11 research outputs found

    ΠžΡΠΎΠ±Π΅Π½Π½ΠΎΡΡ‚ΠΈ примСнСния ΠΊΠΎΠΌΠ±ΠΈΠ½ΠΈΡ€ΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ ΠΏΠΎΠ΄Ρ…ΠΎΠ΄Π° ΠΊ ΠΎΡ†Π΅Π½ΠΈΠ²Π°Π½ΠΈΡŽ нСопрСдСлённости Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΎΠ² ΠΈΠ·ΠΌΠ΅Ρ€Π΅Π½ΠΈΠΉ

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    The article exposes description of features of the combined approach application to the evaluation of measurement results uncertainty. The aim of this work is the justification and development of new science-driven approaches to achieve maximum efficacy of measurements on the criteria "accuracy/costs" at the stated level of confidence.It provides theoretical base for correctness of combined approach to assess measurement results uncertainty. There is proposition to conventionally divide measurement process into fragments – combining objects, each from shall be considered as individual element for evaluation. It is well known that combining objects can be formed by grouping individual components (resources) of the measurement process either via separate stages of the measurement process.Correctness of such approach is based on the application of "resource" and "process" approaches as regards identification of the factors that affect the measurement results uncertainty. This article provides recommendations on selection of model or empiric approach for evaluating of particular contributions from combining objects of different types into total uncertainty of the final measurement result. In order to improve the validity of empiric approach of the criteria of sufficiency of measurement method uncertainty examination was formulated. It is recommended to evaluate the total uncertainty of the final measurement result by complexation of evaluations of particular total uncertainty of the results for all fragments according to the uncertainties distribution law.It is determined two typical cases of effective application of the combined approach to evaluation of measurement results uncertainty: method of direct measurements and method of indirect measurements. This article considers features of effective application of the combined approach for both situations providing corresponding examples. Special attention is paid to the application of the combined approach to assessing the test results uncertainty. As distinct from the measurement process realized under normal conditions, testing process includes additional external influence factors that are determined by test conditions.РассмотрСны особСнности эффСктивного примСнСния ΠΊΠΎΠΌΠ±ΠΈΠ½ΠΈΡ€ΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ ΠΏΠΎΠ΄Ρ…ΠΎΠ΄Π° ΠΊ ΠΎΡ†Π΅Π½ΠΈΠ²Π°Π½ΠΈΡŽ нСопрСдСлённости Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΎΠ² ΠΈΠ·ΠΌΠ΅Ρ€Π΅Π½ΠΈΠΉ. ЦСлью Π΄Π°Π½Π½ΠΎΠΉ Ρ€Π°Π±ΠΎΡ‚Ρ‹ являлось обоснованиС ΠΈ Ρ€Π°Π·Π²ΠΈΡ‚ΠΈΠ΅ Π½ΠΎΠ²Ρ‹Ρ… Π½Π°ΡƒΠΊΠΎΡ‘ΠΌΠΊΠΈΡ… ΠΏΠΎΠ΄Ρ…ΠΎΠ΄ΠΎΠ² ΠΏΠΎ Π΄ΠΎΡΡ‚ΠΈΠΆΠ΅Π½ΠΈΡŽ максимальной эффСктивности ΠΈΠ·ΠΌΠ΅Ρ€Π΅Π½ΠΈΠΉ ΠΏΠΎ ΠΊΡ€ΠΈΡ‚Π΅Ρ€ΠΈΡŽ Β«Ρ‚ΠΎΡ‡Π½ΠΎΡΡ‚ΡŒ/Ρ‚Ρ€ΡƒΠ΄ΠΎΡ‘ΠΌΠΊΠΎΡΡ‚ΡŒΒ» ΠΏΡ€ΠΈ Π·Π°Π΄Π°Π½Π½ΠΎΠΉ стСпСни довСрия.ВСорСтичСски обоснована ΠΊΠΎΡ€Ρ€Π΅ΠΊΡ‚Π½ΠΎΡΡ‚ΡŒ ΠΊΠΎΠΌΠ±ΠΈΠ½ΠΈΡ€ΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ ΠΏΠΎΠ΄Ρ…ΠΎΠ΄Π° ΠΊ ΠΎΡ†Π΅Π½ΠΈΠ²Π°Π½ΠΈΡŽ нСопрСдСлённости Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΎΠ² ΠΈΠ·ΠΌΠ΅Ρ€Π΅Π½ΠΈΠΉ. ΠŸΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΎ процСсс измСрСния условно Π΄Π΅Π»ΠΈΡ‚ΡŒ Π½Π° Ρ„Ρ€Π°Π³ΠΌΠ΅Π½Ρ‚Ρ‹ – ΠΎΠ±ΡŠΠ΅ΠΊΡ‚Ρ‹ комбинирования, ΠΊΠ°ΠΆΠ΄Ρ‹ΠΉ ΠΈΠ· ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Ρ… слСдуСт Ρ€Π°ΡΡΠΌΠ°Ρ‚Ρ€ΠΈΠ²Π°Ρ‚ΡŒ ΠΊΠ°ΠΊ ΡΠ°ΠΌΠΎΡΡ‚ΠΎΡΡ‚Π΅Π»ΡŒΠ½Ρ‹ΠΉ элСмСнт оцСнивания. УстановлСно, Ρ‡Ρ‚ΠΎ ΠΎΠ±ΡŠΠ΅ΠΊΡ‚Ρ‹ комбинирования ΠΌΠΎΠ³ΡƒΡ‚ Π±Ρ‹Ρ‚ΡŒ сформированы ΠΏΡƒΡ‚Ρ‘ΠΌ группирования Π»ΠΈΠ±ΠΎ ΠΎΡ‚Π΄Π΅Π»ΡŒΠ½Ρ‹Ρ… ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½Ρ‚ΠΎΠ² (рСсурсов) процСсса ΠΈΠ·ΠΌΠ΅Ρ€Π΅Π½ΠΈΠΉ, Π»ΠΈΠ±ΠΎ ΠΎΡ‚Π΄Π΅Π»ΡŒΠ½Ρ‹Ρ… этапов процСсса ΠΈΠ·ΠΌΠ΅Ρ€Π΅Π½ΠΈΠΉ.ΠšΠΎΡ€Ρ€Π΅ΠΊΡ‚Π½ΠΎΡΡ‚ΡŒ Ρ‚Π°ΠΊΠΎΠ³ΠΎ ΠΏΠΎΠ΄Ρ…ΠΎΠ΄Π° обоснована ΠΏΡ€ΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ΠΌ «рСсурсного» ΠΈ «процСссного» ΠΏΠΎΠ΄Ρ…ΠΎΠ΄ΠΎΠ² ΠΊ ΠΈΠ΄Π΅Π½Ρ‚ΠΈΡ„ΠΈΠΊΠ°Ρ†ΠΈΠΈ Π²Π»ΠΈΡΡŽΡ‰ΠΈΡ… Π½Π° Π½Π΅ΠΎΠΏΡ€Π΅Π΄Π΅Π»Ρ‘Π½Π½ΠΎΡΡ‚ΡŒ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Π° ΠΈΠ·ΠΌΠ΅Ρ€Π΅Π½ΠΈΠΉ. ΠŸΡ€ΠΈΠ²Π΅Π΄Π΅Π½Ρ‹ Ρ€Π΅ΠΊΠΎΠΌΠ΅Π½Π΄Π°Ρ†ΠΈΠΈ ΠΏΠΎ Π²Ρ‹Π±ΠΎΡ€Ρƒ модСльного ΠΈΠ»ΠΈ эмпиричСского ΠΏΠΎΠ΄Ρ…ΠΎΠ΄ΠΎΠ² для оцСнивания частных Π²ΠΊΠ»Π°Π΄ΠΎΠ² ΠΎΠ±ΡŠΠ΅ΠΊΡ‚ΠΎΠ² комбинирования Ρ€Π°Π·Π»ΠΈΡ‡Π½ΠΎΠ³ΠΎ Ρ‚ΠΈΠΏΠ° Π² ΡΡƒΠΌΠΌΠ°Ρ€Π½ΡƒΡŽ Π½Π΅ΠΎΠΏΡ€Π΅Π΄Π΅Π»Ρ‘Π½Π½ΠΎΡΡ‚ΡŒ ΠΊΠΎΠ½Π΅Ρ‡Π½ΠΎΠ³ΠΎ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Π° ΠΈΠ·ΠΌΠ΅Ρ€Π΅Π½ΠΈΠΉ. Для ΠΏΠΎΠ²Ρ‹ΡˆΠ΅Π½ΠΈΡ достовСрности эмпиричСского ΠΏΠΎΠ΄Ρ…ΠΎΠ΄Π° сформулирован ΠΊΡ€ΠΈΡ‚Π΅Ρ€ΠΈΠΉ достаточности исслСдования нСопрСдСлённости ΠΌΠ΅Ρ‚ΠΎΠ΄Π° ΠΈΠ·ΠΌΠ΅Ρ€Π΅Π½ΠΈΠΉ. ΠžΡ†Π΅Π½ΠΈΠ²Π°Π½ΠΈΠ΅ суммарной нСопрСдСлённости ΠΊΠΎΠ½Π΅Ρ‡Π½ΠΎΠ³ΠΎ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Π° ΠΈΠ·ΠΌΠ΅Ρ€Π΅Π½ΠΈΠΉ Ρ€Π΅ΠΊΠΎΠΌΠ΅Π½Π΄ΠΎΠ²Π°Π½ΠΎ ΠΏΡ€ΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡ‚ΡŒ ΠΏΡƒΡ‚Ρ‘ΠΌ комплСксирования ΠΎΡ†Π΅Π½ΠΎΠΊ частных суммарных нСопрСдСлённостСй Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΎΠ² всСх Ρ„Ρ€Π°Π³ΠΌΠ΅Π½Ρ‚ΠΎΠ² ΠΏΠΎ Π·Π°ΠΊΠΎΠ½Ρƒ распространСния нСопрСдСлённостСй.Π’Ρ‹Π΄Π΅Π»Π΅Π½Ρ‹ Π΄Π²Π° Ρ‚ΠΈΠΏΠΈΡ‡Π½Ρ‹Ρ… случая эффСктивного примСнСния ΠΊΠΎΠΌΠ±ΠΈΠ½ΠΈΡ€ΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ ΠΏΠΎΠ΄Ρ…ΠΎΠ΄Π° ΠΊ ΠΎΡ†Π΅Π½ΠΈΠ²Π°Π½ΠΈΡŽ нСопрСдСлённости Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΎΠ² ΠΈΠ·ΠΌΠ΅Ρ€Π΅Π½ΠΈΠΉ: ΠΌΠ΅Ρ‚ΠΎΠ΄ прямых ΠΈΠ·ΠΌΠ΅Ρ€Π΅Π½ΠΈΠΉ ΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄ косвСнных ΠΈΠ·ΠΌΠ΅Ρ€Π΅Π½ΠΈΠΉ. РассмотрСны особСнности эффСктивного примСнСния ΠΊΠΎΠΌΠ±ΠΈΠ½ΠΈΡ€ΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ ΠΏΠΎΠ΄Ρ…ΠΎΠ΄Π° для ΠΎΠ±Π΅ΠΈΡ… ситуаций Π½Π° ΠΊΠΎΠ½ΠΊΡ€Π΅Ρ‚Π½Ρ‹Ρ… ΠΏΡ€ΠΈΠΌΠ΅Ρ€Π°Ρ…. ОсобоС Π²Π½ΠΈΠΌΠ°Π½ΠΈΠ΅ ΡƒΠ΄Π΅Π»Π΅Π½ΠΎ ΠΏΡ€ΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡŽ ΠΊΠΎΠΌΠ±ΠΈΠ½ΠΈΡ€ΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ ΠΏΠΎΠ΄Ρ…ΠΎΠ΄Π° для оцСнивания нСопрСдСлённости Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΎΠ² испытаний. Π’ ΠΎΡ‚Π»ΠΈΡ‡ΠΈΠ΅ ΠΎΡ‚ процСсса ΠΈΠ·ΠΌΠ΅Ρ€Π΅Π½ΠΈΠΉ, Ρ€Π΅Π°Π»ΠΈΠ·ΡƒΠ΅ΠΌΠΎΠ³ΠΎ Π² Π½ΠΎΡ€ΠΌΠ°Π»ΡŒΠ½Ρ‹Ρ… условиях, Π² процСсс испытаний Π²ΠΎΠ²Π»Π΅Ρ‡Π΅Π½Ρ‹ Π΄ΠΎΠΏΠΎΠ»Π½ΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹Π΅ Ρ„Π°ΠΊΡ‚ΠΎΡ€Ρ‹ Π²Π½Π΅ΡˆΠ½ΠΈΡ… воздСйствий, ΠΎΠΏΡ€Π΅Π΄Π΅Π»Ρ‘Π½Π½Ρ‹Π΅ условиями испытаний

    ΠžΡ†Π΅Π½ΠΊΠ° производствСнной тСхнологичности конструкции Π² ΠΆΠΈΠ·Π½Π΅Π½Π½ΠΎΠΌ Ρ†ΠΈΠΊΠ»Π΅ издСлия

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    On the basis of technical and economic analysis of the properties of relations between design and technological solutions, a method for the integral assessment of production manufacturability by combining individual manufacturability coefficients at different stages of the product life cycle is suggested. Separate coefficients take into account the influence degree of various constituent stages on the labor intensity of production and maintenance, repair and disposal of the product structure. Design and technological solutions in design systems imply the use of properties such as reflexivity, symmetry and transitivity. As a result, it is proposed to understand the properties set of the product design that determine its adaptability to achieve optimal costs in production and disposal for specified quality indicators and work conditions. A list of manufacturability coefficients of manufacturing a product design has been determined, including coefficients of purchase, repeatability of details and connections, material hardness, borrowing, typing, precision, roughness, mass. An examination of the effectiveness assessment the use tools, equipment and other objects of the technological environment at the stages design and technological production preparation is formalized. The examination includes an analysis of the frequency and duration of the meeting of structural parts elements and the tools state at the stages of their manufacture, operation and disposal.На основС Ρ‚Π΅Ρ…Π½ΠΈΠΊΠΎ-экономичСского Π°Π½Π°Π»ΠΈΠ·Π° свойств ΠΎΡ‚Π½ΠΎΡˆΠ΅Π½ΠΈΠΉ конструкторско-тСхнологичСских Ρ€Π΅ΡˆΠ΅Π½ΠΈΠΉ ΠΏΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½ ΠΌΠ΅Ρ‚ΠΎΠ΄ ΠΈΠ½Ρ‚Π΅Π³Ρ€Π°Π»ΡŒΠ½ΠΎΠΉ ΠΎΡ†Π΅Π½ΠΊΠΈ производствСнной тСхнологичности ΠΏΡƒΡ‚Π΅ΠΌ объСдинСния ΠΎΡ‚Π΄Π΅Π»ΡŒΠ½Ρ‹Ρ… коэффициСнтов тСхнологичности Π½Π° Ρ€Π°Π·Π»ΠΈΡ‡Π½Ρ‹Ρ… этапах ΠΆΠΈΠ·Π½Π΅Π½Π½ΠΎΠ³ΠΎ Ρ†ΠΈΠΊΠ»Π° издСлия. ΠžΡ‚Π΄Π΅Π»ΡŒΠ½Ρ‹Π΅ коэффициСнты ΡƒΡ‡ΠΈΡ‚Ρ‹Π²Π°ΡŽΡ‚ ΡΡ‚Π΅ΠΏΠ΅Π½ΡŒ влияния Ρ€Π°Π·Π»ΠΈΡ‡Π½Ρ‹Ρ… ΡΠΎΡΡ‚Π°Π²Π»ΡΡŽΡ‰ΠΈΡ… этапов Π½Π° Ρ‚Ρ€ΡƒΠ΄ΠΎΠ΅ΠΌΠΊΠΎΡΡ‚ΡŒ производства ΠΈ обслуТивания, Ρ€Π΅ΠΌΠΎΠ½Ρ‚Π° ΠΈ ΡƒΡ‚ΠΈΠ»ΠΈΠ·Π°Ρ†ΠΈΠΈ конструкции издСлия. ΠšΠΎΠ½ΡΡ‚Ρ€ΡƒΠΊΡ‚ΠΎΡ€ΡΠΊΠΎ-тСхнологичСскиС Ρ€Π΅ΡˆΠ΅Π½ΠΈΡ Π² систСмах проСктирования ΠΏΡ€Π΅Π΄ΠΏΠΎΠ»Π°Π³Π°ΡŽΡ‚ использованиС Ρ‚Π°ΠΊΠΈΡ… свойств, ΠΊΠ°ΠΊ Ρ€Π΅Ρ„Π»Π΅ΠΊΡΠΈΠ²Π½ΠΎΡΡ‚ΡŒ, ΡΠΈΠΌΠΌΠ΅Ρ‚Ρ€ΠΈΡ‡Π½ΠΎΡΡ‚ΡŒ ΠΈ Ρ‚Ρ€Π°Π½Π·ΠΈΡ‚ΠΈΠ²Π½ΠΎΡΡ‚ΡŒ. Π’ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Π΅ ΠΏΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΎ ΠΏΠΎΠ΄ производствСнной Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³ΠΈΡ‡Π½ΠΎΡΡ‚ΡŒΡŽ ΠΏΠΎΠ½ΠΈΠΌΠ°Ρ‚ΡŒ ΡΠΎΠ²ΠΎΠΊΡƒΠΏΠ½ΠΎΡΡ‚ΡŒ свойств конструкции издСлия, ΠΎΠΏΡ€Π΅Π΄Π΅Π»ΡΡŽΡ‰ΠΈΡ… Π΅Π΅ ΠΏΡ€ΠΈΡΠΏΠΎΡΠΎΠ±Π»Π΅Π½Π½ΠΎΡΡ‚ΡŒ ΠΊ Π΄ΠΎΡΡ‚ΠΈΠΆΠ΅Π½ΠΈΡŽ ΠΎΠΏΡ‚ΠΈΠΌΠ°Π»ΡŒΠ½Ρ‹Ρ… Π·Π°Ρ‚Ρ€Π°Ρ‚ ΠΏΡ€ΠΈ производствС ΠΈ ΡƒΡ‚ΠΈΠ»ΠΈΠ·Π°Ρ†ΠΈΠΈ для Π·Π°Π΄Π°Π½Π½Ρ‹Ρ…Β ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»Π΅ΠΉ качСства ΠΈ условий выполнСния Ρ€Π°Π±ΠΎΡ‚. ΠžΠΏΡ€Π΅Π΄Π΅Π»Π΅Π½ ΠΏΠ΅Ρ€Π΅Ρ‡Π΅Π½ΡŒ коэффициСнтов тСхнологичности изготовлСния конструкции издСлия, Π²ΠΊΠ»ΡŽΡ‡Π°ΡŽΡ‰ΠΈΠΉ коэффициСнты покупаСмости, повторяСмости Π΄Π΅Ρ‚Π°Π»Π΅ΠΉ ΠΈ соСдинСний, твСрдости ΠΌΠ°Ρ‚Π΅Ρ€ΠΈΠ°Π»Π°, заимствования, Ρ‚ΠΈΠΏΠΈΠ·Π°Ρ†ΠΈΠΈ, точности, ΡˆΠ΅Ρ€ΠΎΡ…ΠΎΠ²Π°Ρ‚ΠΎΡΡ‚ΠΈ, массы. Π€ΠΎΡ€ΠΌΠ°Π»ΠΈΠ·ΠΎΠ²Π°Π½Π° экспСртиза ΠΎΡ†Π΅Π½ΠΊΠΈ эффСктивности примСнСния инструмСнтов, срСдств оснащСния ΠΈ Π΄Ρ€ΡƒΠ³ΠΈΡ… ΠΎΠ±ΡŠΠ΅ΠΊΡ‚ΠΎΠ² тСхнологичСской срСды Π½Π° стадиях конструкторской ΠΈ тСхнологичСской ΠΏΠΎΠ΄Π³ΠΎΡ‚ΠΎΠ²ΠΊΠΈ производства. ЭкспСртиза Π²ΠΊΠ»ΡŽΡ‡Π°Π΅Ρ‚ Π°Π½Π°Π»ΠΈΠ· частоты ΠΈ ΠΏΡ€ΠΎΠ΄ΠΎΠ»ΠΆΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎΡΡ‚ΠΈ встрСчи конструктивных элСмСнтов Π΄Π΅Ρ‚Π°Π»Π΅ΠΉ ΠΈ состояния инструмСнтов Π½Π° этапах ΠΈΡ… изготовлСния, эксплуатации ΠΈ ΡƒΡ‚ΠΈΠ»ΠΈΠ·Π°Ρ†ΠΈΠΈ

    РИБК-ΠžΠ Π˜Π•ΠΠ’Π˜Π ΠžΠ’ΠΠΠΠ«Π™ ΠŸΠžΠ”Π₯ΠžΠ” К Π ΠΠ—Π ΠΠ‘ΠžΠ’ΠšΠ• ΠœΠ•Π’ΠžΠ”Π˜Πš ΠšΠžΠΠ’Π ΠžΠ›Π―

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    The necessity for scientific and methodical study of methods for monitoring the characteristics of flameresistance of building structures has the highest priority in the field of fire safety. The aim of this work was to provide the required degree of reliability of the results of quality control of flame-resistant coatings of building structures and high efficiency of decisions due to the risk-based approach to the development of control methods.Substantiated risk-based approach to the development of methods of control, involving the consideration on the basis of process model, control flame-resistance of building object in all possible potential problems that can cause the risk of incorrect decision-making. A model of the risks arising from the control of the flameretardant coating thickness has been developed. Two major risk groups have been identified. The first group is related to the uncertainty of coating thickness measurement at a single control point. The second group of risks is related to the unrepresentativeness of selective control over the entire surface of the construction object as a whole Potential risk sources have been identified for each group. For the entire range of sources of particular risks the results of studies of the mechanisms of their manifestation, the estimated degree of influence on the accuracy of the control of compliance of flame-retardant coating thickness requirements. The analysis is carried out on the basis of both theoretical and experimental statistical studies on a number of construction projects.According to the results of the analysis of all particular risks of control unreliability, rational ways of their minimization in the form of technical or organizational and technical measures, which are refl in the developed project of the control method, are proposed. Project control method was built on the basis of a agreed scheme of control of the thickness of the fl coating of building structures sequentially the three parties.Β Formulated and solved the task of the metrological control of the thickness of the flame-retardant coating as indirect measurement methods non-destructive thickness measurements. Theoretical and applied aspects of the process of flame-retardant coating thickness control of building structures under conditions of high risk of making incorrect decisions on the results of control are considered.ΠΠ΅ΠΎΠ±Ρ…ΠΎΠ΄ΠΈΠΌΠΎΡΡ‚ΡŒ Π½Π°ΡƒΡ‡Π½ΠΎ-мСтодичСской ΠΏΡ€ΠΎΡ€Π°Π±ΠΎΡ‚ΠΊΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊ контроля характСристик огнСстойкости ΡΡ‚Ρ€ΠΎΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹Ρ… конструкций (БК) ΠΈΠΌΠ΅Π΅Ρ‚ Π½Π°ΠΈΠ²Ρ‹ΡΡˆΠΈΠΉ ΠΏΡ€ΠΈΠΎΡ€ΠΈΡ‚Π΅Ρ‚ Π² области обСспСчСния ΠΏΠΎΠΆΠ°Ρ€Π½ΠΎΠΉ бСзопасности. ЦСлью Π΄Π°Π½Π½ΠΎΠΉ Ρ€Π°Π±ΠΎΡ‚Ρ‹ являлось обСспСчСниС Ρ‚Ρ€Π΅Π±ΡƒΠ΅ΠΌΠΎΠΉ стСпСни достовСрности Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΎΠ² контроля качСства огнСстойких ΠΏΠΎΠΊΡ€Ρ‹Ρ‚ΠΈΠΉ ΡΡ‚Ρ€ΠΎΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹Ρ… конструкций ΠΈ высокой эффСктивности ΠΏΡ€ΠΈΠ½ΠΈΠΌΠ°Π΅ΠΌΡ‹Ρ… Ρ€Π΅ΡˆΠ΅Π½ΠΈΠΉ Π·Π° счСт риск-ΠΎΡ€ΠΈΠ΅Π½Ρ‚ΠΈΡ€ΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ ΠΏΠΎΠ΄Ρ…ΠΎΠ΄Π° ΠΊ Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚ΠΊΠ΅ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠΈ контроля.Обоснован риск-ΠΎΡ€ΠΈΠ΅Π½Ρ‚ΠΈΡ€ΠΎΠ²Π°Π½Π½Ρ‹ΠΉ ΠΏΠΎΠ΄Ρ…ΠΎΠ΄ ΠΊ Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚ΠΊΠ΅ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠΈ контроля, ΠΏΡ€Π΅Π΄ΠΏΠΎΠ»Π°Π³Π°ΡŽΡ‰ΠΈΠΉ рассмотрСниС Π½Π° Π±Π°Π·Π΅ процСссной ΠΌΠΎΠ΄Π΅Π»ΠΈ контроля огнСстойкости ΡΡ‚Ρ€ΠΎΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎΠ³ΠΎ ΠΎΠ±ΡŠΠ΅ΠΊΡ‚Π° всСх Π²ΠΎΠ·ΠΌΠΎΠΆΠ½Ρ‹Ρ… ΠΏΠΎΡ‚Π΅Π½Ρ†ΠΈΠ°Π»ΡŒΠ½Ρ‹Ρ… ΠΏΡ€ΠΎΠ±Π»Π΅ΠΌ, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Π΅ ΠΌΠΎΠ³ΡƒΡ‚ Π²Ρ‹Π·Π²Π°Ρ‚ΡŒ риск Π½Π΅ΠΊΠΎΡ€Ρ€Π΅ΠΊΡ‚Π½ΠΎΠ³ΠΎ принятия Ρ€Π΅ΡˆΠ΅Π½ΠΈΡ. Π Π°Π·Ρ€Π°Π±ΠΎΡ‚Π°Π½Π° модСль рисков, Π²ΠΎΠ·Π½ΠΈΠΊΠ°ΡŽΡ‰ΠΈΡ… ΠΏΡ€ΠΈ ΠΊΠΎΠ½Ρ‚Ρ€ΠΎΠ»Π΅ Ρ‚ΠΎΠ»Ρ‰ΠΈΠ½Ρ‹ ΠΎΠ³Π½Π΅Π·Π°Ρ‰ΠΈΡ‚Π½ΠΎΠ³ΠΎ покрытия. Π˜Π΄Π΅Π½Ρ‚ΠΈΡ„ΠΈΡ†ΠΈΡ€ΠΎΠ²Π°Π½Ρ‹ Π΄Π²Π΅ основныС Π³Ρ€ΡƒΠΏΠΏΡ‹ рисков. ΠŸΠ΅Ρ€Π²Π°Ρ Π³Ρ€ΡƒΠΏΠΏΠ° связана с Π½Π΅ΠΎΠΏΡ€Π΅Π΄Π΅Π»Π΅Π½Π½ΠΎΡΡ‚ΡŒΡŽ измСрСния Ρ‚ΠΎΠ»Ρ‰ΠΈΠ½Ρ‹ покрытия Π² Π΅Π΄ΠΈΠ½ΠΈΡ‡Π½ΠΎΠΉ Ρ‚ΠΎΡ‡ΠΊΠ΅ контроля. Вторая Π³Ρ€ΡƒΠΏΠΏΠ° рисков связана с Π½Π΅Ρ€Π΅ΠΏΡ€Π΅Π·Π΅Π½Ρ‚Π°Ρ‚ΠΈΠ²Π½ΠΎΡΡ‚ΡŒΡŽ Π²Ρ‹Π±ΠΎΡ€ΠΎΡ‡Π½ΠΎΠ³ΠΎ контроля всСй повСрхности ΡΡ‚Ρ€ΠΎΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎΠ³ΠΎ ΠΎΠ±ΡŠΠ΅ΠΊΡ‚Π° Π² Ρ†Π΅Π»ΠΎΠΌ. Для ΠΊΠ°ΠΆΠ΄ΠΎΠΉ Π³Ρ€ΡƒΠΏΠΏΡ‹ ΠΎΠΏΡ€Π΅Π΄Π΅Π»Π΅Π½Ρ‹ ΠΏΠΎΡ‚Π΅Π½Ρ†ΠΈΠ°Π»ΡŒΠ½Ρ‹Π΅ источники рисков. Для всСго комплСкса источников частных рисков ΠΏΡ€ΠΈΠ²Π΅Π΄Π΅Π½Ρ‹ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹ исслСдований ΠΌΠ΅Ρ…Π°Π½ΠΈΠ·ΠΌΠΎΠ² ΠΈΡ… проявлСния, ΠΎΡ†Π΅Π½Π΅Π½Π° ΡΡ‚Π΅ΠΏΠ΅Π½ΡŒ влияния Π½Π° Π΄ΠΎΡΡ‚ΠΎΠ²Π΅Ρ€Π½ΠΎΡΡ‚ΡŒ контроля соотвСтствия Ρ‚ΠΎΠ»Ρ‰ΠΈΠ½Ρ‹ ΠΎΠ³Π½Π΅Π·Π°Ρ‰ΠΈΡ‚Π½ΠΎΠ³ΠΎ покрытия трСбованиям. Анализ ΠΏΡ€ΠΎΠ²Π΅Π΄Π΅Π½ Π½Π° основС ΠΊΠ°ΠΊ тСорСтичСских, Ρ‚Π°ΠΊ ΠΈ ΡΠΊΡΠΏΠ΅Ρ€ΠΈΠΌΠ΅Π½Ρ‚Π°Π»ΡŒΠ½Ρ‹Ρ… статистичСских исслСдований Π½Π° рядС ΡΡ‚Ρ€ΠΎΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹Ρ… ΠΎΠ±ΡŠΠ΅ΠΊΡ‚ΠΎΠ².По Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Π°ΠΌ Π°Π½Π°Π»ΠΈΠ·Π° всСх частных рисков нСдостовСрности контроля ΠΏΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½Ρ‹ Ρ€Π°Ρ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½Ρ‹Π΅ ΠΏΡƒΡ‚ΠΈ ΠΈΡ… ΠΌΠΈΠ½ΠΈΠΌΠΈΠ·Π°Ρ†ΠΈΠΈ Π² Π²ΠΈΠ΄Π΅ тСхничСских ΠΈΠ»ΠΈ ΠΎΡ€Π³Π°Π½ΠΈΠ·Π°Ρ†ΠΈΠΎΠ½Π½ΠΎ-тСхничСских ΠΌΠ΅Ρ€, Π½Π°ΡˆΠ΅Π΄ΡˆΠΈΡ… ΠΎΡ‚Ρ€Π°ΠΆΠ΅Π½ΠΈΠ΅ Π² Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚Π°Π½Π½ΠΎΠΌ ΠΏΡ€ΠΎΠ΅ΠΊΡ‚Π΅ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠΈ контроля. ΠŸΡ€ΠΎΠ΅ΠΊΡ‚ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠΈ контроля построСн Π½Π° основС согласованной схСмы контроля Ρ‚ΠΎΠ»Ρ‰ΠΈΠ½Ρ‹ ΠΎΠ³Π½Π΅Π·Π°Ρ‰ΠΈΡ‚Π½ΠΎΠ³ΠΎ покрытия ΡΡ‚Ρ€ΠΎΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹Ρ… конструкций ΠΏΠΎΡΠ»Π΅Π΄ΠΎΠ²Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎ трСмя сторонами.Π‘Ρ„ΠΎΡ€ΠΌΡƒΠ»ΠΈΡ€ΠΎΠ²Π°Π½Π° ΠΈ Ρ€Π΅ΡˆΠ΅Π½Π° мСтрологичСская Π·Π°Π΄Π°Ρ‡Π° контроля Ρ‚ΠΎΠ»Ρ‰ΠΈΠ½Ρ‹ ΠΎΠ³Π½Π΅Π·Π°Ρ‰ΠΈΡ‚Π½ΠΎΠ³ΠΎ покрытия ΠΊΠ°ΠΊ косвСнноС ΠΈΠ·ΠΌΠ΅Ρ€Π΅Π½ΠΈΠ΅ Π½Π΅Ρ€Π°Π·Ρ€ΡƒΡˆΠ°ΡŽΡ‰ΠΈΠΌΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄Π°ΠΌΠΈ Ρ‚ΠΎΠ»Ρ‰ΠΈΠ½ΠΎΠΌΠ΅Ρ‚Ρ€ΠΈΠΈ. РассмотрСны тСорСтичСскиС ΠΈ ΠΏΡ€ΠΈΠΊΠ»Π°Π΄Π½Ρ‹Π΅ аспСкты процСсса контроля Ρ‚ΠΎΠ»Ρ‰ΠΈΠ½Ρ‹ ΠΎΠ³Π½Π΅Π·Π°Ρ‰ΠΈΡ‚Π½ΠΎΠ³ΠΎ ΠΏΠΎΠΊΡ€Ρ‹Ρ‚ΠΈΡΒ ΡΡ‚Ρ€ΠΎΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹Ρ… конструкций Π² условиях высокого риска принятия Π½Π΅ΠΊΠΎΡ€Ρ€Π΅ΠΊΡ‚Π½ΠΎΠ³ΠΎ Ρ€Π΅ΡˆΠ΅Π½ΠΈΡ ΠΏΠΎ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Π°ΠΌ контроля

    Method of singular wavelet: data approximation and smoothing according to process effectiveness

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    This work examines the universal algorithm of function approximation by method of singular wavelets, which allows to solve a problem of function smoothing and interpolation (quasi-interpolation) given on non-uniform mesh at Rn

    ΠžΡΠΎΠ±Π΅Π½Π½ΠΎΡΡ‚ΠΈ примСнСния ΠΊΠΎΠΌΠ±ΠΈΠ½ΠΈΡ€ΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ ΠΏΠΎΠ΄Ρ…ΠΎΠ΄Π° ΠΊ ΠΎΡ†Π΅Π½ΠΈΠ²Π°Π½ΠΈΡŽ нСопрСдСлённости Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΎΠ² ΠΈΠ·ΠΌΠ΅Ρ€Π΅Π½ΠΈΠΉ

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    The article exposes description of features of the combined approach application to the evaluation of measurement results uncertainty. The aim of this work is the justification and development of new science-driven approaches to achieve maximum efficacy of measurements on the criteria "accuracy/costs" at the stated level of confidence. It provides theoretical base for correctness of combined approach to assess measurement results uncertainty. There is proposition to conventionally divide measurement process into fragments – combining objects, each from shall be considered as individual element for evaluation. It is well known that combining objects can be formed by grouping individual components (resources) of the measurement process either via separate stages of the measurement process. Correctness of such approach is based on the application of "resource" and "process" approaches as regards identification of the factors that affect the measurement results uncertainty. This article provides recommendations on selection of model or empiric approach for evaluating of particular contributions from combining objects of different types into total uncertainty of the final measurement result. In order to improve the validity of empiric approach of the criteria of sufficiency of measurement method uncertainty examination was formulated. It is recommended to evaluate the total uncertainty of the final measurement result by complexation of evaluations of particular total uncertainty of the results for all fragments according to the uncertainties distribution law. It is determined two typical cases of effective application of the combined approach to evaluation of measurement results uncertainty: method of direct measurements and method of indirect measurements. This article considers features of effective application of the combined approach for both situations providing corresponding examples. Special attention is paid to the application of the combined approach to assessing the test results uncertainty. As distinct from the measurement process realized under normal conditions, testing process includes additional external influence factors that are determined by test conditions

    Features of Аpplication of a Π‘ombined Аpproach to the Π•valuation of the Мeasurement Results Uncertainty

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    The article exposes description of features of the combined approach application to the evaluation of measurement results uncertainty. The aim of this work is the justification and development of new science-driven approaches to achieve maximum efficacy of measurements on the criteria "accuracy/costs" at the stated level of confidence.It provides theoretical base for correctness of combined approach to assess measurement results uncertainty. There is proposition to conventionally divide measurement process into fragments – combining objects, each from shall be considered as individual element for evaluation. It is well known that combining objects can be formed by grouping individual components (resources) of the measurement process either via separate stages of the measurement process.Correctness of such approach is based on the application of "resource" and "process" approaches as regards identification of the factors that affect the measurement results uncertainty. This article provides recommendations on selection of model or empiric approach for evaluating of particular contributions from combining objects of different types into total uncertainty of the final measurement result. In order to improve the validity of empiric approach of the criteria of sufficiency of measurement method uncertainty examination was formulated. It is recommended to evaluate the total uncertainty of the final measurement result by complexation of evaluations of particular total uncertainty of the results for all fragments according to the uncertainties distribution law.It is determined two typical cases of effective application of the combined approach to evaluation of measurement results uncertainty: method of direct measurements and method of indirect measurements. This article considers features of effective application of the combined approach for both situations providing corresponding examples. Special attention is paid to the application of the combined approach to assessing the test results uncertainty. As distinct from the measurement process realized under normal conditions, testing process includes additional external influence factors that are determined by test conditions

    Method of singular wavelet: data approximation and smoothing according to process effectiveness

    No full text
    This work examines the universal algorithm of function approximation by method of singular wavelets, which allows to solve a problem of function smoothing and interpolation (quasi-interpolation) given on non-uniform mesh at Rn

    THE RISK-ORIENTED APPROACH TO THE DEVELOPMENT OF CONTROL METHOD

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    The necessity for scientific and methodical study of methods for monitoring the characteristics of flameresistance of building structures has the highest priority in the field of fire safety. The aim of this work was to provide the required degree of reliability of the results of quality control of flame-resistant coatings of building structures and high efficiency of decisions due to the risk-based approach to the development of control methods.Substantiated risk-based approach to the development of methods of control, involving the consideration on the basis of process model, control flame-resistance of building object in all possible potential problems that can cause the risk of incorrect decision-making. A model of the risks arising from the control of the flameretardant coating thickness has been developed. Two major risk groups have been identified. The first group is related to the uncertainty of coating thickness measurement at a single control point. The second group of risks is related to the unrepresentativeness of selective control over the entire surface of the construction object as a whole Potential risk sources have been identified for each group. For the entire range of sources of particular risks the results of studies of the mechanisms of their manifestation, the estimated degree of influence on the accuracy of the control of compliance of flame-retardant coating thickness requirements. The analysis is carried out on the basis of both theoretical and experimental statistical studies on a number of construction projects.According to the results of the analysis of all particular risks of control unreliability, rational ways of their minimization in the form of technical or organizational and technical measures, which are refl in the developed project of the control method, are proposed. Project control method was built on the basis of a agreed scheme of control of the thickness of the fl coating of building structures sequentially the three parties.Β Formulated and solved the task of the metrological control of the thickness of the flame-retardant coating as indirect measurement methods non-destructive thickness measurements. Theoretical and applied aspects of the process of flame-retardant coating thickness control of building structures under conditions of high risk of making incorrect decisions on the results of control are considered

    Atmospheric Plasma Spraying Evolution Since the Sixties Through Modeling, Measurements and Sensors

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    International audienceThis paper presents, through examples, the evolutions of atmospheric plasma spraying since the sixties. The drastic improvement of the spray conditions and coatings reproducibility during more than 50 years was linked both to researches in laboratories and developments of spray equipment’s (plasma torches, computerized control panels, robots to spray coatings on complex parts, sensors working in the harsh environment of spray booths…). This evolution is illustrated through the following topics: (1) plasma forming gas thermodynamic and transport properties either at local thermodynamic equilibrium or more recently at two temperatures; (2) evolution of plasma spray torches since the nineties; (3) plasma jet and in-flight particle measurements with laboratory equipment’s and then sensors in spray booths; (4) plasma jets and torches modeling as well as heat and momentum transfer to particles; (5) splats formation and layering

    Closely related, yet unique: Distinct homo- and heterodimerization patterns of G protein coupled chemokine receptors and their fine-tuning by cholesterol

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    Chemokine receptors, a subclass of G protein coupled receptors (GPCRs), play essential roles in the human immune system, they are involved in cancer metastasis as well as in HIV-infection. A plethora of studies show that homo- and heterodimers or even higher order oligomers of the chemokine receptors CXCR4, CCR5, and CCR2 modulate receptor function. In addition, membrane cholesterol affects chemokine receptor activity. However, structural information about homo- and heterodimers formed by chemokine receptors and their interplay with cholesterol is limited. Here, we report homo- and heterodimer configurations of the chemokine receptors CXCR4, CCR5, and CCR2 at atomistic detail, as obtained from thousands of molecular dynamics simulations. The observed homodimerization patterns were similar for the closely related CC chemokine receptors, yet they differed significantly between the CC receptors and CXCR4. Despite their high sequence identity, cholesterol modulated the CC homodimer interfaces in a subtype-specific manner. Chemokine receptor heterodimers display distinct dimerization patterns for CXCR4/CCR5 and CXCR4/CCR2. Furthermore, associations between CXCR4 and CCR5 reveal an increased cholesterol-sensitivity as compared to CXCR4/CCR2 heterodimerization patterns. This work provides a first comprehensive structural overview over the complex interaction network between chemokine receptors and indicates how heterodimerization and the interaction with the membrane environment diversifies the function of closely related GPCRs
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