In this article, an impedance debris sensor capable of simultaneously detecting inductance and resistance parameters is presented, which mainly consists of two planar coils in parallel, two excitation silicon steel strips inserted in the inner hole of coils and a built-in silicon steel strip located in the center of channel. The excitation silicon steel strips and the built-in silicon steel strip establish a detection region with a high-gradient magnetic field to improve the sensitivity of the sensor. And the square channel makes full use of the sensitive detection region, thereby further increasing the detection throughput. Experiments have shown that the amplitudes of the inductance and resistance pulses generated by the same particle many times through the detection region are different. The uncertainty of the sensor can be reduced for accurate size information by combining the detection results of the inductance and resistance parameters. By comparing and analyzing the inductance parameter detection result and the resistance parameter detection result, the impedance debris sensor can distinguish and measure 25  μ m iron particle and 85  μ m copper particle. With its high sensitivity, high throughput, and capability of multiparameter detection, this sensor can potentially be used for health monitoring of hydraulic equipment.

An Impedance Debris Sensor Based on a High-Gradient Magnetic Field for High Sensitivity and High Throughput

In the diagnosis of lung cancer, electronic nose (E-nose) has attracted much attention by detecting the volatile organic compounds (VOCs) in exhaled breath. In this research, an E-nose platform with a novel thermal desorption preconcentration subsystem is designed to verify whether analyzing VOCs can reliably differentiate lung cancer patients from healthy individuals and patients with benign pulmonary diseases. To this end, total 87 subjects (46 patients with lung cancer, 36 healthy volunteers and 5 patients with benign pulmonary diseases) are enrolled for the sensor array data collection. 13 composite features are extracted from each sensor, and some classical classifiers are established to demonstrate the feasibility of identifying lung cancer patients through VOCs. To improve the performance, considering the inherent characteristics of E-nose data, a sparse group feature selection (FS) method is applied to the raw sensor array data. It is observed that the FS method can reduce data dimensionality and improve the classification performance significantly. Statistical analysis for the effect of age and smoking habit on classification results shows that no significant influences are found.

Lung cancer detection via breath by electronic nose enhanced with a sparse group feature selection approach

A high sensitivity micro impedance sensor is presented for oil condition monitoring. The sensor consists of a microfluidic chip and a sensing unit. The sensing unit contains two solenoid coils and eight silicon steel tips, which can generate a highly focusing magnetic field. The micro impedance sensor can not only distinguish between ferromagnetic and non-ferromagnetic metal particles, but also water droplets and air bubbles in oil. The simulation results show that the magnetic induction is significantly improved due to the silicon steel tips, and the electric field intensity is also slightly enhanced. In the inductance experiments, the sensitivity is extremely improved based on magnetic focusing by silicon steel tips, iron particles with diameters down to $18\mu $ m and copper particles with diameters down to 75 $\mu \text{m}$ have been successfully detected by using the simple high sensitivity micro impedance sensor. In the capacitance experiments, the signal to noise ratio (SNR) of the micro impedance sensor with silicon steel tips is slightly improved; water droplets with diameters down to 100 $\mu \text{m}$ and air bubbles with diameters down to 200 $\mu \text{m}$ have been detected. The high sensitivity micro impedance sensor has been demonstrated to achieve the precise measurement of particle sizes and the accurate counting of microparticles.

A High Sensitivity Micro Impedance Sensor Based on Magnetic Focusing for Oil Condition Monitoring

The wear debris in hydraulic oil or lubricating oil has a wealth of equipment operating information, which is an important basis for large mechanical equipment detection and fault diagnosis. Based on traditional inductive oil detection technology, magnetic nanoparticles are exploited in this paper. A new inductive oil detection sensor is designed based on the characteristics of magnetic nanoparticles. The sensor improves detection sensitivity based on distinguishing between ferromagnetic and non-ferromagnetic wear debris. Magnetic nanoparticles increase the internal magnetic field strength of the solenoid coil and the stability of the internal magnetic field of the solenoid coil. During the experiment, the optimal position of the sensor microchannel was first determined, then the effect of the magnetic nanoparticles on the sensor's detection was confirmed, and finally the concentration ratio of the mixture was determined. The experimental results show that the inductive oil detection sensor made of magnetic nanoparticle material had a higher detection effect, and the signal-to-noise ratio (SNR) of 20-70 μm ferromagnetic particles was increased by 20%-25%. The detection signal-to-noise ratio (SNR) of 80-130 μm non-ferromagnetic particles was increased by 16%-20%. The application of magnetic nanoparticles is a new method in the field of oil detection, which is of great significance for fault diagnosis and the life prediction of hydraulic systems.

/pdf/inductive-magnetic-nanoparticle-sensor-based-on-microfluidic-gvsesqugoz.pdf

Inductive Magnetic Nanoparticle Sensor based on Microfluidic Chip Oil Detection Technology.

Inductive oil debris sensors have been widely used in the health monitoring of mechanical equipment. Such sensors are important for fault diagnosis, life prediction, and prevention of catastrophic failures. In this article, the concept that the residual voltage caused by the asymmetry of two incentive coils hinders the improvement of the sensor resolution is theoretically demonstrated for the first time. In order to achieve ultrasensitive detection, a novel two-stage autoasymmetrical compensation circuit (AACC) is introduced into the triple-coil debris sensor to automatically suppress the residual voltage in real time. The experimental results show the successful detection of 70 μ m (diameter or D ) ferrous particles and 165 μ m ( D ) nonferrous particles in a sensing channel with a diameter of 43 mm. The AACC is verified effectively to maintain the residual voltage at an ultrasmall value even in the presence of environmental fluctuations, and the sensitivity of the sensor using AACC is more than 31 times that of the sensor without AACC.

Ultrasensitive Inductive Debris Sensor With a Two-Stage Autoasymmetrical Compensation Circuit

A highly sensitive triple-coil inductive debris sensor based on an effective unbalance compensation circuit

https://iopscience.iop.org/article/10.1088/1361-6501/ab49c5/pdf

Interference reducing by low-voltage excitation for a debris sensor with triple-coil structure

Triple-Coil Inductive Debris Sensor with Special Shielded Coils for Depressing Interference of Dielectric Components

A highly sensitive inductive wear debris sensor based on intermittent excitation is presented for real-time condition monitoring of machinery faults. The specially designed intermittent excitation method utilizes short-term large currents to periodically generate a strong alternating magnetic field, thus attaining enhanced sensitivity and low heat generation at the same time. A combination of different excitation currents is also applied for multisensitivity measurement to expand the detectable size range and detection accuracy, which is suitable for industrial occasions with complex detection requirements. In order to verify the effectiveness of intermittent excitation, a sensor prototype and signal processing system have been constructed. The testing results demonstrate that the sensitivity of the proposed sensor using intermittent excitation with a duty cycle of 1% is 10 times that of constant excitation with the same power consumption. A wide detectable size range of 48–1426 μm iron particles and 112–3802 μm copper particles in a 10 mm diameter sensing channel have been realized by dual-sensitivity measurement with outstanding temperature stability and size accuracy. The design concept of intermittent excitation can be extended to various types of debris sensors and other online detection equipment for great performance improvement.

Min Qian

Papers

A highly sensitive triple-coil inductive debris sensor based on an effective unbalance compensation circuit

Ultrasensitive Inductive Debris Sensor With a Two-Stage Autoasymmetrical Compensation Circuit

Interference reducing by low-voltage excitation for a debris sensor with triple-coil structure

Triple-Coil Inductive Debris Sensor with Special Shielded Coils for Depressing Interference of Dielectric Components

Wear Debris Sensor Using Intermittent Excitation for High Sensitivity, Wide Detectable Size Range, and Low Heat Generation