Wear Debris Detection Research Articles

An Inductive Debris Sensor Based on a High-Gradient Magnetic Field

The health condition of mechanical systems can be characterized by wear debris in lube oil. Therefore, wear debris detection is necessary for the fault prediction and diagnosis of mechanical systems. This paper presents an inductive debris sensor based on a high-gradient magnetic field. An induction coil is placed in a high-gradient magnetic field, and an induced voltage is generated when wear debris in the oil pipe flows through a magnetic field. A mathematical model of the sensor is established, and the output signal of the sensor is similar to that of a three-coil inductive debris sensor. The experimental results show that the sensor is capable of detecting 25- $\mu \text{m}$ ferromagnetic particles. The sensor driven by a constant current has a simple structure and is feasible for on-line wear monitoring.

Multichannel Inductive Sensor Based on Phase Division Multiplexing for Wear Debris Detection.

Inductive wear debris sensor has been widely used in real time machine lubricant oil condition monitoring and fault forecasting. However, the small sensing zone, which is designed for high sensitivity, of the existing sensors leads to low throughput. In order to improve the throughput, a novel multichannel wear debris sensor that is based on phase division multiplexing is presented. By introducing the phase shift circuit into the system, multiple sensing coils could work at different initial phases. Multiple signals of sensing coils could be combined into one output without information loss. Synchronized sampling is used for data recording, and output signals of multiple sensing coils are extracted from the recorded data. A four-channel wear debris sensor system was designed to demonstrate our method. Subsequently, crosstalk analysis, pseudo-dynamic testing and dynamic testing were conducted to check the sensing system. Results show that signals of four sensing coils could be simultaneously detected and the detection limit for ferrous wear debris is 33 μm. Using the presented method, real time wear debris detection in multiple channels could be achieved without increasing the number of excitation source and data acquisition equipment.

Hyper-Heuristic Capacitance Array Method for Multi-Metal Wear Debris Detection.

Online detection of fatigued wear debris in the lubricants of aero-engines can provide warning of engine failure during flight, thus having great economic and social benefits. In this paper, we propose a capacitance array sensor and a hyper-heuristic partial differential equation (PDE) inversion method for detecting multiple micro-scale metal debris, combined with self-adaptive cellular genetic (SA-CGA) and morphological algorithms. Firstly, different from the traditional methods, which are limited in multi-induction-Dirac-boundary-inversion, a mathematical model with non-local boundary conditions is established. Furthermore, a hyper-heuristic method based on prior knowledge is also proposed to extract the wear character. Moreover, a 12-plate array circulating sensor and corresponding detection system are designed. The experimental results were compared with the optical microscopy. The results show that under the conditions of 1~3 wear debris with diameters of between 250–900 μm, the accuracy of the proposed method is 10–38% higher than those of the traditional methods. The recognition error of the wear debris counts decreases to 0.

高精度磨粒检测传感器的设计及研究

高精度磨粒检测传感器的设计及研究

A 3×3 wear debris sensor array for real time lubricant oil conditioning monitoring using synchronized sampling

A high throughput wear debris sensor consisting of 3×3 sensing channels is presented for real time online lubricant oil conditioning monitoring. Time division multiplexing was applied to the sensing channels for measuring responses of multiple channels using one set of measurement electronics. Crosstalk among the 3×3 sensing channels was eliminated by diodes that are connected in series with each channel. Parallel L-C-R resonance was also applied to each sensing coil to increase the sensitivity. Furthermore, a unique synchronized sampling method was used to reduce the date size 50 times. Finally, we demonstrated that the sensor is capable of real time detection of wear debris as small as 50µm in SAE 0W-5 at a flow rate of 460ml/min; the measured debris concentration is in good agreement with the estimated actual concentration. The design can be extended to a N×N sensor array for an extremely high throughput without sacrificing the sensitivity, and can potentially be used for real time wear debris monitoring for health condition of rotating or reciprocating machineries.

Oxidation wear monitoring based on the color extraction of on-line wear debris

Oxidation associated wear usually involves high temperature and often accelerates lubrication degradation and failure processes. The color of oxide wear debris highly corresponds with the severities of oxidation wear. Therefore, on-line detection of oxide wear debris has the advantage of revealing the wear condition in a timely manner. This paper presents a color extraction method of wear debris for on-line oxidation monitoring. Images of moving wear particles in lubricant were captured via an on-line imaging system. Image preprocessing methods were adopted to separate wear particles from the background and to improve the image quality through a motion-blurred restoration process before the colors of the wear debris were extracted. By doing this, two typical types of oxide wear debris, red Fe2O3 and black Fe3O4, were identified. Furthermore, a statistical clustering model was established for automatic determination of the two typical types of oxide wear particles. Finally, the effectiveness of the proposed method was verified by performing real-time oxidation wear monitoring of experimental data. The proposed method provides a feasible approach to detect early oxidation wear and monitor its progress in a running machine.

An integrated lubricant oil conditioning sensor using signal multiplexing

One effective approach to detect signs of potential failure of a rotating or reciprocating machine is to examine the conditions of its lubrication oil. Here we present an integrated oil condition sensor for detecting both wear debris and lubricant properties. The integrated sensor consists of miniature multiplexed sensing elements for detection of wear debris and measurements of viscosity and moisture. The oil debris sensing element consists of eight sensing channels to detect wear debris in parallel; the elements for measuring oil viscosity and moisture, based on interdigital electrode sensing, were fabricated using micromachining. The integrated sensor was installed and tested in a laboratory lubricating system. Signal multiplexing was applied to the outputs of the three sensing elements such that responses from all sensing elements were obtained within two measurements, and the signal-to-noise ratio was improved. Testing results show that the integrated sensor is capable of measuring wear debris (>50 µm), moisture (>50 ppm) and viscosity (>12.4 cSt) at a high throughput (200 ml min−1). The device can be potentially used for online health monitoring of rotating machines.

High Throughput Wear Debris Detection in Lubricants Using a Resonance Frequency Division Multiplexed Sensor

With a long time goal of detecting signs of potential machine failure, we demonstrate a proof-of-principle multiplexed, multichannel, inductive pulse sensor based on resonant frequency division multiplexing for high throughput detection of micro-scale metallic debris in lubricants. In the four-channel sensor, each sensing coil is connected to a specific external capacitance to form a parallel LC circuit that has a unique resonant frequency. Only one combined sinusoidal excitation signal consisting of four frequencies components that are close to the 4 sensing channels’ resonant frequencies was applied to the sensor, and only one combined voltage response was measured. Because each sensing channel exhibited a peak amplitude at its resonant frequency, the signals for each individual channel were recovered from the combined response by taking the spectrum components at each resonant frequency with an improved signal-to-noise ratio. Inductance change for each channel was then calculated from signals of individual channels. Testing results show that the use of resonant frequency division multiplexing allows simultaneous detection of debris in lubricants using only one set of detection electronics; for the four-channel sensor, there is a 300 % increase in throughput. The resonant frequency division multiplexing concept can be potentially applied to a multichannel oil debris sensor with a large number of sensing channels to achieve a very high throughput, which is necessary for online health monitoring of rotating and reciprocal mechanical components.

Improving sensitivity of an inductive pulse sensor for detection of metallic wear debris in lubricants using parallel LC resonance method

Detection of small metallic wear debris is critical to identify abnormal wear conditions for prognosis of pending machinery failure. In this paper we applied an inductance–capacitance (LC) resonance method to an inductive pulse debris sensor to increase the sensitivity. By adding an external capacitor to the sensing coil of the sensor, a parallel LC resonance circuit is formed that has a unique resonant frequency. At an excitation frequency close to the resonant frequency, impedance change (and thus change in voltage output) of the LC circuit caused by the passage of a debris particle is amplified due to sharp change in impedance at the resonant peak; thus signal-to-noise ratio and sensitivity are significantly improved. Using an optimized measurement circuit, iron particles ranging from 32 to 96 µm and copper particles ranging from 75 to 172 µm were tested. Results showed that the parallel LC resonance method is capable of detecting a 20 µm iron particle and a 55 µm copper particle while detection limits for the non-resonance method are 45 and 125 µm, respectively. In contrast to the non-resonant method, the sensitivity of the resonance method has been significantly improved.

An integrated ultrasonic–inductive pulse sensor for wear debris detection

One approach to detect signs of potential machine failure is to detect wear debris in the lubrication oil of a rotating or reciprocating machine because the size and the concentration of wear debris particles in the oil show a direct relationship with the level of wear. In this article, a proof-of-principle integrated wear debris sensor consisting of an ultrasonic pulse sensor and an inductive pulse sensor for detecting wear debris in lubrication oil is presented. The ultrasonic pulse sensor detects all solid debris (metallic and non-metallic debris). A flow recess structure is utilized to ensure that all wear debris passes the acoustic focal region so that all debris can be accurately counted and sized. The inductive pulse sensor detects and counts all metallic debris (ferrous and non-ferrous) based on the inductive Coulter counting principle. By comparing the results from the two sensing components, the sensor is capable of differentiating and detecting non-metallic debris, ferrous metallic debris and non-ferrous metallic debris.

On-Line Wear Debris Detection in Lubricating Oil for Condition Based Health Monitoring of Rotary Machinery

Condition based monitoring has become essential in maintaining and extending the health of high-speed rotating and reciprocating machinery. One effective approach to detect signs of potential failure of a rotating or reciprocating machine is to examine the wear debris in its lubricating oil. Recent patents and research articles on on-line wear debris detection in lubricating oil are reviewed in this paper, including electrical impedance detection, acoustic detection, optical detection, pressure detection, online x-ray spectrography, resonant frequency detection, and electrostatic charge detection. Advantages and limitations of each detection method are discussed. Keywords: Debris, condition monitoring, on-line detection, particle sensor, condition-based maintenance

Implant wear debris detection apparatus and method

A system for detecting wear debris particulate from a medical implant within the body of a living animal is provided. The system includes an acoustic transmitter for transmitting acoustinc energy from outside the body to a soft tissue region proximate the medical implant containing wear debris particles; an acoustic receiver located outside the body to detect resultant acoustic energy generated by the wear debris particles and produce a received signal indicative thereof; a processor for processing the received signal to evaluate at least one parameter associated with the wear debris particles; and an output for indicating the at least one parameter.

Comparison of oil analysis and filter content analysis: A case study

Oil filters contain useful information on wear that has occurred in the oil-wetted mechanical system. However, filter analysis for wear detection is seldom performed, because the method is fairly cumbersome. On the other hand spectral oil-analysis can be economically done in highly automated laboratories and is therefore widely accepted. This paper describes the case involving a small passenger car diesel engine, where the results of the filter analysis were compared with the results of simultaneously performed oil analysis using X-ray fluorescence. Oil and filter samples were analysed after each 10,000 km, when oil and filter changes took place, over the life of the engine to 165,000 km. The results, as derived from the filter samples, showed a roughly shaped bath-tub curve development of the wear rate before the final stage of serious deterioration. However, the oil analysis did not confirm this trend. It is believed that the different in characteristics between a filter sample and an oil sample, and the effects of particle size and of oil filtration on the oil sample, may cause this discrepancy. If the latter is the case, care has to be taken in oil sampling for wear analysis, particularly in systems with fine full-flow filtration. Suggestions are made at the end of the paper for the design of dedicated diagnostic filters for wear debris detection.

Wear-debris detection and analysis techniques for lubricant-based condition monitoring

The characteristics of wear debris found in the lubricant flow of a machine are reviewed along with their relationships to specific wear processes. Current wear-debris detection and analysis techniques are described with reference to systems at the research and development stage. The features of these systems are compared with those of an ideal system and an outline of a novel technique is given.

The condition monitoring of heavily loaded spur gears

A short-duration high-tooth-load test on case-hardened spur gears was run on an experimental gear rig with a view to comparing the performance of various condition monitoring techniques. The condition monitoring techniques used all relied on the detection of wear debris in the oil and included atomic absorption spectrometry, X-ray fluorescence, particle counting and ferrography. They all proved to be successful in signalling accelerated wear after 100 h of operation. Examination of the gears at the termination of the test indicated that the gears had worn by a combination of surface plastic deformation and pitting.