Understanding the Applications of High Precision Stress And Strain Measurements in Modern Control Systems
Bio: Joe Flanagan has over 12 years in electronic engineering and design and is the current Project Engineer at Tacuna Systems. They provide hardware and service solutions for the for the strain measurement industry across a range of applications.
Over the years, the methods of determining the amount of mechanical stress and strain on an object have improved. The original equipment manufacturers have developed products that enable a high precision measurement of stress, strain, and other related parameters.
The development of these high precision instruments has led to their adoption by many industries for process control/automation. A lot of modern control systems now incorporate one form or another of a stress/strain measurement into their process loop.
This article aims to establish the basis for understanding how and why there is even a need to incorporate stress/strain measuring instruments into process control. Here, the principle of operation of the measuring instruments are briefly explained, the concepts of modern control systems are also explained, and some applications that integrate the measurements into modern control systems.
Stress And Strain Measurement
This article uses the strain gauge load cell to illustrate how stress and strain can be measured. However, in practice, there are other types of sensor devices used for this measurement, examples are piezoelectric sensors, optical force sensors, accelerometers, capacitive sensors, etc.
The measurement of stress and strain can also serve as an indirect measure or physical estimation of related parameters such as displacement, force, torque, acceleration, pressure, and vibration.
The devices used for this measurement is made up of different subsystems, the block diagram below illustrates the basic structure of a measurement device.
For the task of stress and strain measurement, each of these blocks is described below:
- The Primary Sensing Element: This system uses an underlying sensing material, that is, the sensor device. The input to this unit is the measurand; the output depends on the type of sensor material. Consider a strain gauge load cell, the primary sensing element is the elastic beam element; The underlying strain gauge material is bonded to the elastic beam element, so when the measurand of choice is applied, the elastic element bends, stretches, or compresses, thereby transmitting this deformation to the bonded strain gauge. Therefore, the output will be a change in the electrical resistance of the strain gauge. It should be noted that the measurand could be mechanical stress, strain, and other related parameters.
- The Variable Conversion Unit: This is the transduction unit. Transduction is defined as the conversion of the signal sensed from a physical phenomenon into another signal form. In the case of electrical transduction, the final form is an electrical signal – voltage or current. For a strain gauge load cell, the underlying strain gauge is included into a Wheatstone bridge circuit, so that the change in its electrical resistance is transformed into an electrical voltage output. The magnitude of this voltage is very small, in millivolts.
- The Signal Conditioning Unit: The elements of this unit are usually electronics circuits made of resistors, capacitors, and instrumentation amplifiers. The input to this unit is the raw analog low magnitude voltage signal. Its function is to isolate the signal from interference sources, filter off noisy signals, and then amplify the signal to a reasonable magnitude. The output of the signal conditioner is, therefore, a high magnitude, less noisy, electrical representation of the applied measurand. The electrical output is still in the analog form but it can be converted into a digital form by feeding it into a digital signal processing unit.
Modern Control Systems
The previous section shows that the output of the whole process of stress/strain measurement could either be the analog or digital form. This can then be used in the corresponding control system either analog/continuous time control or digital/discrete time control.
Modern control systems are discrete-time based and the control strategies are implemented by a digital computer. The dominance of digital control techniques in modern systems is due to the cheap and fast processing power of computers. Although, computers have limited capacity, the range of their capacity is still sufficient to cater to the computational demands of control engineering.
They are different classifications of control systems, but the measurement of stress/strain and related parameters are used majorly in closed-loop feedback systems. The basic configuration of digital control systems is shown in figure 1 below.
Figure 1. A Digital Control System
This configuration can be broken down into two sections:
- The feed-forward path consisting of the computer, digital-to-analog converter (DAC), and the actuator and the process.
- The feedback path consisting of the sensor and the analog-to-digital converter (ADC).
It can be seen how the sensor is placed in a control system to provide measurement for feedback. The sensor measures the output and produces its equivalent analog electrical output that is then converted into a digital form - by the ADC – to be fed as input into the computer. Why the need to convert to a digital form? You may ask, the reason is that computers only understand 1’s and 0’s – binary digits, bits.
Now, the digital measurement from the sensor is then compared with a reference input. The reference input is a digital equivalent of the desired output. This reference input can either be constant over time – making the computer a regulator, or it could be varying over time – making the computer a controller.
What actually performs a computational operation on the reference input and the feedback input is an algorithm – a computer software. In practice, there are a wide variety of techniques used to create the control algorithm, the most common and basic being the Proportional, Integral, and Derivative (PID) class.
The result of the computing produces a control action or control signal that is then converted from its digital form to an analog form by the DAC, so as to affect the actuator that in turn affects the process, and in turn, affects the desired controlled variable/output.
To fully appreciate and understand these concepts let’s take a look at some real practical examples in the next section.
Batch Weighing Systems: The process of batch weighing finds applications in various industries such as construction, metallurgical, pharmaceutical, and food processing. It involves the feeding of a certain weight of ingredients into a collective vessel through an actuator – also called the feeder. There are different techniques used for batch weighing, it could be a single sequential weighing, where each ingredient in weighed one at a time into the collective vessel. It could also be multiple simultaneous weighing.Depending on the type of weighing and feeding technique used, the collective vessel is usually supported on a strain gauge load cell. The load cell then acts to help monitor the amount of weight of ingredients added to the vessel. This value is then feedback to a control computer that compares the current output weight with the desired reference weight. So take for example, in a baking factory, the amount of flour needed to be added into a mixer is 50Kg; the desired amount of flour, 50Kg is inputted into the computer. The flour is then poured into the feeder, and it starts feeding into the mixing vessel. The load cell under the vessel keeps outputting the present weight per time and immediately the amount of flour reaches 50Kg, the regulating computer stops the feeder. The block diagram below explains this better.
Robotic systems: A robot has several parts such as the manipulator, computer controller, actuators, and sensors. Some robotic designs incorporate what is called a hybrid position/force controller which can be used to effect guarded moves. A guarded move is such that the manipulator moves in a particular direction until the touch sensor feels a particular force. The touch signal is then routed to the controller that halts the motion. A touch sensor could range from a simple switch circuit to a piezo-resistive strain gauge material; hence, providing a high precision indirect indication of the sensed force. Robots also perform material handling and gripping, here, tactile sensors are mounted on appropriate locations on the gripper/end effector. These sensors are then able to interact with the object by determining its orientation; the output of the sensor is then used to control the amount of force with which the object is gripped. For example, a robot could be used to serve water with a glass cup. If it applies too much force, the cup breaks; if the applied force is less, the cup falls and breaks. It must be able to apply just the right force and also know where to grab the cup for proper orientation. It should be noted that tactile sensors are also force sensors that use the stress/strain induced on a sensing material as an indication of the applied force.
- The Essential Guide to Load Cells, Tacuna Systems.
- Connecting a Force Sensor to a Data Acquisition System, Tacuna Systems
- Handbook of Modern Sensors, Physics, Design, and Applications, Jacob Fraden.
- Introduction to Robotics: Mechanics and Control by John J. Craig
- Fayang You, Jianqi An, "Iterative Learning Control for Batch Weighing and Feeding Process*," in 2018 37th Chinese Control Conference (CCC), 2018.