Oil wear particle monitoring sensor and oil online monitoring system outputting vibration signal

Abstract

The invention relates to an oil abrasive particle monitoring sensor and an oil online monitoring system outputting vibration signals. The induction coil of the monitoring sensor is located between two overlapping planar coils parallel to each other, and the planar coil is connected to a constant current source. The central axis of the induction coil is parallel to the planar coil, and there is a gap between the induction coil and the planar coil. The length of the induction coil is smaller than the outer diameter of the planar coil. The sensor of this online oil monitoring system is installed in the lubricating oil circuit of the mechanical equipment, and the output of the induction coil is connected to the Maxwell-Wien bridge, and the output of the latter is respectively connected to the oil abrasive particles and the vibration signal acquisition circuit, and then through the analog The digital conversion circuit is connected to the microcontroller. There is a comprehensive fault analysis module in the microcontroller, and the microcontroller is connected to the display screen to display the metal abrasive particle signal and vibration signal online, and display the current fault information of the mechanical equipment. The invention timely and accurately judges mechanical faults; the system is small in size and portable, and can be installed in mobile devices for on-line monitoring of faults.

Description

technical field [0001] The invention relates to the field of machine state monitoring and fault diagnosis, in particular to an oil abrasive particle monitoring sensor outputting vibration signals and an oil online monitoring system. Background technique [0002] With the continuous development of mechanical equipment technology, its internal structure is also more complex. Correspondingly, the means of monitoring the operation status of mechanical equipment are also constantly improving, so as to continuously maintain the normal operation of mechanical equipment. The most commonly used monitoring signals for mechanical operation status are three types of vibration signals: displacement, velocity and acceleration. This kind of vibration signal can accurately characterize the dynamic characteristics of equipment in real time, from which early weak fault signals can be extracted and fault location can be performed. [0003] In order to predict early failures more effectively,...

AI Technical Summary

Problems solved by technology

However, the existing online oil wear particle sensors must use DAQ cards to collect data and use traditional computers for analysis. The existing microprocessors are not competent for the acquisition, processing and analysis of such sensor signals.

Therefore, such sensors are difficult to configure and realize online monitoring in mobile mechanical equipment (such as automobile engines)

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