CN111457958A - Port machine equipment situation monitoring method and device, computer equipment and storage medium - Google Patents
Port machine equipment situation monitoring method and device, computer equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the invention discloses a method for monitoring the situation of port equipment, which comprises the steps of acquiring monitoring data corresponding to each mechanical component in the port equipment in real time through a preset sensor; acquiring preset index data of each mechanical component, and judging the running state of each mechanical component according to the index data and the monitoring data, wherein the running state is classified into an abnormal state or a normal state; analyzing the monitoring data corresponding to the mechanical component with the abnormal operation state to determine the abnormal information of the mechanical component; and establishing a situation map according to the abnormal information, and pushing the situation map to the monitoring display equipment. The method can track the running state of the port machine equipment in real time, improve the monitoring efficiency of the port machine equipment, avoid safety accidents and unplanned long-time halt of the port machine equipment, and improve the operation and running efficiency of the port machine equipment. In addition, a port machine equipment situation monitoring device, computer equipment and a storage medium are also provided.
Description
Technical Field
The invention relates to the technical field of computer data processing, in particular to a method and a device for monitoring the situation of port machinery equipment, computer equipment and a storage medium.
Background
With the change of wharf operation environment (less and less labor force, increased labor cost, improved operation efficiency, reduced maintenance time and improved automation degree of equipment, such as remote control and full automation wharfs), the objective requirement is to change the original passive maintenance mode into preventive maintenance and active maintenance mode, so as to reduce maintenance cost and improve maintenance benefit. The conventional maintenance mode is to perform equipment inspection periodically according to the operation cycle of the equipment, and the inspection is generally performed in the form that a maintenance worker goes to the site to visually inspect or inspect the equipment by means of related tools. Such inspection and repair is inefficient and cannot be timely serviced in the event of equipment failure.
That is to say, the user more and more pays attention to the control to important mechanical parts, avoids these spare part failures to bring long-time shutdown and the adverse effect to the operation, and the realization of preventive maintenance just needs to adopt scientific, accurate reliable means to carry out real-time on-line monitoring to important mechanical parts, in time masters equipment running state, consequently, needs provide a port machine equipment situation monitoring scheme urgently to guarantee the normal operating of port machine equipment, improve port machine operating efficiency.
Disclosure of Invention
In view of the above, it is necessary to provide a method and an apparatus for monitoring a situation of a port machine, a computer device, and a storage medium, which can improve the operation efficiency of the port machine.
A method for monitoring the situation of port machinery equipment is characterized by comprising the following steps:
acquiring monitoring data corresponding to each mechanical component in port machinery equipment in real time through a preset sensor;
acquiring preset index data of each mechanical component, and judging the running state of each mechanical component according to the index data and the monitoring data, wherein the running state is classified into an abnormal state or a normal state;
analyzing monitoring data corresponding to a mechanical component with an abnormal operation state to determine abnormal information of the mechanical component;
and establishing a situation map according to the abnormal information, and pushing the situation map to monitoring display equipment.
A port machinery equipment situation monitoring device, the device includes:
the first acquisition module is used for acquiring monitoring data corresponding to each mechanical component in the port machinery equipment in real time through a preset sensor;
the judging module is used for acquiring preset index data of each mechanical component and judging the running state of each mechanical component according to the index data and the monitoring data, wherein the running state is divided into an abnormal state or a normal state;
the analysis module is used for analyzing the monitoring data corresponding to the mechanical component with the abnormal operation state to determine the abnormal information of the mechanical component;
and the display module is used for establishing a situation map according to the abnormal information and pushing the situation map to the monitoring display equipment.
A computer device comprising a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of:
acquiring monitoring data corresponding to each mechanical component in port machinery equipment in real time through a preset sensor;
acquiring preset index data of each mechanical component, and judging the running state of each mechanical component according to the index data and the monitoring data, wherein the running state is classified into an abnormal state or a normal state;
analyzing monitoring data corresponding to a mechanical component with an abnormal operation state to determine abnormal information of the mechanical component;
and establishing a situation map according to the abnormal information, and pushing the situation map to monitoring display equipment.
A computer-readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the steps of:
acquiring monitoring data corresponding to each mechanical component in port machinery equipment in real time through a preset sensor;
acquiring preset index data of each mechanical component, and judging the running state of each mechanical component according to the index data and the monitoring data, wherein the running state is classified into an abnormal state or a normal state;
analyzing monitoring data corresponding to a mechanical component with an abnormal operation state to determine abnormal information of the mechanical component;
and establishing a situation map according to the abnormal information, and pushing the situation map to monitoring display equipment.
The port machine equipment situation monitoring method comprises the steps of acquiring monitoring data corresponding to each mechanical component in port machine equipment in real time through a preset sensor; acquiring preset index data of each mechanical component, and judging the running state of each mechanical component according to the index data and the monitoring data, wherein the running state is classified into an abnormal state or a normal state; analyzing the monitoring data corresponding to the mechanical component with the abnormal operation state to determine the abnormal information of the mechanical component; and establishing a situation map according to the abnormal information, and pushing the situation map to the monitoring display equipment. The method can track the running state of the port machine equipment in real time, improve the monitoring efficiency of the port machine equipment, avoid safety accidents and unplanned long-time halt of the port machine equipment, and improve the operation and running efficiency of the port machine equipment.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Wherein:
FIG. 1 is a flow diagram of a method for monitoring a situation of a port machinery equipment in one embodiment;
FIG. 2 is a flow diagram of a method for determining an operating condition of various mechanical components in one embodiment;
FIG. 3 is a flow diagram of a method for determining anomaly information for a mechanical component in one embodiment;
FIG. 4 is a flowchart of a method for monitoring a situation of a port machinery equipment in another embodiment;
FIG. 5 is a flowchart of a method for monitoring a situation of a port machinery equipment in yet another embodiment;
FIG. 6 is a flow chart of a method for monitoring a situation of a port machinery equipment in yet another embodiment;
FIG. 7 is a flow diagram of a method for predicting a trend of a fault in a port machinery device in one embodiment;
FIG. 8 is a block diagram of a device for monitoring a situation of a port machinery in an embodiment;
FIG. 9 is a block diagram of a computer device in one embodiment.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In one embodiment, as shown in FIG. 1, a port machinery situation monitoring method is provided, which is applied to a port facility. The method for monitoring the situation of the port machinery equipment specifically comprises the following steps:
and step 102, acquiring monitoring data corresponding to each mechanical component in the port machinery equipment in real time through a preset sensor.
The port machine equipment refers to important mechanical equipment of a dock or a port, and the mechanical equipment comprises a plurality of mechanical components, such as a lifting mechanism, a trolley mechanism, a pitching mechanism, a cart mechanism and the like. The monitoring data refers to signal data of the mechanical component during operation, such as signals of vibration, rotating speed, temperature and the like. Specifically, the monitoring data of each mechanical component may be collected in real time through a preset sensor, where the preset sensor may be an acceleration sensor, a speed sensor, a displacement sensor, or the like.
And 104, acquiring preset index data of each mechanical component, and judging the running state of each mechanical component according to the index data and the monitoring data, wherein the running state is classified into an abnormal state or a normal state.
The preset index data refers to better monitoring data when the corresponding mechanical component works normally, and is used as a basis for measuring whether the running state of the mechanical component is normal or not. Specifically, according to the model and the parameters of each mechanical component, corresponding index data are configured and stored in the database, so that the preset index data of the port machine system can be searched from the database, the monitoring data is compared with the index data of the corresponding mechanical component, and the running state of each mechanical component is judged according to the comparison result. Further, the index data in this embodiment also supports updating, and the specific implementation manner is as follows: according to the change condition of the running state and the monitoring data of the mechanical component within a period of time, the index data is updated by utilizing the system import and export function, so that the condition that the monitoring data and the running state of the mechanical component can change along with the change of the working duration of the mechanical component is adapted, and the accuracy of judging the running state of the mechanical component is further improved.
And 106, analyzing the monitoring data corresponding to the mechanical component with the abnormal operation state to determine the abnormal information of the mechanical component.
The abnormal information refers to the type, location, severity, etc. of the failure of the mechanical component. Specifically, in order to ensure the assembling operation of the port machine equipment, it is necessary to analyze a mechanical component in an abnormal operating state, that is, after the monitored data collected in real time is converted, data analysis is performed by using relevant tools such as time domain waveform, frequency spectrum and envelope demodulation, and abnormal information is determined according to the analysis result, so that information such as specific fault, part and reason of the port machine equipment is determined, so that diagnosis or alarm processing can be performed according to the abnormal information subsequently, and the operating efficiency of the port machine equipment is improved.
And step 108, establishing a situation map according to the abnormal information, and pushing the situation map to the monitoring display equipment.
The situation map is a graph used for displaying the abnormal state change trend of each mechanical component, is used for realizing visualization of port machinery equipment monitoring, and improves the convenience of monitoring the port machinery equipment. Specifically, the abnormal information of each mechanical component is analyzed and counted to form a situation map, and the situation map is pushed to a monitoring display device (such as a display screen) in a network protocol mode. According to the method, the abnormal information of the port machine equipment can be visually displayed by establishing the situation map, the running state of the port machine equipment is tracked in real time, and the monitoring efficiency of the port machine equipment is improved. Furthermore, the fault information can be pre-judged and predicted according to the change trend of the situation map, so that maintenance personnel can conveniently make a preventive maintenance strategy in advance, safety accidents of port machinery equipment and unplanned long-time shutdown are avoided, and the operation and running efficiency of the port machinery equipment are improved.
According to the method for monitoring the situation of the port machine equipment, monitoring data corresponding to each mechanical component in the port machine equipment are acquired in real time through a preset sensor; acquiring preset index data of each mechanical component, and judging the running state of each mechanical component according to the index data and the monitoring data, wherein the running state is classified into an abnormal state or a normal state; analyzing the monitoring data corresponding to the mechanical component with the abnormal operation state to determine the abnormal information of the mechanical component; and establishing a situation map according to the abnormal information, and pushing the situation map to the monitoring display equipment. The method can track the running state of the port machine equipment in real time, improve the monitoring efficiency of the port machine equipment, avoid safety accidents and unplanned long-time halt of the port machine equipment, and improve the operation and running efficiency of the port machine equipment.
As shown in fig. 2, in one embodiment, acquiring index data of each mechanical component, and determining an operation state of each mechanical component according to the index data and the monitoring data includes:
104A, respectively carrying out waveform transformation processing on the monitoring data corresponding to each mechanical component, and determining the vibration characteristic value of each mechanical component;
step 104C, when the difference value is within the preset threshold value range, judging that the running state of the corresponding mechanical component is a normal state;
and step 104D, when the difference value is not within the preset threshold value range, judging that the running state of the corresponding mechanical component is an abnormal state.
The waveform transformation processing is a processing mode for converting the signal data into a vibration waveform diagram, a vibration characteristic value of a corresponding mechanical component can be determined according to the vibration waveform diagram, the vibration characteristic value can reflect the characteristic of a vibration signal, and the vibration characteristic value can include a waveform characteristic value, a pulse characteristic value, a kurtosis characteristic value, a skewness characteristic value and/or a margin characteristic value corresponding to the vibration waveform diagram. Then respectively calculating the difference value between the vibration characteristic value of each mechanical component and corresponding preset index data; and then, comparing the difference value with a preset threshold range, and judging the running state of the mechanical component according to the comparison result. In this embodiment, the signal characteristics of the mechanical component are better represented by converting the monitoring data into the vibration characteristic values, and the signal characteristics can reflect the operation information of the mechanical component and are analyzed based on the signal characteristics, so that the accuracy of judging the operation state is improved.
As shown in fig. 3, in an embodiment, analyzing the monitoring data corresponding to the abnormal operation state to determine the abnormal information of the mechanical component includes:
and step 106C, determining the fault type of the mechanical component and the corresponding fault position as abnormal information according to the defect characteristic frequency.
The defect characteristic frequency refers to the working frequency of the mechanical component in the presence of a fault. The fault positions can comprise a motor measuring point, a gear box measuring point, a winding drum measuring point, a pulley measuring point and the like, and can be judged according to the equipment position acquired by the signal and the corresponding waveform characteristic value. The failure type of the mechanical component may be: bearing faults, looseness (e.g. foundation looseness, bearing looseness, coupling faults), stator faults (e.g. stator winding looseness), rotor faults (e.g. rotor eccentricity, rotor cage bar looseness, rotor cage bar breakage), unbalance (rotor unbalance) and misalignment, gear faults (e.g. broken teeth, tooth flank wear and spalling present) or bearing faults (e.g. caused by bearing outer ring, inner ring, rolling element or cage damage), reel faults (e.g. reel deformation) or bearing faults. Specifically, Fourier transformation is carried out on the vibration characteristic value, a fundamental frequency obtained after transformation is extracted, the defect characteristic frequency is determined according to the component amplitude of the fundamental frequency, and the abnormal information of the mechanical component can be determined according to the mapping table of the abnormal information of the mechanical component corresponding to the defect characteristic frequency and the defect characteristic frequency.
As shown in fig. 4, in an embodiment, after establishing a situation map according to the anomaly information and pushing the situation map to the monitoring display device, the method further includes:
and step 114, determining the fault degree grade of the mechanical component according to the difference value and the fault degree grade table.
In this embodiment, first, the fault type and the corresponding fault location of each mechanical component are extracted from the situation map, and then the fault degree grade of the mechanical component, that is, the fault severity of the mechanical component, is determined according to the mapping relationship between the difference calculated in step 114 and the corresponding fault degree grade obtained from the database, so that corresponding maintenance strategies are formulated for the mechanical components with different fault degree grades in the following process, and the normal operation of the port machinery equipment is ensured.
As shown in fig. 5, in an embodiment, after determining the failure level of the mechanical component according to the magnitude of the difference and the failure level table, the method further includes:
The diagnosis frequency refers to a vibration frequency which can ensure normal operation of the mechanical component. Specifically, according to the fault degree grade, the adjustment direction (increase or decrease) and the adjustment amplitude of the defect characteristic frequency are determined, the diagnosis frequency is obtained, and the frequency of the mechanical component is adjusted to the diagnosis frequency, so that the purpose of self-diagnosis processing is achieved. In the embodiment, the frequency of the mechanical component is adjusted to the diagnosis frequency to perform self-diagnosis processing, so that the intelligent degree of port machinery equipment maintenance is improved.
As shown in fig. 6, in an embodiment, after the creating a situation map according to the abnormal information and pushing the situation map to the monitoring display device, the method further includes:
and step 124, analyzing the overall situation map, and predicting the fault trend of the port machinery equipment.
In the embodiment, firstly, the situation maps in a plurality of time periods are spliced according to the time sequence to form an overall situation map, and the fault trend of the port machinery equipment is predicted according to the change trend of the overall situation map. The method and the device have the advantages that the working rule of the port machine equipment can be determined by counting the situation diagrams at different time intervals, the fault trend of the port machine equipment is pre-judged according to the working rule, the prediction of the port machine equipment is realized, a preventive maintenance strategy is formulated later, and the condition that long-time shutdown affects operation is reduced.
As shown in fig. 7, in one embodiment, analyzing the overall situation map to predict a failure trend of the port machinery equipment includes:
and step 124C, predicting the fault trend of the port machinery equipment according to the fault trend graph.
In this embodiment, because the overall situation diagram describes the abnormal information of the port machinery equipment in a time period, the change trend of the operation state of the port machinery equipment can be objectively reflected, curve fitting is performed according to the change trend and the change speed of the curve of the overall situation diagram, that is, curve analysis and prediction are performed according to the change rule of the situation diagram and the change rule of the port machinery equipment, so that an obtained fault trend curve diagram has a high reference value for predicting the fault trend of the port machinery equipment, the trend of fault parts of the port machinery equipment can be obtained in advance, and further, countermeasures can be made in advance, so that the operation efficiency of the port machinery equipment can be improved.
As shown in fig. 8, in one embodiment, a port machinery situation monitoring apparatus is provided, the apparatus comprising:
the acquisition module 802 is configured to acquire monitoring data corresponding to each mechanical component in the port machinery equipment in real time through a preset sensor;
the judging module 804 is configured to obtain preset index data of each mechanical component, and judge an operation state of each mechanical component according to the index data and the monitoring data, where the operation state is an abnormal state or a normal state;
an analysis module 806, configured to analyze monitoring data corresponding to a mechanical component in an abnormal operating state to determine abnormal information of the mechanical component;
and the display module 808 is configured to establish a situation map according to the abnormal information, and push the situation map to the monitoring display device.
In one embodiment, the determining module comprises:
the transformation unit is used for respectively carrying out waveform transformation processing on the monitoring data corresponding to each mechanical component and determining the vibration characteristic value of each mechanical component;
the first calculation unit is used for calculating the difference value between the vibration characteristic value of each mechanical component and the corresponding preset index data;
the first judging unit is used for judging that the running state of the corresponding mechanical component is a normal state when the difference value is within a preset threshold range;
and the second judging unit is used for judging that the corresponding running state of the mechanical component is an abnormal state when the difference value is not within the preset threshold range.
In one embodiment, the analysis module comprises:
the acquiring unit is used for acquiring the vibration characteristic value of the mechanical component with the abnormal operation state;
the second calculation unit is used for calculating the defect characteristic frequency of the corresponding mechanical component according to the vibration characteristic value;
and the first determining unit is used for determining the fault type of the mechanical component and the corresponding fault position as the abnormal information according to the defect characteristic frequency.
In one embodiment, the port equipment situation monitoring apparatus further includes:
the extracting module is used for extracting the fault type and the corresponding fault position of each mechanical component from the situation map;
the searching module is used for acquiring a corresponding fault degree grade table from a database according to the fault type and the corresponding fault position;
and the determining module is used for determining the fault degree grade of the mechanical component according to the difference value and the fault degree grade table.
In one embodiment, the port equipment situation monitoring apparatus further includes:
the detection module is used for determining the diagnosis frequency of the mechanical component according to the defect characteristic frequency and the fault degree;
and the self-diagnosis module is used for adjusting the frequency of the mechanical component to the diagnosis frequency to perform self-diagnosis processing.
In one embodiment, the port equipment situation monitoring apparatus further includes:
the second acquisition module is used for acquiring a plurality of situation maps within a preset time period;
the combination module is used for combining the plurality of situation maps into an integral situation map according to a time sequence;
and the prediction module is used for analyzing the overall situation map and predicting the fault trend of the port machinery equipment.
In one embodiment, the prediction module comprises:
the second determining unit is used for determining curve change trend and change speed according to the overall situation map;
the fitting unit is used for performing curve fitting according to the curve change trend and the change speed to generate a fault trend curve chart;
and the prediction unit is used for predicting the fault trend of the port machinery equipment according to the fault trend graph.
FIG. 9 is a diagram illustrating an internal structure of a computer device in one embodiment. The computer device may specifically be a server including, but not limited to, a high performance computer and a cluster of high performance computers. As shown in fig. 9, the computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium of the computer device stores an operating system and also stores a computer program, and when the computer program is executed by a processor, the computer program can enable the processor to realize the harbor machine device situation monitoring method. The internal memory may also have a computer program stored therein, which when executed by the processor, causes the processor to perform a method of monitoring a posture of a port machinery device. Those skilled in the art will appreciate that the architecture shown in fig. 9 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, the port machinery situation monitoring method provided by the application can be implemented in a form of a computer program, and the computer program can be run on a computer device as shown in fig. 9. The memory of the computer equipment can store various program templates forming the port machine equipment situation monitoring device. For example, the first obtaining module 802, the determining module 804, the analyzing module 806, and the displaying module 808 may be utilized.
A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing the following steps when executing the computer program: acquiring monitoring data corresponding to each mechanical component in port machinery equipment in real time through a preset sensor; acquiring preset index data of each mechanical component, and judging the running state of each mechanical component according to the index data and the monitoring data, wherein the running state is classified into an abnormal state or a normal state; analyzing monitoring data corresponding to a mechanical component with an abnormal operation state to determine abnormal information of the mechanical component; and establishing a situation map according to the abnormal information, and pushing the situation map to monitoring display equipment.
In one embodiment, acquiring index data of each mechanical component, and determining an operating state of each mechanical component according to the index data and the monitoring data includes: respectively carrying out waveform transformation processing on the monitoring data corresponding to each mechanical component to determine the vibration characteristic value of each mechanical component; respectively calculating the difference value between the vibration characteristic value of each mechanical component and the corresponding preset index data; when the difference value is within a preset threshold value range, judging that the running state of the corresponding mechanical component is a normal state; and when the difference is not within the preset threshold range, judging that the corresponding running state of the mechanical component is an abnormal state.
In one embodiment, the analyzing the monitoring data corresponding to the abnormal operating state to determine the abnormal information of the mechanical component includes: acquiring a vibration characteristic value of a mechanical component with an abnormal operation state; calculating the defect characteristic frequency of the corresponding mechanical component according to the vibration characteristic value; and determining the fault type of the mechanical component and the corresponding fault position according to the defect characteristic frequency as the abnormal information.
In one embodiment, after the creating a situation map according to the abnormal information and pushing the situation map to a monitoring display device, the method further includes: extracting the fault type and the corresponding fault position of each mechanical component from the situation map; acquiring a corresponding fault degree grade table from a database according to the fault type and the corresponding fault position; and determining the fault degree grade of the mechanical component according to the difference value and the fault degree grade table.
In one embodiment, after the determining the fault level of the mechanical component according to the magnitude of the difference value and the fault level table, the method further includes: determining the diagnosis frequency of the mechanical component according to the defect characteristic frequency and the fault degree; and adjusting the frequency of the mechanical component to the diagnosis frequency to perform self-diagnosis treatment.
In one embodiment, after the creating a situation map according to the abnormal information and pushing the situation map to a monitoring display device, the method further includes: acquiring a plurality of situation maps within a preset time period; combining the plurality of situation maps into an integral situation map according to a time sequence; and analyzing the overall situation map and predicting the fault trend of the port machinery equipment.
In one embodiment, analyzing the overall situation map and predicting the fault trend of the port machinery equipment comprises the following steps: determining curve change trend and change speed according to the overall situation map; performing curve fitting according to the curve change trend and the change speed to generate a fault trend curve chart; and predicting the fault trend of the port machinery equipment according to the fault trend graph.
A computer-readable storage medium storing a computer program, the computer program when executed by a processor implementing the steps of: acquiring monitoring data corresponding to each mechanical component in port machinery equipment in real time through a preset sensor; acquiring preset index data of each mechanical component, and judging the running state of each mechanical component according to the index data and the monitoring data, wherein the running state is classified into an abnormal state or a normal state; analyzing monitoring data corresponding to a mechanical component with an abnormal operation state to determine abnormal information of the mechanical component; and establishing a situation map according to the abnormal information, and pushing the situation map to monitoring display equipment.
In one embodiment, acquiring index data of each mechanical component, and determining an operating state of each mechanical component according to the index data and the monitoring data includes: respectively carrying out waveform transformation processing on the monitoring data corresponding to each mechanical component to determine the vibration characteristic value of each mechanical component; respectively calculating the difference value between the vibration characteristic value of each mechanical component and the corresponding preset index data; when the difference value is within a preset threshold value range, judging that the running state of the corresponding mechanical component is a normal state; and when the difference is not within the preset threshold range, judging that the corresponding running state of the mechanical component is an abnormal state.
In one embodiment, the analyzing the monitoring data corresponding to the abnormal operating state to determine the abnormal information of the mechanical component includes: acquiring a vibration characteristic value of a mechanical component with an abnormal operation state; calculating the defect characteristic frequency of the corresponding mechanical component according to the vibration characteristic value; and determining the fault type of the mechanical component and the corresponding fault position according to the defect characteristic frequency as the abnormal information.
In one embodiment, after the creating a situation map according to the abnormal information and pushing the situation map to a monitoring display device, the method further includes: extracting the fault type and the corresponding fault position of each mechanical component from the situation map; acquiring a corresponding fault degree grade table from a database according to the fault type and the corresponding fault position; and determining the fault degree grade of the mechanical component according to the difference value and the fault degree grade table.
In one embodiment, after the determining the fault level of the mechanical component according to the magnitude of the difference value and the fault level table, the method further includes: determining the diagnosis frequency of the mechanical component according to the defect characteristic frequency and the fault degree; and adjusting the frequency of the mechanical component to the diagnosis frequency to perform self-diagnosis treatment.
In one embodiment, after the creating a situation map according to the abnormal information and pushing the situation map to a monitoring display device, the method further includes: acquiring a plurality of situation maps within a preset time period; combining the plurality of situation maps into an integral situation map according to a time sequence; and analyzing the overall situation map and predicting the fault trend of the port machinery equipment.
Those skilled in the art will appreciate that all or a portion of the processes in the methods of the embodiments described above may be implemented by computer programs that may be stored in a non-volatile computer-readable storage medium, which when executed, may include the processes of the embodiments of the methods described above, wherein any reference to memory, storage, database or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, non-volatile memory may include read-only memory (ROM), programmable ROM (prom), electrically programmable ROM (eprom), electrically erasable programmable ROM (eeprom), or flash memory, volatile memory may include Random Access Memory (RAM) or external cache memory, RAM is available in a variety of forms, such as static RAM (sram), Dynamic RAM (DRAM), synchronous sdram (sdram), double data rate sdram (ddr sdram), enhanced sdram (sdram), synchronous link (sdram), dynamic RAM (rdram) (rdram L), direct dynamic RAM (rdram), and the like, and/or external cache memory.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method for monitoring the situation of port machinery equipment is characterized by comprising the following steps:
acquiring monitoring data corresponding to each mechanical component in port machinery equipment in real time through a preset sensor;
acquiring preset index data of each mechanical component, and judging the running state of each mechanical component according to the index data and the monitoring data, wherein the running state is classified into an abnormal state or a normal state;
analyzing monitoring data corresponding to a mechanical component with an abnormal operation state to determine abnormal information of the mechanical component;
and establishing a situation map according to the abnormal information, and pushing the situation map to monitoring display equipment.
2. The port equipment situation monitoring method according to claim 1, wherein the acquiring index data of each mechanical component and judging the operation state of each mechanical component according to the index data and the monitoring data comprises:
respectively carrying out waveform transformation processing on the monitoring data corresponding to each mechanical component to determine the vibration characteristic value of each mechanical component;
respectively calculating the difference value between the vibration characteristic value of each mechanical component and the corresponding preset index data;
when the difference value is within a preset threshold value range, judging that the running state of the corresponding mechanical component is a normal state;
and when the difference is not within the preset threshold range, judging that the corresponding running state of the mechanical component is an abnormal state.
3. The port machinery situation monitoring method of claim 2, wherein analyzing the monitoring data corresponding to the abnormal operation state to determine the abnormal information of the mechanical component comprises:
acquiring a vibration characteristic value of a mechanical component with an abnormal operation state;
calculating the defect characteristic frequency of the corresponding mechanical component according to the vibration characteristic value;
and determining the fault type of the mechanical component and the corresponding fault position according to the defect characteristic frequency as the abnormal information.
4. The port machine equipment situation monitoring method according to claim 1, further comprising, after the establishing a situation map according to the anomaly information and pushing the situation map onto a monitoring display device:
extracting the fault type and the corresponding fault position of each mechanical component from the situation map;
acquiring a corresponding fault degree grade table from a database according to the fault type and the corresponding fault position;
and determining the fault degree grade of the mechanical component according to the difference value and the fault degree grade table.
5. The port equipment situation monitoring method of claim 3, further comprising, after said determining a level of failure of the mechanical component based on the magnitude of the difference and the table of levels of failure,:
determining the diagnosis frequency of the mechanical component according to the defect characteristic frequency and the fault degree;
and adjusting the frequency of the mechanical component to the diagnosis frequency to perform self-diagnosis treatment.
6. The port machine equipment situation monitoring method according to claim 1, further comprising, after the establishing a situation map according to the anomaly information and pushing the situation map onto a monitoring display device:
acquiring a plurality of situation maps within a preset time period;
combining the plurality of situation maps into an integral situation map according to a time sequence;
and analyzing the overall situation map and predicting the fault trend of the port machinery equipment.
7. The port machinery situation monitoring method of claim 6, wherein the analyzing the overall situation map to predict the failure trend of the port machinery comprises:
determining curve change trend and change speed according to the overall situation map;
performing curve fitting according to the curve change trend and the change speed to generate a fault trend curve chart;
and predicting the fault trend of the port machinery equipment according to the fault trend graph.
8. The utility model provides a port machine equipment situation monitoring device which characterized in that, port machine equipment situation monitoring device includes:
the first acquisition module is used for acquiring monitoring data corresponding to each mechanical component in the port machinery equipment in real time through a preset sensor;
the judging module is used for acquiring preset index data of each mechanical component and judging the running state of each mechanical component according to the index data and the monitoring data, wherein the running state is divided into an abnormal state or a normal state;
the analysis module is used for analyzing the monitoring data corresponding to the mechanical component with the abnormal operation state to determine the abnormal information of the mechanical component;
and the display module is used for establishing a situation map according to the abnormal information and pushing the situation map to the monitoring display equipment.
9. A computer arrangement comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor when executing the computer program performs the steps of the method for monitoring a situation in a port equipment according to any of claims 1 to 7.
10. A computer-readable storage medium, storing a computer program, wherein the computer program, when executed by a processor, performs the steps of the method for monitoring a situation in a port machinery device according to any one of claims 1 to 7.
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