Plunger pump fault online diagnosis method based on rotating speed frequency amplitude

Abstract

The invention provides a plunger pump fault online diagnosis method based on a rotating speed frequency amplitude, which belongs to the field of plunger pump state detection and mainly comprises the steps of pressure sensor data acquisition and processing, load pressure spectrum analysis and plunger pump fault diagnosis based on the rotating speed frequency amplitude. The method comprises the specific steps that a high-frequency pressure sensor is arranged at an outlet of a plunger pump, and real-time data input is provided for fault diagnosis; a pressure signal conditioning and digital-to-analog conversion device is built, data transmission is completed, and data interfering with fault diagnosis is eliminated; fourier transform is carried out on the processed pressure signal to extract the rotating speed frequency of the plunger pump; and the specific fault type is judged based on the corresponding relation between the rotating speed frequency amplitude of the plunger pump and the specific fault. According to the method, based on the difference of the rotating speed frequency component amplitudes of load pressure signals under different plunger pump friction pair abrasion fault types, the mapping relation between the rotating speed frequency amplitudes and the plunger pump friction pair abrasion fault types is established, and the plunger pump load pressure signals serve as data input; and the specific wear fault type of the friction pair of the plunger pump is monitored and evaluated in real time. According to the invention, state monitoring and condition-based maintenance of the plunger pump are facilitated.

Description

Technical Field

[0001] The present invention belongs to the field of plunger pump condition monitoring, and relates to an online fault diagnosis method for plunger pumps based on rotational speed frequency amplitude. Background Art

[0002] Hydraulic systems are widely used in the industrial field due to advantages such as fast dynamic response, large output power, and self-lubrication. As the core power component of the hydraulic system, the operating reliability of the plunger pump directly affects the reliability and safety of the equipment. The most common fault of the plunger pump is the wear of three friction pairs (plunger pair, port plate pair, and slipper pair). The wear degradation of the friction pairs will lead to an increase in internal leakage, a decrease in volumetric efficiency, and further cause insufficient output pressure and flow rate, increased vibration and noise, and increased oil temperature. This not only reduces the efficiency and accuracy of the system but also accelerates the decline of system performance and even causes sudden accidents. Therefore, the fault diagnosis of plunger pumps has become a hot research topic in recent years.

[0003] The traditional method of diagnosing plunger pump faults by regular inspection seriously affects the working efficiency of the plunger pump system. The existing data-driven plunger pump fault diagnosis methods rely on a large amount of test data, and the algorithms have poor adaptability to different types of plunger pumps and different types of faults. Therefore, the traditional fault diagnosis methods have problems such as insufficient adaptability and poor real-time performance under complex working conditions and are difficult to meet the requirements of modern industry for predictive maintenance. To address this technical bottleneck, an online fault diagnosis method for plunger pumps based on rotational speed frequency amplitude is proposed. When a plunger pump fails, the most direct manifestation is the change in the pressure pulsation at the oil outlet. The manifestation forms of pressure pulsation are different under different fault types, and spectral analysis is a powerful tool for analyzing different signal components. The online monitoring of the health status of the plunger pump is realized through non-invasive pressure signal analysis, providing a high-precision and low-cost solution for the maintenance of the hydraulic system. Summary of the Invention

[0004] (1) Objectives of the Invention

[0005] Aiming at the problem that the fault diagnosis of plunger pumps relies on a large amount of test data, the present invention proposes an online fault diagnosis method for plunger pumps based on rotational speed frequency amplitude. Based on the differences in the amplitudes of specific frequency components of the load pressure signal under different fault types, the present invention establishes a mapping relationship between the rotational speed frequency amplitude and the plunger pump fault type, and uses the plunger pump load pressure signal as the data input to monitor and evaluate the plunger pump fault type in real time. This provides convenient conditions for the condition monitoring and daily maintenance of plunger pumps.

[0006] (2) Technical Solutions

[0007] The technical solution of the present invention is: an online diagnosis method for plunger pump faults based on speed frequency amplitude, including the following contents: pressure sensor data acquisition and processing, load pressure spectrum analysis and plunger pump fault type diagnosis algorithm based on speed frequency amplitude. The specific steps are:

[0008] Step 1: Install a pressure sensor at the oil outlet pipeline of this model of plunger pump. The specific installation position is related to the pump body structure of the plunger pump. Install it as needed to measure the real-time pressure data of the plunger pump outlet load, providing a data basis for subsequent signal processing and plunger pump fault type diagnosis;

[0009] Step 2: The signals collected by the pressure sensor are all processed by the signal conditioning and digital-to-analog conversion device, and the sensor data is collected into the computer through the A / I port to realize real-time data transmission;

[0010] Step 3: The data collected by the computer needs to be cleaned by a special algorithm to remove data that interferes with the diagnosis of the plunger pump fault type. Data cleaning is necessary and irreplaceable in this process. Due to the strong correlation between the speed spectrum amplitude of the load pressure and the plunger pump fault type, bad sample data will greatly affect the accuracy of the fault type diagnosis. Abnormal data caused by cleaning sensor system errors, digital-to-analog conversion errors, etc. need to be eliminated. Finally, the load pressure P is collected. o ;

[0011] Step 4: Load pressure data P of the piston pump o Perform Fourier transform to obtain spectrum signals and analyze them to extract frequency characteristics under different fault conditions. Determine the base frequency through intelligent algorithm, and then obtain the speed frequency and amplitude of the plunger pump, providing characteristic data for the subsequent diagnosis of the plunger pump fault type.

[0012] Step 5: Determine the fault type of the plunger pump based on the corresponding amplitude of the extracted plunger pump speed spectrum, select the appropriate threshold as the discrimination condition, develop an intelligent algorithm and build a model to realize real-time diagnosis of the plunger pump fault type.

[0013] (III) Beneficial Effects of the Invention

[0014] The beneficial effects of the present invention are: providing an online diagnosis method for plunger pump faults based on speed frequency amplitude, taking the real-time evaluation of the plunger pump as the starting point, and based on the strong correlation between the load pressure component of the plunger pump and the fault type, developing and verifying its intelligent diagnosis algorithm. This method solves the problem of online diagnosis of internal faults of the plunger pump without disassembly, and realizes the diagnosis of the fault type of the plunger pump. This method characterizes the internal working state of the plunger pump in real time, ensures the high-efficiency operation of the plunger pump, and improves the operational reliability and safety of the plunger pump. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is the flowchart of the on-line fault diagnosis method for the plunger pump based on the rotational speed frequency amplitude in the present invention.

[0016] Figure 2 This is a schematic diagram of the arrangement of the pressure sensors of the plunger pump in the embodiment of the present invention.

[0017] Figure 3 This is a schematic diagram of the processing and conversion of the pressure signal of the plunger pump in the embodiment of the present invention.

[0018] Figure 4 This is the discrimination logic diagram of the plunger pair wear fault type in the embodiment of the present invention.

[0019] Figure 5 This is the interface diagram of the visualization platform for diagnosing the plunger pair wear fault type in the embodiment of the present invention Detailed implementation manners

[0020] The following takes the plunger pair wear fault as an example to specifically illustrate the present invention. This example studies three situations of plunger pair wear (normal working condition, single-column wear and two-plunger wear). The described implementation manners are only a special case of the method of the present invention and do not represent the entire implementation process.

[0021] This example takes a certain type of plunger pump as the research object. This system uses a motor to drive the main shaft of the plunger pump to provide torque and rotational speed. The present invention selects to set a group of threshold classifications at the rotational speed frequency as the fault diagnosis criteria for different rotational speeds and different fault types under a certain rated pressure. Figure 1 This is the flowchart of diagnosing three types of fault types of the plunger pair based on the load pressure in the present invention. Its main contents include: data acquisition and processing of the pressure sensor; the corresponding relationship between the rotational speed frequency component based on the load pressure and the plunger pair wear fault type, and obtaining the specific fault type of the plunger pair wear from the load pressure signal. The specific implementation steps are as follows:

[0022] Step 1: Install a pressure sensor at the oil outlet pipeline of the plunger pump to measure the real-time pressure data of the plunger pump load, providing a data basis for subsequent signal processing and diagnosing the plunger pair wear fault type. Its specific installation position is as Figure 2 shown. The outlet load of this plunger pump is changed by adjusting the proportional overflow valve;

[0023] Step 2: The signal collected by the pressure sensor passes through the signal conditioning and analog-to-digital conversion device, and the sensor data is collected into the computer through the A / I port, and memory is allocated for real-time data transmission, as Figure 3 shown;

[0024] Step 3: Subsequently, the data is cleaned by the algorithms inside the computer to remove the data with abnormal load pressure, such as Figure 3 shown. Due to the strong correlation between the rotational speed frequency component of the load pressure and the plunger pair wear fault type, the bad sample data will greatly affect the diagnosis of the plunger pair wear fault type and needs to be intelligently eliminated, such as cleaning the data anomalies caused by sensor system errors, digital-to-analog conversion errors, etc. Finally, the load pressure P o is collected;

[0025] Since the long-term experimental data acquisition of the plunger pump will generate systematic errors, random errors, and fault-introduced errors. The systematic errors mainly come from the zero drift and temperature drift of the sensor, manifested as the slow fluctuation of the baseline in the spectrogram; the changes in the spectrogram caused by the systematic errors and random errors are negligible compared to the fault-introduced errors. Therefore, the results are basically reliable in theory.

[0026] Step 4: Based on the mapping relationship between the rotational speed frequency amplitude of the pressure signal spectrogram and the plunger pair fault, using the plunger pump load pressure data P o as the input, develop an intelligent algorithm to realize the diagnosis of the plunger pair wear fault type of the plunger pump. The specific algorithm logic is as follows:

[0027] First, at a specific pressure and different rotational speed conditions, remove the DC component from the load pressure P o and perform Fourier transform to obtain the spectrogram.

[0028] Second, detect the spectral peak through the sliding window algorithm and determine the fundamental frequency through algorithm screening.

[0029] Third, according to the multiple relationship between the rotational speed frequency and the fundamental frequency, determine the rotational speed frequency. To ensure the reliability of the results, after capturing the fundamental frequency and calculating the rotational speed frequency, re-search for the maximum value within a certain range on both sides with the calculated value as the center, so that the point where the rotational speed frequency is located and its amplitude can be accurately calculated;

[0030] Fourth, construct a three-level fault classification model with the amplitude of the rotational speed frequency point as the core criterion, and design a suitable set of thresholds a1 and a2 as the discriminant basis for the three fault types at different rotational speeds under a certain rated pressure. The judgment logic of the plunger pair wear fault type is as Figure 4 shown.

[0031] Step 5: Develop a visual operation platform to realize the real-time monitoring of the time-domain diagram and frequency-domain diagram of the pressure signal. The interface of the visual platform for diagnosing the plunger pair wear fault type is as Figure 5 shown.

Claims

1. An online fault diagnosis method for a plunger pump based on the rotational speed frequency amplitude, characterized in that Collection and processing of pressure signals, calculation of rotational speed frequency amplitude, and confirmation of the fault types of the piston pump. The specific steps are as follows: Step 1: Use a pressure sensor to collect the pressure signal at the outlet of the plunger pump, and process the collected signal to obtain the pressure signal P o ; Step 2: For the pressure signal P o perform Fourier transform, extract the frequency characteristics under different fault conditions respectively, determine the fundamental frequency through intelligent algorithms, and then obtain the rotational speed frequency and its amplitude; Step 3: Based on the differences in the amplitudes of the rotational speed frequency components of the load pressure signal under different fault types, establish the mapping relationship between the rotational speed frequency amplitude and the fault types of the piston pump. Design a suitable set of fault classification thresholds to confirm the specific fault types of the piston pump through intelligent algorithms.

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