Method and system for monitoring the operating state of a hydraulic pump group

Abstract

The application discloses a hydraulic pump set operation state monitoring method and system, and relates to the technical field of hydraulic pump set operation state monitoring. The hydraulic pump set operation state monitoring method comprises the following steps: collecting first health state characteristic parameters of a hydraulic pump set under a standard operation state; establishing a performance change prediction curve corresponding to the hydraulic pump set according to the first health state characteristic parameters; collecting second health state characteristic parameters of the hydraulic pump set under a real-time operation state under an actual working condition; and comparing the second health state characteristic parameters with the first health state characteristic parameters corresponding to the performance change prediction curve to determine whether the hydraulic pump set is in a healthy operation state under the actual working condition. The application solves the technical problem that the operation state monitoring effect of the hydraulic pump set is poor and the health condition of the hydraulic pump set cannot be predicted.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of tunneling engineering, further relates to a hydraulic pump set operation state monitoring method and system, and particularly relates to a main drive hydraulic pump set motion health state monitoring method and system of a tunneling machine. BACKGROUND

[0002] The main drive system of the tunneling machine is a hydraulic power source composed of a hydraulic pump set, a drive motor set, an oil tank, a directional valve, a throttle valve, an overflow valve and a control valve. It supplies oil according to the flow direction, pressure and flow rate required by the main drive system, and is suitable for various machines with separated drive devices and hydraulic stations. The hydraulic station is connected to the drive device (oil cylinder or motor) by an oil pipe, and the hydraulic system can realize various specified actions.

[0003] As the power source of the execution element in the hydraulic main drive system, the hydraulic pump set is usually driven by multiple hydraulic pumps to rotate the cutter head for tunneling. If the operation of the hydraulic pump set cannot be discovered and warned in time due to problems, it will cause the machine to shut down and the construction period to be delayed. Therefore, how to ensure the stable and reliable operation of the main drive hydraulic system has become the focus of the equipment operator. In order to minimize the downtime of the pump set, the preventive maintenance and fault warning system of the pump set have become an important direction. For preventive maintenance, the state monitoring of the pump station is a very important link, and the quality level of the state monitoring directly affects the accuracy of the subsequent fault warning system and the effect of preventive maintenance.

[0004] In the prior art, the monitoring method of the pump set mainly installs temperature, pressure and liquid level sensors on the pump set to measure the temperature of the hydraulic oil, the output pressure of the plunger pump and the liquid level of the hydraulic oil. However, there is a lack of monitoring of the water content in the oil, the metal particle content in the oil, the oil viscosity, the motor current, the accumulator pressure and other data, and it is impossible to display the data records and curves of the monitored quantities, and it is also impossible to analyze and realize the operation health state detection and fault warning of the pump set through the monitored data, so as to provide maintenance suggestions for the equipment operator, resulting in poor effect of preventive maintenance of the pump set. In addition, in the prior art, the monitoring of the pump set mainly reflects the parameter collection of the system, and cannot analyze and deeply learn on the basis of the existing data, so as to evaluate and judge the health state of the pump set, and further to know the health condition of the equipment, and to predict the health condition of the equipment, so as to meet the demand of intelligent control and early warning.

[0005] In view of the problem that the operation state monitoring effect of the hydraulic pump set is poor and the health condition of the hydraulic pump set cannot be predicted in the related art, no effective solution has been given at present.

[0006] Therefore, the inventor proposes a hydraulic pump set operation state monitoring method and system through years of experience and practice in the relevant industry to overcome the defects of the prior art. SUMMARY

[0007] The present application aims to provide a hydraulic pump set operation state monitoring method and system, which can monitor the real-time operation health state of the hydraulic pump set under actual operation state according to the time-varying characteristic law of performance degradation of the hydraulic pump set, and give timely warning of possible failures, thereby prolonging the normal operation time of the hydraulic pump set and improving the operation efficiency of the hydraulic pump set, facilitating timely maintenance of the hydraulic pump set.

[0008] Another object of the present application is to provide a hydraulic pump set operation state monitoring method and system, which can complete data monitoring and analysis of the operation state of the hydraulic pump set without manned operation, greatly improving the automation and intelligence.

[0009] The object of the present application can be achieved by the following scheme:

[0010] The present application provides a hydraulic pump set operation state monitoring method, which comprises the following steps:

[0011] Collecting a first health state characteristic parameter of the hydraulic pump set under standard operation state;

[0012] Establishing a performance change prediction curve corresponding to the hydraulic pump set according to the first health state characteristic parameter;

[0013] Under actual working conditions, collecting a second health state characteristic parameter of the hydraulic pump set under real-time operation state;

[0014] Comparing the second health state characteristic parameter with the corresponding first health state characteristic parameter on the performance change prediction curve to determine whether the hydraulic pump set is in a healthy operation state under actual working conditions.

[0015] In a preferred embodiment of the present application, the collection of the first health state characteristic parameter of the hydraulic pump set under standard operation state comprises:

[0016] Collecting operation data of the hydraulic pump set under standard operation state;

[0017] Extracting the first health state characteristic parameter from the operation data.

[0018] In a preferred embodiment of the present application, the first health state characteristic parameter comprises one or any combination of volumetric efficiency parameter, vibration characteristic parameter, flow parameter and oil parameter of the hydraulic pump under standard operation state.

[0019] In a preferred embodiment of the present application, the establishing of the performance change prediction curve corresponding to the hydraulic pump set comprises:

[0020] drawing a performance degradation curve of the hydraulic pump set in a standard operating state according to the first health state characteristic parameter;

[0021] trend prediction is performed on the extended form of the performance degradation curve to form the performance change prediction curve.

[0022] In a preferred embodiment of the present application, the trend prediction performed on the extended form of the performance degradation curve to form the performance change prediction curve comprises:

[0023] a plurality of groups of the performance degradation curves are combined to form a sample library;

[0024] a neural network is used to perform sample learning on the performance degradation curves in the sample library, and trend prediction is performed on the extended form of the performance degradation curve to form the performance change prediction curve.

[0025] In a preferred embodiment of the present application, the second health state characteristic parameter comprises one or any combination of a volumetric efficiency parameter, a vibration characteristic parameter, a flow parameter, and an oil parameter under an actual working condition of the hydraulic pump.

[0026] In a preferred embodiment of the present application, the comparison of the second health state characteristic parameter with the corresponding first health state characteristic parameter on the performance change prediction curve to determine whether the hydraulic pump set is in a healthy operating state under an actual working condition comprises:

[0027] a preset deviation range is set;

[0028] the second health state characteristic parameter is compared with the corresponding first health state characteristic parameter on the performance change prediction curve;

[0029] if the deviation value of the second health state characteristic parameter and the corresponding first health state characteristic parameter is within the preset deviation range, the hydraulic pump set is in a healthy operating state;

[0030] if the deviation value of the second health state characteristic parameter and the corresponding first health state characteristic parameter is outside the preset deviation range and lasts for a preset time, the hydraulic pump set is in an abnormal operating state.

[0031] In a preferred embodiment of the present application, if the hydraulic pump set is in an abnormal operating state, a warning is given.

[0032] The present application provides a hydraulic pump set operating state monitoring system, which comprises:

[0033] a first acquisition unit, configured to acquire a first health state characteristic parameter of the hydraulic pump set under a standard operation state;

[0034] a first processing unit, configured to establish a performance change prediction curve corresponding to the hydraulic pump set according to the first health state characteristic parameter;

[0035] a second acquisition unit, configured to acquire a second health state characteristic parameter of the hydraulic pump set under a real-time operation state under an actual working condition;

[0036] a second processing unit, configured to compare the second health state characteristic parameter with the first health state characteristic parameter corresponding to the performance change prediction curve to determine whether the hydraulic pump set is in a healthy operation state under the actual working condition.

[0037] In a preferred embodiment of the present application, the first acquisition unit comprises:

[0038] an acquisition module, configured to acquire operation data of the hydraulic pump set under the standard operation state;

[0039] an extraction module, configured to extract the first health state characteristic parameter from the acquired operation data.

[0040] In a preferred embodiment of the present application, the first processing unit comprises:

[0041] a performance degradation curve acquisition module, configured to draw a performance degradation curve of the hydraulic pump set under the standard operation state according to the first health state characteristic parameter;

[0042] a performance change prediction curve acquisition module, configured to perform trend prediction on an extension mode of the performance degradation curve to form the performance change prediction curve.

[0043] In a preferred embodiment of the present application, the second processing unit comprises:

[0044] a preset module, configured to preset a deviation range;

[0045] a comparison module, configured to compare the second health state characteristic parameter with the first health state characteristic parameter corresponding to the performance change prediction curve;

[0046] a first judgment module, configured to determine that the hydraulic pump set is in a healthy operation state if a deviation value of the second health state characteristic parameter and the corresponding first health state characteristic parameter is within the preset deviation range;

[0047] The second judging module is configured to determine that the hydraulic pump group is in an abnormal running state if the deviation value of the second health state characteristic parameter from the corresponding first health state characteristic parameter is outside the preset deviation range and lasts for a preset time.

[0048] In a preferred embodiment of the present application, the hydraulic pump group running state monitoring system further comprises a sensor module, a data acquisition module and a control system, the sensor module is arranged at a preset detection position of the hydraulic pump group to collect running data of the hydraulic pump group, a detection signal output end of the sensor module is connected with a detection signal receiving end of the data acquisition module, and a detection signal output end of the data acquisition module is connected with a detection signal receiving end of the control system.

[0049] In a preferred embodiment of the present application, the hydraulic pump group running state monitoring system further comprises a cloud platform, and the data acquisition module is communicatively connected with the cloud platform.

[0050] In a preferred embodiment of the present application, the data acquisition module is internally provided with a SIM card and / or a wireless network card, and the data acquisition module is communicatively connected with the cloud platform.

[0051] In a preferred embodiment of the present application, the sensor module at least comprises an oil leakage flow meter, a flushing flow meter, an oil monitoring flow meter, a radial vibration sensor, an axial vibration sensor and a pressure sensor.

[0052] As described above, the hydraulic pump group running state monitoring method and system of the present application have the following characteristics and advantages: the first health state characteristic parameter of the hydraulic pump group under a standard running state is collected; a performance change prediction curve corresponding to the hydraulic pump group is established according to the first health state characteristic parameter; the second health state characteristic parameter of the hydraulic pump group under a real-time running state is collected when the hydraulic pump group is put into an actual working condition, and whether the second health state characteristic parameter is within a preset deviation range is determined by comparing the second health state characteristic parameter with the corresponding first health state characteristic parameter on the performance change prediction curve, so as to determine whether the hydraulic pump group under the actual working condition is in a healthy running state. The present application can reduce downtime of the hydraulic pump group caused by failure, prolong the normal running time of the hydraulic pump group, improve the running efficiency of the hydraulic pump group, facilitate timely maintenance of the hydraulic pump group, and automatically and intelligently monitor and analyze the running state data of the hydraulic pump group without manual attendance. BRIEF DESCRIPTION OF DRAWINGS

[0053] The following drawings are merely intended to schematically illustrate and explain the present application, and do not limit the scope of the present application.

[0054] Wherein:

[0055] Figure 1 : is one of the flow chart of the hydraulic pump set operation state monitoring method of the present application.

[0056] Figure 2 : is the second flow chart of the hydraulic pump set operation state monitoring method of the present application.

[0057] Figure 3 : is the third flow chart of the hydraulic pump set operation state monitoring method of the present application.

[0058] Figure 4 : is the fourth flow chart of the hydraulic pump set operation state monitoring method of the present application.

[0059] Figure 5 : is the fifth flow chart of the hydraulic pump set operation state monitoring method of the present application.

[0060] Figure 6 : is one of the structural block diagram of the hydraulic pump set operation state monitoring system of the present application.

[0061] Figure 7 : is the second structural block diagram of the hydraulic pump set operation state monitoring system of the present application.

[0062] Figure 8 : is the third structural block diagram of the hydraulic pump set operation state monitoring system of the present application.

[0063] Figure 9 : is the fourth structural block diagram of the hydraulic pump set operation state monitoring system of the present application.

[0064] Figure 10 : is the fifth structural block diagram of the hydraulic pump set operation state monitoring system of the present application.

[0065] Figure 11 : is the setting position schematic diagram of the sensor module in the hydraulic pump set operation state monitoring system of the present application.

[0066] The figure reference in the present application is:

[0067] 10, first acquisition unit; 101, acquisition module;

[0068] 102, extraction module; 20, first processing unit;

[0069] 201, performance degradation curve acquisition module; 202, performance change prediction curve acquisition module;

[0070] 30, second acquisition unit; 40, second processing unit;

[0071] 401, preset module; 402, comparison module;

[0072] 403, first judging module; 404, second judging module;

[0073] 50, sensor module; 501, oil leakage flow meter;

[0074] 502, flushing flow meter; 503, oil monitoring flow meter;

[0075] 504, radial vibration sensor; 505, axial vibration sensor;

[0076] 506, pressure sensor; 60, data acquisition module;

[0077] 70, control system; 80, cloud platform. DETAILED DESCRIPTION

[0078] In order to have a clearer understanding of the technical features, objectives and effects of the present application, the specific embodiments of the present application will be described with reference to the accompanying drawings.

[0079] Embodiment one

[0080] As shown in the drawings, the present application provides a hydraulic pump set operating state monitoring method, which comprises the following steps: Figure 1 Step S1: collecting first health state characteristic parameters of the hydraulic pump set under standard operating state; wherein the standard operating state is that the hydraulic pump set is not affected by the external working environment, and only the loss under the normal working state of itself is considered.

[0081] Further, the first health state characteristic parameters can also be fitted according to the long-term operating state data and test data of the hydraulic pump set, and different types of hydraulic pump sets correspond to different first health state characteristic parameters.

[0082] In an optional embodiment of the present application, as shown in the drawings, step S1 comprises:

[0083] Figure 2 Step S101: collecting operating data of the hydraulic pump set under the standard operating state;

[0084] Step S102: extracting the first health state characteristic parameters from the collected operating data. Wherein the first health state characteristic parameters include but are not limited to one or any combination of the volumetric efficiency parameters, vibration characteristic parameters, flow parameters and oil parameters under the standard operating state of the hydraulic pump. Wherein the volumetric efficiency parameter is used as the main index parameter, and the vibration characteristic parameter, flow parameter and oil parameter are used as the auxiliary index parameter.

[0085] Step S102: extracting the first health state characteristic parameters from the collected operating data. Wherein the first health state characteristic parameters include but are not limited to one or any combination of the volumetric efficiency parameters, vibration characteristic parameters, flow parameters and oil parameters under the standard operating state of the hydraulic pump. Wherein the volumetric efficiency parameter is used as the main index parameter, and the vibration characteristic parameter, flow parameter and oil parameter are used as the auxiliary index parameter. Step S102: extracting the first health state characteristic parameters from the collected operating data. Wherein the first health state characteristic parameters include but are not limited to one or any combination of the volumetric efficiency parameters, vibration characteristic parameters, flow parameters and oil parameters under the standard operating state of the hydraulic pump. Wherein the volumetric efficiency parameter is used as the main index parameter, and the vibration characteristic parameter, flow parameter and oil parameter are used as the auxiliary index parameter.

[0086] Further, the vibration characteristic parameter at least includes axial vibration data and radial vibration data of the hydraulic pump set; the flow parameter at least includes leakage flow data and flushing flow data of the hydraulic pump set; and the oil parameter at least includes moisture content data, oil viscosity data and metal particle content data in the oil.

[0087] Step S2: establishing a performance change prediction curve corresponding to the hydraulic pump set according to the first health state characteristic parameter;

[0088] In an optional embodiment of the present application, as shown in Figure 3 Step S2 includes:

[0089] Step S201: collecting the first health state characteristic parameter corresponding to different time points, and drawing a performance degradation curve of the hydraulic pump set in a standard operating state (a curve about the relationship between the first health state characteristic parameter of the hydraulic pump set and time) according to the first health state characteristic parameter and the corresponding time point.

[0090] Step S202: performing trend prediction on the extension form of the performance degradation curve to form the performance change prediction curve.

[0091] Further, as shown in Figure 4 Step S202 includes:

[0092] Step S2021: grouping multiple performance degradation curves to form a sample library.

[0093] Step S2022: performing sample learning and training on the performance degradation curve in the sample library by using a neural network, and performing trend prediction on the extension form of the performance degradation curve (the trend prediction can also be performed according to the change of the first health state characteristic parameter at different time points) to form the performance change prediction curve.

[0094] Step S3: collecting the second health state characteristic parameter of the hydraulic pump set in a real-time operating state under actual working conditions. The second health state characteristic parameter includes but is not limited to one or any combination of the volumetric efficiency parameter, the vibration characteristic parameter, the flow parameter and the oil parameter of the hydraulic pump under actual working conditions. The volumetric efficiency parameter is used as a main index parameter, and the vibration characteristic parameter, the flow parameter and the oil parameter are used as auxiliary index parameters.

[0095] Further, the vibration characteristic parameter at least includes axial vibration data and radial vibration data of the hydraulic pump set; the flow parameter at least includes leakage flow data and flushing flow data of the hydraulic pump set; and the oil parameter at least includes moisture content data, oil viscosity data and metal particle content data in the oil.

[0096] Step S4: comparing the second health state characteristic parameter with the corresponding first health state characteristic parameter on the performance change prediction curve to determine whether the hydraulic pump set is in a healthy operating state under the actual working condition.

[0097] In an optional embodiment of the present application, as shown in Figure 5 Step S4 includes:

[0098] Step S401: presetting a deviation range Δσ1 between the second health state characteristic parameter and the corresponding first health state characteristic parameter on the performance change prediction curve (the Δσ1 can be set according to the actual working condition of the hydraulic pump set);

[0099] Step S402: comparing the second health state characteristic parameter with the corresponding first health state characteristic parameter on the performance change prediction curve to obtain an actual deviation value σ1;

[0100] Step S403: if the deviation value of the second health state characteristic parameter and the corresponding first health state characteristic parameter is within the preset deviation range (i.e. σ1 < Δσ1), the hydraulic pump set is in a healthy operating state;

[0101] Step S404: if the deviation value of the second health state characteristic parameter and the corresponding first health state characteristic parameter is outside the preset deviation range (i.e. σ1 > Δσ1), and the duration of the deviation value of the second health state characteristic parameter and the corresponding first health state characteristic parameter being outside the preset deviation range reaches a preset time Δt1 (the Δt1 can be set according to the actual working condition of the hydraulic pump set), the hydraulic pump set is in an abnormal operating state, and a warning needs to be given (an alarm signal can be sent in multiple ways such as sound, light, image display, etc.), reminding the staff to check and maintain the hydraulic pump set.

[0102] Specifically, the vibration data (axial vibration data and / or radial vibration data) of the hydraulic pump set is also monitored, and a deviation range Δσ2 (Δσ2 can be set according to the actual working condition of the hydraulic pump set) between the actual vibration data of the hydraulic pump set and the corresponding vibration data on the performance change prediction curve is preset, the actual vibration data is compared with the corresponding vibration data on the performance change prediction curve, the actual deviation value σ2 is obtained, if the deviation value between the actual vibration data and the corresponding vibration data on the performance change prediction curve is within the preset deviation range (i.e. σ2 < Δσ2), the hydraulic pump set is in a healthy running state; if the deviation value between the actual vibration data and the corresponding vibration data on the performance change prediction curve is outside the preset deviation range (i.e. σ2 > Δσ2), and the duration of the deviation value of the second health state characteristic parameter and the corresponding first health state characteristic parameter being outside the preset deviation range reaches a preset time Δt2 (Δt2 can be set according to the actual working condition of the hydraulic pump set, which can be the same as or different from Δt1), the hydraulic pump set is in an abnormal vibration running state, and needs to be warned to remind the staff to check and maintain the hydraulic pump set.

[0103] The hydraulic pump set running state monitoring method has the characteristics and advantages that:

[0104] I. The hydraulic pump set running state monitoring method can monitor and predict the running health state of the hydraulic pump set in the actual running state according to the performance degradation time-varying characteristic law of the hydraulic pump set, can reduce the downtime caused by failure of the hydraulic pump set, prolong the normal running time of the hydraulic pump set, improve the running efficiency of the hydraulic pump set, facilitate timely maintenance of the hydraulic pump set, and can complete data monitoring and analysis of the running state of the hydraulic pump set without manual attendance, and the automation and intelligence degree is greatly improved.

[0105] II. The hydraulic pump set running state monitoring method can greatly prolong the service life of the hydraulic pump set, ensure long-period stable running of the hydraulic pump set, and effectively save equipment cost through intelligent maintenance and failure prediction of the hydraulic pump set.

[0106] Embodiment II

[0107] As shown in Figure 6 The present application provides a hydraulic pump set running state monitoring system, which comprises a first acquisition unit 10, a first processing unit 20, a second acquisition unit 30 and a second processing unit 40, wherein:

[0108] The first acquisition unit 10 is configured to acquire a first health state characteristic parameter of the hydraulic pump set in a standard operation state, wherein the standard operation state refers to a state in which the hydraulic pump set is not affected by an external working environment and only considers a loss in a normal working state.

[0109] The first processing unit 20 is configured to establish a performance change prediction curve of the hydraulic pump set according to the first health state characteristic parameter.

[0110] The second acquisition unit 30 is configured to acquire a second health state characteristic parameter of the hydraulic pump set in a real-time operation state in an actual working condition, wherein the second health state characteristic parameter includes but is not limited to one or any combination of a volumetric efficiency parameter, a vibration characteristic parameter, a flow parameter and an oil parameter of the hydraulic pump in the actual working condition.

[0111] The second processing unit 40 is configured to compare the second health state characteristic parameter with the corresponding first health state characteristic parameter on the performance change prediction curve to determine whether the hydraulic pump set is in a healthy operation state in the actual working condition.

[0112] In an optional embodiment of the present application, as shown in Figure 7 The first acquisition unit 10 includes an acquisition module 101 and an extraction module 102, and wherein:

[0113] The acquisition module 101 is configured to acquire operation data of the hydraulic pump set in the standard operation state.

[0114] The extraction module 102 is configured to extract the first health state characteristic parameter from the acquired operation data.

[0115] In an optional embodiment of the present application, as shown in Figure 8 The first processing unit 20 includes a performance degradation curve acquisition module 201 and a performance change prediction curve acquisition module 202, and wherein:

[0116] The performance degradation curve acquisition module 201 is configured to acquire the first health state characteristic parameter corresponding to different time points and draw a performance degradation curve (a curve about the relationship between the first health state characteristic parameter of the hydraulic pump set and time) of the hydraulic pump set in the standard operation state according to the first health state characteristic parameter and the corresponding time points.

[0117] The performance change prediction curve acquisition module 202 is configured to predict the trend of the extended form of the performance degradation curve to form a performance change prediction curve. Specifically, a plurality of performance degradation curves can be grouped to form a sample library, and a neural network can be used to sample and train the performance degradation curves in the sample library, and the trend of the extended form of the performance degradation curve can be predicted (the trend can also be predicted according to the change of the first health state characteristic parameter at different time points) to form a performance change prediction curve.

[0118] In an optional embodiment of the present application, as shown in Figure 9 The second processing unit 40 includes a preset module 401, a comparison module 402, a first judgment module 403, and a second judgment module 404, wherein:

[0119] The preset module 401 is configured to preset a deviation range Δσ1 between the second health state characteristic parameter and the corresponding first health state characteristic parameter on the performance change prediction curve (the deviation range Δσ1 can be set according to the actual working condition of the hydraulic pump set).

[0120] The comparison module 402 is configured to compare the second health state characteristic parameter with the corresponding first health state characteristic parameter on the performance change prediction curve to obtain an actual deviation value σ1.

[0121] The first judgment module 403 is configured to determine that the hydraulic pump set is in a healthy running state if the deviation value between the second health state characteristic parameter and the corresponding first health state characteristic parameter is within the preset deviation range (i.e., σ1 < Δσ1).

[0122] The second judgment module 404 is configured to determine that the hydraulic pump set is in an abnormal running state and needs to be prewarned to remind the staff to check and maintain the hydraulic pump set if the deviation value between the second health state characteristic parameter and the corresponding first health state characteristic parameter is outside the preset deviation range (i.e., σ1 > Δσ1) and the duration of the deviation value between the second health state characteristic parameter and the corresponding first health state characteristic parameter being outside the preset deviation range reaches a preset time Δt1 (the preset time Δt1 can be set according to the actual working condition of the hydraulic pump set).

[0123] In an optional embodiment of the present application, as shown in Figure 10As shown, the hydraulic pump set operating state monitoring system further comprises a sensor module 50, a data acquisition module 60 and a control system 70. The sensor module 50 is arranged at a preset detection position of the hydraulic pump set to collect operating data corresponding to different positions of the hydraulic pump set through multiple sensors of the sensor module 50. The detection signal output end of the sensor module 50 is connected with the detection signal receiving end of the data acquisition module 60, and the detection signal output end of the data acquisition module 60 is connected with the detection signal receiving end of the control system 70. The sensor module 50 sends the collected detection signals to the data acquisition module 60 in the form of analog signals, the data acquisition module 60 feeds back the collected analog signals to the control system 70, and the control system 70 analyzes and predicts whether the hydraulic pump set is in a healthy operating state according to the received signals and records and classifies the data.

[0124] Further, the control system 70 can be, but is not limited to, a PLC controller.

[0125] Further, as shown in Figure 10 The hydraulic pump set operating state monitoring system further comprises a cloud platform 80, and the data acquisition module 60 is in communication connection with the cloud platform 80. The cloud platform 80 can be arranged on a mobile terminal and / or a computer terminal. The cloud platform 80 can be used to remotely configure and control the data acquisition module 60 and the control system 70, and the alarm value of a variable can be set on the cloud platform 80. Information can be reminded on the mobile terminal and / or the computer terminal in an alarm state.

[0126] Further, the data acquisition module 60 is built-in with a SIM card and / or a wireless network card, and the data acquisition module is in communication connection with the cloud platform. The data acquisition module 60 is powered by a 24V power adapter, and a network connection and communication are established between the data acquisition module 60 and the cloud platform 80 through the SIM card and / or the wireless network card.

[0127] Further, as shown in Figure 11 The sensor module 50 at least comprises an oil leakage flowmeter 501, a flushing flowmeter 502, an oil monitoring flowmeter 503, a radial vibration sensor 504, an axial vibration sensor 505 and a pressure sensor 506. The oil leakage flowmeter 501 can be arranged at the oil leakage port of the hydraulic pump, the flushing flowmeter 502 can be arranged at the position where the flushing port of the pump shell is connected with a pipeline, the oil monitoring flowmeter 503 can be arranged at the outlet pipeline of the hydraulic pump, the radial vibration sensor 504 can be arranged on the shell of the hydraulic pump and along the radial direction of the cylinder body, the radial vibration sensor 504 can also be arranged on the reversing valve of the hydraulic pump and along the radial direction of the reversing valve, the axial vibration sensor 505 can be arranged on the shell of the hydraulic pump and along the axial direction of the cylinder body, the axial vibration sensor 505 can also be arranged on the reversing valve of the hydraulic pump and along the axial direction of the reversing valve, and the pressure sensor 506 can be arranged at the inlet and outlet pipelines of the hydraulic pump.

[0128] The hydraulic pump group operation state monitoring system has the following characteristics and advantages:

[0129] 1. The hydraulic pump group operation state monitoring system is helpful for the effective implementation of the preventive maintenance of the hydraulic pump group of the heading machine, thereby reducing the downtime caused by the failure of the hydraulic pump group, and reducing the construction cost and the construction period cost.

[0130] 2. The hydraulic pump group operation state monitoring system can realize the long-life and long-period stable operation of the pump group to a great extent through intelligent maintenance, and can effectively save the equipment cost.

[0131] The above merely illustrates the specific embodiments of the present application, and is not intended to limit the scope of the present application. Any equivalent changes and modifications made by any person skilled in the art without departing from the concept and principle of the present application shall fall within the scope of the present application.

Claims

1. A hydraulic pump set operation state monitoring method for monitoring the operation state of a hydraulic pump set of a main drive of a tunneling machine, characterized by, The hydraulic pump set operation state monitoring method comprises the following steps: Collecting first health state characteristic parameters of the hydraulic pump set under standard operation state; Collecting operation data of the hydraulic pump set under standard operation state; Extracting the first health state characteristic parameters from the operation data collected, wherein the first health state characteristic parameters comprise one or any combination of volumetric efficiency parameters, vibration characteristic parameters, flow parameters and oil parameters of the hydraulic pump under standard operation state; Establishing a performance change prediction curve corresponding to the hydraulic pump set according to the first health state characteristic parameters; Drawing a performance degradation curve of the hydraulic pump set under standard operation state according to the first health state characteristic parameters; Trend prediction of the extension form of the performance degradation curve to form the performance change prediction curve; Forming a sample library by grouping multiple performance degradation curves; Sample learning of the performance degradation curve in the sample library by using neural network, and trend prediction of the extension form of the performance degradation curve or the change of the first health state characteristic parameters at different time points to form the performance change prediction curve; Collecting second health state characteristic parameters of the hydraulic pump set under real-time operation state under actual working condition, wherein the second health state characteristic parameters comprise one or any combination of volumetric efficiency parameters, vibration characteristic parameters, flow parameters and oil parameters of the hydraulic pump under actual working condition; Comparing the second health state characteristic parameters with the corresponding first health state characteristic parameters on the performance change prediction curve to determine whether the hydraulic pump set is in healthy operation state under actual working condition; Collecting the corresponding operation data of the hydraulic pump set at different positions by multiple sensors of a sensor module, wherein the sensor module at least comprises an oil leakage flow meter, a flushing flow meter, an oil monitoring flow meter, a radial vibration sensor, an axial vibration sensor and a pressure sensor, the oil leakage flow meter is arranged at the oil leakage port of the hydraulic pump, the flushing flow meter is arranged at the position where the flushing port of the pump shell is connected with the pipeline, the oil monitoring flow meter is arranged at the outlet pipeline of the hydraulic pump, the radial vibration sensor is arranged on the shell of the hydraulic pump and along the radial direction of the cylinder body and / or arranged on the reversing valve of the hydraulic pump and along the radial direction of the reversing valve, the axial vibration sensor is arranged on the pump shell of the hydraulic pump and along the axial direction of the cylinder body and / or arranged on the reversing valve of the hydraulic pump and along the axial direction of the reversing valve, and the pressure sensor is arranged at the inlet and outlet pipelines of the hydraulic pump.

2. The hydraulic pump set operating condition monitoring method of claim 1, wherein The comparison of the second health state characteristic parameters with the corresponding first health state characteristic parameters on the performance change prediction curve to determine whether the hydraulic pump set is in healthy operation state under actual working condition comprises: Predefining a deviation range; Comparing the second health state characteristic parameters with the corresponding first health state characteristic parameters on the performance change prediction curve; If the deviation value of the second health state characteristic parameters and the corresponding first health state characteristic parameters is within the pre-defined deviation range, the hydraulic pump set is in healthy operation state. If the deviation value of the second health state characteristic parameter from the corresponding first health state characteristic parameter is outside the preset deviation range and lasts for a preset time, the hydraulic pump set is in an abnormal running state.

3. The hydraulic pump set operating condition monitoring method of claim 2, wherein, If the hydraulic pump set is in an abnormal running state, a warning is given.

4. A hydraulic pump set operation state monitoring system that monitors the operation state of a hydraulic pump set using the hydraulic pump set operation state monitoring method according to any one of claims 1 to 3, characterized by The hydraulic pump set running state monitoring system comprises: A first acquisition unit for acquiring a first health state characteristic parameter of the hydraulic pump set in a standard running state; An acquisition module for acquiring running data of the hydraulic pump set in the standard running state; An extraction module for extracting the first health state characteristic parameter from the acquired running data; A first processing unit for establishing a performance change prediction curve of the hydraulic pump set according to the first health state characteristic parameter; The first processing unit comprises: A performance degradation curve acquisition module for drawing a performance degradation curve of the hydraulic pump set in the standard running state according to the first health state characteristic parameter; A performance change prediction curve acquisition module for trend prediction on the extension form of the performance degradation curve to form the performance change prediction curve; A second acquisition unit for acquiring a second health state characteristic parameter of the hydraulic pump set in a real-time running state under actual working conditions; A second processing unit for comparing the second health state characteristic parameter with the corresponding first health state characteristic parameter on the performance change prediction curve to determine whether the hydraulic pump set is in a healthy running state under actual working conditions; The hydraulic pump set running state monitoring system further comprises a sensor module, a data acquisition module and a control system, the sensor module is arranged at a preset detection position of the hydraulic pump set to acquire running data of the hydraulic pump set, a detection signal output end of the sensor module is connected with a detection signal receiving end of the data acquisition module, and a detection signal output end of the data acquisition module is connected with a detection signal receiving end of the control system; The sensor module at least comprises an oil leakage flowmeter, a flushing flowmeter, an oil monitoring flowmeter, a radial vibration sensor, an axial vibration sensor and a pressure sensor, the oil leakage flowmeter is arranged at an oil leakage port of a housing of the hydraulic pump, the flushing flowmeter is arranged at a position where a flushing port of a pump housing is connected with a pipeline, the oil monitoring flowmeter is arranged at an outlet pipeline of the hydraulic pump, the radial vibration sensor is arranged on the housing of the hydraulic pump and along the radial direction of a cylinder body and / or is arranged on a reversing valve in the hydraulic pump and along the radial direction of the reversing valve, the axial vibration sensor is arranged on the housing of the hydraulic pump and along the axial direction of the cylinder body and / or is arranged on the reversing valve in the hydraulic pump and along the axial direction of the reversing valve, and the pressure sensor is arranged at an inlet and outlet pipeline of the hydraulic pump.

5. The hydraulic pump set operating condition monitoring system as set forth in claim 4, wherein, The second processing unit comprises: A preset module for presetting a deviation range; A comparison module for comparing the second health state characteristic parameter with the corresponding first health state characteristic parameter on the performance change prediction curve; The first judging module is configured to determine that the hydraulic pump group is in a healthy running state if the deviation value of the second health state characteristic parameter from the corresponding first health state characteristic parameter is within the preset deviation range. The second judging module is configured to determine that the hydraulic pump group is in an abnormal running state if the deviation value of the second health state characteristic parameter from the corresponding first health state characteristic parameter is outside the preset deviation range and lasts for a preset time.

6. The hydraulic pump set operating condition monitoring system as set forth in claim 4, wherein The hydraulic pump group running state monitoring system further comprises a cloud platform, and the data acquisition module is in communication connection with the cloud platform.

7. The hydraulic pump set operating condition monitoring system as set forth in claim 6, wherein The data acquisition module is internally provided with a SIM card and / or a wireless network card, and the data acquisition module is in communication connection with the cloud platform.

Images