An Advanced Vibration Based Real-Time Machine Health and Process Monitoring System

Author(s):  
Chandra Jalluri ◽  
Prashanth Magadi ◽  
Mohan Viswanathan ◽  
Richard Furness ◽  
Werner Kluft ◽  
...  

The ever-increasing emphasis on product quality with increased productivity has been driving the automotive manufacturing industry to find new ways to produce high quality products without increasing production time and manufacturing costs. In addition, automotive manufacturing plants are implementing flexible manufacturing strategies with computer numerical control (CNC) machining centers to address excess capacity, shifting consumer trends and future volume uncertainty of products. Over time, plants have used several preventative and predictive maintenance methods to address machine reliability. Such systems include, but are not limited to, scheduling machine down times at regular intervals to check/replace bearings and other spindle/slide components before they can have an adverse affect on part quality. However, most of these methods and traditional systems are not cost effective and cause significant machine down-times, safety concerns and labor overheads and do not reliably monitor other process issues, such as, clamping, incoming stock variations and thermal phenomena. This paper describes an advanced real-time vibration based machine health and process monitoring system that has been developed to address the above issues. The system, called Condition Indicator Analysis Box for CNC (CIAB™-CNC), is easily configurable, and provides real-time data and historical trends of machines, processes and tooling, enabling manufacturing plants to make accurate predictions regarding future production runs. The system also aids in the optimization of preventative maintenance tasks in a cost effective manner. The developed system monitors machine spindle and slide for unbalance, misalignment, damaged/spalled bearings, mechanical looseness, and ball screw issues. Additionally, it performs in-process monitoring during machining as well as non-machining by individual tool and/or feature to detect tool breakages, quality issues and other gross process or machine anomalies. Innovative statistical trending algorithms enable the system to automatically adapt to valid process/parameter changes and significantly reduce the chances of false alarms and warnings. The developed system provides manufacturing plants with a tool to analyze machine tools and their associated components in an effort to gather information they can use effectively to make decisions regarding flexible machines, processes and tooling.

2011 ◽  
Vol 63 (2) ◽  
pp. 248-254 ◽  
Author(s):  
T. A. Cochrane ◽  
D. Wicke ◽  
A. O’Sullivan

Waterways can contribute to the beauty and livelihood of urban areas, but maintaining their hydro-ecosystem health is challenging because they are often recipients of contaminated water from stormwater runoff and other discharges. Public awareness of local waterways’ health and community impacts to these waterways is usually poor due to of lack of easily available information. To improve community awareness of water quality in urban waterways in New Zealand, a web portal was developed featuring a real-time waterways monitoring system, a public forum, historical data, interactive maps, contaminant modelling scenarios, mitigation recommendations, and a prototype contamination alert system. The monitoring system featured in the web portal is unique in the use of wireless mesh network technology, direct integration with online modelling, and a clear target of public engagement. The modelling aims to show the origin of contaminants within the local catchment and to help the community prioritize mitigation efforts to improve water quality in local waterways. The contamination alert system aims to keep managers and community members better informed and to provide a more timely response opportunity to avert any unplanned or accidental contamination of the waterways. Preliminary feedback has been positive and is being supported by local and regional authorities. The system was developed in a cost-effective manner providing a community focussed solution for quantifying and mitigating key contaminants in urban catchments and is applicable and transferable to other cities with similar stormwater challenges.


2018 ◽  
pp. 188-198 ◽  
Author(s):  
Uma Arun ◽  
Natarajan Sriraam

Today's healthcare technology provides promising solutions to cater to the needs of patients. The development of wearable physiological monitoring system has reached home-centric patients by ensuring faster healthcare services. The primary advantage of this system is activation of alarms to alert the specialist in a nearby hospital to attend to any sort of emergency. Specifically, cardiac-related problems need special attention when a 24-hour Holter monitors ECG signals and identifies the level of abnormalities under various circumstances. Although several brands of Holters exist in market, there is a huge demand for digitized Holter recorders. These recorders can simultaneously analyse cardiac signals in real time mode and store the data and reuse them for next 24 hours. As home-centric based wearable cardiac monitoring system gains much attention recently, there is a need to design and develop a cardiac monitoring system by establishing a trade-off between the required clinical diagnostic quality and cost. This research study highlights a comprehensive survey of various cardiac monitoring systems under wire, wireless and wearable modes. This provides an insight into the need of the hour in bringing a cost-effective wearable system. The study provides an insight of the technological aspects of the existing cardiac monitoring system and suggests a viable design suitable for developing countries.


Author(s):  
Deepak T. Mohan ◽  
Jeffrey Birt ◽  
Can Saygin ◽  
Jaganathan Sarangapani

Fastening operations are extensively used in the aerospace industry and constitute for more than a quarter of the total cost. Inspection of fasteners is another factor that adds cost and complexity to the overall process. Inspection is usually carried out on a sampling-basis as a stand-alone process after the fastening process is completed. Lack of capability to inspect all fasteners in a cost effective manner and the need to remove non-value added activities, such as inspection by itself, in order to reduce the manufacturing lead time have been the motivation behind this study. This paper presents a novel diagnostics scheme based on Mahalanobis-Taguchi System (MTS) for monitoring the quality of rotary-type fastening operations in real-time. This approach encompasses (1) integrating a torque sensor, a pressure sensor, and an optical encoder on a hand-held rotary-type fastening tool; (2) obtaining process parameters via the embedded sensors and generating process signatures in real-time; and (3) detecting anomalies on the tool using a wireless mote that communicates the decision with a base station. The anomalies investigated in this study are the grip length variations as under grip and normal grip, and presence of re-used fasteners. The proposed scheme has been implemented on prototype rotary tool for bolt-nut type of fasteners and tested under a variety of experimental settings. The experimental results have shown that the proposed approach is successful, with an accuracy of over 95% in detecting grip lengths of fasteners in real-time during the process.


2020 ◽  
Author(s):  
Lavinia Tunini ◽  
David Zuliani ◽  
Paolo Fabris ◽  
Marco Severin

<p>The Global Navigation Satellite Systems (GNSS) provide a globally extended dataset of primordial importance for a wide range of applications, such as crustal deformation, topographic measurements, or near surface processes studies. However, the high costs of GNSS receivers and the supporting software can represent a strong limitation for the applicability to landslide monitoring. Low-cost tools and techniques are strongly required to face the plausible risk of losing the equipment during a landslide event.</p><p>Centro di Ricerche Sismologiche (CRS) of Istituto Nazionale di Oceanografia e di Geofisica Sperimentale OGS in collaboration with SoluTOP, in the last years, has developed a cost-effective GNSS device, called LZER0, both for post-processing and real-time applications. The aim is to satisfy the needs of both scientific and professional communities which require low-cost equipment to increase and improve the measurements on structures at risk, such as landslides or buildings, without losing precision.</p><p>The landslide monitoring system implements single-frequency GNSS devices and open source software packages for GNSS positioning, dialoguing through Linux shell scripts. Furthermore a front-end web page has been developed to show real-time tracks. The system allows measuring real-time surface displacements with a centimetre precision and with a cost ten times minor than a standard RTK GPS operational system.</p><p>This monitoring system has been tested and now applied to two landslides in NE- Italy: one near Tolmezzo municipality and one near Brugnera village. Part of the device development has been included inside the project CLARA 'CLoud plAtform and smart underground imaging for natural Risk Assessment' funded by the Italian Ministry of Education, University and Research (MIUR).</p>


2014 ◽  
Vol 663 ◽  
pp. 657-661 ◽  
Author(s):  
Khashayar Danesh Narooei ◽  
Rizauddin Ramli

Computer numerical control (CNC) machines have been widely used in automotive manufacturing industries especially of machining operation in automotive part such as engine body and cylinder. One of the key features that improve efficiency of CNC machining is through the optimization of tool path. Previous researcher to optimize tool path has premeditated several approaches. This paper aims to provide a critical review of those approaches that have been developed in tool path. The developed tool path approaches covered different types of machining process under various constraints condition. This paper focuses on tool path generation in CNC machining such as milling and cutting process. Based on our finding, this review paper collects information on tool path optimization and recommends future research direction.


Symmetry ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1233 ◽  
Author(s):  
Chen ◽  
Xie ◽  
Yuan ◽  
Huang ◽  
Li

To monitor the tool wear state of computerized numerical control (CNC) machining equipment in real time in a manufacturing workshop, this paper proposes a real-time monitoring method based on a fusion of a convolutional neural network (CNN) and a bidirectional long short-term memory (BiLSTM) network with an attention mechanism (CABLSTM). In this method, the CNN is used to extract deep features from the time-series signal as an input, and then the BiLSTM network with a symmetric structure is constructed to learn the time-series information between the feature vectors. The attention mechanism is introduced to self-adaptively perceive the network weights associated with the classification results of the wear state and distribute the weights reasonably. Finally, the signal features of different weights are sent to a Softmax classifier to classify the tool wear state. In addition, a data acquisition experiment platform is developed with a high-precision CNC milling machine and an acceleration sensor to collect the vibration signals generated during tool processing in real time. The original data are directly fed into the depth neural network of the model for analysis, which avoids the complexity and limitations caused by a manual feature extraction. The experimental results show that, compared with other deep learning neural networks and traditional machine learning network models, the model can predict the tool wear state accurately in real time from original data collected by sensors, and the recognition accuracy and generalization have been improved to a certain extent.


2006 ◽  
Vol 55 (1) ◽  
pp. 43-51 ◽  
Author(s):  
Alex J. Stephens ◽  
Flavia Huygens ◽  
John Inman-Bamber ◽  
Erin P. Price ◽  
Graeme R. Nimmo ◽  
...  

The aim of this study was to identify a set of genetic polymorphisms that efficiently divides methicillin-resistant Staphylococcus aureus (MRSA) strains into groups consistent with the population structure. The rationale was that such polymorphisms could underpin rapid real-time PCR or low-density array-based methods for monitoring MRSA dissemination in a cost-effective manner. Previously, the authors devised a computerized method for identifying sets of single nucleotide polymorphisms (SNPs) with high resolving power that are defined by multilocus sequence typing (MLST) databases, and also developed a real-time PCR method for interrogating a seven-member SNP set for genotyping S. aureus. Here, it is shown that these seven SNPs efficiently resolve the major MRSA lineages and define 27 genotypes. The SNP-based genotypes are consistent with the MRSA population structure as defined by eburst analysis. The capacity of binary markers to improve resolution was tested using 107 diverse MRSA isolates of Australian origin that encompass nine SNP-based genotypes. The addition of the virulence-associated genes cna, pvl and bbp/sdrE, and the integrated plasmids pT181, pI258 and pUB110, resolved the nine SNP-based genotypes into 21 combinatorial genotypes. Subtyping of the SCCmec locus revealed new SCCmec types and increased the number of combinatorial genotypes to 24. It was concluded that these polymorphisms provide a facile means of assigning MRSA isolates into well-recognized lineages.


Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1708 ◽  
Author(s):  
Miguel Martin-Abadal ◽  
Ana Ruiz-Frau ◽  
Hilmar Hinz ◽  
Yolanda Gonzalez-Cid

During the past decades, the composition and distribution of marine species have changed due to multiple anthropogenic pressures. Monitoring these changes in a cost-effective manner is of high relevance to assess the environmental status and evaluate the effectiveness of management measures. In particular, recent studies point to a rise of jellyfish populations on a global scale, negatively affecting diverse marine sectors like commercial fishing or the tourism industry. Past monitoring efforts using underwater video observations tended to be time-consuming and costly due to human-based data processing. In this paper, we present Jellytoring, a system to automatically detect and quantify different species of jellyfish based on a deep object detection neural network, allowing us to automatically record jellyfish presence during long periods of time. Jellytoring demonstrates outstanding performance on the jellyfish detection task, reaching an F1 score of 95.2%; and also on the jellyfish quantification task, as it correctly quantifies the number and class of jellyfish on a real-time processed video sequence up to a 93.8% of its duration. The results of this study are encouraging and provide the means towards a efficient way to monitor jellyfish, which can be used for the development of a jellyfish early-warning system, providing highly valuable information for marine biologists and contributing to the reduction of jellyfish impacts on humans.


2010 ◽  
Vol 34-35 ◽  
pp. 1109-1113
Author(s):  
Wang Dong Wei

The home monitoring system designed in this paper used the combination of a home gateway controller and the ZigBee coordinator, the connection of the ZigBee coordinator and the terminal nodes through wireless mode, to issue the collected real-time data to the Intemet with a web page form, and the dynamic real-time update, so that the intelligent monitoring of the home-based internal environment is achieved. This system overcomes the shortcomings of traditional wired control system, has good currency, high expansibility, and can shorten the intelligent home product development cycle, help to design and develop powerful, cost-effective powerful, cost-effective home products.


Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4615
Author(s):  
Olivier Pieters ◽  
Emiel Deprost ◽  
Jonas Van Der Donckt ◽  
Lore Brosens ◽  
Pieter Sanczuk ◽  
...  

Monitoring climate change, and its impacts on ecological, agricultural, and other societal systems, is often based on temperature data derived from official weather stations. Yet, these data do not capture most microclimates, influenced by soil, vegetation and topography, operating at spatial scales relevant to the majority of organisms on Earth. Detecting and attributing climate change impacts with confidence and certainty will only be possible by a better quantification of temperature changes in forests, croplands, mountains, shrublands, and other remote habitats. There is an urgent need for a novel, miniature and simple device filling the gap between low-cost devices with manual data download (no instantaneous data) and high-end, expensive weather stations with real-time data access. Here, we develop an integrative real-time monitoring system for microclimate measurements: MIRRA (Microclimate Instrument for Real-time Remote Applications) to tackle this problem. The goal of this platform is the design of a miniature and simple instrument for near instantaneous, long-term and remote measurements of microclimates. To that end, we optimised power consumption and transfer data using a cellular uplink. MIRRA is modular, enabling the use of different sensors (e.g., air and soil temperature, soil moisture and radiation) depending upon the application, and uses an innovative node system highly suitable for remote locations. Data from separate sensor modules are wirelessly sent to a gateway, thus avoiding the drawbacks of cables. With this sensor technology for the long-term, low-cost, real-time and remote sensing of microclimates, we lay the foundation and open a wide range of possibilities to map microclimates in different ecosystems, feeding a next generation of models. MIRRA is, however, not limited to microclimate monitoring thanks to its modular and wireless design. Within limits, it is suitable or any application requiring real-time data logging of power-efficient sensors over long periods of time. We compare the performance of this system to a reference system in real-world conditions in the field, indicating excellent correlation with data collected by established data loggers. This proof-of-concept forms an important foundation to creating the next version of MIRRA, fit for large scale deployment and possible commercialisation. In conclusion, we developed a novel wireless cost-effective sensor system for microclimates.


Sign in / Sign up

Export Citation Format

Share Document