Technical condition change detection using Anderson–Darling statistic approach for LHD machines – engine overheating problem

Wodecki, Jacek; Stefaniak, Paweł; Michalak, Anna; Wyłomańska, Agnieszka; Zimroz, Radosław

doi:10.1080/17480930.2017.1388336

Cited by 29 publications

(14 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Secondly, data distributions within segments are modeled with smoothed histograms to visually observe the differences between the classes. In this work segmentation has been done manually, however in future work we plan to do segmentation automatically [1,2,[12][13][14].…”

Section: Methodsmentioning

confidence: 99%

“…play key role in gaining productivity of the entire facility. They are designed to work in harsh mining conditions (high temperature, humidity, dust and salinity) and high load-operation [1][2][3]. Efficiency oriented operation of loaders is main cause of their short total life time (~3-4 years).…”

Section: Introductionmentioning

confidence: 99%

“…Efficiency oriented operation of loaders is main cause of their short total life time (~3-4 years). Developed monitoring system leads to identification of main causes of failure events by allowing to follow operational parameters and to perform much more advanced context analysis [1,4]. However, beside typical condition-monitoring-related approach to manage the fleet, there are other areas of interest, that are potent for analysis and viable for efficiency optimization from the management point of view.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Mobile based vibration monitoring and its application to road quality monitoring in deep underground mine

Zimoz¹,

Wodecki²,

Hebda-Sobkowicz³

et al. 2018

Vib. proced.

Self Cite

View full text Add to dashboard Cite

Road quality is an important issue in everyday life for all car owners. This issue seems to be critically important in underground mines, where LHD machines are used for material transport. One of the biggest problems for LHD operation is relatively quick tires degradation. One of possible reasons might be road surface quality, indeed. However, driver's skills as well as ways of machine operation (loading, acceleration, breaking...) might also play a crucial role. Nowadays, many of machines are equipped with onboard monitoring system that allows to monitor basic parameters (speed, torque, temperatures, pressures etc.) at some predefined components. To complete the picture, we propose to use proposed already (but not for mining applications) vibration measurement for road roughness evaluation. To measure vibration acceleration is relatively easy task (we used simple smartphone here), unfortunately method of parametrization and concluding about road quality is still a challenge in mining case. In this paper we have presented a short communication related to first experimental work and some ideas how to deal with this problem using statistical tools for signal modeling.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Mobile based vibration monitoring and its application to road quality monitoring in deep underground mine

Zimoz¹,

Wodecki²,

Hebda-Sobkowicz³

et al. 2018

Vib. proced.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Timusk et al proposed a method for the automated operating mode classification of online monitoring systems [28]. Wodecki discussed long-term data analysis for condition monitoring purposes [29], Al-Chalabi et al [30] discussed the problem of reliability in drilling. The problem of data acquisition, validation and analysis for LHD machines has been discussed in [31].…”

Section: Monitoring Of the Drilling Process-the State Of The Artmentioning

confidence: 99%

Process Monitoring in Heavy Duty Drilling Rigs—Data Acquisition System and Cycle Identification Algorithms

et al. 2020

Self Cite

View full text Add to dashboard Cite

The monitoring of drilling processes is a well-known topic in the mining industry. It is widely used for rock mass characterization, bit wear monitoring and drilling process assessment. However on-board monitoring systems used for this purpose are installed only on a limited number of machines, and breakdowns are possible. There is a need for a data acquisition system that can be used on different drilling rigs and for an automatic data analysis procedure. In this paper, we focused on the automatic detection of drilling cycles, presenting a simple yet reliable system to be universally installed on drilling rigs. The proposed solution covers hardware and software. It is based on the measurement of electric current and acoustic signals. The signal processing methods include threshold-based segmentation, a short-time envelope spectrum and a spectrum for the representation of results. The results of the research have been verified on a real drilling rig within the testing site of its manufacturer by comparing the results with the data of the on-board monitoring system installed on the machine. Novel aspects of our approach include the detection of the pre-boring stage, which has an intermediate amplitude that masks the real drilling cycles, and the use of the percussion instantaneous frequency, which is estimated by acoustic recordings.

show abstract

“…In the daily life activities, accidents occur due to different reasons [3][4][5], one of the primary reason is brake malfunction which caused due to poor upkeep and product imperfection as well as the technical issue inside the vehicle could be another reason or because of oversight of driver [6]. Moreover, engine overheating could be happened due to several things, usually the consequence of a low coolant level or coolant loss and this may be the result of leaks in hoses, the engine or the radiator [7][8]. A faulty thermostat is another common cause of overheating, when this happen it prevent the flow of coolant from the engine to the radiator [9].…”

Section: Introductionmentioning

confidence: 99%

Integrate for car brake failure and engine overheat system

Subhashini

Albanna

Abdulla

2020

IJEECS

View full text Add to dashboard Cite

<span>One of the most important features in a car is its braking system and engine. The braking system enables the driver to control the speed of the vehicle when the need arises in order to protect the car, driver and other road users from accidents which might be fatal. The performance of the entire car also relies largely on the effective delivery and operation of the car engine whose ability to deliver the required performance is hinged on its temperature. In recent years a variety of IOT based monitoring and control systems have been explored in various areas of modern technology. This Final Year research project proposes the design and development of an IOT based vehicle brake failure and engine overheating system. The proposed system utilizes a network of sensors to monitor the temperature of the car engine, obstacles along the path of the car and the speed of the vehicle. The sensor data retrieved from the monitoring system is used by the control system consisting of a microcontroller to make decisive automatic decisions for the vehicle brake and failure system. A warning system consisting of LCD, Buzzer and LED has also been added into the system to warn the driver regarding the operation of the braking and engine overheating system. Two microcontrollers have been utilized for this research i.e. Arduino Uno for sensor data acquisition and processing and a Raspberry Pi microcontroller for purposes of sending the data wirelessly to a web platform. The web platform developed enables the user to remotely access real-time and past data from the system vehicle brake failure and engine overheating system. A variety of tests were conducted on the system to evaluate its performance whereby 95.4% accuracy was achieved in in terms of the ability of the car to effectively and automatically brake in the presence of obstacles and in terms of speed control. Testing done on the ability of the system to accurately monitor the engine temperature shows that its able to achieve 97.5% accuracy. The IOT system is able to transmit the sensor data retrieved from the system using both WIFI and mobile data whereby an average transmission time of 2.32 s and 4.33 s was recorded for each system respectively.</span>

show abstract

Technical condition change detection using Anderson–Darling statistic approach for LHD machines – engine overheating problem

Cited by 29 publications

References 8 publications

Mobile based vibration monitoring and its application to road quality monitoring in deep underground mine

Mobile based vibration monitoring and its application to road quality monitoring in deep underground mine

Process Monitoring in Heavy Duty Drilling Rigs—Data Acquisition System and Cycle Identification Algorithms

Integrate for car brake failure and engine overheat system

Contact Info

Product

Resources

About