Definitions Soft sensor is a common name for software where several measurements are processed together. There may be dozens or even hundreds of measurements. The interaction of the signals can be used for calculating new quantities that can not be measured. Soft sensors or inferential calculators are operators' virtual eyes. Soft sensors create windows to a process where physical equivalents a...

A soft tactile sensor able to detect both normal and tangential forces is fabricated with a simple method using conductive textile. Owing to the multi-layered architecture, the capacitive-based tactile sensor is highly sensitive (less than 10 mg and 8 μm, for minimal detectable weight and displacement, respectively) within a wide normal force range (potentially up to 27 N (400 kPa)) and natural...

One of the challenges of utilizing soft sensors is that their prediction accuracy deteriorates with time due to multiple factors, including changes in operating conditions. Once soft sensors are designed, a mechanism to maintain or update these models is highly desirable in industry. This paper proposes an index that can monitor the prediction performance of soft sensor models and provide guida...

In this paper, a predictive soft sensor via a Recurrent Neural Network is proposed for sensing the area between the tires and the terrain, which is one of the most important issues in the automotive industry, in fact, keeping a tire contact patch suitable ensures the comfort and maneuverability of the vehicle. The core of the soft sensor is an recurrent neural network, the training of a recurre...

For meeting the forecasting target of key technology indicators in the flotation process, a BP neural network soft-sensor model based on features extraction of flotation froth images and optimized by shuffled cuckoo search algorithm is proposed. Based on the digital image processing technique, the color features in HSI color space, the visual features based on the gray level cooccurrence matrix...

Sensors take measurements and provide feedback to the user via a calibrated system, in soft sensing the development of such systems is complicated by the presence of nonlinearities, e.g. contact, material properties and complex geometries. When designing soft-sensors it is desirable for them to be inexpensive and capable of providing high resolution output. Often these constraints limit the com...

The parameters of mill load (ML) not only represent the load of the ball mill, but also determine the grinding production ratio (GPR) of the grinding process. In this paper, a novel soft sensor approach based on multi-spectral segments partial least square (PLS) model and on-line adaptive weighted fusion algorithm is proposed to estimate the ML parameters. At first, frequency spectrums of the s...

For predicting the key technology indicators (concentrate grade and tailings recovery rate) of flotation process, a feed-forward neural network (FNN) based soft-sensor model optimized by the hybrid algorithm combining particle swarm optimization (PSO) algorithm and gravitational search algorithm (GSA) is proposed. Although GSA has better optimization capability, it has slow convergence velocity...

Control of nonlinear systems exhibiting complex dynamic behavior is a challenging task because such systems present a variety of behavioral patterns depending on the values of physical parameters and intrinsic features. Understanding the behavior of the nonlinear dynamic systems and controlling them at the desired conditions is important to enhance their performance. In this work, a soft sensor...