scholarly journals An Impedance Sensor for Distinguishing Multi-Contaminants in Hydraulic Oil of Offshore Machinery

Micromachines ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1407
Author(s):  
Haotian Shi ◽  
Dian Huo ◽  
Hongpeng Zhang ◽  
Wei Li ◽  
Yuqing Sun ◽  
...  
Keyword(s):  
Steel Strip ◽  
Silicon Steel ◽  
Detection Sensitivity ◽  
Distribution Area ◽  
Metal Debris ◽  
Hydraulic Oil ◽  
Hydraulic Machinery ◽  
Steel Strips ◽  
Impedance Sensor ◽  
The Magnetic Field

The cleanliness of hydraulic oil can reflect the service life of the oil and the wear state of hydraulic machinery. An impedance sensor is proposed to distinguish multi-contaminants in hydraulic oil. The impedance sensor has two detection modes: the inductance-resistance mode is used to detect metal debris, and the capacitance mode is used to distinguish water droplets and air bubbles. By adding a built-in silicon steel strip and an external silicon steel strip with high magnetic permeability, the distribution area, strength, and uniformity of the magnetic field are enhanced to improve the detection sensitivity under inductance and resistance parameters. In addition, the silicon steel strips are used as electrode plates to introduce capacitance parameter detection. The experimental results show that the resistance detection method based on coil successfully improves the detection ability for non-ferromagnetic metal debris. The impedance sensor for distinguishing multi-contaminants in hydraulic oil can provide technical support for fault diagnosis of offshore hydraulic machinery.

scholarly journals A Novel Impedance Micro-Sensor for Metal Debris Monitoring of Hydraulic Oil

Micromachines ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 150
Author(s):  
Hongpeng Zhang ◽  
Haotian Shi ◽  
Wei Li ◽  
Laihao Ma ◽  
Xupeng Zhao ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Wear Debris ◽  
Detection Method ◽  
Silicon Steel ◽  
Detection Sensitivity ◽  
Normal Operation ◽  
Metal Debris ◽  
Hydraulic Oil ◽  
Steel Strips ◽  
The Magnetic Field

Hydraulic oil is the key medium for the normal operation of hydraulic machinery, which carries various wear debris. The information reflected by the wear debris can be used to predict the early failure of equipment and achieve predictive maintenance. In order to realize the real-time condition monitoring of hydraulic oil, an impedance debris sensor that can detect inductance and resistance parameters is designed and studied in this paper. The material and size of wear debris can be discriminated based on inductance-resistance detection method. Silicon steel strips and two rectangular channels are designed in the sensor. The silicon steel strips are used to enhance the magnetic field strength, and the double rectangular detection channels can make full use of the magnetic field distribution region, thereby improving the detection sensitivity and throughput of the sensor. The comparison experiment shows that the coils in series are more suitable for the monitoring of wear debris. By comparing and analyzing the direction and the presence or absence of the signal pulses, the debris sensor can detect and distinguish 46 µm iron particles and 110 µm copper particles. This impedance detection method provides a new technical support for the high-precision distinguishing measurement of metal debris. The sensor can not only be used for oil detection in the laboratory, but also can be made into portable oil detection device for machinery health monitoring.

scholarly journals Improving the Detection Ability of Inductive Micro-Sensor for Non-Ferromagnetic Wear Debris

Micromachines ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1108
Author(s):  
Man Wang ◽  
Haotian Shi ◽  
Hongpeng Zhang ◽  
Dian Huo ◽  
Yucai Xie ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Steel Strip ◽  
Excitation Frequency ◽  
Signal Amplitude ◽  
Ferromagnetic Metal ◽  
Detection Sensitivity ◽  
Metal Debris ◽  
Detection Ability ◽  
Inductive Sensor ◽  
The Magnetic Field

The inductive debris sensor has been studied because of its wide application prospects in mechanical health monitoring. In order to ensure a high-precision detection performance, a comprehensive method to improve the detection sensitivity and detection ability of the inductive sensor for non-ferromagnetic metal debris is proposed. Based on the characteristics of the eddy current inside the metal, the change of the coil impedance caused by the metal debris is increased by enhancing the magnetic field strength and selecting the optimal excitation frequency. The impedance detection method involving inductance and resistance parameters is used to improve the detection limit of non-ferromagnetic metal debris. The experimental results verify that the magnetic field in the detection region can be enhanced by adding a silicon steel strip (paramagnetic material) in the central hole of the coil, thereby greatly improving the detection sensitivity of the inductive sensor, and the concentrated distribution of the magnetic field avoids the double-peak signals generated by a single particle. The characteristics of the signal amplitude of non-ferromagnetic debris with excitation frequency are studied. Higher inductance, resistance amplitudes, and signal-to-noise ratio (SNR) can be obtained by using a high-frequency alternating current. Compared with inductance parameter detection, resistance parameter detection can detect smaller non-ferromagnetic debris. Combining the detection results of the inductance and resistance parameters can effectively improve the sensor’s ability to detect non-ferromagnetic debris.

scholarly journals Neural Network for Metal Detection Based on Magnetic Impedance Sensor

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4456
Author(s):  
Sungjae Ha ◽  
Dongwoo Lee ◽  
Hoijun Kim ◽  
Soonchul Kwon ◽  
EungJo Kim ◽  
...  
Keyword(s):  
Neural Network ◽  
Magnetic Field ◽  
Deep Learning ◽  
Short Term Memory ◽  
Magnetic Impedance ◽  
Detection Technology ◽  
Metal Detection ◽  
Long Short Term Memory ◽  
Impedance Sensor ◽  
The Magnetic Field

The efficiency of the metal detection method using deep learning with data obtained from multiple magnetic impedance (MI) sensors was investigated. The MI sensor is a passive sensor that detects metal objects and magnetic field changes. However, when detecting a metal object, the amount of change in the magnetic field caused by the metal is small and unstable with noise. Consequently, there is a limit to the detectable distance. To effectively detect and analyze this distance, a method using deep learning was applied. The detection performances of a convolutional neural network (CNN) and a recurrent neural network (RNN) were compared from the data extracted from a self-impedance sensor. The RNN model showed better performance than the CNN model. However, in the shallow stage, the CNN model was superior compared to the RNN model. The performance of a deep-learning-based (DLB) metal detection network using multiple MI sensors was compared and analyzed. The network was detected using long short-term memory and CNN. The performance was compared according to the number of layers and the size of the metal sheet. The results are expected to contribute to sensor-based DLB detection technology.

scholarly journals Optimization of the process of steel strip perforation and nickel platting for the purpose of elimination of trichloroethylene from the cleaning process of perforated steel strip

2009 ◽  
Vol 63 (1) ◽  
pp. 57-60
Author(s):  
Aleksandra Petrovic ◽  
Slavica Glisic
Keyword(s):  
Organic Solvent ◽  
Steel Strip ◽  
Cleaning Process ◽  
Used Oil ◽  
Additional Heating ◽  
Steel Strips ◽  
The Many ◽  
Made In

In the production of pocket type electrodes for Ni-Cd batteries perforation of proper steel strips and then nickel platting of perforated steel strips were made. In the nickel platting process, the organic solvent, trichloroethylene, has previously been used for cleaning. Due to the carcinogenic nature of trichloroethylene and the many operations previously required during cleaning, it was considered to do cleaning of perforated steel strips without use of the mentioned organic solvent. In the purpose of elimination of trichloroethylene from the cleaning process of perforated steel strips, the tests of perforation of steel strips with use of oils of different viscosity were made. It was shown that there was no dysfunction during the work of the perforation plants, meaning there was no additional heating of the strips, deterring of the steel filings, nor excessive wearing of the perforation apparatus. The perforation percent was the same irrelevant of the viscosity of the used oil. Before being perforated using the oils with different viscosity, the nickel platting steel strips were cleaned in different degreasers (based on NaOH as well as on KOH). It was shown that efficient cleaning without the use of trichloroethylene is possible with the use of oil with smaller viscosity in the perforated steel strips process and the degreaser based on KOH in the cleaning process, before nickel platting. It also appeared that the alkali degreaser based on KOH was more efficient, bath corrections were made less often and the working period of the baths was longer, which all in summary means less quantity of chemicals needed for degreasing of perforated steel strips.

scholarly journals Silicon Steel Strip Profile Control Technology for Six-High Cold Rolling Mill with Small Work Roll Radius

Metals ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 401
Author(s):  
Hainan He ◽  
Jian Shao ◽  
Xiaochen Wang ◽  
Quan Yang ◽  
Xiawei Feng
Keyword(s):  
Cold Rolling ◽  
Rolling Mill ◽  
Steel Strip ◽  
Work Roll ◽  
Rolling Process ◽  
Silicon Steel ◽  
Cold Rolling Mill ◽  
Strip Profile ◽  
Profile Control ◽  
Small Work

Due to the requirement of magnetic properties of silicon steel sheets, producing high-precision size strips is the main aim of the cold rolling industry. The tapered work roll shifting technique of the six-high cold rolling mill is effective in reducing the difference in transverse thickness of the strip edge, but the effective area is limited, especially for a high crown strip after the hot rolling process. The six-high mill with a small work roll size can produce a strip with higher strength and lower thickness under a smaller rolling load. At the same time, the profile of the strip can be substantially improved. By advancing a well-established analytical method, a series of simulation analyses are conducted to reveal the effectiveness of a small work roll radius for the strip profile in the six-high cold rolling process. Through the analysis of flattening deformation and deflection deformation on the load, the change rule of the strip profile produced by the work roll with a small roll diameter can be obtained. Combined with theoretical analysis and industrial experiments, it can be found that the improvement effect of the small work roll radius on the profile of the silicon strip is as significant.

An Analysis of the Bonding Energy through Pull-Out Tests for Aerated Concrete with Various Steel Strip Geometries

2011 ◽  
Vol 275 ◽  
pp. 55-58 ◽  
Author(s):  
Dariusz Alterman ◽  
Juan Vilches ◽  
Thomas Rainer Neitzert
Keyword(s):  
Surface Area ◽  
Steel Strip ◽  
Bonding Energy ◽  
Ball Joint ◽  
Pull Out ◽  
Steel Strips ◽  
Aerated Concrete ◽  
Set Up ◽  
The Relationship

The relationship between various steel strip geometries and the bonding energy through pull-out tests of aerated concrete specimens is investigated. Prismatic concrete samples containing embedded steel strips with and without holes of differing sizes and quantities were analysed. Improvements of the bonding energy through pull-out tests by 70% are possible by increasing the number of holes on a steel strip from one to four while maintaining a constant surface area. The energy increased even up to 130% for strips containing holes compared to strips without. In addition, the tests have been carried out with a novel easy to assemble set-up containing a freely adjustable ball-joint and a plate with embedded bolts to avoid eccentricity during pull-out tests.

Analysis of ZDDP Films on Sticking Defects by FEM during Hot Rolling of Ferritic Stainless Steel Strips

2016 ◽  
Vol 846 ◽  
pp. 96-101
Author(s):  
Liang Hao ◽  
Zheng Yi Jiang ◽  
Dian Yao Gong ◽  
Dong Bin Wei ◽  
Xia Wei Cheng ◽  
...  
Keyword(s):  
Finite Element Method ◽  
Stainless Steel ◽  
Ferritic Stainless Steel ◽  
Hot Rolling ◽  
Steel Strip ◽  
Crack Size ◽  
Surface Characterisation ◽  
Fem Model ◽  
Steel Strips ◽  
Simulation Results

The aim of this study is to understand the effect of zinc dialkyl dithio phosphate (ZDDP) films on sticking defects during the hot rolling of ferritic stainless steel strips. The surface characterisation and crack propagation are very important for the sticking defects of ferritic stainless steel strip. A finite element method (FEM) model is constructed with different crack size ratios, in which the profile of the strip roughness and ZDDP films are taken into consideration. Simulation results show that the widths of cracks tend to be reduced with the introduction of ZDDP films, improving the sticking defects, which is confirmed by the hot rolling trials.

Effect of Hot-Rolled Microstructure on the Recrystallization Texture of Cold-Rolled Non-Oriented Electrical Steel

2011 ◽  
Vol 298 ◽  
pp. 203-208 ◽  
Author(s):  
Zi Li Jin ◽  
Wei Li ◽  
Yi Ming Li
Keyword(s):  
Cold Rolling ◽  
Electrical Steel ◽  
Texture Evolution ◽  
Steel Strip ◽  
Silicon Steel ◽  
Grain Structure ◽  
Recrystallization Annealing ◽  
Rolled Sheet ◽  
Cold Rolled ◽  
Hot Rolled

With the help of orientation distribution function (ODF) analysis, experiments of different hot band grain microstructure 0.33% silicon steel were cold-rolled and annealed in the laboratory，to study the effect of the microstructure hot-rolled steel strip for cold rolled non-oriented silicon steel microstructure and texture of recrystallization annealing. The results show that hot rolled microstructure on cold rolled Non-Oriented Electrical Steel cold-rolled sheet evolution of texture and recrystallization have important influence, the quiaxed grain structure of steel by cold rolling and recrystallization annealing, the recrystallization speed than the fiber grain-based mixed crystals recrystallization fast , With the equiaxed grains made of cold rolled silicon steel after annealing the {110}<UVW> texture components was enhanced and {100}<uwv> texture components weakened. Different microstructure condition prior to cold rolling in the recrystallization annealing process the texture evolution has the obvious difference, the equiaxial grain steel belt cold rolling and annealing, has the strong crystal orientation. This shows that the equiaxed grain when hot microstructure is detrimental to the magnetic properties of cold-rolled non-oriented silicon steel to improve and increase.

scholarly journals Multifunctional Detection Sensor and Sensitivity Improvement of a Double Solenoid Coil Sensor

Micromachines ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 377 ◽  
Author(s):  
Laihao Ma ◽  
Zhiwei Xu ◽  
Hongpeng Zhang ◽  
Weiliang Qiao ◽  
Haiquan Chen
Keyword(s):  
Silicon Steel ◽  
Detection Sensitivity ◽  
Metal Particles ◽  
Iron Particles ◽  
Water Droplets ◽  
Copper Particles ◽  
Detection Model ◽  
Steel Sheets ◽  
Capacitance Detection ◽  
Improvement Effect

A multifunction detection sensor for hydraulic oil contaminants based on a microfluidic chip is proposed, which consists of double solenoid coils and a straight microchannel. The inductance detection model of metal particles and capacitance detection model of nonmetal particles are constructed theoretically. In order to further improve detection sensitivity, experiments of effects of silicon steel sheets on the sensitivity of detection are carried out. Experimental results show that the silicon steel sheets can significantly improve the detection sensitivity of metal particles. The inductance amplitude and signal-to-noise (SNR) of iron particles ranging from 60–130 μm and copper particles ranging from 120–180 μm can be increased by at least 7.0–2.4 and 4.5–2.0 times, respectively. We demonstrate the successful detection of 30 μm iron particles and 90 μm copper particles using double solenoid coils with silicon steel sheets. In capacitance detection experiments, the silicon steel sheets can improve the sensitivity of capacitance detection, but the improvement effect is not obvious. We demonstrate the successful detection of 140 μm water droplets and 240 μm bubbles using double solenoid coils with and without silicon steel sheets. The capacitance amplitude and SNR of detecting water droplets ranging from 140–150 μm and bubbles ranging from 240–250 μm can be increased by 37.4–21.9% and 18.5–8.0% using double solenoid coils with silicon steel sheets, respectively.

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