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Soft Sensor
Soft sensor or virtual sensor is a common name for software where several measurements are processed together. Commonly soft sensors are based on control theory and also receive the name of state observer. There may be dozens or even hundreds of measurements. The interaction of the signals can be used for calculating new quantities that need not be measured. Soft sensors are especially useful in data fusion, where measurements of different characteristics and dynamics are combined. It can be used for fault diagnosis as well as control applications. Well-known software algorithms that can be seen as soft sensors include Kalman filters. More recent implementations of soft sensors use neural networks or fuzzy computing. Examples of soft sensor applications: * Kalman filters for estimating the location * Velocity estimators in electric motors * Estimating process data using self-organizing neural networks * Fuzzy computing in process control * Estimators of food quality See also * ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Virtual Sensing
Virtual sensing techniques, also called soft sensing, proxy sensing, inferential sensing, or surrogate sensing, are used to provide feasible and economical alternatives to costly or impractical physical measurement instrument Instrumentation is a collective term for measuring instruments, used for indicating, measuring, and recording physical quantities. It is also a field of study about the art and science about making measurement instruments, involving the related .... A virtual sensing system uses information available from other measurements and process parameters to calculate an estimate of the quantity of interest. In the field of gas sensors, an array of virtual sensors Benefits of virtual sensors for air quality monitoring in humid conditions can substitute electronic noses. Virtual gas sensors can be obtained by using a single sensor working in dynamic mode, i.e., working in repeated cycles that include a customized range of temperature, voltage, or both, which is e ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
State Observer
In control theory, a state observer, state estimator, or Luenberger observer is a system that provides an estimate of the state space (controls), internal state of a given real system, from measurements of the Input/output, input and output of the real system. It is typically computer-implemented, and provides the basis of many practical applications. Knowing the system state is necessary to solve many control theory problems; for example, stabilizing a system using Full state feedback, state feedback. In most practical cases, the physical state of the system cannot be determined by direct observation. Instead, indirect effects of the internal state are observed by way of the system outputs. A simple example is that of vehicles in a tunnel: the rates and velocities at which vehicles enter and leave the tunnel can be observed directly, but the exact state inside the tunnel can only be estimated. If a system is Observability, observable, it is possible to fully reconstruct the sy ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Sensor Fusion
Sensor fusion is a process of combining sensor data or data derived from disparate sources so that the resulting information has less uncertainty than would be possible if these sources were used individually. For instance, one could potentially obtain a more accurate location estimate of an indoor object by combining multiple data sources such as video cameras and WiFi localization signals. The term ''uncertainty reduction'' in this case can mean more accurate, more complete, or more dependable, or refer to the result of an emerging view, such as stereoscopic vision (calculation of depth information by combining two-dimensional images from two cameras at slightly different viewpoints). The data sources for a fusion process are not specified to originate from identical sensors. One can distinguish ''direct fusion'', ''indirect fusion'' and fusion of the outputs of the former two. Direct fusion is the fusion of sensor data from a set of heterogeneous or homogeneous sensors, soft s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Diagnosis
Diagnosis (: diagnoses) is the identification of the nature and cause of a certain phenomenon. Diagnosis is used in a lot of different academic discipline, disciplines, with variations in the use of logic, analytics, and experience, to determine "causality, cause and effect". In systems engineering and computer science, it is typically used to determine the causes of symptoms, mitigations, and solutions. Computer science and networking * Bayesian network * Complex event processing * Diagnosis (artificial intelligence) * Event correlation * Fault management * Fault tree analysis * Grey problem * RPR problem diagnosis * Remote diagnostics * Root cause analysis * Troubleshooting * Unified Diagnostic Services Mathematics and logic * Bayesian probability * Hickam's dictum, Block Hackam's dictum * Occam's razor * Regression analysis#Regression diagnostics, Regression diagnostics * Sutton's law Medicine * Medical diagnosis * Molecular diagnostics Methods * CDR computerized assessment ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Kalman Filter
In statistics and control theory, Kalman filtering (also known as linear quadratic estimation) is an algorithm that uses a series of measurements observed over time, including statistical noise and other inaccuracies, to produce estimates of unknown variables that tend to be more accurate than those based on a single measurement, by estimating a joint probability distribution over the variables for each time-step. The filter is constructed as a mean squared error minimiser, but an alternative derivation of the filter is also provided showing how the filter relates to maximum likelihood statistics. The filter is named after Rudolf E. Kálmán. Kalman filtering has numerous technological applications. A common application is for guidance, navigation, and control of vehicles, particularly aircraft, spacecraft and ships Dynamic positioning, positioned dynamically. Furthermore, Kalman filtering is much applied in time series analysis tasks such as signal processing and econometrics. K ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Neural Network
A neural network is a group of interconnected units called neurons that send signals to one another. Neurons can be either biological cells or signal pathways. While individual neurons are simple, many of them together in a network can perform complex tasks. There are two main types of neural networks. *In neuroscience, a '' biological neural network'' is a physical structure found in brains and complex nervous systems – a population of nerve cells connected by synapses. *In machine learning, an '' artificial neural network'' is a mathematical model used to approximate nonlinear functions. Artificial neural networks are used to solve artificial intelligence problems. In biology In the context of biology, a neural network is a population of biological neurons chemically connected to each other by synapses. A given neuron can be connected to hundreds of thousands of synapses. Each neuron sends and receives electrochemical signals called action potentials to its conne ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Fuzzy Logic
Fuzzy logic is a form of many-valued logic in which the truth value of variables may be any real number between 0 and 1. It is employed to handle the concept of partial truth, where the truth value may range between completely true and completely false. By contrast, in Boolean algebra, Boolean logic, the truth values of variables may only be the integer values 0 or 1. The term ''fuzzy logic'' was introduced with the 1965 proposal of fuzzy set theory by mathematician Lotfi A. Zadeh, Lotfi Zadeh. Fuzzy logic had, however, been studied since the 1920s, as Łukasiewicz logic, infinite-valued logic—notably by Jan Łukasiewicz, Łukasiewicz and Alfred Tarski, Tarski. Fuzzy logic is based on the observation that people make decisions based on imprecise and non-numerical information. Fuzzy models or fuzzy sets are mathematical means of representing vagueness and imprecise information (hence the term fuzzy). These models have the capability of recognising, representing, manipulating, in ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Location (geography)
In geography, location or place is used to denote a region (point, line, or area) on Earth's surface. The term ''location'' generally implies a higher degree of certainty than ''place'', the latter often indicating an entity with an ambiguous boundary, relying more on human or social attributes of place identity and sense of place than on geometry. A populated place is called a ''Human settlement, settlement''. Types Locality A suburb, locality, human settlement, settlement, or populated place is likely to have a well-defined name but a boundary that is not well defined, but rather varies by context. London, for instance, has a legal boundary, but this is unlikely to completely match with general usage. An area within a town, such as Covent Garden in London, also almost always has some ambiguity as to its extent. In geography, location is considered to be more precise than "place". Relative location A relative location, or situation, is described as a displacement from another si ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Electric Motor
An electric motor is a machine that converts electrical energy into mechanical energy. Most electric motors operate through the interaction between the motor's magnetic field and electric current in a electromagnetic coil, wire winding to generate Laplace force in the form of torque applied on the motor's shaft. An electric generator is mechanically identical to an electric motor, but operates in reverse, converting mechanical energy into electrical energy. Electric motors can be powered by direct current (DC) sources, such as from batteries or rectifiers, or by alternating current (AC) sources, such as a power grid, Inverter (electrical), inverters or electrical generators. Electric motors may also be classified by considerations such as power source type, construction, application and type of motion output. They can be brushed motor, brushed or brushless motor, brushless, single-phase electric power, single-phase, two-phase electric power, two-phase, or three-phase electric p ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Self-organization
Self-organization, also called spontaneous order in the social sciences, is a process where some form of overall order and disorder, order arises from local interactions between parts of an initially disordered system. The process can be spontaneous when sufficient energy is available, not needing control by any external agent. It is often triggered by seemingly random Statistical fluctuations, fluctuations, amplified by positive feedback. The resulting organization is wholly decentralized, :wikt:distribute, distributed over all the components of the system. As such, the organization is typically Robustness, robust and able to survive or self-healing material, self-repair substantial perturbation theory, perturbation. Chaos theory discusses self-organization in terms of islands of predictability in a sea of chaotic unpredictability. Self-organization occurs in many physics, physical, chemistry, chemical, biology, biological, robotics, robotic, and cognitive systems. Examples of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
Process Control
Industrial process control (IPC) or simply process control is a system used in modern manufacturing which uses the principles of control theory and physical industrial control systems to monitor, control and optimize continuous Industrial processes, industrial production processes using control algorithms. This ensures that the industrial machines run smoothly and safely in factories and efficiently use energy to transform raw materials into high-quality finished products with reliable consistency while reducing Efficient energy use#Industry, energy waste and economic costs, something which could not be achieved purely by human manual control. In IPC, control theory provides the theoretical framework to understand system dynamics, predict outcomes and design control strategies to ensure predetermined objectives, utilizing concepts like feedback loops, stability analysis and controller design. On the other hand, the physical apparatus of IPC, based on automation technologies, cons ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
State Observer
In control theory, a state observer, state estimator, or Luenberger observer is a system that provides an estimate of the state space (controls), internal state of a given real system, from measurements of the Input/output, input and output of the real system. It is typically computer-implemented, and provides the basis of many practical applications. Knowing the system state is necessary to solve many control theory problems; for example, stabilizing a system using Full state feedback, state feedback. In most practical cases, the physical state of the system cannot be determined by direct observation. Instead, indirect effects of the internal state are observed by way of the system outputs. A simple example is that of vehicles in a tunnel: the rates and velocities at which vehicles enter and leave the tunnel can be observed directly, but the exact state inside the tunnel can only be estimated. If a system is Observability, observable, it is possible to fully reconstruct the sy ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] [Amazon] |
