температура

The main information parameters of the microclimate of greenhouse premises are substantiated, in particular: air temperature, relative humidity, illumination of greenhouse premises, soil temperature, soil humidity, the concentration of carbon dioxide. The cyber-physical system for vegetables’ cultivation with the regulation of temperature-humidity-insolation regime contains three subsystems, namely the subsystem of temperature control, the subsystem of humidity control, and the subsystem of insolation control.

Gas flow temperature is an important parameter of the process, determines the quantitative and qualitative indicators of the original product, the presence of defects, the state of technological equipment, as well as the safety of the process. Therefore, its measurement must be carried out continuously, with high accuracy, low inertia and high reliability, since the information signal about the value of temperature is used in information-measuring systems and automatic control and regulation systems.

Investigations of methodical errors of two-color compensative and classical energy and spectral ratio pyrometry are  performed  under  conditions  of  changeable  radiative  characteristics  of metal  alloys. To  quantitatively  estimate  the  radiative characteristics we  proposed  such  parameters  as  an  average  level  of  emissivity  and  selectivity  factor. As  average  (adjustment) values  of  these  parameters  we  chose  the  values,  which  correspond  to  tungsten  in  vacuum  with  temperature  1600  K  (for wavelengths  0.7  and  0.9 µm).

The successful implementation of the systems of automation in metallurgical industry is impossible without the presence of reliable primary information about the parameters of technological process. A temperature is one of basic parameters that determine the quantitative and quality indicators of the final products. Therefore the technological processes of metallurgical industry need the presence of various primary transformers of temperature with high accuracy, sensitivity, stability and resistance to interference.

Study  of  the  dependence  of  the  temperature  determination  error  on  the  emissivity  factor  of  materials  is conducted  in  the  paper.  The  mathematical  models,  which  describe  the  ratio  of  thermodynamic  temperature  and  measured imaginary temperatures, taking into account the emissivity factor, are analyzed. The constructions of the full radiation, brightness radiation, and spectral ratio radiation pyrometers are underpinned by the considered models.

The  current  article  describes  the  results  of  the  study  of  the  neural  networks  temperature  prediction  error dependence  on  measurement  errors,  which  are  random,  nonlinear  and  multiplicative  errors.  It  is  noted  applicability  of  the architecture of neural network for temperature prediction. The formula of temperature step response for ideal sensor is given. 

The choice of ways of obtaining information about the temperature of the surface layers of a moving object is the crucial in determining  the  type of  temperature transducers. This choice depends on  the  row of specific  factors:  the speed of movement of the measured object relative the object, the state of the surface, the presence of related agents in near-surface layers, the presence of disturbing factors - noise, vibration, etc. The major factor seems to be the value of the heat carried out from the diagnosed object with the help of intermediate substance. 

Two main methods of contact measurement of steel temperature are applied in industry: with help of disposable  and multiple  used  thermotransducers.  Reusable  ones  are  fixed  to  the  bottom  of  the  graphite  tip  fixed directly on the reinforcement. Then they are able to measure the temperature of the graphite surface. Since it needs to even the graphite temperature and the temperature of the melt metal, the measuring takes some extra time. Therefore the  thermotransducer  is mounted  in  the metal  for a  long  time.

Current article considers the results of the study of air and water flow temperature prediction error on the number of  inputs  in  neural  network.  Authors  guide  the  architecture  of  neural  network  for  temperature  prediction.  The  formula  of temperature step  response  for  real sensor  is given. Also,  the method  for  calculating  the  time  constants  for  the  temperature step response formula using real measurement data is considered.

While studying the physical foundations of the temperature standard, we obtained a quantum unit of temperature as the value of the temperature jump when one electron-phonon scattering per unit time. We expressed it in terms of the ratio of fundamental physical constants h/kB; it is equal to 3.199 493 42 ∙ 10-11 K with a relative standard uncertainty of 59.2 ∙ 10-8. The investigated quantum standard is recommended for use as an "intrinsic standard", which does not require continuously repeated measurements (to check its accuracy) in relation to the current unit of temperature.