CN114764459A - Fault processing method and system for working machine and electronic equipment - Google Patents
Fault processing method and system for working machine and electronic equipment Download PDFInfo
- Publication number
- CN114764459A CN114764459A CN202011640616.7A CN202011640616A CN114764459A CN 114764459 A CN114764459 A CN 114764459A CN 202011640616 A CN202011640616 A CN 202011640616A CN 114764459 A CN114764459 A CN 114764459A
- Authority
- CN
- China
- Prior art keywords
- parameters
- fault
- working
- historical
- machine
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000003672 processing method Methods 0.000 title abstract description 12
- 238000003745 diagnosis Methods 0.000 claims abstract description 73
- 238000004458 analytical method Methods 0.000 claims abstract description 64
- 238000000034 method Methods 0.000 claims abstract description 52
- 230000002159 abnormal effect Effects 0.000 claims description 14
- 238000012545 processing Methods 0.000 claims description 12
- 238000004590 computer program Methods 0.000 claims description 11
- 238000013024 troubleshooting Methods 0.000 description 11
- 230000008569 process Effects 0.000 description 9
- 238000010586 diagram Methods 0.000 description 8
- 238000012423 maintenance Methods 0.000 description 8
- 238000012544 monitoring process Methods 0.000 description 5
- 238000010276 construction Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 230000008859 change Effects 0.000 description 3
- 230000009467 reduction Effects 0.000 description 3
- 238000013500 data storage Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000007257 malfunction Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 238000009435 building construction Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000000354 decomposition reaction Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 238000005192 partition Methods 0.000 description 1
- 230000006798 recombination Effects 0.000 description 1
- 238000005215 recombination Methods 0.000 description 1
- 230000000306 recurrent effect Effects 0.000 description 1
- 230000003252 repetitive effect Effects 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/903—Querying
- G06F16/90335—Query processing
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M13/00—Testing of machine parts
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/903—Querying
Abstract
The invention discloses a fault processing method and system for a working machine, an electronic device and a computer readable storage medium, which solve the problem of low fault judgment efficiency. The application provides a fault handling method for a working machine, which comprises the following steps: acquiring historical operation parameters of the operation machine in the working time period, wherein the historical operation parameters comprise working parameters and control parameters of the operation machine at different working time nodes; according to the historical operation parameters, fault diagnosis and analysis are carried out; and outputting and/or displaying the result of the fault diagnosis analysis.
Description
Technical Field
The present disclosure relates to the field of work machine technologies, and in particular, to a method and a system for processing a fault of a work machine, and an electronic device.
Background
With the continuous development of engineering technology, concrete pump trucks and other operation machines are more and more widely applied to various fields of production and life. As large mechanical equipment necessary for building construction, the concrete pump truck causes great economic loss of construction units due to failure and shutdown. Therefore, it is urgently required to improve the troubleshooting capability of the concrete pump truck so as to improve the operation efficiency and reduce the economic loss.
In the prior art, a monitoring scheme of a concrete pump truck cantilever crane system safety performance by utilizing a concrete pump truck cantilever crane monitoring system is characterized in that a sensor is arranged at a key part of a cantilever crane system, the key part with a fault in the cantilever crane system is monitored by the sensor, and an equipment display is used for giving an alarm prompt, so that the difficulty of troubleshooting is reduced to a certain extent.
However, in the above prior art, it is determined whether some independent components of the boom system are abnormal by determining whether the sensor data exceeds a set threshold. The fault judgment standard is too simple, and a plurality of faults occurring in the boom system are not caused by the damage of key parts with sensors, so that when the faults occur, workers still need to go to a construction site for troubleshooting.
Disclosure of Invention
Therefore, the application provides a fault processing method and system for a working machine and an electronic device, and solves the technical problem of low fault judgment efficiency in the prior art.
In a first aspect, the present application provides a method for handling a fault of a work machine, including: acquiring historical operation parameters of the operation machine during the working time period, wherein the historical operation parameters comprise working parameters and control parameters of the operation machine at different working time nodes; according to the historical operation parameters, fault diagnosis and analysis are carried out; and outputting and/or displaying the results of the fault diagnosis analysis.
With reference to the first aspect, in a possible implementation manner, the working parameter includes at least one of a pressure of each arm cylinder of the working machine, an included angle between each arm of the working machine, and a vibration amplitude of each arm of the working machine; the control parameters include control parameters of a remote control of the work machine and/or control parameters of an operating handle or operating buttons of the work machine.
With reference to the first aspect, in a possible implementation manner, the method further includes: and acquiring the current operation parameters of the operation machine, comparing the current operation parameters with the historical operation parameters, and outputting or/and displaying the analysis result of whether the operation machine has faults or not.
With reference to the first aspect, in a possible implementation manner, before obtaining the historical operation parameters of the work machine during the operation period, the method further includes: and storing historical operation parameters of the operation machine during the working period.
With reference to the first aspect, in one possible implementation manner, the storing the historical operation parameters of the work machine during the operation period includes: measuring working parameters of the working machine at a plurality of working time nodes within a working time period, and obtaining the operating parameters of the working machine at the working time nodes; and classifying the obtained operation parameters according to the types of the operation parameters to obtain a plurality of historical operation parameter sets, wherein each operation parameter in each historical operation parameter set corresponds to each operating time node.
With reference to the first aspect, in a possible implementation manner, the performing fault diagnosis analysis according to the historical operation parameters includes: searching abnormal working parameters according to working parameters of the working machine at different working times, and performing fault diagnosis and analysis according to the abnormal working parameters and control parameters of the occurrence time of the abnormal working parameters; or, according to the historical operation parameters, searching a fault database, and performing fault diagnosis analysis according to the fault database;
with reference to the first aspect, in a possible implementation manner, the result of the fault diagnosis analysis is output to a control terminal or a mobile terminal of the work machine, and the result of the fault diagnosis analysis includes a fault diagnosis conclusion and/or a fault processing flow.
With reference to the first aspect, in a possible implementation manner, the performing fault diagnosis analysis according to the historical operation parameters further includes forming a trend statistical chart from data in the historical operation parameters; storing the trend statistics in a historical job parameter database; and carrying out fault diagnosis and analysis according to the trend statistical chart.
The present application also provides a fault handling system for a work machine for implementing the above method, the system comprising:
the historical data acquisition module is configured to acquire historical operation parameters of the working machine in working time periods, wherein the historical operation parameters comprise working parameters and control parameters of the working machine in different working time nodes; the fault diagnosis analysis module is configured to perform fault diagnosis analysis according to the historical operation parameters; and a result output module configured to output and/or display a result of the fault diagnosis analysis.
The application also provides an electronic device, which comprises a data acquisition device for acquiring data; a processor; and a memory having stored therein computer program instructions which, when executed by the processor, cause the processor to perform a fault handling method as claimed in any one of the preceding claims.
The present application further provides a computer-readable storage medium storing a computer program, which when executed by a processor, causes the processor to execute the fault handling method according to any one of the above embodiments.
According to the fault processing method of the working machine, the historical working parameters of the working machine during the working period are obtained, and fault diagnosis and analysis are carried out according to the historical working parameters; and outputting and/or displaying the results of the fault diagnosis analysis. When a fault occurs, historical operation parameters can be acquired, the operation parameters and the control parameters are combined, analysis is carried out to obtain a diagnosis result, the fault analysis of equipment can be carried out remotely through data, and a final fault diagnosis result is sent to a mobile terminal or a vehicle terminal to be checked by a client or a maintenance person. Therefore, remote fault diagnosis is realized, on-site fault diagnosis and analysis are not needed, the labor cost is reduced, and the troubleshooting efficiency of the equipment is improved.
Drawings
The above and other objects, features and advantages of the present application will become more apparent by describing in more detail embodiments of the present application with reference to the attached drawings. The accompanying drawings are included to provide a further understanding of the embodiments of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the principles of the application. In the drawings, like reference numbers generally indicate like parts or steps.
Fig. 1 is a flowchart illustrating a method for handling a fault of a work machine according to an embodiment of the present disclosure.
Fig. 2 is a schematic flow chart illustrating a fault handling method according to another embodiment of the present application.
Fig. 3 is a schematic flow chart illustrating a fault handling method according to another embodiment of the present application.
Fig. 4 is a flowchart illustrating a process of storing historical job parameters in a fault handling method according to another embodiment of the present application.
Fig. 5 is a schematic flowchart illustrating a recurring fault determination process in a fault handling method for a work machine according to another embodiment of the present disclosure.
Fig. 6 is a schematic structural diagram illustrating a fault handling system of a work machine according to an embodiment of the present disclosure.
Fig. 7 is a schematic structural diagram illustrating a fault handling system of a work machine according to another embodiment of the present disclosure.
Fig. 8 is a schematic structural diagram of an embodiment of an electronic device according to an embodiment of the present disclosure.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. The embodiments of the present application, and all other embodiments that can be obtained by a person of ordinary skill in the art without any inventive work, shall fall within the scope of protection of the present application.
Summary of the application
In order to solve the technical problem of low troubleshooting efficiency of the operation machinery, in the prior art, a monitoring scheme of a concrete pump truck cantilever crane monitoring system for the safety performance of the concrete pump truck cantilever crane system is utilized, a sensor is distributed at a key part of the cantilever crane system, the key part with a fault in the cantilever crane system is monitored through the sensor, and an alarm prompt is given through an equipment display, so that the troubleshooting difficulty is reduced to a certain extent, and the troubleshooting efficiency is improved.
However, the above prior art determines whether some independent components of the boom system are abnormal by determining whether the sensor data exceeds a set threshold. The fault judgment standard is too simple, and a plurality of faults occurring in the boom system are not caused by the damage of key parts with sensors, so that when the faults occur, workers still need to go to a construction site for troubleshooting.
In view of the above technical problems, the present application provides a method for handling a fault of a working machine, where the working machine may be a large-scale engineering equipment such as a concrete pump truck or a crane, and the present embodiment takes the concrete pump truck as an example, but it should be understood that the related control method and strategy thereof may also be applied to other working machines such as an excavator, a crane, a fire truck, and a pump truck. The fault processing method utilizes historical operation parameters of equipment stored in a database, carries out fault diagnosis analysis by combining the working parameters and the control parameters, and gives a diagnosis conclusion. The final fault diagnosis result is sent to the mobile terminal or the vehicle terminal or displayed on a display screen for a client or a maintenance worker to check, so that the technical problems that the fault information acquisition accuracy is poor and the fault reason cannot be remotely judged in the prior art are solved.
Exemplary Fault handling method
Fig. 1 is a flowchart illustrating a method for handling a fault of a work machine according to an embodiment of the present disclosure. As shown in fig. 1, the method for processing a failure in a working machine includes the steps of:
step 10: acquiring historical operation parameters of the operation machine during the working time period, wherein the historical operation parameters comprise working parameters and control parameters of the operation machine at different working time nodes;
specifically, the working parameters include at least one of pressure of each arm cylinder of the working machine, an included angle between each arm of the working machine, and vibration amplitude of each arm of the working machine; the control parameters include control parameters of a remote control of the work machine and/or control parameters of an operating handle or operating buttons of the work machine.
The historical operating parameters in a certain operating time period can be separated by the same time interval or different time intervals.
Step 20: according to the historical operation parameters, fault diagnosis and analysis are carried out;
step 30: and outputting and/or displaying the result of the fault diagnosis analysis.
According to the fault processing method of the working machine, when a fault occurs, historical working parameters can be obtained, the working parameters and the control parameters are combined and analyzed to obtain a diagnosis result, the fault analysis of the equipment can be remotely carried out through data, and a final fault diagnosis result is sent to a mobile terminal or a vehicle terminal to be checked by a client or a maintenance person. Therefore, remote fault diagnosis is realized, on-site fault diagnosis and analysis are not needed, the labor cost is reduced, and the troubleshooting efficiency of the equipment is improved.
Fig. 2 is a schematic flow chart of a fault handling method according to another embodiment of the present application. As shown in fig. 2, the fault handling method further comprises control parameters of a remote control of the work machine and/or control parameters of an operating handle or operating buttons of the work machine.
Step 40: acquiring current operation parameters of the operation machine;
when the current operation parameters comprise the collected data, the corresponding sensors or the measuring equipment output the instant values of the corresponding parameters to the controller.
Step 50: comparing the current operation parameters with historical operation parameters; and
step 30: and outputting or/and displaying the analysis result of whether the working machine has the fault.
The fault handling method shown in fig. 1 is more useful in situations where, when a work machine is malfunctioning in the field, the operator or a line of maintenance personnel cannot immediately diagnose the cause, type, and specific component of the malfunction, and the diagnosis can be given by a remote support server, which may be a malfunction occurring 5 minutes or an hour ago.
The fault handling method shown in fig. 2 may be a method of diagnosing the current operating condition of the work machine. For example, when the field operator needs to reduce the angle between the 2-arm and the 1-arm at a rate of 3 degrees per minute, this command is issued by operating the handle. Also, under normal conditions, such a reduction rate can be achieved with 1 and 2 arms when other components are not malfunctioning, which is recorded in historical operating parameters. However, the angle between the arm 2 and the arm 1 is not actually reduced according to the above speed, or is not reduced, and due to insufficient illumination at the construction site at night, the operator cannot see clearly, or the operator cannot accurately judge whether the actual reduction speed of the included angle is the desired reduction speed.
Therefore, after the current operation parameters are obtained, the current operation parameters can be compared with the historical operation parameters, and according to the fact that the operation parameters and the control parameters of other arm frames are basically the same, but the angle between the arm 2 and the arm 1 does not reach the expected speed, the fault, which may be oil leakage or insufficient oil pressure, of the oil cylinder controlling the arm 2 or the control valve of the oil cylinder can be diagnosed, and the fault is fed back to an operator. Therefore, the real-time monitoring function of the operating equipment can be realized, and the on-site operator can be prompted when the operator does not find the fault, so that the fault is prevented from developing to a more serious direction, the possibility of spending more time to solve the fault is reduced, and the utilization efficiency of the operating machine is improved.
Fig. 3 is a schematic flow chart illustrating a fault handling method according to another embodiment of the present application. As shown in fig. 3, the fault handling method, before obtaining the historical operation parameters of the work machine during the operation period, further includes:
step 15: historical work parameters of the work machine during the work time period are stored.
Fig. 4 is a flowchart illustrating a process of storing historical job parameters in a fault handling method according to another embodiment of the present application. As shown in fig. 4, the process of storing the historical job parameters includes the steps of:
step 101: measuring working parameters of the working machine under a plurality of time nodes in a working time period, and obtaining operating parameters of the working machine at the working time nodes;
in an actual use scenario, the set working time period may theoretically be any earlier time range than the current time, and the time period may be selected according to a sample requirement, and generally, the longer the time period is selected, the more densely the divided time nodes are, the higher the accuracy of the database is.
However, considering the cost problem, on the premise of meeting the use requirement, a more reasonable time period and divided time nodes can be set. In this embodiment, the operation time period is set to 300 hours when the work machine is in an operating state, and the divided time nodes are to acquire the operation parameters of the work machine at intervals of 1 second, that is, at intervals of 1 second. It should be understood that the time nodes of the partition may be shorter or longer, such as 2 seconds, 5 seconds, 8 seconds, 10 seconds, 0.5 seconds apart to acquire data. The particular time intervals between the time nodes may be selected according to the computational power of the processor, the storage capabilities of the memory, and the frequency with which the corresponding parameters of the device change over time.
Step 102: and classifying the obtained operation parameters according to the types of the operation parameters to obtain a plurality of historical operation parameter groups, wherein each operation parameter in each historical operation parameter group corresponds to each working time node.
In an actual use scenario, in an actual data acquisition process, due to the fact that the obtained parameter types are more, for example, multiple data such as the engine speed, the deflection angle of the knuckle arm, the amplitude of the knuckle arm and the like can be obtained simultaneously, and different types of data represent different fault positions and fault types. For example, regarding possible failures of the knuckle arms, which are mainly related to the angles of the knuckle arms, the pressures of the cylinders of the respective knuckle arms, the vibration amplitude frequencies of the knuckle arms, and other numerical values, it may be only necessary to retrieve the corresponding data, regardless of information of the engine of the concrete pump truck, such as the engine speed, the engine temperature, and the like. Therefore, in order to improve the accuracy of fault determination and the efficiency of determination, a plurality of types of faults may be classified, that is, the obtained sets of operation parameters may be classified to form a plurality of sets of historical operation parameter sets for each work machine.
For example, taking pump truck No. 1 as an example, the pump truck has five arms, and there may be multiple sets of historical operating parameter sets with respect to the pump truck No. 1, and for example, 1-arm angle historical operating parameter set, 1-arm and 2-arm angle historical operating parameter set, … …, 4-arm and 5-arm angle historical operating parameter set, 1-arm cylinder historical operating parameter set, 2-arm cylinder historical operating parameter set, … …, 5-arm cylinder historical operating parameter set, 1-arm vibration amplitude historical operating parameter set, 2-arm vibration amplitude historical operating parameter set, … …, 5-arm vibration amplitude historical operating parameter set, and so on may be formed.
In an embodiment of the present application, the fault diagnosis and analysis are performed according to historical operating parameters, which specifically includes the following steps:
searching abnormal working parameters according to working parameters of the operation machine at different working time, and performing fault diagnosis and analysis according to the abnormal working parameters and control parameters of the occurrence time of the abnormal working parameters;
for example, taking the change of the arm angle as an example, when the change of the included angle between the 2-section arm and the 3-section arm exceeds 1 degree/minute when the data in the database is inspected, the processor starts to observe the arm support control signal of the remote controller. If the operation parameters of the signals for controlling the 2-section arm or 3-section arm to move are read, the normal movement of the arm support is judged at the moment; if the remote controller does not give a signal for controlling the action of any section of arm at the moment, an internal leakage fault of the arm support system at the moment is diagnosed; if the remote controller does not give a signal for controlling the movement of the arm with the length of 2 or 3 at the moment but has a signal for controlling the movement of other arms, the arm support system is judged to have a card-issuing fault at the moment.
Or, searching a fault database according to the historical operation parameters, and performing fault diagnosis and analysis according to the fault database;
specifically, when the determined fault condition is a condition which has occurred in history and is stored in the historical job parameter database, the automatic determination of the troubleshooting condition can be realized through an automatic calling mode. Fig. 5 is a schematic flowchart illustrating a recurring failure determination process in a failure processing method for a working machine according to another embodiment of the present application; as shown in fig. 5, the recurrent failure determination process includes:
step 501: judging whether each current operation parameter is consistent with the working parameter of the corresponding historical operation parameter, and the time corresponding to the working parameter consistent with the current operation parameter in each historical operation parameter is consistent, calling fault diagnosis logic information prestored in a historical operation parameter database, wherein the fault diagnosis logic information comprises the type of the fault, the fault occurrence position, the time of the fault occurrence before and the working parameter at the time; sending fault diagnosis logic information to the intelligent terminal; and
specifically, the consistency of the operating parameters does not mean that the operating parameters are the same, and in the engineering practice in the field, the consistency may be considered when the difference is less than 1% or less than 0.5%.
Taking the pump truck No. 1 as an example, in the current operation parameters obtained at a certain time, the current operation parameters are all consistent with the arm angle of 1 joint, the arm angle of 12 joint, the arm angle of … … and the arm angle of 45 at 20 o 'clock 12/2/2020 in the historical operation parameters of the equipment, the pressure of the arm cylinder of 1 joint, the pressure of the arm cylinder of 2 joint, the pressure of the arm cylinder of … … and the pressure of the arm cylinder of 5 joint are also consistent, the vibration amplitude of 1 joint, the vibration amplitude of 2 joint, the vibration amplitude of … … and the vibration amplitude of 5 joint are consistent, and at 20 o' clock 12/2/2020, the fault information of the arm cylinder of 1 joint is fed back to the maintenance personnel.
Step 502: and judging whether each current operation parameter is inconsistent with the corresponding working parameter of the historical operation parameter, and/or judging whether the time corresponding to the working parameter consistent with the current operation parameter in each historical operation parameter is inconsistent, and outputting the current operation parameter and each group of historical operation parameters in a visual form.
For example, in the current operation parameters obtained at a certain time, the pressure of the 1-joint arm cylinder is only consistent with the pressure of the 1-joint arm cylinder at 20 o 'clock of 12, month and 4 of 2020, while the 1-joint arm angle is only consistent with the angle of the 1-joint arm cylinder at 20 o' clock of 12, month and 13 of 2020, and the corresponding time when the angles are consistent is different from the corresponding time when the pressures are consistent, so step 501 is not executed, and step 502 is executed.
In an embodiment of the present application, outputting and/or displaying a result of the fault diagnosis analysis further includes:
and outputting the fault diagnosis and analysis result to a control terminal or a mobile terminal of the working machine, wherein the fault diagnosis and analysis result comprises a fault diagnosis conclusion and/or a fault processing flow.
The fault diagnosis analysis result output to the control terminal or the mobile terminal of the working machine comprises a fault diagnosis conclusion and a fault processing flow, so that a field maintenance worker can refer to the fault processing flow to process the fault of the working machine after receiving the corresponding fault diagnosis conclusion, the maintenance uniformity is improved, and the possibility of equipment damage caused by improper operation of the processing worker is reduced.
The application provides a fault processing method for a working machine, which comprises the following steps: acquiring historical operation parameters of the operation machine during the working time period, wherein the historical operation parameters comprise working parameters and control parameters of the operation machine at different working time nodes; according to the historical operation parameters, fault diagnosis and analysis are carried out; and outputting and/or displaying the result of the fault diagnosis analysis. According to the fault processing method of the working machine, when a fault occurs, historical working parameters can be obtained, the working parameters and the control parameters are combined and analyzed to obtain a diagnosis result, the fault analysis of the equipment can be remotely carried out through data, and a final fault diagnosis result is sent to a mobile terminal or a vehicle terminal to be checked by a client or a maintenance person. Therefore, remote fault diagnosis is realized, on-site fault diagnosis and analysis are not needed, the labor cost is reduced, and the troubleshooting efficiency of the equipment is improved.
In addition, according to the fault processing method of the working machine of the embodiment, the fault diagnosis processing method can be used in various ways, such as forming data in historical working parameters into a trend statistical chart; storing the trend statistical chart in a historical operation parameter database; according to the trend statistical chart, fault diagnosis and analysis are performed, during specific analysis, automatic analysis can be performed by the system, and analysis can also be performed by experts of the type of operation machinery, of course, the analyzed result can be output, and specific reference is made to the foregoing embodiment.
Exemplary Fault handling System
Fig. 6 is a schematic structural diagram of a fault handling system of a work machine according to an embodiment of the present disclosure; as shown in fig. 6, the present application also provides a fault handling system for a work machine, for implementing the above method, the system comprising:
a historical data acquiring module 910 configured to acquire historical operation parameters of the work machine during the work time period, where the historical operation parameters include work parameters and control parameters of the work machine at different work time nodes; a fault diagnosis analysis module 920 configured to perform fault diagnosis analysis according to the historical operation parameters; and a result output module 930 configured to output and/or display the results of the fault diagnosis analysis.
Fig. 7 is a schematic structural diagram illustrating a fault handling system of a work machine according to another embodiment of the present disclosure. As shown in fig. 7, the fault handling system further includes a current parameter processing module 940 configured to obtain current operation parameters of the work machine, compare the current operation parameters with historical operation parameters, and output or/and display an analysis result of whether the work machine has a fault.
In an embodiment of the present application, a data storage module 950 is also included and configured to store historical work parameters of the work machine during the work hours.
In an embodiment of the present application, the data storage module 950 includes: the parameter obtaining unit is configured to measure working parameters of the working machine under a plurality of working time nodes in a working time period and obtain operating parameters of the working machine of the working time nodes; and a classification unit configured to classify the obtained job parameters according to the types of the job parameters to obtain a plurality of historical job parameter sets, wherein each job parameter in each historical job parameter set corresponds to each working time node.
In an embodiment of the present application, the fault diagnosis and analysis module 920 is configured to search for an abnormal working parameter according to working parameters of the working machine at different working times, and perform fault diagnosis and analysis according to the abnormal working parameter and a control parameter of an occurrence time of the abnormal working parameter, or configured to search for a fault database according to historical working parameters, and perform fault diagnosis and analysis according to the fault database.
In an embodiment of the present application, the result output module is configured to output a result of the fault diagnosis analysis to a control terminal or a mobile terminal of the work machine, where the result of the fault diagnosis analysis includes a fault diagnosis conclusion and/or a fault handling process.
The detailed functions and operations of the respective modules in the above-described fault handling system 90 have been described in detail in the fault handling method described above with reference to fig. 1 to 5, and therefore, a repetitive description thereof will be omitted herein.
It should be noted that the fault handling system 90 according to the embodiment of the present application may be integrated into the electronic device 60 as a software module and/or a hardware module, in other words, the electronic device 60 may include the fault handling system 90. For example, the fault handling system 90 may be a software module in the operating system of the electronic device 60, or may be an application developed for it; of course, the fault handling system 90 may also be one of many hardware modules of the electronic device 60.
In another embodiment of the present application, the fault handling system 90 and the electronic device 60 may also be separate devices (e.g., servers), and the fault handling system 90 may be connected to the electronic device 60 via a wired and/or wireless network and transmit interactive information according to an agreed data format.
Exemplary electronic device
The present application further provides an electronic device, the device comprising: the device comprises a data acquisition device, a processor and a memory;
the data acquisition device is used for acquiring data; the memory is used for storing one or more program instructions; a processor for executing one or more program instructions to perform the above-described method.
Next, an electronic apparatus according to an embodiment of the present application is described with reference to fig. 8. Fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the application.
As shown in fig. 8, the electronic device 60 includes one or more processors 601 and memory 602.
Processor 601 may be a Central Processing Unit (CPU) or other form of processing unit having data processing capabilities and/or instruction execution capabilities, and may control other components in electronic device 60 to perform desired functions.
The memory 602 may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. Volatile memory can include, for example, Random Access Memory (RAM), cache memory (or the like). The non-volatile memory may include, for example, Read Only Memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on a computer-readable storage medium and executed by processor 601 to implement the fault handling methods or other desired functions of the work machine of the various embodiments of the present application described above. Various content such as positioning error parameters may also be stored in the computer readable storage medium.
In one example, the electronic device 60 may further include: an input device 603 and an output device 604, which are interconnected by a bus system and/or other form of connection mechanism (not shown).
The input device 603 may include, for example, a keyboard, a mouse, and the like.
The output device 604 may output various information including the determined exercise data and the like to the outside. The output means 604 may comprise, for example, a display, a communication network, a remote output device connected thereto, and the like.
Of course, for the sake of simplicity, only some of the components of the electronic device 60 relevant to the present application are shown in fig. 8, and components such as a bus, an input/output interface, and the like are omitted. In addition, the electronic device 60 may include any other suitable components depending on the particular application.
Exemplary computer program product and computer-readable storage Medium
In addition to the above-described methods and apparatus, embodiments of the present application may also be a computer program product comprising computer program instructions that, when executed by a processor, cause the processor to perform the steps in the method of fault handling for a work machine according to various embodiments of the present application described in the present specification.
The computer program product may be used to write program code for performing the operations of embodiments of the present application in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server.
Furthermore, embodiments of the present application may also be a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, cause the processor to perform the steps in the method of fault handling for a work machine according to various embodiments of the present application.
A computer-readable storage medium may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may include, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The basic principles of the present application have been described above with reference to specific embodiments, but it should be noted that advantages, effects, etc. mentioned in the present application are only examples and are not limiting, and the advantages, effects, etc. must not be considered to be possessed by various embodiments of the present application. Furthermore, the foregoing disclosure of specific details is for the purpose of illustration and description and is not intended to be limiting, since the foregoing disclosure is not intended to be exhaustive or to limit the disclosure to the precise details disclosed.
The block diagrams of devices, apparatuses, systems referred to in this application are only given as illustrative examples and are not intended to require or imply that the connections, arrangements, configurations, etc. must be made in the manner shown in the block diagrams. These devices, apparatuses, devices, systems may be connected, arranged, configured in any manner, as will be appreciated by those skilled in the art. Words such as "including," "comprising," "having," and the like are open-ended words that mean "including, but not limited to," and are used interchangeably therewith. The words "or" and "as used herein mean, and are used interchangeably with, the word" and/or, "unless the context clearly dictates otherwise. The word "such as" is used herein to mean, and is used interchangeably with, the phrase "such as but not limited to".
It should also be noted that in the devices, apparatuses, and methods of the present application, the components or steps may be decomposed and/or recombined. These decompositions and/or recombinations are to be considered as equivalents of the present application.
The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the application. Thus, the present application is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
The present invention is not intended to be limited to the particular embodiments shown and described, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method of handling a failure in a work machine, comprising:
acquiring historical operation parameters of the operation machine in the working time period, wherein the historical operation parameters comprise working parameters and control parameters of the operation machine at different working time nodes;
according to the historical operation parameters, fault diagnosis and analysis are carried out; and
and outputting and/or displaying the result of the fault diagnosis analysis.
2. The fault handling method according to claim 1,
the working parameters comprise at least one of pressure of oil cylinders of all sections of arms of the working machine, included angles among all sections of arms of the working machine and vibration amplitude of all sections of arms of the working machine; the control parameters include control parameters of a remote control of the work machine and/or control parameters of an operating handle or operating buttons of the work machine.
3. The fault handling method according to claim 1, further comprising:
and acquiring the current operation parameters of the operation machine, comparing the current operation parameters with the historical operation parameters, and outputting or/and displaying the analysis result of whether the operation machine has faults or not.
4. The fault handling method of claim 1, further comprising, prior to the obtaining historical work parameters for the work machine during the operating time period:
storing the historical work parameters of the work machine over the period of operation.
5. The fault handling method of claim 4, wherein the storing the historical operating parameters of the work machine over the operating time period comprises:
measuring the operating parameters of the work machine at a plurality of the operating time nodes within the operating time period and obtaining the operating parameters of the work machine at the operating time nodes; and
and classifying the obtained operation parameters according to the types of the operation parameters to obtain a plurality of historical operation parameter sets, wherein each operation parameter in each historical operation parameter set corresponds to each working time node.
6. The fault handling method of claim 1 wherein the performing fault diagnostic analysis based on the historical operating parameters comprises:
searching abnormal working parameters according to the working parameters of the working machine at different working times, and performing fault diagnosis and analysis according to the abnormal working parameters and the control parameters of the occurrence time of the abnormal working parameters; or, according to the historical operation parameters, searching a fault database, and performing fault diagnosis analysis according to the fault database;
the outputting and/or displaying the result of the fault diagnosis analysis comprises:
and outputting the fault diagnosis and analysis result to a control terminal or a mobile terminal of the working machine, wherein the fault diagnosis and analysis result comprises a fault diagnosis conclusion and/or a fault processing flow.
7. The fault handling method of claim 1 wherein the performing fault diagnostic analysis based on the historical operating parameters further comprises:
forming a trend statistical chart from the data in the historical operation parameters;
storing the trend statistics in a historical job parameter database;
and performing fault diagnosis and analysis according to the trend statistical chart.
8. A fault handling system for a work machine, the system comprising:
the historical data acquisition module is configured to acquire historical operation parameters of the working machine in working time periods, wherein the historical operation parameters comprise working parameters and control parameters of the working machine in different working time nodes;
the fault diagnosis and analysis module is configured to carry out fault diagnosis and analysis according to the historical operation parameters; and
a result output module configured to output and/or display a result of the fault diagnosis analysis.
9. An electronic device, comprising:
the data acquisition device is used for acquiring data;
a processor; and
a memory having stored therein computer program instructions which, when executed by the processor, cause the processor to carry out the fault handling method of any of claims 1 to 7.
10. A computer-readable storage medium, having stored thereon computer program instructions, which, when executed by a processor, cause the processor to perform the fault handling method of any one of claims 1 to 7.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011640616.7A CN114764459A (en) | 2020-12-31 | 2020-12-31 | Fault processing method and system for working machine and electronic equipment |
| PCT/CN2021/103614 WO2022142223A1 (en) | 2020-12-31 | 2021-06-30 | Work machine fault processing method, system, and electronic device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011640616.7A CN114764459A (en) | 2020-12-31 | 2020-12-31 | Fault processing method and system for working machine and electronic equipment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114764459A true CN114764459A (en) | 2022-07-19 |
Family
ID=82260165
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011640616.7A Pending CN114764459A (en) | 2020-12-31 | 2020-12-31 | Fault processing method and system for working machine and electronic equipment |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN114764459A (en) |
| WO (1) | WO2022142223A1 (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115828452A (en) * | 2022-11-16 | 2023-03-21 | 华能国际电力股份有限公司上海石洞口第二电厂 | Belt sampling equipment diagnosis and optimization method and system based on Internet of things and 5G |
| CN116484268B (en) * | 2023-06-21 | 2023-09-05 | 西安黑石智能科技有限公司 | Intelligent industrial equipment fault diagnosis system based on machine learning |
| CN116588122B (en) * | 2023-07-17 | 2023-10-20 | 山东港口工程管理咨询有限公司 | Oil leakage monitoring method, equipment and medium based on remote control vehicle |
| CN117807155A (en) * | 2024-03-01 | 2024-04-02 | 深圳润世华软件和信息技术服务有限公司 | Method, equipment and storage medium for generating multi-dimensional early warning prompt information |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102313580A (en) * | 2011-09-24 | 2012-01-11 | 三一重型装备有限公司 | Fault diagnosis device and method for frequency converter of coal machine |
| CN105404281A (en) * | 2015-12-14 | 2016-03-16 | 湖南三一智能控制设备有限公司 | Fault diagnosis apparatus and method of engineering machinery |
| CN109506921A (en) * | 2018-12-24 | 2019-03-22 | 西安科技大学 | A kind of rotary machinery fault diagnosis and method for early warning |
| CN111830940A (en) * | 2020-07-24 | 2020-10-27 | 三一重机有限公司 | Engineering machine fault diagnosis method, terminal, system and electronic equipment |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160332750A1 (en) * | 2015-01-12 | 2016-11-17 | Hamilton Sundstrand Corporation | Aircraft active history memory module |
| CN109425123A (en) * | 2017-08-31 | 2019-03-05 | 青岛经济技术开发区海尔热水器有限公司 | A kind of water-heater system method for diagnosing and processing fault and system based on big data |
| CN110399926B (en) * | 2019-07-26 | 2021-11-30 | 广州辰创科技发展有限公司 | Street lamp fault diagnosis method and device |
| CN111459103B (en) * | 2020-03-21 | 2021-02-12 | 江苏科瑞德智控自动化科技有限公司 | Loom communication system based on MCGS configuration screen |
| CN111525694B (en) * | 2020-05-08 | 2021-12-31 | 广东电网有限责任公司惠州供电局 | Intelligent switch cabinet marking device and method based on Internet of things |
-
2020
- 2020-12-31 CN CN202011640616.7A patent/CN114764459A/en active Pending
-
2021
- 2021-06-30 WO PCT/CN2021/103614 patent/WO2022142223A1/en active Application Filing
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102313580A (en) * | 2011-09-24 | 2012-01-11 | 三一重型装备有限公司 | Fault diagnosis device and method for frequency converter of coal machine |
| CN105404281A (en) * | 2015-12-14 | 2016-03-16 | 湖南三一智能控制设备有限公司 | Fault diagnosis apparatus and method of engineering machinery |
| CN109506921A (en) * | 2018-12-24 | 2019-03-22 | 西安科技大学 | A kind of rotary machinery fault diagnosis and method for early warning |
| CN111830940A (en) * | 2020-07-24 | 2020-10-27 | 三一重机有限公司 | Engineering machine fault diagnosis method, terminal, system and electronic equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2022142223A1 (en) | 2022-07-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114764459A (en) | Fault processing method and system for working machine and electronic equipment | |
| CN107369303B (en) | Factory's intelligent diagnosing method, apparatus and system | |
| US8099672B2 (en) | System and method for continuous online safety and reliability monitoring | |
| US8019570B2 (en) | System and method for continuous online safety and reliability monitoring | |
| EP1111550B1 (en) | Method and system for monitoring the condition of an individual machine | |
| JP6647824B2 (en) | Error diagnosis system and error diagnosis method | |
| JP3839478B2 (en) | Method for analyzing process data of technical equipment | |
| CN112727965B (en) | Fault monitoring method and device for brake of coal mining machine | |
| JP2006277185A (en) | Failure predictive diagnosis support system | |
| EP3301528A1 (en) | Plant operation system and plant operation method | |
| JP3961018B2 (en) | Monitoring system for technical equipment | |
| KR101748282B1 (en) | Plant diagnosis system and diagnosis method using the same | |
| CN113093670A (en) | Instrument control state monitoring method, system and monitoring platform | |
| CN110442100B (en) | Thermal control intelligent DCS diagnosis early warning method and system | |
| CN116823220A (en) | Cable running state monitoring platform and equipment | |
| KR20060011136A (en) | A system for pneumatic monitoring system of the vessel | |
| JPH06271240A (en) | Trouble diagnostic device for elevator | |
| JP3178954B2 (en) | Plant monitoring equipment | |
| CN112151195B (en) | Method and device for checking potential safety hazards of power distribution equipment | |
| CN114326719A (en) | Inspection robot control method, inspection robot control system, computer equipment and storage medium | |
| WO2005013098A2 (en) | Continuous online safety and reliability monitoring | |
| US20230341844A1 (en) | Method and System for Diagnosing Messages | |
| CN113625676B (en) | Engineering machinery fault diagnosis method and system, field diagnosis device and storage medium | |
| JP7232205B2 (en) | SECURITY MONITORING SYSTEM AND SECURITY MONITORING METHOD | |
| KR20040050973A (en) | Total management system and control method for realtime monitoring of time interlock |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |