CN116527538B - Intelligent equipment fault state diagnosis method and system based on big data - Google Patents
Intelligent equipment fault state diagnosis method and system based on big data Download PDFInfo
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- 238000004891 communication Methods 0.000 claims description 6
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
- H04L43/0805—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability
- H04L43/0817—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability by checking functioning
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
- H04L43/0805—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability
- H04L43/0811—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability by checking connectivity
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Abstract
The invention discloses a fault state diagnosis method and a fault state diagnosis system for intelligent equipment based on big data.A fault diagnosis server sends a fault diagnosis instruction of a first operation part to intelligent equipment to be diagnosed, and the fault diagnosis server receives a first fault message of the first operation part sent by the intelligent equipment to be diagnosed; the fault diagnosis server receives a second fault message of a second operation part sent by the intelligent equipment to be diagnosed, and determines a fault message set; when the fault diagnosis server determines that the characteristic parameters of the next operation part of the current operation part of the intelligent equipment carried in the first fault message in the fault message set are the same as the characteristic parameters of the current operation part of the intelligent equipment carried in the second fault message in the fault message set. The invention can effectively diagnose the fault state under the scene of multiple intelligent devices and accurately early warn the fault state.
Description
Technical Field
The invention relates to the technical field of intelligent equipment, in particular to an intelligent equipment fault state diagnosis method and system based on big data.
Background
In recent years, high-rise buildings, high-rise apartments and the like are increasing, and once intelligent equipment fails and the like, households cannot use the intelligent equipment, so that the intelligent equipment brings great trouble to the households. Therefore, it is important for the maintenance management company of the smart device to send maintenance personnel to the installation site of the smart device at regular intervals, to diagnose the state of the smart device by the maintenance personnel, and to prevent the malfunction.
However, in the fault diagnosis method in the prior art, the electrical system is always kept in an electrified state in the fault diagnosis process of the intelligent equipment, when a certain electrical element of the electrical system is in fault but not diagnosed by adopting the diagnosis method, a worker judges that the electrical system is normal through experience, then the intelligent equipment is continuously operated by using the control cabinet to diagnose whether the mechanical system is in fault or not, and the fault exists in the electrical system at the moment, so that the fault cannot be diagnosed in the step, that is, when the electrical system is kept in the electrified state, the situation that whether the intelligent equipment is in mechanical or electrical system is in fault cannot be rapidly judged by adopting the diagnosis method exists.
Disclosure of Invention
In order to solve the problems of inaccurate and untimely fault state diagnosis of the current intelligent equipment, the invention provides a method and a system for diagnosing the fault state of the intelligent equipment based on big data.
According to a first aspect of the invention, the invention claims a fault state diagnosis method of intelligent equipment based on big data, the method comprises the following steps:
the method comprises the steps that a fault diagnosis server sends a fault diagnosis instruction of a first operation part to intelligent equipment to be diagnosed, wherein the fault diagnosis instruction comprises characteristic parameters and indication information of the intelligent equipment to be diagnosed;
the fault diagnosis server receives a first fault message of a first operation part sent by the intelligent equipment to be diagnosed, wherein the first fault message is a fault response message generated by the first operation part of the intelligent equipment to be diagnosed in response to the fault diagnosis instruction sent by the fault diagnosis server, the first fault message comprises a characteristic parameter of the intelligent equipment to be diagnosed, a first sensor characteristic parameter, a characteristic parameter of the first operation part of the intelligent equipment to be diagnosed, a time when the first operation part of the intelligent equipment to be diagnosed receives the fault diagnosis instruction, and a characteristic parameter of a next operation part of the first operation part of the intelligent equipment to be diagnosed, the first sensor characteristic parameter is determined by the first operation part of the intelligent equipment to be diagnosed according to indication information in the fault diagnosis instruction sent by the fault diagnosis server, the first sensor characteristic parameter is used for representing generation time of the first fault message, and the fault diagnosis server receives a plurality of fault messages containing generation time;
The fault diagnosis server receives a second fault message of a second operation part sent by the intelligent equipment to be diagnosed, the second fault message is a fault response message generated by the second operation part of the intelligent equipment to be diagnosed in response to the fault diagnosis instruction of the first operation part sent by the intelligent equipment to be diagnosed, the next operation part of the first operation part of the intelligent equipment to be diagnosed is the second operation part of the intelligent equipment to be diagnosed, the second fault message comprises a characteristic parameter of the intelligent equipment to be diagnosed, a characteristic parameter of a second sensor, the characteristic parameter of the second operation part of the intelligent equipment to be diagnosed, the time when the second operation part of the intelligent equipment to be diagnosed receives the fault diagnosis instruction of the first operation part sent by the intelligent equipment to be diagnosed, the characteristic parameter of the first operation part of the intelligent equipment to be diagnosed and the characteristic parameter of the next operation part of the second operation part of the intelligent equipment to be diagnosed, the second sensor characteristic parameter is the characteristic parameter of the second operation part to be diagnosed, the second fault message is generated by the second operation part to be diagnosed, and the fault message is generated by the second fault message, the fault response message is generated by the first fault diagnosis instruction, and the fault message is generated by the second fault message;
The fault diagnosis server determining a set of fault messages, the set of fault messages comprising at least one fault message;
when the fault diagnosis server determines that the characteristic parameter of the next operation part of the current operation part of the intelligent equipment carried in the first fault message in the fault message set is the same as the characteristic parameter of the current operation part of the intelligent equipment carried in the second fault message in the fault message set, the fault diagnosis server determines that the first operation part of the intelligent equipment to be diagnosed and the second operation part of the intelligent equipment to be diagnosed are adjacent intelligent equipment operation parts.
Further, before the fault diagnosis server sends the fault diagnosis instruction of the first operation part to the intelligent device to be diagnosed, the method further includes:
the fault diagnosis server encapsulates the characteristic parameters of the fault transaction to be diagnosed and the indication information to generate fault description, wherein the fault description is the fault diagnosis instruction, and the characteristic parameters of the fault transaction to be diagnosed and the indication information are carried in a relation table of the fault description; or (b)
The fault diagnosis server adds the characteristic parameters of the fault transaction to be diagnosed, the indication information and fingerprint information into the service diagnosis instruction generated by the fault diagnosis server according to the application program to obtain the service diagnosis instruction carrying the fault diagnosis instruction, wherein the fingerprint information is used for indicating that the service diagnosis instruction carrying the fault diagnosis instruction carries the fault diagnosis instruction.
Further, the first fault message carries a characteristic parameter of a current operation part of the intelligent device and a characteristic parameter of a next operation part of the current operation part of the intelligent device, the characteristic parameter of the current operation part of the intelligent device carried in the first fault message is a characteristic parameter of a first operation part of the intelligent device to be diagnosed, the characteristic parameter of the next operation part of the current operation part of the intelligent device carried in the first fault message is a characteristic parameter of a second operation part of the intelligent device to be diagnosed, the characteristic parameter of the current operation part of the intelligent device carried in the second fault message is a characteristic parameter of a second operation part of the intelligent device to be diagnosed.
Further, each fault message in the fault message set carries a sensor characteristic parameter, a characteristic parameter of a current operating part of the intelligent device, and a characteristic parameter of a next operating part of the current operating part of the intelligent device, and the method includes:
the fault diagnosis server determines a specific fault message from the plurality of fault messages, wherein the value of the sensor characteristic parameter carried in the specific fault message is larger than the values of the sensor characteristic parameters carried in other fault messages in the plurality of fault messages;
the fault diagnosis server determines whether fault information of the intelligent equipment operation part indicated by the characteristic parameter of the next operation part of the intelligent equipment current operation part carried in the specific fault information is received or not;
when the fault diagnosis server determines that the fault message of the intelligent device operation part indicated by the characteristic parameter of the next operation part of the intelligent device current operation part carried in the specific fault message is not received, determining that the intelligent device operation part indicated by the characteristic parameter of the next operation part of the intelligent device current operation part carried in the specific fault message is the intelligent device operation part with the fault.
Further, the method further comprises:
the fault diagnosis server determines a difference value between the time when the second operation part of the intelligent equipment to be diagnosed receives the fault diagnosis instruction and the time when the first operation part of the intelligent equipment to be diagnosed receives the fault diagnosis instruction according to the time when the first operation part of the intelligent equipment to be diagnosed receives the fault diagnosis instruction, which is carried in the first fault message, and the time when the second operation part of the intelligent equipment to be diagnosed receives the fault diagnosis instruction, which is carried in the second fault message;
and when the difference value is larger than a preset threshold value, the fault diagnosis server determines that a communication line between the first operation part of the intelligent equipment to be diagnosed and the second operation part of the intelligent equipment to be diagnosed has faults.
According to a second aspect of the present invention, the present invention claims a fault state diagnosis system for intelligent equipment based on big data, which is characterized in that the system comprises a sending unit, a receiving unit and a processing unit;
the sending unit is used for sending a fault diagnosis instruction to a first operation part of the intelligent equipment to be diagnosed, wherein the fault diagnosis instruction comprises characteristic parameters and indication information of the intelligent equipment to be diagnosed;
The receiving unit is configured to receive a first fault message of a first operation component sent by the to-be-diagnosed smart device, where the first fault message is a fault response message generated by the first operation component of the to-be-diagnosed smart device in response to the fault diagnosis instruction sent by the fault diagnosis server, the first fault message includes a feature parameter of the to-be-diagnosed smart device, a first sensor feature parameter, a feature parameter of the to-be-diagnosed smart device, a time when the first operation component of the to-be-diagnosed smart device receives the fault diagnosis instruction, and a feature parameter of a next operation component of the first operation component of the to-be-diagnosed smart device, where the first sensor feature parameter is determined by the first operation component of the to-be-diagnosed smart device according to the indication information in the fault diagnosis instruction sent by the fault diagnosis server, and the first sensor feature parameter is used to characterize a generation time of the first fault message, and the fault diagnosis server receives a plurality of fault messages including the generation time; and receiving a second fault message of a second operating part sent by the intelligent device to be diagnosed, wherein the second fault message is a fault response message generated by the second operating part of the intelligent device to be diagnosed in response to the fault diagnosis instruction of the first operating part sent by the intelligent device to be diagnosed, a next operating part of the first operating part of the intelligent device to be diagnosed is the second operating part of the intelligent device to be diagnosed, the second fault message comprises a characteristic parameter of the intelligent device to be diagnosed, a characteristic parameter of a second sensor, the characteristic parameter of the second operating part of the intelligent device to be diagnosed, a time when the second operating part of the intelligent device to be diagnosed receives the fault diagnosis instruction of the first operating part sent by the intelligent device to be diagnosed, the characteristic parameter of the first operating part of the intelligent device to be diagnosed and a characteristic parameter of a next operating part of the second operating part of the intelligent device to be diagnosed, the second fault message is generated by the second operating part to be diagnosed, the second operating part to be diagnosed is a fault response message generated by the second operating part to be diagnosed, the first fault message is generated by the second fault message, and the fault response message is generated by the second fault message;
The processing unit is used for determining a fault message set, wherein the fault message set comprises at least one fault message; and when the fault diagnosis server determines that the characteristic parameter of the next operation part of the current operation part of the intelligent device carried in the first fault message in the fault message set is the same as the characteristic parameter of the current operation part of the intelligent device carried in the second fault message in the fault message set, the fault diagnosis server determines that the first operation part of the intelligent device to be diagnosed and the second operation part of the intelligent device to be diagnosed are adjacent intelligent device operation parts.
Further, the processing unit is further configured to encapsulate the characteristic parameter of the fault transaction to be diagnosed and the indication information, and generate a fault description, where the fault description is the fault diagnosis instruction, and the characteristic parameter of the fault transaction to be diagnosed and the indication information are carried in a relationship table of the fault description; or adding the characteristic parameters of the fault transaction to be diagnosed, the indication information and fingerprint information into the service diagnosis instruction generated by the application program to obtain the service diagnosis instruction carrying the fault diagnosis instruction, wherein the fingerprint information is used for indicating that the service diagnosis instruction carrying the fault diagnosis instruction carries the fault diagnosis instruction.
Further, the first fault message carries a characteristic parameter of a current operation part of the intelligent device and a characteristic parameter of a next operation part of the current operation part of the intelligent device, the characteristic parameter of the current operation part of the intelligent device carried in the first fault message is a characteristic parameter of a first operation part of the intelligent device to be diagnosed, the characteristic parameter of the next operation part of the current operation part of the intelligent device carried in the first fault message is a characteristic parameter of a second operation part of the intelligent device to be diagnosed, the characteristic parameter of the current operation part of the intelligent device carried in the second fault message is a characteristic parameter of a second operation part of the intelligent device to be diagnosed.
Further, each fault message in the plurality of fault messages carries a sensor characteristic parameter, a characteristic parameter of a current operating part of the intelligent device and a characteristic parameter of a next operating part of the current operating part of the intelligent device;
the processing unit is further configured to determine a specific fault message from the plurality of fault messages, where a value of a sensor characteristic parameter carried in the specific fault message is greater than a value of a sensor characteristic parameter carried in other fault messages in the plurality of fault messages; determining whether a fault message of the intelligent equipment operation part indicated by the characteristic parameter of the next operation part of the intelligent equipment current operation part carried in the specific fault message is received or not; and when the fault message of the intelligent equipment operation part indicated by the characteristic parameter of the next operation part of the intelligent equipment current operation part carried in the specific fault message is not received, determining that the intelligent equipment operation part indicated by the characteristic parameter of the next operation part of the intelligent equipment current operation part carried in the specific fault message is the intelligent equipment operation part with fault.
Further, the processing unit is further configured to determine a difference value between a time when the second operation part of the intelligent device to be diagnosed receives the fault diagnosis instruction and a time when the first operation part of the intelligent device to be diagnosed receives the fault diagnosis instruction according to a time when the first operation part of the intelligent device to be diagnosed receives the fault diagnosis instruction, which is carried in the first fault message, and a time when the second operation part of the intelligent device to be diagnosed receives the fault diagnosis instruction, which is carried in the second fault message; and when the difference value is larger than a preset threshold value, the fault diagnosis server determines that a communication line between the first operation part of the intelligent equipment to be diagnosed and the second operation part of the intelligent equipment to be diagnosed has faults.
The invention discloses a fault state diagnosis method and a fault state diagnosis system for intelligent equipment based on big data.A fault diagnosis server sends a fault diagnosis instruction of a first operation part to intelligent equipment to be diagnosed, and the fault diagnosis server receives a first fault message of the first operation part sent by the intelligent equipment to be diagnosed, wherein the first fault message is a fault response message generated by the first operation part of the intelligent equipment to be diagnosed in response to the fault diagnosis instruction sent by the fault diagnosis server; the fault diagnosis server receives a second fault message of a second operation part sent by the intelligent equipment to be diagnosed, and determines a fault message set; when the fault diagnosis server determines that the characteristic parameters of the next operation part of the current operation part of the intelligent equipment carried in the first fault message in the fault message set are the same as the characteristic parameters of the current operation part of the intelligent equipment carried in the second fault message in the fault message set. The invention can effectively diagnose the fault state under the scene of multiple intelligent devices and accurately early warn the fault state.
Drawings
FIG. 1 is a workflow diagram of a method for diagnosing a fault condition of an intelligent device based on big data according to the present invention;
FIG. 2 is a second workflow diagram of a method for diagnosing a fault condition of an intelligent device based on big data according to the present invention;
FIG. 3 is a third workflow diagram of a method for diagnosing a fault condition of an intelligent device based on big data according to the present invention;
fig. 4 is a structural block diagram of an intelligent device fault state diagnosis system based on big data according to the present invention.
Detailed Description
According to a first aspect of the present invention, referring to fig. 1, the present invention claims a fault state diagnosis method for intelligent equipment based on big data, the method includes:
the fault diagnosis server sends a fault diagnosis instruction of the first operation part to the intelligent equipment to be diagnosed, wherein the fault diagnosis instruction comprises characteristic parameters and indication information of the intelligent equipment to be diagnosed;
the method comprises the steps that a fault diagnosis server receives a first fault message of a first operation part sent by an intelligent device to be diagnosed, wherein the first fault message is a fault response message generated by the first operation part of the intelligent device to be diagnosed in response to a fault diagnosis instruction sent by the fault diagnosis server, the first fault message comprises a characteristic parameter of the intelligent device to be diagnosed, a first sensor characteristic parameter, a characteristic parameter of the first operation part of the intelligent device to be diagnosed, the time for the first operation part of the intelligent device to be diagnosed to receive the fault diagnosis instruction, and a characteristic parameter of a next operation part of the first operation part of the intelligent device to be diagnosed, the first sensor characteristic parameter is determined by the first operation part of the intelligent device to be diagnosed according to indication information in the fault diagnosis instruction sent by the fault diagnosis server, the first sensor characteristic parameter is used for representing the generation time of the first fault message, and the fault diagnosis server receives a plurality of fault messages containing the generation time;
The fault diagnosis server receives a second fault message of a second operation part sent by the intelligent equipment to be diagnosed, wherein the second fault message is a fault response message generated by the second operation part of the intelligent equipment to be diagnosed in response to a fault diagnosis instruction of a first operation part sent by the intelligent equipment to be diagnosed, the next operation part of the first operation part of the intelligent equipment to be diagnosed is the second operation part of the intelligent equipment to be diagnosed, the second fault message comprises a characteristic parameter of the intelligent equipment to be diagnosed, a characteristic parameter of the second operation part of the intelligent equipment to be diagnosed, the time when the second operation part of the intelligent equipment to be diagnosed receives a fault diagnosis instruction of a first operation part sent by the intelligent equipment to be diagnosed, the characteristic parameter of the first operation part of the intelligent equipment to be diagnosed and the characteristic parameter of the next operation part of the first operation part of the intelligent equipment to be diagnosed, the second sensor characteristic parameter is determined according to the instruction information in the fault diagnosis instruction of the first operation part to be diagnosed, the second sensor characteristic parameter is used for generating a fault message containing multiple fault messages, and the fault message is generated by the second sensor, and the fault message is generated at the time when the second fault message is generated;
The fault diagnosis server determines a fault message set, wherein the fault message set comprises at least one fault message;
when the fault diagnosis server determines that the characteristic parameter of the next operation part of the current operation part of the intelligent equipment carried in the first fault message in the fault message set is the same as the characteristic parameter of the current operation part of the intelligent equipment carried in the second fault message in the fault message set, the fault diagnosis server determines that the first operation part of the intelligent equipment to be diagnosed and the second operation part of the intelligent equipment to be diagnosed are adjacent intelligent equipment operation parts.
Wherein in this embodiment the intelligent device is an elevator.
Further, before the fault diagnosis server sends the fault diagnosis instruction of the first operation part to the intelligent device to be diagnosed, the method further includes:
the fault diagnosis server encapsulates the characteristic parameters and the indication information of the fault transaction to be diagnosed to generate fault description, the fault description is a fault diagnosis instruction, and the characteristic parameters and the indication information of the fault transaction to be diagnosed are carried in a relation table of the fault description; or (b)
The fault diagnosis server adds characteristic parameters, indication information and fingerprint information of a fault transaction to be diagnosed into a service diagnosis instruction generated by the fault diagnosis server according to an application program to obtain the service diagnosis instruction carrying the fault diagnosis instruction, wherein the fingerprint information is used for indicating that the service diagnosis instruction carrying the fault diagnosis instruction carries the fault diagnosis instruction.
In the process that the intelligent equipment car moves downwards or upwards, the intelligent equipment car can enable the driving part of the hoisting rope to rotate, the operating part rotates to cut the magnetic field, and accordingly current is generated in the coil, the whole driving part forms a generator, electric energy generated by the generator is lost by load, the rotation of the rotor in the process of loss receives resistance, when the resistance and the pulling force of car movement reach a balance, the intelligent equipment car can move downwards or upwards in a mode close to a uniform speed, and accordingly the moving speed of the intelligent equipment car is close to the moving speed of the intelligent equipment car when the intelligent equipment is in fault, the sound generated by the moving operation of the intelligent equipment car is close to the moving operation of the intelligent equipment when the intelligent equipment is in fault, and whether the sound generated by the moving operation of the intelligent equipment car is in fault is convenient to judge.
Further, the first fault message carries a characteristic parameter of a current operation part of the intelligent device and a characteristic parameter of a next operation part of the current operation part of the intelligent device, the characteristic parameter of the current operation part of the intelligent device carried in the first fault message is a characteristic parameter of a first operation part of the intelligent device to be diagnosed, the characteristic parameter of the next operation part of the current operation part of the intelligent device carried in the first fault message is a characteristic parameter of a second operation part of the intelligent device to be diagnosed, the characteristic parameter of the current operation part of the intelligent device carried in the second fault message is a characteristic parameter of the second operation part of the intelligent device to be diagnosed.
Further, referring to fig. 2, each fault message in the fault message set carries a sensor feature parameter, a feature parameter of a current operating part of the intelligent device, and a feature parameter of a next operating part of the current operating part of the intelligent device, and the method includes:
the fault diagnosis server determines a specific fault message from the plurality of fault messages, wherein the value of the sensor characteristic parameter carried in the specific fault message is larger than the values of the sensor characteristic parameters carried in other fault messages in the plurality of fault messages;
the fault diagnosis server determines whether fault information of the intelligent equipment operation part indicated by the characteristic parameter of the next operation part of the intelligent equipment current operation part carried in the specific fault information is received;
when the fault diagnosis server determines that the fault message of the intelligent device operation part indicated by the characteristic parameter of the next operation part of the intelligent device current operation part carried in the specific fault message is not received, determining that the intelligent device operation part indicated by the characteristic parameter of the next operation part of the intelligent device current operation part carried in the specific fault message is the intelligent device operation part with the fault.
Wherein in this embodiment the coefficient of friction between the power components is obtained by the vertically running acceleration of the smart device. The friction coefficient between the power components here may be the friction coefficient between the rotor groove of the running component and the hoisting wire rope. Because the intelligent equipment rotates due to the rotation of the operation parts when the motor rotates in the operation processThe resistance between the sub-groove and the traction steel wire rope (hereinafter abbreviated as power resistance) drives the steel wire rope to enable the car and the counterweight to move relatively, and the car moves up and down along the guide rail in the hoistway. The resistance f=ma, where a is the acceleration of the vertical travel of the car. M is the equivalent total mass of the vertically moving object such as a car. Thus, the vertical running acceleration a of the smart device is closely related to the kinetic resistance F. When the dynamic resistance F is unstable, for example, large or small, the vertical running acceleration of the car is also large or small relative to the acceleration of the intelligent device in the normal state. Whereas the dynamic resistance f=μf N . Wherein mu is the friction coefficient of the rotor groove of the operation part and the traction steel wire rope, and F is determined by the surface materials of the steel wire rope and the operation part, the conditions of abrasion, lubrication and the like N A traction force is generated for the rotation of the motor. Under the normal power-on rotation of the motor, it can be considered that F N The value is normal. The failure of the dynamic resistance F is due to the failure of mu. In fact, when the intelligent equipment is used, the steel wire rope and the running parts can be worn, or the lubricating grease is too much, so that the intelligent equipment needs to be maintained in time. When the mu value is increased due to the abrasion of the surfaces of the steel wire rope and the running parts, the vertical running acceleration a of the lift car is increased; conversely, if μ is smaller, the vertical running acceleration a of the car is smaller. Under severe conditions, phenomena such as slipping of a steel wire rope, sliding of a car, top rushing, squatting and the like can occur, so that the magnitude of a mu value can be reversely pushed out by monitoring the vertical running acceleration a of the car in real time, and the friction coefficient of a rotor groove of a running part and a traction steel wire rope, namely abrasion or lubrication condition can be diagnosed, and the situation is prevented.
Further, referring to fig. 3, the method further includes:
the fault diagnosis server determines a difference value between the time when the second operation part of the intelligent equipment to be diagnosed receives the fault diagnosis instruction and the time when the first operation part of the intelligent equipment to be diagnosed receives the fault diagnosis instruction according to the time when the first operation part of the intelligent equipment to be diagnosed receives the fault diagnosis instruction, which is carried in the first fault message, and the time when the second operation part of the intelligent equipment to be diagnosed receives the fault diagnosis instruction, which is carried in the second fault message;
And when the difference value is larger than a preset threshold value, the fault diagnosis server determines that a communication line between the first operation part of the intelligent equipment to be diagnosed and the second operation part of the intelligent equipment to be diagnosed has faults.
According to a second aspect of the present invention, referring to fig. 4, the present invention claims a fault state diagnosis system for intelligent equipment based on big data, which is characterized in that the system comprises a transmitting unit, a receiving unit and a processing unit;
the sending unit is used for sending a fault diagnosis instruction to a first operation part of the intelligent equipment to be diagnosed, wherein the fault diagnosis instruction comprises characteristic parameters and indication information of the intelligent equipment to be diagnosed;
the system comprises a receiving unit, a fault diagnosis server and a fault diagnosis unit, wherein the receiving unit is used for receiving a first fault message of a first operation part sent by the intelligent equipment to be diagnosed, the first fault message is a fault response message generated by the first operation part of the intelligent equipment to be diagnosed in response to a fault diagnosis instruction sent by the fault diagnosis server, the first fault message comprises a characteristic parameter of the intelligent equipment to be diagnosed, a first sensor characteristic parameter, a characteristic parameter of the first operation part of the intelligent equipment to be diagnosed, the time for the first operation part of the intelligent equipment to be diagnosed to receive the fault diagnosis instruction, and a characteristic parameter of a next operation part of the first operation part of the intelligent equipment to be diagnosed, the first sensor characteristic parameter is determined by the first operation part of the intelligent equipment to be diagnosed according to indication information in the fault diagnosis instruction sent by the fault diagnosis server, and the first sensor characteristic parameter is used for representing the generation time of the first fault message, and the fault diagnosis server receives a plurality of fault messages containing the generation time; the method comprises the steps that a first fault message of a first operation part of a to-be-diagnosed intelligent device is received, the first fault message is a fault response message generated by the first operation part of the to-be-diagnosed intelligent device in response to a fault diagnosis instruction of the first operation part of the to-be-diagnosed intelligent device, the next operation part of the first operation part of the to-be-diagnosed intelligent device is the second operation part of the to-be-diagnosed intelligent device, the first fault message comprises a characteristic parameter of the to-be-diagnosed intelligent device, a characteristic parameter of a second sensor, a characteristic parameter of the to-be-diagnosed intelligent device, a time when the second operation part of the to-be-diagnosed intelligent device receives the fault diagnosis instruction of the first operation part of the to-be-diagnosed intelligent device, a characteristic parameter of the to-be-diagnosed intelligent device and a characteristic parameter of the next operation part of the to-be-diagnosed intelligent device, the second sensor characteristic parameter is determined according to the indication information in the fault diagnosis instruction of the first operation part of the to-be-diagnosed intelligent device, the second sensor characteristic parameter is used for generating a fault message, and the fault message is generated by generating a fault message, and the fault message comprises a fault message;
A processing unit for determining a set of fault messages, the set of fault messages comprising at least one fault message; and when the fault diagnosis server determines that the characteristic parameter of the next operation part of the current operation part of the intelligent equipment carried in the first fault message in the fault message set is the same as the characteristic parameter of the current operation part of the intelligent equipment carried in the second fault message in the fault message set, the fault diagnosis server determines that the first operation part of the intelligent equipment to be diagnosed and the second operation part of the intelligent equipment to be diagnosed are adjacent intelligent equipment operation parts.
Further, the processing unit is further configured to encapsulate the feature parameter and the indication information of the fault transaction to be diagnosed, generate a fault description, and the fault description is a fault diagnosis instruction, where the feature parameter and the indication information of the fault transaction to be diagnosed are carried in a relationship table of the fault description; or adding characteristic parameters, indication information and fingerprint information of the fault transaction to be diagnosed into the service diagnosis instruction generated by the application program to obtain the service diagnosis instruction carrying the fault diagnosis instruction, wherein the fingerprint information is used for indicating that the service diagnosis instruction carrying the fault diagnosis instruction carries the fault diagnosis instruction.
Further, the first fault message carries a characteristic parameter of a current operation part of the intelligent device and a characteristic parameter of a next operation part of the current operation part of the intelligent device, the characteristic parameter of the current operation part of the intelligent device carried in the first fault message is a characteristic parameter of a first operation part of the intelligent device to be diagnosed, the characteristic parameter of the next operation part of the current operation part of the intelligent device carried in the first fault message is a characteristic parameter of a second operation part of the intelligent device to be diagnosed, the characteristic parameter of the current operation part of the intelligent device carried in the second fault message is a characteristic parameter of the second operation part of the intelligent device to be diagnosed.
Further, each fault message in the plurality of fault messages carries a sensor characteristic parameter, a characteristic parameter of a current operating part of the intelligent equipment and a characteristic parameter of a next operating part of the current operating part of the intelligent equipment;
the processing unit is further used for determining a specific fault message from the plurality of fault messages, wherein the value of the sensor characteristic parameter carried in the specific fault message is larger than the values of the sensor characteristic parameters carried in other fault messages in the plurality of fault messages; determining whether a fault message of an intelligent device operation part indicated by a characteristic parameter of the next operation part of the current operation part of the intelligent device carried in a specific fault message is received or not; and when the fault message of the intelligent equipment operation part indicated by the characteristic parameter of the next operation part of the intelligent equipment current operation part carried in the specific fault message is not received, determining that the intelligent equipment operation part indicated by the characteristic parameter of the next operation part of the intelligent equipment current operation part carried in the specific fault message is the intelligent equipment operation part with fault.
Further, the processing unit is further configured to determine a difference value between a time when the second operation part of the intelligent device to be diagnosed receives the fault diagnosis instruction and a time when the first operation part of the intelligent device to be diagnosed receives the fault diagnosis instruction according to a time when the first operation part of the intelligent device to be diagnosed receives the fault diagnosis instruction, which is carried in the first fault message, and a time when the second operation part of the intelligent device to be diagnosed receives the fault diagnosis instruction, which is carried in the second fault message; and when the difference value is larger than a preset threshold value, the fault diagnosis server determines that a communication line between the first operation part of the intelligent equipment to be diagnosed and the second operation part of the intelligent equipment to be diagnosed has faults.
According to another embodiment of the present invention, the present invention further claims a method for diagnosing a fault state of an intelligent device based on big data, wherein the method includes:
the method comprises the steps that a first operation part of the intelligent equipment to be diagnosed obtains a fault diagnosis instruction, wherein the fault diagnosis instruction comprises characteristic parameters and indication information of the intelligent equipment to be diagnosed;
generating a first fault message by a first operation part of the intelligent equipment to be diagnosed according to a fault diagnosis instruction, wherein the first fault message is a fault response message generated by the first operation part of the intelligent equipment to be diagnosed in response to the fault diagnosis instruction, the first fault message comprises a characteristic parameter of the intelligent equipment to be diagnosed, a first sensor characteristic parameter, a characteristic parameter of the first operation part of the intelligent equipment to be diagnosed, a time for the first operation part of the intelligent equipment to be diagnosed to receive the fault diagnosis instruction, and a characteristic parameter of a next operation part of the first operation part of the intelligent equipment to be diagnosed, the first sensor characteristic parameter is determined by the first operation part of the intelligent equipment to be diagnosed according to indication information in the fault diagnosis instruction sent by a fault diagnosis server, the first sensor characteristic parameter is used for representing generation time of the first fault message, and the fault diagnosis server receives a plurality of fault messages containing the generation time;
The first operation part of the intelligent equipment to be diagnosed sends a first fault message to the fault diagnosis server, so that the fault diagnosis server determines the adjacent intelligent equipment operation parts of the first operation part of the intelligent equipment to be diagnosed according to the received fault message set.
Further, the first operation part of the intelligent equipment to be diagnosed adds one to a field of a sensor characteristic parameter for determining to generate a fault message by a receiver of the fault diagnosis instruction in the indication information of the fault diagnosis instruction to obtain updated indication information;
the first operation part of the intelligent equipment to be diagnosed sends a fault diagnosis instruction carrying updated indication information to the second operation part of the intelligent equipment to be diagnosed.
Those skilled in the art will appreciate that various modifications and improvements can be made to the disclosure. For example, the various devices or components described above may be implemented in hardware, or may be implemented in software, firmware, or a combination of some or all of the three.
A flowchart is used in this disclosure to describe the steps of a method according to an embodiment of the present disclosure. It should be understood that the preceding or following steps are not necessarily performed exactly as the sensor. Rather, the various steps may be processed in reverse order or simultaneously. Also, other operations may be added to these processes.
Those of ordinary skill in the art will appreciate that all or a portion of the steps of the methods described above may be implemented by a computer program to instruct related hardware, and the program may be stored in a computer readable storage medium, such as a read only memory, a magnetic disk, or an optical disk. Alternatively, all or part of the steps of the above embodiments may be implemented using one or more integrated circuits. Accordingly, each module/unit in the above embodiment may be implemented in the form of hardware, or may be implemented in the form of a software functional module. The present disclosure is not limited to any specific form of combination of hardware and software.
Unless defined otherwise, all terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The foregoing is illustrative of the present disclosure and is not to be construed as limiting thereof. Although a few exemplary embodiments of this disclosure have been described, those skilled in the art will readily appreciate that many modifications are possible in the exemplary embodiments without materially departing from the novel teachings and advantages of this disclosure. Accordingly, all such modifications are intended to be included within the scope of this disclosure as defined in the claims. It is to be understood that the foregoing is illustrative of the present disclosure and is not to be construed as limited to the specific embodiments disclosed, and that modifications to the disclosed embodiments, as well as other embodiments, are intended to be included within the scope of the appended claims. The disclosure is defined by the claims and their equivalents.
In the description of the present specification, reference to the terms "one embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that: many changes, modifications, substitutions and variations may be made to the embodiments without departing from the spirit and principles of the invention, the scope of which is defined by the claims and their equivalents.
Claims (10)
1. A method for diagnosing a fault state of an intelligent device based on big data, the method comprising:
the method comprises the steps that a fault diagnosis server sends a fault diagnosis instruction of a first operation part to intelligent equipment to be diagnosed, wherein the fault diagnosis instruction comprises characteristic parameters and indication information of the intelligent equipment to be diagnosed;
The fault diagnosis server receives a first fault message of a first operation part sent by the intelligent equipment to be diagnosed, wherein the first fault message is a fault response message generated by the first operation part of the intelligent equipment to be diagnosed in response to the fault diagnosis instruction sent by the fault diagnosis server, the first fault message comprises a characteristic parameter of the intelligent equipment to be diagnosed, a first sensor characteristic parameter, a characteristic parameter of the first operation part of the intelligent equipment to be diagnosed, a time when the first operation part of the intelligent equipment to be diagnosed receives the fault diagnosis instruction, and a characteristic parameter of a next operation part of the first operation part of the intelligent equipment to be diagnosed, the first sensor characteristic parameter is determined by the first operation part of the intelligent equipment to be diagnosed according to indication information in the fault diagnosis instruction sent by the fault diagnosis server, the first sensor characteristic parameter is used for representing generation time of the first fault message, and the fault diagnosis server receives a plurality of fault messages containing generation time;
the fault diagnosis server receives a second fault message of a second operation part sent by the intelligent equipment to be diagnosed, the second fault message is a fault response message generated by the second operation part of the intelligent equipment to be diagnosed in response to the fault diagnosis instruction of the first operation part sent by the intelligent equipment to be diagnosed, the next operation part of the first operation part of the intelligent equipment to be diagnosed is the second operation part of the intelligent equipment to be diagnosed, the second fault message comprises a characteristic parameter of the intelligent equipment to be diagnosed, a characteristic parameter of a second sensor, the characteristic parameter of the second operation part of the intelligent equipment to be diagnosed, the time when the second operation part of the intelligent equipment to be diagnosed receives the fault diagnosis instruction of the first operation part sent by the intelligent equipment to be diagnosed, the characteristic parameter of the first operation part of the intelligent equipment to be diagnosed and the characteristic parameter of the next operation part of the second operation part of the intelligent equipment to be diagnosed, the second sensor characteristic parameter is the characteristic parameter of the second operation part to be diagnosed, the second fault message is generated by the second operation part to be diagnosed, and the fault message is generated by the second fault message, the fault response message is generated by the first fault diagnosis instruction, and the fault message is generated by the second fault message;
The fault diagnosis server determining a set of fault messages, the set of fault messages comprising at least one fault message;
when the fault diagnosis server determines that the characteristic parameter of the next operation part of the current operation part of the intelligent equipment carried in the first fault message in the fault message set is the same as the characteristic parameter of the current operation part of the intelligent equipment carried in the second fault message in the fault message set, the fault diagnosis server determines that the first operation part of the intelligent equipment to be diagnosed and the second operation part of the intelligent equipment to be diagnosed are adjacent intelligent equipment operation parts.
2. The method of claim 1, wherein before the fault diagnosis server sends the fault diagnosis instruction of the first operating component to the smart device to be diagnosed, the method further comprises:
the fault diagnosis server encapsulates the characteristic parameters of the fault transaction to be diagnosed and the indication information to generate fault description, wherein the fault description is the fault diagnosis instruction, and the characteristic parameters of the fault transaction to be diagnosed and the indication information are carried in a relation table of the fault description; or (b)
The fault diagnosis server adds the characteristic parameters of the fault transaction to be diagnosed, the indication information and fingerprint information into the service diagnosis instruction generated by the fault diagnosis server according to the application program to obtain the service diagnosis instruction carrying the fault diagnosis instruction, wherein the fingerprint information is used for indicating that the service diagnosis instruction carrying the fault diagnosis instruction carries the fault diagnosis instruction.
3. The method according to claim 1 or 2, wherein the first fault message carries a characteristic parameter of a current operation part of the intelligent device and a characteristic parameter of a next operation part of the current operation part of the intelligent device, the characteristic parameter of the current operation part of the intelligent device carried in the first fault message is a characteristic parameter of a first operation part of the intelligent device to be diagnosed, the characteristic parameter of the next operation part of the current operation part of the intelligent device carried in the first fault message is a characteristic parameter of a second operation part of the intelligent device to be diagnosed, the characteristic parameter of the current operation part of the intelligent device carried in the second fault message is a characteristic parameter of a second operation part of the intelligent device to be diagnosed.
4. A method according to claim 3, wherein each fault message in the set of fault messages carries a sensor characteristic parameter, a characteristic parameter of a currently operating component of the intelligent device, and a characteristic parameter of a next operating component of the currently operating component of the intelligent device, the method comprising:
the fault diagnosis server determines a specific fault message from the plurality of fault messages, wherein the value of the sensor characteristic parameter carried in the specific fault message is larger than the values of the sensor characteristic parameters carried in other fault messages in the plurality of fault messages;
the fault diagnosis server determines whether fault information of the intelligent equipment operation part indicated by the characteristic parameter of the next operation part of the intelligent equipment current operation part carried in the specific fault information is received or not;
when the fault diagnosis server determines that the fault message of the intelligent device operation part indicated by the characteristic parameter of the next operation part of the intelligent device current operation part carried in the specific fault message is not received, determining that the intelligent device operation part indicated by the characteristic parameter of the next operation part of the intelligent device current operation part carried in the specific fault message is the intelligent device operation part with the fault.
5. The method according to claim 1, wherein the method further comprises:
the fault diagnosis server determines a difference value between the time when the second operation part of the intelligent equipment to be diagnosed receives the fault diagnosis instruction and the time when the first operation part of the intelligent equipment to be diagnosed receives the fault diagnosis instruction according to the time when the first operation part of the intelligent equipment to be diagnosed receives the fault diagnosis instruction, which is carried in the first fault message, and the time when the second operation part of the intelligent equipment to be diagnosed receives the fault diagnosis instruction, which is carried in the second fault message;
and when the difference value is larger than a preset threshold value, the fault diagnosis server determines that a communication line between the first operation part of the intelligent equipment to be diagnosed and the second operation part of the intelligent equipment to be diagnosed has faults.
6. The intelligent equipment fault state diagnosis system based on big data is characterized by comprising a sending unit, a receiving unit and a processing unit;
the sending unit is used for sending a fault diagnosis instruction to a first operation part of the intelligent equipment to be diagnosed, wherein the fault diagnosis instruction comprises characteristic parameters and indication information of the intelligent equipment to be diagnosed;
The receiving unit is configured to receive a first fault message of a first operation component sent by the to-be-diagnosed smart device, where the first fault message is a fault response message generated by the first operation component of the to-be-diagnosed smart device in response to the fault diagnosis instruction sent by the fault diagnosis server, the first fault message includes a feature parameter of the to-be-diagnosed smart device, a first sensor feature parameter, a feature parameter of the to-be-diagnosed smart device, a time when the first operation component of the to-be-diagnosed smart device receives the fault diagnosis instruction, and a feature parameter of a next operation component of the first operation component of the to-be-diagnosed smart device, where the first sensor feature parameter is determined by the first operation component of the to-be-diagnosed smart device according to the indication information in the fault diagnosis instruction sent by the fault diagnosis server, and the first sensor feature parameter is used to characterize a generation time of the first fault message, and the fault diagnosis server receives a plurality of fault messages including the generation time; and receiving a second fault message of a second operating part sent by the intelligent device to be diagnosed, wherein the second fault message is a fault response message generated by the second operating part of the intelligent device to be diagnosed in response to the fault diagnosis instruction of the first operating part sent by the intelligent device to be diagnosed, a next operating part of the first operating part of the intelligent device to be diagnosed is the second operating part of the intelligent device to be diagnosed, the second fault message comprises a characteristic parameter of the intelligent device to be diagnosed, a characteristic parameter of a second sensor, the characteristic parameter of the second operating part of the intelligent device to be diagnosed, a time when the second operating part of the intelligent device to be diagnosed receives the fault diagnosis instruction of the first operating part sent by the intelligent device to be diagnosed, the characteristic parameter of the first operating part of the intelligent device to be diagnosed and a characteristic parameter of a next operating part of the second operating part of the intelligent device to be diagnosed, the second fault message is generated by the second operating part to be diagnosed, the second operating part to be diagnosed is a fault response message generated by the second operating part to be diagnosed, the first fault message is generated by the second fault message, and the fault response message is generated by the second fault message;
The processing unit is used for determining a fault message set, wherein the fault message set comprises at least one fault message; and when the fault diagnosis server determines that the characteristic parameter of the next operation part of the current operation part of the intelligent device carried in the first fault message in the fault message set is the same as the characteristic parameter of the current operation part of the intelligent device carried in the second fault message in the fault message set, the fault diagnosis server determines that the first operation part of the intelligent device to be diagnosed and the second operation part of the intelligent device to be diagnosed are adjacent intelligent device operation parts.
7. The system of claim 6, wherein the system further comprises a controller configured to control the controller,
the processing unit is further configured to encapsulate the characteristic parameter of the fault transaction to be diagnosed and the indication information, and generate a fault description, where the fault description is the fault diagnosis instruction, and the characteristic parameter of the fault transaction to be diagnosed and the indication information are carried in a relationship table of the fault description; or adding the characteristic parameters of the fault transaction to be diagnosed, the indication information and fingerprint information into the service diagnosis instruction generated by the application program to obtain the service diagnosis instruction carrying the fault diagnosis instruction, wherein the fingerprint information is used for indicating that the service diagnosis instruction carrying the fault diagnosis instruction carries the fault diagnosis instruction.
8. The system of claim 7, wherein the first fault message carries a characteristic parameter of a current operating part of the intelligent device and a characteristic parameter of a next operating part of the current operating part of the intelligent device, the characteristic parameter of the current operating part of the intelligent device carried in the first fault message is a characteristic parameter of a first operating part of the intelligent device to be diagnosed, the characteristic parameter of the next operating part of the current operating part of the intelligent device carried in the first fault message is a characteristic parameter of a second operating part of the intelligent device to be diagnosed, the characteristic parameter of the current operating part of the intelligent device carried in the second fault message is a characteristic parameter of a second operating part of the intelligent device to be diagnosed.
9. The system of claim 8, wherein each fault message in the plurality of fault messages carries a sensor characteristic parameter, a characteristic parameter of a currently operating component of the intelligent device, and a characteristic parameter of a next operating component of the currently operating component of the intelligent device;
The processing unit is further configured to determine a specific fault message from the plurality of fault messages, where a value of a sensor characteristic parameter carried in the specific fault message is greater than a value of a sensor characteristic parameter carried in other fault messages in the plurality of fault messages; determining whether a fault message of the intelligent equipment operation part indicated by the characteristic parameter of the next operation part of the intelligent equipment current operation part carried in the specific fault message is received or not; and when the fault message of the intelligent equipment operation part indicated by the characteristic parameter of the next operation part of the intelligent equipment current operation part carried in the specific fault message is not received, determining that the intelligent equipment operation part indicated by the characteristic parameter of the next operation part of the intelligent equipment current operation part carried in the specific fault message is the intelligent equipment operation part with fault.
10. The system of claim 9, wherein the processing unit is further configured to determine a difference between a time when the second operational component of the smart device to be diagnosed receives the fault diagnosis instruction and a time when the first operational component of the smart device to be diagnosed receives the fault diagnosis instruction according to a time when the first operational component of the smart device to be diagnosed receives the fault diagnosis instruction, which is carried in the first fault message, and a time when the second operational component of the smart device to be diagnosed receives the fault diagnosis instruction, which is carried in the second fault message; and when the difference value is larger than a preset threshold value, the fault diagnosis server determines that a communication line between the first operation part of the intelligent equipment to be diagnosed and the second operation part of the intelligent equipment to be diagnosed has faults.
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