Online oil debris monitoring of rotating machinery: A detailed review of more than three decades

Sun, Jiayi; Wang, Liming; Li, Jianfeng; Li, Fangyi; Lu, Haiyang

doi:10.1016/j.ymssp.2020.107341

Cited by 91 publications

(30 citation statements)

References 104 publications

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“…To keep the diesel engine in good condition, it is necessary to monitor the operating conditions of the machine parameters. These parameters are lubricant temperature and lubricant pressure [34], engine coolant temperature [35], rotational speed [36], and battery charger voltage [37]. The other essential data is the engine running hours (RH), where RH functions to find out the accumulative time of how long the engine has been running.…”

Section: A Gq (Engine Monitoring Supports Cbm)mentioning

confidence: 99%

Modern Monitoring Instrument to Support Fishing Vessel Operation and Maintenance: A Review

Abrori¹,

Sidhi²,

Prasetyo³

2021

International Journal on Advanced Science, Engineering and Information Technology

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Determining the maintenance strategy for fishing vessels propulsion engines can use engine operational monitoring data. This data is used to prepare the implementation time, spare parts, labor, and costs. Unfortunately, many fishing vessels do not have this data. Currently, electronic devices are available for monitoring machine operations. This device is cheap, easy to use, takes responsibility for various physical quantity parameters, displays it on LCD, stores it digitally, and transmits data wirelessly. This paper aims to review the application of engine operational monitoring tools to apply to fishing vessel propulsion engines. The material used is scientific articles consisting of journals and proceedings indexed by online databases. Several keywords are used to obtain scientific articles that are suitable for the study. The method used is a literature review that is systematically reviewed by applying inclusion and exclusion. The results obtained in this article are the parameters for monitoring propulsion engines, namely temperature, pressure, rotational speed, and hours the engine runs. The monitoring device requires sensors to detect physical parameters, a microcontroller to process data, an LCD to display monitoring results, and memory to store data to obtain this data. The device supports wireless communication via Bluetooth or WiFi radio signal. Fishing vessels are operating in offshore areas that are not covered by internet networks as IoT communication transmissions. Further research on how to transmit operational engine data from offshore to onshore without an internet signal so that data can be accessed using the internet network.

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Section: A Gq (Engine Monitoring Supports Cbm)mentioning

confidence: 99%

Modern Monitoring Instrument to Support Fishing Vessel Operation and Maintenance: A Review

Abrori¹,

Sidhi²,

Prasetyo³

2021

International Journal on Advanced Science, Engineering and Information Technology

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“…They aim to plan to repair these systems rather than catastrophic damage caused by unexpected defects. The most well-known techniques for the prevention of rotating systems are temperature control (thermography) [7] and [8], oil debris control [9] and [10], acoustic analysis [11] and [12] and vibration signal control (analysis) [13] and [14]. The significant advantage of vibration analysis is that it can detect and identify the defect evolution before it becomes severe and causes catastrophic damage.…”

Section: Introductionmentioning

confidence: 99%

Early Detection of Defects in Gear Systems Using Autocorrelation of Morlet Wavelet Transforms

Ayad¹,

Saoudi²,

Rezki³

et al. 2022

sv-jme

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The supervision task of industrial systems is vital, and the prediction of damage avoids many problems. If any system defects are not detected in the early stage, this system will continue to degrade, which may cause serious economic loss. In industrial systems, the defects change the behaviour and characteristics of the vibration signal. This change is the signature of the presence of the defect. The challenge is the early detection of this signature. The difficulty of the vibration signal is that the signal is very noisy, non-stationary and non-linear. In this study, a new method for the early defect detection of a gear system is proposed. This approach is based on vibration analysis by finding the defect’s signature in the vibration signal. This approach has used the autocorrelation of Morlet wavelet transforms (AMWT). Firstly, simulation validation is introduced. The validation of the approach on a real system is given in the second validation part.

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“…As key working fluid of mechanical equipment, hydraulic oil has the functions of transmitting hydraulic energy, lubricating friction pair of hydraulic system, cooling system and so on [1]. During the operation of mechanical equipment, wear debris formed by mechanical wear will contaminate the lubricating oil, and the polluted oil will also aggravate the wear of the moving pair and cause the failure of the mechanical equipment [2]. Wear debris are the most direct information element for revealing the tribological surface wear mechanism, monitoring the process of wear and diagnosing the type of wear failure [3].…”

Section: Introductionmentioning

confidence: 99%

Online Detection System of Metal Wear Debris Based on Symmetrical Magnetic Excitation Balance Magnetic Field Model

Bai

et al. 2022

Preprint

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The metal wear debris generated by wear during the operation of the mechanical equipment can reflect the fault status of the equipment, and the online monitoring of the metal wear debris in the oil can timely understand the operation information of the equipment. Aiming at the effective response of metal wear debris under symmetrical magnetic excitation, an online monitoring system for metal wear debris with dual-coil balanced magnetic excitation was developed. Based on the spatial magnetic field distribution of the current-carrying element, an analytical model of the magnetic field intensity distribution of a single-turn current-carrying ring is designed, and it is optimized as a single set of coils made of a current-carrying ring, and the coupling of the magnetic excitation of the symmetrical double coil is deduced. The magnetic field distribution model is simulated and analyzed by numerical method. The flow channel of the system is 8 mm. After the semi-physical simulation test with the wear debris speed of 3.03-5.25 m/s, the sensor can realize the detection of 100 μm ferromagnetic metal and 1000 μm non-ferromagnetic metal. The experiment verifies the correctness of the simulation model of the coupled magnetic field distribution. This research provides technical support for the detection of hydraulic oil contaminants, which is of great significance for preventing hydraulic system failures and extending the working life of hydraulic equipment.

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Online oil debris monitoring of rotating machinery: A detailed review of more than three decades

Cited by 91 publications

References 104 publications

Modern Monitoring Instrument to Support Fishing Vessel Operation and Maintenance: A Review

Modern Monitoring Instrument to Support Fishing Vessel Operation and Maintenance: A Review

Early Detection of Defects in Gear Systems Using Autocorrelation of Morlet Wavelet Transforms

Online Detection System of Metal Wear Debris Based on Symmetrical Magnetic Excitation Balance Magnetic Field Model

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