CN113110399A - Method and system for diagnosing faults of working machine - Google Patents
Method and system for diagnosing faults of working machine Download PDFInfo
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- CN113110399A CN113110399A CN202110552911.5A CN202110552911A CN113110399A CN 113110399 A CN113110399 A CN 113110399A CN 202110552911 A CN202110552911 A CN 202110552911A CN 113110399 A CN113110399 A CN 113110399A
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- G—PHYSICS
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
- G05B23/0262—Confirmation of fault detection, e.g. extra checks to confirm that a failure has indeed occurred
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- G—PHYSICS
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
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Abstract
The invention provides a method and a system for diagnosing faults of a working machine, wherein the method is applied to a terminal and comprises the following steps: receiving a first input; displaying a fault diagnosis interface in response to the first input; acquiring fault information; and displaying a fault diagnosis result on the fault diagnosis display interface based on the fault information. According to the fault diagnosis method provided by the invention, the fault information of the working machine is obtained, the fault diagnosis result is generated based on the fault information, the fault of the working machine is quickly and accurately diagnosed, the fault diagnosis result is displayed on the fault display interface, guidance is provided for fault diagnosis and maintenance, and the maintenance efficiency of the working machine is improved.
Description
Technical Field
The invention relates to the technical field of working machines, in particular to a method and a system for diagnosing faults of a working machine.
Background
The working machine is generally an electromechanical and hydraulic integrated device, and devices such as a power system, an electric control system and a hydraulic system in the working machine have complex structures. Each device of the work machine includes a plurality of actuators for performing a compound action. In the prior art, when a working machine breaks down, a professional maintenance worker is required to use special diagnosis equipment to disassemble the working machine so as to diagnose the fault. The fault diagnosis process is complex and the accuracy is low. Especially, in recent years, the electric control system is more and more widely applied to the excavator, and how to efficiently utilize the modern intelligent means to diagnose the fault becomes a problem to be solved urgently for enhancing the product value.
Disclosure of Invention
The invention provides a method and a system for diagnosing faults of a working machine, which are used for solving the defect that the fault diagnosis process of the working machine in the prior art is complex.
The invention provides a fault diagnosis method for a working machine, which is applied to a terminal and comprises the following steps:
receiving a first input;
displaying a fault diagnosis interface in response to the first input;
acquiring fault information;
and displaying a fault diagnosis result on the fault diagnosis interface based on the fault information.
According to the method for diagnosing the fault of the working machine, the step of acquiring the fault information comprises the following steps:
receiving the fault information sent by the fault diagnostor, wherein the fault information is obtained by preprocessing the fault diagnostor based on original fault data;
alternatively, the first and second electrodes may be,
receiving original fault data sent by the controller;
and obtaining the fault information based on the original fault data.
According to a method for diagnosing a fault of a working machine provided by the present invention, the displaying a fault diagnosis result on the fault diagnosis interface based on the fault information includes:
querying a fault tree based on the fault information;
generating the fault diagnosis result;
displaying the fault diagnosis result on the fault diagnosis interface;
and sending the fault information to a cloud server.
According to the work machine fault diagnosis method provided by the present invention, further comprising:
and receiving the fault diagnosis result sent by the cloud server.
The present invention also provides a work machine fault diagnosis system, including:
controllers and terminals for work machines;
the controller is used for generating original fault data based on the operation state parameters of the operation machine so that the terminal can obtain fault information;
the terminal is used for receiving a first input and responding to the first input to display a fault diagnosis interface; acquiring the fault information; and displaying a fault diagnosis result on the fault diagnosis interface based on the fault information.
According to the present invention, there is provided a work machine failure diagnosis system, further comprising:
a fault diagnostor electrically connected to the controller;
the fault diagnoser is used for acquiring the original fault data of the controller; and generating the fault information based on the original fault data and sending the fault information to the terminal.
According to the present invention, there is provided a work machine failure diagnosis system, further comprising:
the cloud server is used for receiving the fault information; and generating the fault diagnosis result based on the fault information, and sending the fault diagnosis result to the terminal.
The present invention also provides a working machine fault diagnosis device including:
a receiving module for receiving a first input;
a response module for displaying a fault diagnosis interface in response to the first input;
the acquisition module is used for acquiring fault information;
and the processing module is used for displaying and generating a fault diagnosis result on the fault diagnosis interface based on the fault information.
The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of any one of the above-mentioned work machine fault diagnosis methods.
The present disclosure also provides a non-transitory computer-readable storage medium having stored thereon a computer program that, when executed by a processor, performs the steps of the work machine fault diagnosis method as described in any one of the above.
According to the method and the system for diagnosing the faults of the working machine, the faults of the working machine are quickly and accurately diagnosed by acquiring the fault information of the working machine, the fault diagnosis result is displayed on the fault display interface based on the fault information, and the maintenance efficiency of the working machine is improved.
Drawings
In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a schematic flow chart diagram of a work machine fault diagnostic method provided by the present disclosure;
FIG. 2 is a schematic diagram of a work machine fault diagnostic system provided by the present disclosure;
FIG. 3 is a schematic structural diagram of a controller in the fault diagnosis system provided by the present invention;
FIG. 4 is a schematic structural diagram of a fault diagnosis device in the fault diagnosis system provided by the present invention;
fig. 5 is a schematic structural diagram of a terminal in the fault diagnosis system provided by the present invention;
fig. 6 is a schematic structural diagram of a cloud server in the fault diagnosis system provided in the present invention;
FIG. 7 is a schematic diagram of a diagnostic flow of the fault diagnosis system provided by the present invention;
fig. 8 is a schematic structural view of a work machine failure diagnosis device provided by the present invention;
fig. 9 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. 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.
The method for diagnosing the fault of the working machine according to the present invention is described below with reference to fig. 1, and the execution subject of the method may be the terminal 30 used by the user, and may be specifically executed by, but not limited to, hardware or software in the terminal 30.
The terminal 30 includes, but is not limited to, other portable communication devices such as a mobile phone or a tablet computer having a display screen. It should also be understood that in some embodiments, the terminal 30 may not be a portable communication device, but rather a desktop computer having a display screen.
The working machine may be a tower crane, an automobile crane, an excavator, a pile driver, a concrete machine, a road roller, a mixer truck, a heading machine, a pump truck, a fire truck or the like.
When a work machine has a fault, a user uses the terminal 30 to establish a data communication link with the work machine through various communication protocols such as CAN or WIFI.
As shown in fig. 1, the work machine fault diagnosis method includes steps 110 to 140.
Wherein the first input may be expressed in at least one of the following ways:
first, the first input may be represented as a touch input, including but not limited to a click input, a slide input, a press input, and the like.
In this embodiment, receiving the first input may be embodied as receiving a first input by a user at a display of the terminal 30.
Second, the first input may be represented as a physical key input.
In this embodiment, the body of the terminal 30 is provided with a physical key corresponding to sharing, and the receiving of the first input may be expressed as receiving the first input that the user presses the corresponding physical key.
Third, the first input may be represented as a voice input.
In this embodiment, the terminal 30 may trigger the display of the failure diagnosis interface when receiving a voice such as "start failure detection".
Of course, in other embodiments, the first input may also be in other forms, including but not limited to character input, and the like, which may be determined according to actual needs, and this is not limited in this application.
It is understood that the first input is used to enable the terminal 30 to display a fault diagnosis interface for the user to obtain fault information of the work machine after operating the fault diagnosis interface of the terminal 30, and therefore, a communication link for transmitting data information between the terminal 30 and the work machine needs to be constructed in advance.
After the terminal 30 responds to the first input, a fault diagnosis interface is displayed, and a user selects and operates a corresponding diagnosis mode on the fault diagnosis interface of the terminal 30 according to the current fault type of the working machine.
For example, a user may select to perform troubleshooting or firmware upgrades at a troubleshooting interface of terminal 30.
And step 130, acquiring fault information.
The terminal 30 acquires the fault information of the work machine, which is mainly provided by the controller 10 in the work machine, according to the selected diagnosis mode.
The controller 10 may be a vehicle controller or another controller in the work machine.
The controller 10 may control the operation of the work machine, braking energy feedback, energy management, network management, fault diagnosis, condition monitoring, and the like.
It should be noted that, in the embodiment of the present invention, the controller 10 writes a controller diagnostic program in the controller development stage, and can detect the state parameters, the port signal strength, the power hydraulic pressure, and other subsystem states generated during the operation of the work machine.
The controller 10 also includes a signal simulation and verification function, and can simulate signals of each sensor in the work machine and diagnose faults of each sensor and its circuit.
The controller 10 may perform analog signal calibration on sensors such as a displacement sensor, a position sensor, an angle sensor, a vibration sensor, a flow sensor, a speed sensor, an oil level sensor, and a temperature sensor of the work machine.
The controller 10 detects an operation state parameter, a port signal strength, and a subsystem state of the working machine, determines whether a failure occurs in the operation process of the working machine according to a detection threshold, and generates original failure data.
It can be understood that the controller 10 generates original fault data, the terminal 30 cannot diagnose a fault by using the original fault data, and after the terminal 30 acquires the original fault data detected by the controller 10, the original fault data needs to be preprocessed to obtain fault information.
The preprocessing of the raw fault data by the terminal 30 may include processing operations such as data filtering, data classification and data transformation.
It is understood that the original fault data is data directly collected by the controller 10, and cannot be visually displayed on the terminal 30, and the fault information obtained by the terminal 30 after preprocessing the original fault data can be visually displayed.
And 140, displaying a fault diagnosis result on a fault diagnosis interface based on the fault information.
The terminal 30 obtains the fault information after preprocessing the original fault data, and the terminal 30 can directly perform fault diagnosis by using the fault information.
The failure information may include information such as the contents of the failure manifestation and the detection data of the relevant failed device.
For example, after a certain centrifugal pump in the working machine shows a lift reduction, a flow shortage, an abnormal vibration, and the like, the controller 10 collects an operation state parameter, a port signal, a state parameter of a subsystem where the centrifugal pump is located, and a sensor signal simulation parameter related to the centrifugal pump.
The terminal 30 preprocesses the collected original fault data to obtain fault information related to the centrifugal pump, where the fault information may include state parameters of the centrifugal pump, such as temperature, pressure, rotation speed, and lift, and signal simulation parameters of a sensor connected to the centrifugal pump.
The terminal 30 may perform interactive analysis through a fault tree according to the fault information, or may determine the cause and location of the fault according to the historical data, generate a fault diagnosis result, and display the fault diagnosis result on a fault diagnosis interface.
It is understood that the fault diagnosis result generated by the terminal 30 may include corresponding maintenance instructions in addition to the fault location and the fault cause.
The generated fault diagnosis result is displayed on the terminal 30, and a user can more intuitively and conveniently carry out fault maintenance work according to the fault diagnosis result.
In specific implementation, taking a failed centrifugal pump as an example, the failure information is state parameters of the centrifugal pump, such as temperature, pressure, rotating speed, lift and the like, and signal simulation parameters of a sensor connected with the centrifugal pump.
The terminal 30 judges that the impeller of the centrifugal pump is corroded through fault tree interactive analysis according to the fault information, the generated fault diagnosis result comprises the position of the centrifugal pump, the fault reason is impeller corrosion, and maintenance guidance is to replace the centrifugal pump.
According to the method for diagnosing the faults of the working machine, the fault information of the working machine is acquired through the terminal 30, the faults of the working machine are quickly and accurately diagnosed, the fault diagnosis result is displayed on the fault diagnosis interface, guidance is provided for fault diagnosis and maintenance, and the maintenance efficiency of the working machine is improved.
In some embodiments, at the time of fault diagnosis, the fault diagnosis device 20 is electrically connected to the controller 10 of the work machine, and fault information after preprocessing is obtained by the fault diagnosis device 20.
The terminal 30 displays a fault diagnosis interface, receives an input for starting a corresponding diagnosis mode, and then sends a first diagnosis instruction to the fault diagnosis device 20.
The first diagnosis instruction is a control instruction that the terminal 30 sends to control the failure diagnosis device 20 to start the failure diagnosis.
Upon receiving the first diagnostic instruction, the fault diagnosis device 20 starts a fault diagnosis procedure, establishes a data communication link with the controller 10, and collects raw fault data generated by the controller 10.
When the controller diagnostic program in the controller 10 generates original fault data, the fault diagnoser 20 collects the original fault data and preprocesses the original fault data by using a filtering algorithm, so as to achieve the purposes of eliminating noise, classifying and the like.
The fault diagnotor 20 is configured with corresponding analysis software to preprocess and analyze the original fault data, and the fault diagnotor 20 can also dynamically display the vibration value, waveform and parameters of the original fault data.
The preprocessing of the raw fault data by fault diagnoser 20 may include processing operations such as data filtering, data classification, and data transformation.
It is understood that after the fault diagnoser 20 preprocesses the original fault data, it converts the data type of the original fault data to remove the noise in the data, and can directly obtain the fault information that can be displayed on the terminal 30.
The terminal 30 further performs data information statistics and display on the fault information sent by the fault diagnoser 20, performs fault diagnosis, and may perform interactive analysis through a fault tree, or may determine the cause and the position of the fault according to historical data to generate a fault diagnosis result.
It will be appreciated that when the fault diagnosis device 20 is electrically connected to the controller 10 of the work machine, a communication link for data information transmission is established, and at the same time, fault information which can be directly displayed can be provided for the terminal 30, so that the fault diagnosis speed of the terminal 30 can be increased.
Moreover, the failure diagnosis device 20 has good adaptability to the working machine, and can write a plurality of diagnosis programs, and one failure diagnosis device 20 can acquire failure information of a plurality of working machines.
In some embodiments, at the time of fault diagnosis, a communication link between controller 10 and terminal 30 of the work machine is established.
The terminal 30 displays the fault diagnosis interface and transmits a second diagnosis instruction to the controller 10 of the work machine upon receiving an input to start a corresponding diagnosis mode.
The second diagnostic instruction is the original fault data control instruction sent by the terminal 30 to control the controller 10 to generate.
After receiving the second diagnosis instruction, the controller 10 detects an operation state parameter, a port signal strength, and a subsystem state of the work machine, determines whether a fault occurs in the operation process of the work machine according to a detection threshold, and generates original fault data.
The terminal 30 receives the original fault data, and performs preprocessing operations such as data filtering, data classification, and data transformation on the original fault data to obtain fault information.
After preprocessing the original fault data, the obtained fault information is displayed on the terminal 30.
The terminal 30 performs fault diagnosis using the fault information, and may perform interactive analysis through a fault tree, or determine the cause and location of the fault according to historical data, to generate a fault diagnosis result.
The fault diagnosis result generated by the terminal 30 includes the fault position, the fault reason and the maintenance guidance, so that the user can more intuitively and conveniently perform the maintenance work of the fault according to the fault diagnosis result.
The fault information of the working machine is acquired through the terminal 30, the fault diagnosis result is generated, the fault of the working machine is diagnosed rapidly and accurately, the fault diagnosis process of the working machine is simplified, and the fault diagnosis can be realized by directly using the terminal 30.
In some embodiments, in step 130, a fault diagnosis result is generated by querying the fault tree based on the fault information, and the fault diagnosis result is displayed on the fault diagnosis interface.
The fault tree is a special inverted tree logic cause and effect relationship diagram, which uses event symbols, logic gate symbols and transfer symbols to describe the cause and effect relationship among various events in the system, and uses the fault tree to diagnose and analyze faults, and is a deductive failure analysis from top to bottom.
The terminal 30 has a corresponding fault tree interaction unit 33, and when the terminal 30 obtains fault information, a fault diagnosis result is generated by querying the fault tree based on the fault information and displayed on a fault diagnosis interface.
Taking a centrifugal pump fault as an example, fault information related to the centrifugal pump is input in the fault tree interaction unit 33, and the fault information may include state parameters of the centrifugal pump, such as temperature, pressure, rotation speed, and lift, and signal simulation parameters of a sensor connected to the centrifugal pump.
The terminal 30 performs interactive query through a fault tree, eliminates faults of a centrifugal pump shaft, a bearing and a pump shell, and judges that an impeller of the centrifugal pump is corroded.
The terminal 30 generates a fault diagnosis result including the position of the centrifugal pump, the fault causes are impeller corrosion, the maintenance guide is to replace the centrifugal pump, and a user can maintain and replace the centrifugal pump at the corresponding position according to the fault diagnosis result.
The terminal 30 may also interact with the cloud server 40, and the terminal 30 sends the fault information to the cloud server 40, and performs fault diagnosis through the cloud server 40 to generate a fault diagnosis result.
The cloud server 40 stores production information tracking and diagnosis communication protocols and related fault auxiliary information related to the work machine diagnosis.
When the terminal 30 is connected to the cloud server 40, both ends can transmit and download data, and the cloud server 40 has a stronger analysis and storage capability than the terminal 30.
For example, the terminal 30 is connected to a 5G network, so as to perform data transmission with the cloud server 40, thereby completing data synchronization.
The terminal 30 is connected to the cloud server 40, and sends the fault information of the current fault to the cloud server 40, and the cloud server 40 generates a fault diagnosis result by means of the strong data analysis capability and data storage capacity of the cloud server 40.
In some embodiments, the terminal 30 may receive the fault diagnosis result sent by the cloud server 40.
The terminal 30 sends the fault information to the cloud server 40, and performs fault diagnosis through the cloud server 40 to generate a fault diagnosis result.
The cloud server 40 sends the generated fault diagnosis result to the terminal 30, and the terminal 30 may display the fault diagnosis result sent by the cloud server 40 on a fault diagnosis interface.
It is understood that the fault diagnosis result generated by the cloud server 40 also includes information such as a fault reason, a fault location, and a maintenance instruction.
The fault diagnosis result generated by the cloud server 40 is combined with more fault history data of different operation machines, so that the fault diagnosis result is more accurate, and the diagnosis process is quicker.
The cloud server 40 may also perform auxiliary services for firmware upgrade of the controller 10 of the work machine, and after the cloud server 40 is connected to the terminal 30, the firmware upgrade of the controller 10 of the work machine connected to the terminal 30 may be directly assisted.
As shown in fig. 2, the present invention also provides a work machine fault diagnosis system including: a controller 10 of a work machine, and a terminal 30.
The terminal 30 is a main device for receiving a user operation, and the terminal 30 has therein hardware or software that performs the above-described failure diagnosis method.
The terminal 30 may be a device comprising a display and a touch sensitive surface including, but not limited to, other portable communication devices such as mobile phones or tablets, and devices with data processing capabilities such as desktop computers.
The working machine may be a tower crane, an automobile crane, an excavator, a pile driver, a concrete machine, a road roller, a mixer truck, a heading machine, a pump truck, a fire truck or the like.
When a work machine malfunctions, a user uses the terminal 30 to establish a data communication link with the controller 10 of the work machine through various communication protocols such as CAN or WIFI.
The controller 10 is configured to generate raw fault data based on the operating state parameters of the work machine for the terminal 30 to obtain fault information.
The controller 10 may be a vehicle controller 10, and may be used to control the operation of the work machine, braking energy feedback, energy management, network management, fault diagnosis, status monitoring, and the like.
The controller 10 writes a controller diagnostic program in a controller development stage, and as shown in fig. 3, after the controller 10 is developed, the controller includes a port signal detection unit 11, a system state detection unit 12, a subsystem state detection unit 13, and a signal simulation verification unit 14.
The port signal detection unit 11 of the controller 10 mainly detects each port signal in the work machine, and collects state parameters related to the strength of the signal.
The system state detection unit 12 and the sub-system state detection unit 13 of the controller 10 mainly detect the states of the control system, the power system, and the hydraulic system of the work machine.
The signal simulation verification unit 14 of the controller 10 may implement a signal simulation verification function, and may simulate signals of each sensor installed in the work machine to diagnose faults of each sensor and its line.
The sensors include, but are not limited to, displacement sensors, position sensors, angle sensors, vibration sensors, flow sensors, speed sensors, fuel level sensors, and temperature sensors.
The controller 10 detects an operation state parameter, a port signal strength, and a subsystem state of the working machine, determines whether a failure occurs in the operation process of the working machine according to a detection threshold, and generates original failure data.
It can be understood that the controller 10 detects that the generated original fault data is the original fault data, the terminal 30 cannot diagnose the fault by using the original fault data, and after the terminal 30 obtains the original fault data detected by the controller 10, the original fault data needs to be preprocessed to obtain the fault information.
The terminal 30 is used for receiving a first input and responding to the first input to display a fault diagnosis interface; and acquiring fault information, wherein the first input is used for calling an instruction for displaying a fault diagnosis interface, and the fault diagnosis interface is displayed for a user to select a corresponding diagnosis mode.
The original fault data is data directly acquired by the controller 10, and cannot be visually displayed on the terminal 30, and the fault information obtained by preprocessing the original fault data by the terminal 30 can be visually displayed.
The terminal 30 obtains the fault information after preprocessing the original fault data, and the terminal 30 can directly perform fault diagnosis by using the fault information to generate a fault diagnosis result.
As shown in fig. 5, the terminal 30 includes a port signal diagnosis unit 31, an auxiliary maintenance unit 32, a fault tree interaction unit 33, and a remote service unit 34.
And the port signal diagnosis unit 31 is configured to perform fault diagnosis on the port signal information in the fault information, and determine whether each port has a fault.
The fault tree interaction unit 33 is configured to generate a fault diagnosis result by querying the fault tree based on the fault information.
The remote service unit 34 is used to establish contact with a remote location, such as the cloud server 40, for data transmission and analysis.
The auxiliary maintenance unit 32 is configured to provide a maintenance instruction based on the fault cause and the fault result generated by the terminal 30, and further refine the fault diagnosis result generated by the terminal 30.
For example, after a centrifugal pump in the working machine shows a decrease in lift, an insufficient flow rate, and abnormal vibration, the controller 10 collects an operation state parameter of the centrifugal pump, a port signal, a state parameter of a subsystem where the centrifugal pump is located, and a signal simulation parameter of a sensor associated with the centrifugal pump.
The terminal 30 preprocesses the collected original fault data to obtain fault information related to the centrifugal pump, where the fault information may include state parameters of the centrifugal pump, such as temperature, pressure, rotation speed, and lift, and signal simulation parameters of a sensor connected to the centrifugal pump.
The terminal 30 may perform interactive analysis through a fault tree according to the fault information, or may determine the cause, location, and maintenance instruction of the fault according to the historical data, generate a fault diagnosis result, and assist the user in performing fault maintenance.
In specific implementation, taking a failed centrifugal pump as an example, the failure information is state parameters of the centrifugal pump, such as temperature, pressure, rotating speed, lift and the like, and signal simulation parameters of a sensor connected with the centrifugal pump.
The terminal 30 judges that the impeller of the centrifugal pump is corroded through fault tree interactive analysis according to the fault information, the generated fault diagnosis result comprises the position of the centrifugal pump, the fault reason is impeller corrosion, and maintenance guidance is to replace the centrifugal pump.
According to the fault diagnosis system of the working machine, the controller 10 is used for collecting original fault data, the terminal 30 receives the original fault data for processing to obtain fault information, a fault diagnosis result is generated and displayed, the fault diagnosis process of the working machine is simplified, the fault diagnosis can be realized by directly using the terminal 30, and the maintenance efficiency of the working machine is improved
In some embodiments, as shown in FIG. 2, the work machine fault diagnostic system further includes a fault diagnoser 20.
At the time of failure diagnosis, the controller 10 of the working machine is electrically connected to the failure diagnosis device 20, and failure information after preprocessing is obtained by the failure diagnosis device 20.
The terminal 30 displays a fault diagnosis interface, receives a corresponding diagnosis mode selected by a user, sends a first diagnosis instruction, controls the fault diagnosis device 20 to start fault diagnosis, and the fault diagnosis device 20 collects original fault data generated by the controller 10, preprocesses the original fault data to generate fault information for the terminal 30 to perform fault diagnosis.
When the controller diagnostic program in the controller 10 generates original fault data, the fault diagnoser 20 collects the original fault data and preprocesses the original fault data by using a filtering algorithm, so as to achieve the purposes of eliminating noise, classifying and the like.
The fault diagnotor 20 is configured with corresponding analysis software to preprocess and analyze the original fault data, and the fault diagnotor 20 can also dynamically display the vibration value, waveform and parameters of the original fault data.
The preprocessing of the raw fault data by fault diagnoser 20 may include processing operations such as data filtering, data classification, and data transformation.
As shown in fig. 4, the fault diagnosis device 20 includes a data transmitting and receiving unit 21, a data processing unit 22, and a network connection unit 23.
The data transceiver 21 is configured to receive original fault data generated by the controller 10, the data processing unit 22 is configured to preprocess the original fault data, and the network connection unit 23 is configured to send fault information obtained through the preprocessing to the terminal 30.
It is understood that after the fault diagnoser 20 preprocesses the original fault data, it converts the data type of the original fault data to remove the noise in the data, and can directly obtain the fault information that can be displayed on the terminal 30.
The terminal 30 further performs data information statistics and display on the fault information sent by the fault diagnoser 20, performs fault diagnosis, and may perform interactive analysis through a fault tree, or may determine the cause and the position of the fault according to historical data to generate a fault diagnosis result.
It will be appreciated that when the fault diagnosis device 20 is electrically connected to the controller 10 of the work machine, a communication link for data information transmission is established, and at the same time, fault information which can be directly displayed can be provided for the terminal 30, so that the fault diagnosis speed of the terminal 30 can be increased.
Moreover, the failure diagnosis device 20 has good adaptability to the working machine, and can write a plurality of diagnosis programs, and one failure diagnosis device 20 can acquire failure information of a plurality of working machines.
In some embodiments, as shown in fig. 2, the work machine fault diagnosis system further includes a cloud server 40, and the terminal 30 and the cloud server 40 cooperate to perform fault diagnosis to generate a fault diagnosis result.
When the terminal 30 is connected to the cloud server 40, both ends can transmit and download data, and the cloud server 40 has a stronger analysis and storage capability than the terminal 30.
For example, the terminal 30 is connected to a 5G network, and performs data transmission with the cloud server 40 to complete data synchronization.
As shown in fig. 6, the cloud server 40 includes a production information tracking unit 41, a maintenance data unit 42, an operation information tracking unit 43, a failure prediction analysis unit 44, and a web monitoring unit 45.
The production information tracking unit 41 is used for tracking production information of the working machine, the operation information tracking unit 43 is used for tracking operation information of the working machine, and the failure prediction analysis unit 44 is used for realizing failure diagnosis and prediction according to the production information, the operation information and the failure information of the working machine.
The web page monitoring unit 45 of the cloud server 40 may provide real-time monitoring web pages for production information, operation information, and fault information of the work machine.
The terminal 30 is connected to the cloud server 40, and sends the fault information of the current fault to the cloud server 40, and after receiving the fault information, the cloud server 40 generates a fault diagnosis result by means of its strong data analysis capability and data storage capacity.
A troubleshooting data unit 42 in cloud server 40 may provide a repair indication for the current failure of the work machine in conjunction with big data analysis.
It is understood that the fault diagnosis result generated by the cloud server 40 also includes information such as a fault reason, a fault location, and a maintenance instruction.
The fault diagnosis result generated by the cloud server 40 is combined with more fault history data of different operation machines, so that the fault diagnosis result is more accurate, and the diagnosis process is quicker.
The cloud server 40 may also perform auxiliary services for firmware upgrade of the controller 10 of the work machine, and after the cloud server 40 is connected to the terminal 30, the firmware upgrade of the controller 10 of the work machine connected to the terminal 30 may be directly assisted.
A specific embodiment is described below.
As shown in fig. 7, a user may diagnose and assist in maintenance of a work machine by the following steps.
When a work machine fault expression 700 occurs, it is first determined whether the fault expression is an expression of poor performance or poor operational coordination 710 or a work machine fault 720.
If the performance of the fault expression 700 is poor or the operational coordination is poor 710, the user may initiate a firmware upgrade process 721 in the fault diagnosis system 711 to perform a firmware upgrade operation on the work machine.
It will be appreciated that cloud server 40 in troubleshooting system 711 may provide significant support and service for firmware upgrades to work machines.
When the fault representation 700 pertains to a work machine fault 720, the user determines whether the work machine is currently in a stopped state 721 and whether the work machine in the stopped state can still be started 721.
For the working machine in the operating state of the opening machine, the user electrically connects the fault diagnosis device 20 in the fault diagnosis system 723 to the controller 10 of the working machine, selects the port signal diagnosis mode on the fault diagnosis interface of the terminal 30, and sends a corresponding diagnosis control instruction through the terminal 30 to perform port signal diagnosis 724.
After the terminal 30 generates and displays the diagnosis result 725, the user can perform maintenance according to the fault maintenance instruction in the diagnosis result 725.
For the operation machine which cannot be started, a user utilizes the fault diagnosis system to perform fault tree query 731, the user selects a fault tree query mode on a fault diagnosis interface of a terminal 730 of the fault diagnosis system, and after a fault result is obtained, maintenance is finished 732 according to a fault maintenance instruction.
It can be understood that, in the actual diagnosis operation of the fault diagnosis system, the user may adjust whether to connect the fault diagnosis device 20 and whether to use the cloud server 40 according to different fault conditions and the current maintenance conditions.
The following describes a working machine failure diagnosis apparatus provided by the present invention, and the working machine failure diagnosis apparatus described below and the working machine failure diagnosis method described above may be referred to in correspondence with each other.
As shown in fig. 8, the present invention provides a work machine failure diagnosis device including:
a receiving module 810 for receiving a first input;
a response module 820 for displaying a fault diagnosis interface in response to the first input;
an obtaining module 830, which obtains fault information;
and the processing module 840 is configured to display a fault diagnosis result on the fault diagnosis interface based on the fault information.
According to the work machine fault diagnosis system provided by the invention, the fault diagnosis result is generated based on the fault information by acquiring the fault information of the work machine, the fault of the work machine is quickly and accurately diagnosed, the fault position, the fault reason and the maintenance guidance are provided, and the maintenance efficiency of the work machine is improved.
In some embodiments, when fault diagnoser 20 is electrically connected to controller 10 of a work machine, acquisition module 830 is further configured to,
and receiving fault information sent by the fault diagnostor 20, wherein the fault information is obtained by preprocessing the fault diagnostor 20 based on original fault data.
In some embodiments, when the terminal 30 is connected to the controller 10 of the work machine, the obtaining module 830 is further configured to receive raw fault data sent by the controller 10; based on the original fault data, fault information is obtained.
In some embodiments, the processing module 840 is further configured to query a fault tree based on the fault information; generating a fault diagnosis result; and displaying a fault diagnosis result on a fault diagnosis interface.
In some embodiments, the processing module 840 is further configured to send the failure information to the cloud server 40; and receiving the fault diagnosis result sent by the cloud server 40.
Fig. 9 illustrates a physical structure diagram of an electronic device, and as shown in fig. 9, the electronic device may include: a processor (processor)910, a communication Interface (Communications Interface)920, a memory (memory)930, and a communication bus 940, wherein the processor 910, the communication Interface 920, and the memory 930 communicate with each other via the communication bus 940. Processor 910 may invoke logic instructions in memory 930 to perform a work machine fault diagnosis method comprising: receiving a first input; displaying a fault diagnosis interface in response to the first input; acquiring fault information; and displaying a fault diagnosis result on a fault diagnosis interface based on the fault information.
Furthermore, the logic instructions in the memory 930 may be implemented in software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, the present disclosure also provides a computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions that, when executed by a computer, enable the computer to perform a method for diagnosing a fault of a work machine provided by the above methods, the method comprising: receiving a first input; displaying a fault diagnosis interface in response to the first input; acquiring fault information; and displaying a fault diagnosis result on a fault diagnosis interface based on the fault information.
In yet another aspect, the present disclosure also provides a non-transitory computer-readable storage medium having stored thereon a computer program that, when executed by a processor, is implemented to perform the method for fault diagnosis of a work machine provided in each of the above aspects, the method comprising: receiving a first input; displaying a fault diagnosis interface in response to the first input; acquiring fault information; and displaying a fault diagnosis result on a fault diagnosis interface based on the fault information.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method of diagnosing a fault in a work machine, applied to a terminal, the method comprising:
receiving a first input;
displaying a fault diagnosis interface in response to the first input;
acquiring fault information;
and displaying a fault diagnosis result on the fault diagnosis interface based on the fault information.
2. The work machine fault diagnosis method according to claim 1, wherein the acquiring fault information includes:
receiving the fault information sent by the fault diagnostor, wherein the fault information is obtained by preprocessing the fault diagnostor based on original fault data;
alternatively, the first and second electrodes may be,
receiving original fault data sent by a controller;
and obtaining the fault information based on the original fault data.
3. The work machine fault diagnosis method according to claim 1 or 2, wherein the displaying a fault diagnosis result on the fault diagnosis interface based on the fault information includes:
querying a fault tree based on the fault information;
generating the fault diagnosis result;
displaying the fault diagnosis result on the fault diagnosis interface;
and sending the fault information to a cloud server.
4. The work machine fault diagnosis method according to claim 3, characterized by further comprising:
and receiving the fault diagnosis result sent by the cloud server.
5. A work machine fault diagnostic system, comprising:
controllers and terminals for work machines;
the controller is used for generating original fault data based on the operation state parameters of the operation machine so that the terminal can obtain fault information;
the terminal is used for receiving a first input and responding to the first input to display a fault diagnosis interface; acquiring the fault information; and displaying a fault diagnosis result on the fault diagnosis interface based on the fault information.
6. The work machine fault diagnostic system of claim 5, further comprising:
a fault diagnostor electrically connected to the controller;
the fault diagnoser is used for acquiring the original fault data of the controller; and generating the fault information based on the original fault data and sending the fault information to the terminal.
7. The work machine fault diagnostic system according to claim 5 or 6, characterized by further comprising:
the cloud server is used for receiving the fault information; and generating the fault diagnosis result based on the fault information, and sending the fault diagnosis result to the terminal.
8. A work machine fault diagnosis device characterized by comprising:
a receiving module for receiving a first input;
a response module for displaying a fault diagnosis interface in response to the first input;
the acquisition module is used for acquiring fault information;
and the processing module is used for displaying a fault diagnosis result on the fault diagnosis interface based on the fault information.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the steps of the work machine fault diagnosis method according to any one of claims 1 to 4 are implemented when the processor executes the program.
10. A non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the work machine fault diagnosis method according to any one of claims 1 to 4.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114734974A (en) * | 2022-04-26 | 2022-07-12 | 三一电动车科技有限公司 | Vehicle brake system fault diagnosis method, device and system and vehicle |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1462328A (en) * | 2001-05-08 | 2003-12-17 | 日立建机株式会社 | Working machine, trouble diagnosis system of working machine, and maintenance system of working machine |
| KR20130063866A (en) * | 2011-12-07 | 2013-06-17 | 모다정보통신 주식회사 | Diagonosis system for m2m device and the method thereof |
| CN103558845A (en) * | 2013-11-08 | 2014-02-05 | 株洲时代电子技术有限公司 | Fault diagnosis system for rail grinding wagon |
| CN105302120A (en) * | 2015-11-19 | 2016-02-03 | 广州云湾信息技术有限公司 | Remote service device, system and method of intelligent equipment |
| CN107244600A (en) * | 2017-07-03 | 2017-10-13 | 申芝电梯有限公司 | A kind of commercial elevator intelligent monitoring system based on Internet of Things |
| CN109689470A (en) * | 2017-07-14 | 2019-04-26 | 株式会社东芝 | Apparatus for diagnosis of abnormality, abnormality diagnostic method and computer program |
| CN112327808A (en) * | 2020-11-09 | 2021-02-05 | 深圳市道通科技股份有限公司 | Automobile fault diagnosis method and system and automobile fault diagnosis instrument |
-
2021
- 2021-05-20 CN CN202110552911.5A patent/CN113110399A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1462328A (en) * | 2001-05-08 | 2003-12-17 | 日立建机株式会社 | Working machine, trouble diagnosis system of working machine, and maintenance system of working machine |
| KR20130063866A (en) * | 2011-12-07 | 2013-06-17 | 모다정보통신 주식회사 | Diagonosis system for m2m device and the method thereof |
| CN103558845A (en) * | 2013-11-08 | 2014-02-05 | 株洲时代电子技术有限公司 | Fault diagnosis system for rail grinding wagon |
| CN105302120A (en) * | 2015-11-19 | 2016-02-03 | 广州云湾信息技术有限公司 | Remote service device, system and method of intelligent equipment |
| CN107244600A (en) * | 2017-07-03 | 2017-10-13 | 申芝电梯有限公司 | A kind of commercial elevator intelligent monitoring system based on Internet of Things |
| CN109689470A (en) * | 2017-07-14 | 2019-04-26 | 株式会社东芝 | Apparatus for diagnosis of abnormality, abnormality diagnostic method and computer program |
| CN112327808A (en) * | 2020-11-09 | 2021-02-05 | 深圳市道通科技股份有限公司 | Automobile fault diagnosis method and system and automobile fault diagnosis instrument |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114734974A (en) * | 2022-04-26 | 2022-07-12 | 三一电动车科技有限公司 | Vehicle brake system fault diagnosis method, device and system and vehicle |
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Application publication date: 20210713 |