University of Central Lancashire: LMI System Design Report, MP4706

This report details the design, implementation, and analysis of a Load Moment Indicator (LMI) system. The system utilizes various sensors such as strain gauges and thermocouples, and a DAQmx card by NI, controlled through LabView software, to monitor and control crane operations. The report covers the system's design, including input sensors, processing elements, and output displays, and presents the results and analysis of the sensor data. It also includes an evaluation of signal conditioning elements and proposes future developments, such as using low-cost controllers like Arduino and Raspberry Pi, and employing various data transmission methods including IoT techniques for improved efficiency and real-time monitoring. The report emphasizes the importance of the LMI system in preventing accidents by providing timely warnings and ensuring safe crane operations.

Electronics
Sensors, instrumentation and control
Student Name –
Student ID –

Contents
INTRODUCTION......................................................................................................................4
DESIGN OF LMI SYSTEM......................................................................................................4
SOFTWARE DESIGN...............................................................................................................5
RESULTS AND ANALYSIS....................................................................................................5
EVALUATION - SIGNAL CONDITIONING ELEMENTS....................................................6
PROPOSAL FOR FUTURE DEVELOPMENT.......................................................................7
Using Low Cost Controller....................................................................................................7
Using various data transmission methods..............................................................................7
References..................................................................................................................................8

INTRODUCTION
The Load Moment Indicator ( LMI ) system is used for the measurement of arm’s moment
and the bearing’s force. A big load is generally lifted by a crane. If the load is more than a
decided limit, then the mechanical and the structural portions may fail. To avoid such a
situation, a signal must be sent to the operator so that he gets the information that the limit
has been crossed. The sensors can be used for this purpose like the pressure sensor, load
sensor and the angle sensor. The system helps to prevent any type of accident by raising an
alarm in the form of sound and light from LED. The limits for various parameters can be
decided based on calculations.

The LMI (Load Moment Indicator) acts as a controller which helps to monitor and control the
operation of the crane effectively. The output values can be displayed on a panel. The Load
Moment Indicator ( LMI ) system helps to generate adequate warning signals which help to
avoid any type of harm in case of overloading of the system. It makes the working of the
overall system safe ( Precup, 2016 ). It provides timely warnings and makes the operator alert
to take timely action for the crane activity.
DESIGN OF LMI SYSTEM
The LMI system consists of 3 major elements : the input sensors, the processing element or
controller and the output elements for displaying the output signals.
In the given system, the LMI controller used is the DAQmx card by Ni. The strain gauge,
trigger switch and the thermocouple act as the input sensing elements. The start and stop push
buttons are used as the input devices. The LMI output controls the starting operation as well
as the warning and the alerting systems. The output devices involve controlling the actuators,
servo motors and the alert systems ( Kumar, 2013 ).
The operation of the system can be explained as follows : In order to start the working of the
system, the push button is used. For the measurement of the pressure, the strain gauge is used.
For the measurement of the temperature, the thermocouple is used. The load is now lifted if
the pressure and temperature values lie in the decided range ( Guimarães, 2013 ). In case of
an overload, an alarm is raised by the warning signal so that the operator becomes alert. The
LED will glow if the temperature rises above a set limit. If the loading capacity is not
exceeded, the system continues to lift the load. The time for running the system till the load
gets balanced is 10 minutes.

SOFTWARE DESIGN
Figure 1
The LabView software is used to design the system shown in the Figure 1. For measuring the
temperature, the DAQmx card by NI is used. The channel used is Max Open. Outrigger
shows the value of counter weight which can make the crane stable and balanced.
RESULTS AND ANALYSIS
Here, the sensors which have been employed for the analysis. They are – temperature sensor
and pressure sensor. The transducers are attached to the NI DAQ part. The configuration of
the panel is done to measure the values obtained from the sensor. If the calculation of the
values is done, it can be seen that the results obtained and the simulation results by NI DAQ
are very close to each other. So, simulation can be preferred for the calculations which can be
used for the system.
The lift is carried out in a vertical manner ( against gravity ). The limit can be estimated for
the crane by using the equation : r * h * C * 0.01. Here, ‘r’ represents the distance between
the base and the heap or range and h * C represents the lift limit. The value of the limits
needs to be decided very carefully. The mean value is found by taking several cases, to obtain
the accurate value.

If ‘i’ is the crane centre – pivot point main boom, ‘j’ is the height of crane pivot point mainly
100 mm between ground and tires and ‘k’ represents the distance of sheaves.
The minimum radius required is given by
0.5 × Outrigger base
Maximum radius required is given by
Maximum main boom length * cos ( 30° ) + k * sin ( 30° ) – i
Crane lifting height is given by
Sqrt ( Main boom length2 + k2 – ( Radius + i )2 + j )
Crane loading capacity is the average of [ ( Maximum ( Lifting height * Capacity ) * Radius )
/ 100 ]
The manner in which the strain measure sensor redirects when meeting strain is organized by
the pressure load cells. While compacted a pressure load cell of s – type is pulled and
extended. They are used for quantifying elastic or dragging loads, making them ideal for
watching cranes and lifting weights. Clasp sensors, pressure connections, load cells and load
fasteners are most widely used.
Compared to the DLWS, clamp sensors attach straight to the crane wire ropes impasse. This
allows them to calculate the heap without impacting the headroom calculation for which a
crane administrator is expected to operate. This form of burden cell is ideal when it needs
overburden restriction. Using an advanced marker or burden cell intensifier, the frame may
provide transfer yield to trigger a light, shut down the action of lifting, offer a perceptible
alert, or any combination of these.
EVALUATION - SIGNAL CONDITIONING ELEMENTS
The strain gauge used is made of metal and consists of a wire and a steel foil in the form of a
grid. By the help of the grid design, the steel quantity is maximized. It reduces the effect of

the Poisson strain and the shear pressure. The pressure felt by the specimen is transferred
towards the stress gauge.
In order to find the lift capacity for the crane, some calculations are involved. The outrigger
base has a width of a few meters, from where the crane works. It provides a pivot and is
portable also. The expansion of the blast’s arm is outwards in the upward direction at an
angle of 30 degree. The length and the maximum height that can be reached by the blast arm
is determined which can be reached while the lifting activities are carried out.
The usage of an H – pillar is a good method to calculate the force of tension.
PROPOSAL FOR FUTURE DEVELOPMENT
Using Low Cost Controller
For the reduction of the system’s total cost, the controller cost needs to be reduced. If the low
cost sensors are used, then this may cause a problem as the quality may be degraded. A low
quality sensor may not be effective in measuring the various parameters ( Aslam, 2020 ). But
the microcontrollers available in the market may be low cost as well as effective in their
working.
The microcontrollers like Arduino and Raspberry Pi are available which offer open source
software for programming. They are very low cost microcontrollers with excellent features
for the design ( Levine, 2012 ). The sensors as well as the display devices can be easily
interfaced to these microcontrollers.
Using various data transmission methods
The wireless systems are more effective and convenient to use as compared to the wired
systems. IoT ( Internet of Things ) techniques can be used to design an efficient LMI system.
The interfacing is really simple for the IoT devices and the LMI system ( Lijuan, 2012 ). The
communication becomes very fast and adequate real time data can be provided to the operator
which can help to avoid any system failure. The vision technology can be used to get the real
time visual monitoring of the various aspects ( Sabih, 2013 ). A camera can be used to

monitor the view pictorially in real time. If the operator can view the condition properly, then
he can take timely action to prevent any type of accident. This makes the system more secure.
References
Aslam, M.S., Dai, X., Hou, J., Li, Q., Ullah, R., Ni, Z. and Liu, Y., 2020. Reliable control
design for composite‐driven scheme based on delay networked T‐S fuzzy
system. International Journal of Robust and Nonlinear Control, 30(4), pp.1622-1642.
Guimarães, M.P., 2013. Controle semiativo de vibrações por força de controle não linear.
Kumar, R., 2013. Efficient active vibration control of smart structures with modified positive
position feedback control using pattern search methods in the presence of instrumentation
phase lead and lag. Journal of Dynamic Systems, Measurement, and Control, 135(6).
Levine, S.E., Bida, T.A., Chylek, T., Collins, P.L., DeGroff, W.T., Dunham, E.W., Lotz, P.J.,
Venetiou, A.J. and Kermani, S.Z., 2012, September. Status and performance of the Discovery
Channel Telescope during commissioning. In Ground-based and Airborne Telescopes
IV (Vol. 8444, p. 844419). International Society for Optics and Photonics.
Lijuan, X.X.L.H.X. and Lianhui, Y., 2012. High precision periodic control method of control
moment gyro gimbal system. Journal of Beijing University of Aeronautics and Astronautics,
(8), p.8.
Precup, R.E., Preitl, S., Bojan-Dragos, C.A., Radac, M.B., Szedlak-Stinean, A.I., Hedrea,
E.L. and Roman, R.C., 2016. Evolving Takagi-Sugeno fuzzy modeling applications of
incremental online identification algorithms. In Proc. XIII InternationalSA UM Conference
on Systems, Automatic Control and Measurements (pp. 3-10).
Sabih, M., 2013. Control algorithms for distributed networked industrial systems (Doctoral
dissertation, King Fahd University of Petroleum and Minerals (Saudi Arabia)).