Wszystkie pola: condition monitoring - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Contemporary challenges in tool condition monitoring
Autorzy:: Jemielniak, Krzysztof
Powiązania:: https://bibliotekanauki.pl/articles/99861.pdf
Data publikacji:: 2019
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: tool wear monitoring
metal cutting
signal processing
signal feature
Opis:: Implementation of robust, reliable tool condition monitoring (TCM) systems in one of the preconditions of introducing of Industry 4.0. While there are a huge number of publications on the subject, most of them concern new, sophisticated methods of signal feature extraction and AI based methods of signal feature integration into tool condition information. Some aspects of TCM algorithms, namely signal segmentation, selection of useful signal features, laboratory measured tool wear as reference value of tool condition – are nowadays main obstacles in the broad applicationof TCM systems in the industry. These aspects are discussed in the paper, and some solutions of the problems are proposed.
Źródło:: Journal of Machine Engineering; 2019, 19, 1; 48-61
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Automatyczna diagnostyka ostrzy narzędzi skrawających
Automatic tool condition monitoring
Autorzy:: Jemielniak, K.
Powiązania:: https://bibliotekanauki.pl/articles/270187.pdf
Data publikacji:: 2012
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: automatyczna diagnostyka
narzędzie skrawające
ostrze
automatic diagnostics
cutting tool
edge
Opis:: W artykule przedstawiono zasady budowy układów diagnostyki stanu narzędzia i procesu skrawania począwszy od ich struktury logicznej przez omówienie wykorzystywanych wielkości fizycznych i czujników, obróbki sygnałów, do sposobów ich integracji w ostateczną diagnozę. Posłużono się przy tym przykładami zaczerpniętymi z budowanych w Zakładzie Automatyzacji i Obróbki skrawaniem układów Automatycznej Diagnostyki Ostrzy Narzędzi Skrawających (ADONiS). W ten sposób przedstawiono główne elementy dorobku naukowego Zakładu w zakresie diagnostyki stanu narzędzia i procesu (DNiPS).
This paper presents principles of tool condition monitoring systems development, beginning from their logical scheme, through employing physical phenomena and sensors, signal processing up to signal feature integration into the final tool condition estimation. Tool condition monitoring systems ADONiS built in the Chair of Automation, Machine Tool and Metal Cutting were taken as an example. Thus main achievements of the Chair in TCM were presented.
Źródło:: Inżynieria Maszyn; 2012, R. 17, z. 1; 17-29
1426-708X
Pojawia się w:: Inżynieria Maszyn
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Relation of process and condition monitoring at deep hole drilling
Autorzy:: Heisel, U.
Sabou, F.
Maier, D.
Powiązania:: https://bibliotekanauki.pl/articles/100005.pdf
Data publikacji:: 2012
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: process
condition monitoring
deep hole drilling
main spindle
Opis:: Process monitoring and condition monitoring are closely related. The basic structure of the tasks is the same. In some cases the may even use the same set of raw data. Monitoring of a process is also influenced by the machine's state. Therefore, the state has to be monitored also. In most cases wear causes a divergence of the intended from the actual state. The paper presents the principles of monitoring the condition of a main spindle as well as monitoring the process of deep hole drilling.
Źródło:: Journal of Machine Engineering; 2012, 12, 1; 99-110
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Intelligent machining: real-time tool condition monitoring and intelligent adaptive control systems
Autorzy:: Hassan, M.
Sadek, A.
Attia, M. H.
Thomson, V.
Powiązania:: https://bibliotekanauki.pl/articles/99921.pdf
Data publikacji:: 2018
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: adaptive control
tool condition monitoring
intelligent machining
Opis:: Unmanned manufacturing systems has recently gained great interest due to the ever increasing requirements of optimized machining for the realization of the fourth industrial revolution in manufacturing ‘Industry 4.0’. Real-time tool condition monitoring (TCM) and adaptive control (AC) machining system are essential technologies to achieve the required industrial competitive advantage, in terms of reducing cost, increasing productivity, improving quality, and preventing damage to the machined part. New AC systems aim at controlling the process parameters, based on estimating the effects of the sensed real-time machining load on the tool and part integrity. Such an aspect cannot be directly monitored during the machining operation in an industrial environment, which necessitates developing new intelligent model-based process controllers. The new generations of TCM systems target accurate detection of systematic tool wear growth, as well as the prediction of sudden tool failure before damage to the part takes place. This requires applying advanced signal processing techniques to multi-sensor feedback signals, in addition to using ultra-high speed controllers to facilitate robust online decision making within the very short time span (in the order of 10 ms) for high speed machining processes. The development of new generations of Intelligent AC and TCM systems involves developing robust and swift communication of such systems with the CNC machine controller. However, further research is needed to develop the industrial internet of things (IIOT) readiness of such systems, which provides a tremendous potential for increased process reliability, efficiency and sustainability.
Źródło:: Journal of Machine Engineering; 2018, 18, 1; 5-17
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: Smart wireless sensor network and configuration of algorithms for condition monitoring applications
Autorzy:: Uhlmann, E.
Laghmouchi, A.
Geisert, C.
Hohwieler, E.
Powiązania:: https://bibliotekanauki.pl/articles/99644.pdf
Data publikacji:: 2017
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: condition monitoring
data analysis
sensor network
algorithm
MEMS sensor
cloud
Opis:: Due to high demand on availability of production systems, condition monitoring is increasingly important. In recent years, the technical development have improved for realization of condition monitoring applications as a result of technological progress in fields such as sensor technology, computer performance and communication technology. Especially, the approaches of Industrie 4.0 and the use of the Internet of Things (IoT) technologies offer high potential to implement condition monitoring solutions. The connection of several sensor data of components to the cloud allows the identification of anomalies or defect pattern, this information can be used for predictive maintenance and new data-driven business models in production industry. This paper illustrates a concept of a smart wireless sensor network for condition monitoring application based on simple electronic components such as the single-board computer Raspberry Pi 2 modules and MEMS (Micro-Electro-Mechanical Systems) vibration sensors and communication standards MQTT (Message Queue Telemetry Transport). The communication architecture used for decentralized data analysis using machine learning algorithms and connection to the cloud is explained. Furthermore, a procedure for rapid configuration of condition monitoring algorithms to classify the current condition of the component is demonstrated.
Źródło:: Journal of Machine Engineering; 2017, 17, 2; 45-55
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 6.

Tytuł:: Towards sustainable and intelligent machining: energy footprint and tool condition monitoring for media-assisted processes
Autorzy:: Dogan, Hakan
Jones, Llyr
Hall, Stephanie
Shokrani, Alborz
Powiązania:: https://bibliotekanauki.pl/articles/24084657.pdf
Data publikacji:: 2023
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: machining
deep learning
tool condition monitoring
energy footprint
Opis:: Reducing energy consumption is a necessity towards achieving the goal of net-zero manufacturing. In this paper, the overall energy footprint of machining Ti-6Al-4V using various cooling/lubrication methods is investigated taking the embodied energy of cutting tools and cutting fluids into account. Previous studies concentrated on reducing the energy consumption associated with the machine tool and cutting fluids. However, the investigations in this study show the significance of the embodied energy of cutting tool. New cooling/lubrication methods such as WS2-oil suspension can reduce the energy footprint of machining through extending tool life. Cutting tools are commonly replaced early before reaching their end of useful life to prevent damage to the workpiece, effectively wasting a portion of the embodied energy in cutting tools. A deep learning method is trained and validated to identify when a tool change is required based on sensor signals from a wireless sensory toolholder. The results indicated that the network is capable of classifying over 90% of the tools correctly. This enables capitalising on the entirety of a tool’s useful life before replacing the tool and thus reducing the overall energy footprint of machining processes.
Źródło:: Journal of Machine Engineering; 2023, 23, 2; 16--40
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 7.

Tytuł:: Real-time tool condition monitoring in milling by means of control charts for auto-correlated data
Autorzy:: Colosimo, B. M.
Moroni, G.
Grasso, M.
Powiązania:: https://bibliotekanauki.pl/articles/100212.pdf
Data publikacji:: 2010
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: statistical process control
profile monitoring
tool condition monitoring
Opis:: Real time monitoring of tool condirions and machining processes has been extensively studies in tne last decades, but a wide gap is stiil present between research activities and commercial tools. One of the factors which currently limit the utilization of these systems is the low flexibility of off-the-shelf solutions: in most cases they need dedicated off-line training sessions to acquire the reference patterns and thresholds, and/or the need for several input data to be defined a priori by a human operator. Instead of exploiting off-line learning sessions and a prior defined thresholds, this paper proposes an approach for automatic modelling of a cutting process and real-time monitoring of its stability that is based only on data acquired on-line during the process itself. This approach avoids any a-priori assumption about expected signal patterns, and it is characterized by an innovative implementation of well known Statistical Process Control techniques. In particular, with regard to milling processes, the paper proposes the utilization of cross-correlation coefficient between repeating signal profiles as the feature to be monitored, and an EWMA (Exponentially Weighted Moving Average) control chart for auto-correlated data as monitoring tool.
Źródło:: Journal of Machine Engineering; 2010, 10, 2; 5-17
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 8.

Tytuł:: On Board Condition Monitoring of Feed Axes by Signal Decomposition for Machines with Ball Screw Drives
Autorzy:: Maier, D.
Sun, Z.
Powiązania:: https://bibliotekanauki.pl/articles/971168.pdf
Data publikacji:: 2009
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: signal analysis
feed drive
wear
Opis:: In order to establish a condition monitoring system to detect wear of the mechanical components of feed drives with ball screws a measuring and data evaluation method has been established. In order to keep the costs down, boundary condition is to use the machines own functionalities only (On Board Diagnosis). At present, most of wear detecting methods use vibration analysis. Here, a signal analysis method is presented that may well complement established methods of vibration analysis. The publication presents a method to exploit positioning data to detect wear of a ball screw drive exemplarily that is run under real conditions. The presented method is partially derived from wear detection methods of roller bearings and may also be adapted for other parts such as linear guides.
Źródło:: Journal of Machine Engineering; 2009, 9, 3; 42-63
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 9.

Tytuł:: A comparision of model and signal based condition monitoring and mode separation for predictive maintenance of feed drives
Autorzy:: Maier, D.
Heisel, U.
Powiązania:: https://bibliotekanauki.pl/articles/100055.pdf
Data publikacji:: 2011
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: mode separation
condition monitoring
ball screw drive
predictive maintenance
Opis:: Modern production strategies increase the demand for closer monitoring of the machine's condition. Especially wear affects its condition. This paper deals with the methodology of condition monitoring that can be based on different sources of data such as controller NC CNC and additional sensors. Two main methods for assessment are signal analysis based exclusively on measurement data and a model based method The latter is based on comparing the simulation of the objects behaviour with the acquired data. Ball screw drives are key elements of machine tools. They considerably contribute to the machine's performance. The paper compares two signal-based wear inducing characteristics and discusses the results. Afterwards a model-based approach is discussed.
Źródło:: Journal of Machine Engineering; 2011, 11, 4; 138-151
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 10.

Tytuł:: In-process control with a sensory tool holder to avoid chatter
Autorzy:: Bleicher, F.
Schörghofer, P.
Habersohn, C.
Powiązania:: https://bibliotekanauki.pl/articles/100160.pdf
Data publikacji:: 2018
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: adaptive control
condition monitoring
chatter
Opis:: Hydro-, steam- and gas- turbines, aircraft components or moulds are milled parts with complex geometries and high requirements for surface quality. The production of such industry components often necessitates the use of long and slender tools. However, instable machining situations together with work pieces with thin wall thickness can lead to dynamic instabilities in the milling processes. Resulting chatter vibrations cause chatter marks on the work piece surface and have influence on the tool lifetime. In order to detect and avoid the occurrence of process instabilities or process failures in an early stage, the Institute for Production Engineering and Laser Technology (IFT) developed an active control system to allow an in-process adaption of machining parameters. This system consists of a sensory tool holder with an integrated low cost acceleration sensor and wireless data transmission under real time conditions. A condition monitoring system using a signal-processing algorithm, which analyses the received acceleration values, is coupled to the NC- control system of the machine tool to apply new set points for feed rate and rotational speed depending on defined optimisation strategies. By the implementation of this system process instabilities can be avoided.
Źródło:: Journal of Machine Engineering; 2018, 18, 3; 16-27
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 11.

Tytuł:: Primary testing of an instrumented tool holder for brush deburring of milled workpieces
Autorzy:: Ramsauer, Christoph
Oswald, Ralf
Schörghofer, Paul
Leder, Norbert
Schmitz, Tony
Bleicher, Friedrich
Powiązania:: https://bibliotekanauki.pl/articles/2086281.pdf
Data publikacji:: 2022
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: condition monitoring
deburring
feature generation
Opis:: Brush deburring requires consistent contact pressure between brush and workpiece. Automating adjustments to control contact pressure has proven difficult, as the sensors available in machine tools are usually not suitable to observe the small amplitude signals caused by this low force process. Additionally, both the power consumption and the vibration signal caused by the process strongly depend on the workpiece surface features. This paper describes a test setup using an instrumented tool holder and presents the corresponding measurement results, aiming to quantify the axial feed of the brush. It also discusses the interpretation of different signal components and provides an outlook on the utilization of the data for tool wear estimation.
Źródło:: Journal of Machine Engineering; 2022, 22, 2; 99--107
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 12.

Tytuł:: Unsupervised detection of state changes during operation of machine elements
Autorzy:: Hillenbrand, Jonas
Fleischer, Jürgen
Powiązania:: https://bibliotekanauki.pl/articles/1429021.pdf
Data publikacji:: 2021
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: condition monitoring
clustering tracking
unsupervised learning
Opis:: Interpretation of sensor data from machine elements is challenging, if no prior knowledge of the system is available. Evaluation methods must adapt surrounding conditions and operation modes. As supervised learning models can be time-consuming to set up, unsupervised learning poses as alternative solution. This paper introduces a new clustering scheme that incorporates iterative cluster retrieval in order to track the clustering results over time. The approach is used to identify changing machine element states such as operating conditions and undesired changes, like incipient damage or wear. We show that knowledge about the evolving clusters can be used to identify operation and failure events. The approach is validated for machine elements with slide and roll contacts, such as ball screws and bearings. The data used has been captured using vibration and acoustic emission sensors. The results show a general applicability to the unsupervised monitoring of machine elements using the proposed approach.
Źródło:: Journal of Machine Engineering; 2021, 21, 2; 35-46
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 13.

Tytuł:: Using sensory tool holder data for optimizing production processes
Autorzy:: Schörghofer, Paul
Pauker, Florian
Leder, Norbert
Mangler, Jürgen
Ramsauer, Christoph
Bleicher, Friedrich
Powiązania:: https://bibliotekanauki.pl/articles/100070.pdf
Data publikacji:: 2019
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: adaptive control
condition monitoring
orchestration platform
Opis:: Today's highly automated manufacturing specifies the service time of a tool in a way that the tooling costs are balanced against the potential costs of a tool failure. However, the potential cost induced by a tool malfunctioning are rather high. Therefore, the current state-of-the art tackles this issue by replacing the tools prematurely at fixed intervals. To tap into the potential of under-utilized tool runtime this work purposes the use of sensory-tool holders and an interfering feedback loop to the machine tool control system. Besides its real-time closed loop control, to avoid tool failure, it also provides data in the context of (a) the work order, (b) the produced part, (c) the NC-block and command line, on (d) specific machines. Based on this data an ex-post analysis to optimize tool-life and productivity scenarios becomes possible, e.g. custom NC-programs for certain work-orders, configurations and machines. Furthermore, downstreamed work steps can be changed e.g. only to measure produced workpieces if abnormal vibrations are reported by in-process-monitoring.
Źródło:: Journal of Machine Engineering; 2019, 19, 3; 43-55
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 14.

Tytuł:: New method for determining single cutting edge breakage of a multi-tooth milling tool based on acceleration measurements of an instrumented tool holder
Autorzy:: Ramsauer, Christoph
Bleicher, Friedrich
Powiązania:: https://bibliotekanauki.pl/articles/1428710.pdf
Data publikacji:: 2021
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: condition monitoring
sensors integration
tool wear
algorithm
Opis:: In machining applications predominantly for automated machining cells, tool life is often not used to its full extend and cutting tools are exchanged prematurely to avoid tool breakage and thus machine downtime or even damage at work piece or machine. Both effective process monitoring and adequate process control require reliable data from sensors and derived indicators that enable meaningful evaluation. Acceleration measurement by the instrumented tool holder provides signals with high quality from close to the cutting zone. Using the monitoring system, the gained data of the instrumented tool holder can be analyzed especially for the use case of unexpected tool wear, chipping of the cutting edge or breakouts at end mills. This paper describes the data analysis based on the rotational sensor and the corresponding effects on the measurement, an advanced assessment of the spectral distribution in the frequency domain and the experimental results of a test series.
Źródło:: Journal of Machine Engineering; 2021, 21, 1; 67-77
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 15.

Tytuł:: Tooling systems with integrated sensors enabling data based process optimization
Autorzy:: Bleicher, Friedrich
Ramsauer, Christoph
Leonhartsberger, Martin
Lamprecht, Matthias
Stadler, Philipp
Strasser, Dominik
Wiedermann, Clemens
Powiązania:: https://bibliotekanauki.pl/articles/1428704.pdf
Data publikacji:: 2021
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: condition monitoring
sensors integration
Industry 4.0
Opis:: Sensor integration into machining equipment has become an important factor for gaining deep process insights mainly driven by increasingly smaller and cheaper sensors and transmitters. Due to advances in microelectronics and communication technology, a broader field of applications in production processes and machine tools can be addressed using sensing devices and their implementation potentials. Ensuring a sensitive but robust data stream from close to the actual process allows not only reliable monitoring but also process and quality control based on sensor information. This paper provides an overview of the utilization of sensor data for the purpose of condition monitoring, model fitting and real-time control coping with stochastic effects. Examples of sensor integration in fields of injection molding, roll forming and heavy-duty milling comprise the state of the art of sensor implementation, data evaluation and possible feedback loops in the respective application scenarios.
Źródło:: Journal of Machine Engineering; 2021, 21, 1; 5-21
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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