Among the core components of the power station hydraulic system, the PFG-142-D high-pressure gear pump undertakes the key task of power transmission. Its operating status directly affects the control accuracy and safety performance of the unit. Based on the life prediction technology of oil particle analysis, a set of accurate equipment health assessment system is constructed by capturing the evolution law of wear products in lubricating oil.

1. Basic technical principles

During the operation of the hydraulic gear pump PFG-142-D, the friction and wear of metal parts will generate characteristic particles in the lubricating oil. The physical form and chemical composition of these particles faithfully record the wear history of the equipment. When fatigue peeling occurs on the gear meshing surface, irregular flaky particles with a diameter of 10-50μm will appear in the oil; spherical particles rich in copper will be produced when the bearing retainer is worn. By continuously tracking the number, size and morphology changes of these particles, the wear stage of the equipment can be accurately determined.

This method adopts a three-level monitoring architecture: online sensors monitor the changes in the total amount of particles in real time, laboratory spectral analysis determines the composition of wear materials, and microscopic imaging technology analyzes the geometric characteristics of particles. This hierarchical and progressive detection mode can not only ensure the timeliness of monitoring, but also obtain accurate wear mechanism judgment.

2. Implementation Methods and Steps

Equipment status baseline establishment: Within 200 hours after the new PFG-142-D high-pressure gear pump is put into operation, oil samples are collected weekly to establish baseline parameters. Record the particle concentration fluctuation range in the normal wear stage, and determine the initial thresholds of parameters such as ferromagnetic particles (PQ value) and element concentration.

Dynamic monitoring system construction: Install electromagnetic particle sensors in the pump inlet and outlet oil circuits to monitor the number changes of hard particles above 15μm in real time. Cooperate with monthly laboratory iron spectrum analysis to obtain particle morphology characteristics and element composition data. When the online monitoring data exceeds the baseline threshold, the deep detection process is automatically triggered.

Intelligent evaluation of wear status: Establish an evaluation model containing 7 characteristic parameters: particle concentration growth rate, main wear element proportion, spherical particle proportion, etc. Through machine learning algorithms to analyze the correlation between parameters, the wear status is divided into three stages: normal wear, accelerated wear, and critical failure.

Life prediction and decision support: Calculate the remaining service life based on the current wear rate. When the predicted life is less than 300 hours, the system automatically generates maintenance recommendations. Targeted solutions are provided for different wear modes: tooth surface wear recommends checking the filtration system first, while bearing wear prompts checking the axial clearance.

3. Key points of technical implementation

The successful application of this method requires grasping three key links: oil sample collection must strictly follow the specifications to ensure that representative samples are obtained from the system flow area; the detection equipment needs to be calibrated with standard particles every quarter to maintain the consistency of the measurement data; the model parameters should be updated and iterated every six months to incorporate the latest equipment operation data.

In the actual operation and maintenance of the power station, it is recommended to adopt a step-by-step implementation strategy: the first stage is to complete the installation of monitoring equipment and establish a baseline; the second stage is to carry out personnel training and process running-in; the third stage is to achieve intelligent early warning of the entire system.

The life prediction method based on oil particle analysis provides a reliable technical path for the refined management of the high-pressure gear pump PFG-142-D. This technology not only realizes the early perception of the health status of the equipment, but more importantly, it establishes a decision-making basis for preventive maintenance.

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E-mail: sales@yoyik.com
Tel: +86-838-2226655
Whatsapp: +86-13618105229

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