What are the best practices for optimizing sensor placement in control networks?

1 Sensor types and functions

Different types of sensors have different functions and characteristics, such as accuracy, precision, range, response time, power consumption, and cost. Depending on your control network, you may need to use sensors that measure physical variables such as temperature, pressure, flow, level, vibration, or position. Some sensors are passive, meaning they do not require external power or signal conditioning, while others are active, meaning they do. You should select the sensor types that best suit your control requirements, process dynamics, environmental conditions, and budget constraints.

2 Sensor number and redundancy

The number of sensors you need in your control network depends on several factors, such as the complexity and dimensionality of the process, the desired level of performance and robustness, the available communication and computation resources, and the trade-off between cost and quality. Generally, more sensors can provide more information and redundancy, which can improve the accuracy and reliability of the control network. However, more sensors also increase the complexity and cost of the network, and may introduce more noise and errors. Therefore, you should balance the benefits and drawbacks of adding or removing sensors, and use methods such as information theory or optimization to determine the optimal number and configuration of sensors.

3 Sensor location and distribution

The location and distribution of sensors in your control network can affect the observability and controllability of the system, which are measures of how well you can estimate and influence the state of the process. Ideally, you want to place the sensors where they can capture the most relevant and diverse information about the process, and where they can communicate effectively with the controllers and actuators. You should also consider the physical constraints and limitations of the process and the network, such as the geometry, accessibility, safety, and interference. You can use techniques such as graph theory, matrix analysis, or optimization to find the best sensor locations and distributions.

4 Sensor calibration and maintenance

Once you have selected and installed the sensors in your control network, you need to calibrate and maintain them regularly to ensure their accuracy and functionality. Calibration is the process of comparing the sensor output with a known standard or reference, and adjusting the sensor parameters or correcting the output accordingly. Maintenance is the process of inspecting, cleaning, repairing, or replacing the sensor components or devices. You should calibrate and maintain your sensors according to the manufacturer's specifications and recommendations, and according to the operating conditions and performance expectations of your control network.

5 Sensor fusion and filtering

Sensor fusion is the process of combining and integrating the data from multiple sensors to obtain a more complete and consistent representation of the process. Sensor fusion can enhance the quality and reliability of the sensor data, and reduce the uncertainty and noise. Sensor filtering is the process of removing or reducing the unwanted or erroneous components from the sensor data, such as outliers, drift, or bias. Sensor filtering can improve the accuracy and precision of the sensor data, and make it more suitable for control and analysis. You can use methods such as statistical analysis, machine learning, or signal processing to perform sensor fusion and filtering.

6 Sensor network design and optimization

Sensor network design and optimization is the overall process of selecting, placing, calibrating, maintaining, fusing, and filtering the sensors in your control network, to achieve your control objectives and minimize costs and errors. Sensor network design and optimization is a complex and challenging task that involves many trade-offs and constraints, and requires a good understanding of the process, the sensors, and the control network. You can use tools such as simulation, modeling, experimentation, or software to assist you in sensor network design and optimization, and to evaluate and compare different sensor network solutions.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?