which the filter is applied, i.e., reducing Dtf.
PID Controller Design Issues
•
Over 90% of
control loops use PI controller.
•
P-only: used for fast responding processes that do
not require offset free operation (e.g., certain level and pressure
controllers)
•
PI: used for fast
responding processes that require offset free operation (e.g., certain flow,
level, pressure, temperature, and composition controllers)
Integrating Processes
•
For integrating
processes, P-only control provides offset-free operation. In fact, if as integral action is added to
such a case, the control performance degrades.
•
Therefore, for
integrating processes, P-only control is all that is usually required.
PID Controller Design Issues
•
PID: use for sluggish processes (i.e., a process
with large deadtime to time constant ratios) or processes that exhibit severe
ringing for PI controllers. PID controllers
are applied to certain temperature and composition control loops. Use derivative action when:
Comparison between PI and PID for a Low qp/tp Ratio
Analysis of Several Commonly Encountered Control Loops
•
Flow control
loops
•
Level control
loops
•
Pressure control
loops
•
Temperature
control loops
•
Composition
control loops
•
DO control loop
•
Biomass
controller
Flow Control Loop
•
Since the flow sensor and the process (changes
in flow rate for a change in the valve position) are so fast, the dynamics of
the flow control loop is controlled by the dynamics of the control valve.
•
Almost always use PI controller.
Deadband of a Control Valve
•
Deadband of industrial valves is between
±10%-±25%.
•
As a result, small changes in the air pressure
applied to the valve do not change the flow rate.
Deadband of Flow Control Loop
•
A control valve (deadband of ±10-25%) in a flow
control loop or with a positioner typically has a deadband for the average
flow rate of less than ±0.5% due to the high frequency opening and closing
of the valve around the specified flow rate.
Level Control Loop
•
Dynamics of the sensor and actuator are fast
compared to the process.
•
Use P-only controller if it is an integrating
process.
Pressure Control Process
•
The sensor is generally faster than the
actuator, which is faster than the process.
•
Use P-only controller if it is an integrating
process otherwise use a PI controller.
Temperature Control Loop
•
The dynamics of the process and sensor are
usually slower than the actuator.
•
Use a PI controller unless the process is
sufficiently sluggish to warrant a PID controller.
Analysis of PI Controller Applied to Typical
Temperature Loop
Further Analysis of Dynamic of a Typical Temperature
Control Loop
•
Note that as the
controller gain is increased, i.e., KcKp increase, the
closed loop time constant becomes smaller.
•
Also, note that
as the controller gain is increased, the value of z decreases.
Composition Control Loop
•
The process is usually the slowest element
followed by the sensor with the actuator being the fastest.
•
Use a PI controller unless the process is
sufficiently sluggish to warrant a PID controller.
DO Control Loop
•
The process and the sensor have approximately
the same dynamic response.
•
This is a fast responding process for which
offset-free operation is desired.
Therefore, PI controller should be used.
Biomass Controller
•
The process for this system is the slowest
element.
•
Because the process is a high-order sluggish
process, a PID controller is required.
Overview
•
The
characteristic equation determines the dynamic behavior of a closed loop
system
•
Proportional, integral, and derivative action
each have unique characteristics.
•
There are a number of different ways to apply a
PID controller.
•
Use a PI controller unless offset is not
important or if the process is sluggish.
•
When analyzing the dynamics of a loop, consider
the dynamics of the actuator, the process, and the sensor separately.
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