CN111598267B - Engineering machine, working data verification method, device and system thereof and storage medium - Google Patents
Engineering machine, working data verification method, device and system thereof and storage medium Download PDFInfo
- Publication number
- CN111598267B CN111598267B CN202010425612.0A CN202010425612A CN111598267B CN 111598267 B CN111598267 B CN 111598267B CN 202010425612 A CN202010425612 A CN 202010425612A CN 111598267 B CN111598267 B CN 111598267B
- Authority
- CN
- China
- Prior art keywords
- cloud
- data
- working data
- controller
- working
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/20—Administration of product repair or maintenance
-
- E—FIXED CONSTRUCTIONS
- E02—HYDRAULIC ENGINEERING; FOUNDATIONS; SOIL SHIFTING
- E02F—DREDGING; SOIL-SHIFTING
- E02F9/00—Component parts of dredgers or soil-shifting machines, not restricted to one of the kinds covered by groups E02F3/00 - E02F7/00
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/02—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP]
- H04L67/025—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP] for remote control or remote monitoring of applications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Computer Networks & Wireless Communication (AREA)
- Human Resources & Organizations (AREA)
- Signal Processing (AREA)
- Operations Research (AREA)
- Physics & Mathematics (AREA)
- General Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Marketing (AREA)
- Health & Medical Sciences (AREA)
- Quality & Reliability (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- Medical Informatics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Mining & Mineral Resources (AREA)
- Civil Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Structural Engineering (AREA)
- Operation Control Of Excavators (AREA)
- Testing And Monitoring For Control Systems (AREA)
Abstract
The disclosure relates to engineering machinery, and a working data verification method, device and system and a storage medium thereof. The working data verification method of the engineering machinery comprises the following steps: the first storage area and the second storage area of the main controller are both stored with working data of the engineering machinery, wherein the main controller is the main controller of the engineering machinery; the main controller performs self-checking on the engineering machinery working data stored in the first storage area and the second storage area to obtain controller-end working data. According to the data verification method and the data verification device, through the master controller double-storage-area working hour meter verification mechanism, the data accuracy is improved, and the error risk is reduced.
Description
Technical Field
The disclosure relates to the field of engineering machinery, and in particular relates to engineering machinery, and a working data verification method, device and system and a storage medium thereof.
Background
The working hours are important data recorded by working conditions of the hydraulic excavator, the accurate statistics of the working hours is an important basis for maintenance and crediting management of manufacturers, and is important reference data for scientifically and reasonably using the excavator by customers.
The related technology works for hours for statistics, the vehicle-mounted terminal uploads data and the data are stored in a cloud; when the working hours are wrong or a new controller is replaced, the calibration is carried out on site through the encryption of the instrument.
Disclosure of Invention
The inventors found through research that: (1) The storage area fault of the related technology in working hours has no alarm and cannot be identified; (2) The related technology has only uploading and storing functions and has no check and alarm functions; (3) When the related art is wrong in working hours, the service personnel must use professional tools for field calibration, so that the service time and the cost are increased.
In view of at least one of the above technical problems, the present disclosure provides an engineering machine, and a working data verification method, device and system thereof, and a storage medium thereof, wherein a master controller double-storage-area working hour meter verification mechanism improves data accuracy and reduces error risk.
According to one aspect of the present disclosure, there is provided a work data verification method for an engineering machine, including:
the first storage area and the second storage area of the main controller are both stored with working data of the engineering machinery, wherein the main controller is the main controller of the engineering machinery;
the main controller performs self-checking on the engineering machinery working data stored in the first storage area and the second storage area to obtain controller-end working data.
In some embodiments of the present disclosure, the work machine work data verification method further includes:
the master controller uploads the controller end working data to the cloud server, and instructs the cloud server to check the cloud working data according to the controller end working data and the cloud working data.
In some embodiments of the present disclosure, the work machine work data verification method further includes:
the main controller judges whether a working data changing instruction of the cloud server is received or not;
and under the condition that the main controller receives the working data changing instruction, the cloud working data are used as working data of the controller end.
In some embodiments of the present disclosure, the work machine work data verification method further includes:
and the main controller sends storage area error alarm information to the client through the cloud server under the condition that the working data self-checking process detects storage area errors.
In some embodiments of the present disclosure, the self-checking, by the main controller, the working data of the working machine stored in the first storage area and the second storage area, and obtaining the working data of the controller includes:
the main controller judges whether the first storage area and the second storage area have faults or not;
Under the condition that the first storage area is free from faults and the second storage area is faulty, the main controller takes the first engineering machinery working data stored in the first storage area as controller end working data, and uploads the controller end working data and the second storage area fault alarm information to the cloud server.
In some embodiments of the present disclosure, the self-checking, by the main controller, the working data of the working machine stored in the first storage area and the second storage area, and obtaining the working data of the controller side further includes:
and under the conditions that the first storage area has a fault and the second storage area has no fault, the main controller takes the second engineering machinery working data stored in the second storage area as controller end working data, and uploads the controller end working data and the first storage area fault alarm information to the cloud server.
In some embodiments of the present disclosure, the self-checking, by the main controller, the working data of the working machine stored in the first storage area and the second storage area, and obtaining the working data of the controller side further includes:
and the main controller takes the cloud working data as controller end working data under the condition that the first storage area has faults and the second storage area has faults, and uploads the controller end working data, the first storage area fault alarm information and the second storage area fault alarm information to the cloud server.
In some embodiments of the present disclosure, the self-checking, by the main controller, the working data of the working machine stored in the first storage area and the second storage area, and obtaining the working data of the controller side further includes:
under the condition that the first storage area has no fault and the second storage area has no fault, the main controller takes the first engineering machinery working data stored in the first storage area as controller end working data, and judges whether the absolute value of the difference value of the first engineering machinery working data and the second engineering machinery working data is larger than a self-checking threshold value;
the method comprises the steps that when the absolute value of the difference value between the first engineering machine working data and the second engineering machine working data is not larger than a self-checking threshold value, the main controller uploads controller end working data to a cloud server;
and uploading the working data of the controller end and the verification abnormality alarm information to the cloud server by the main controller under the condition that the absolute value of the difference value of the working data of the first engineering machine and the working data of the second engineering machine is not larger than the self-verification threshold value.
In some embodiments of the present disclosure, the work machine work data verification method further includes:
the cloud server receives the work data of the controller end uploaded by the main controller, wherein the main controller is the engineering machinery main controller;
The cloud server acquires cloud work data;
and the cloud server performs cloud work data verification according to the controller end work data and the cloud work data.
According to another aspect of the present disclosure, there is provided a method for checking work data of an engineering machine, including:
the cloud server receives the work data of the controller end uploaded by the main controller, wherein the main controller is the engineering machinery main controller;
the cloud server acquires cloud work data;
and the cloud server performs cloud work data verification according to the controller end work data and the cloud work data.
In some embodiments of the present disclosure, the cloud server performing cloud work data verification according to the controller end work data and the cloud work data includes:
the cloud server judges whether the difference value between the cloud working data and the controller end working data is larger than a first threshold value or whether the controller end working data is equal to 0;
and under the condition that the difference value between the cloud work data and the work data of the controller end is larger than a first threshold value or the work data of the controller end is equal to 0, the cloud server sends fault abnormal alarm information to the client and sends a work data changing instruction and the cloud work data to the main controller.
In some embodiments of the present disclosure, the cloud server performing cloud working data verification according to the controller end working data and the cloud working data further includes:
the cloud server acquires cloud self-counting working data;
the cloud server judges whether the difference value between the working data of the controller end and the cloud self-calculated working data is larger than a second threshold value;
when the difference value between the working data of the controller end and the cloud self-counting working data is larger than a second threshold value, the cloud server takes the cloud self-counting working data as cloud working data, sends failure abnormality alarm information to the client, and sends a working data changing instruction and cloud working data to the main controller;
and under the condition that the difference value between the work data of the controller end and the cloud self-counting work data is not greater than a second threshold value, the cloud server sends the cloud work data to the main controller.
According to another aspect of the present disclosure, there is provided a main controller including:
the first storage area and the second storage area are used for respectively storing working data of the engineering machinery, wherein the main controller is the engineering machinery main controller;
and the self-checking module is used for carrying out self-checking on the engineering machinery working data stored in the first storage area and the second storage area to obtain the working data of the controller end.
In some embodiments of the present disclosure, the main controller is configured to perform operations for implementing the work machine work data verification method according to any one of the embodiments described above.
According to another aspect of the present disclosure, there is provided a main controller including:
a main controller memory for storing instructions;
and the main controller processor is used for executing the instructions to enable the main controller to execute the operations for realizing the working data verification method of the engineering machinery according to any embodiment.
According to another aspect of the present disclosure, there is provided a cloud server, including:
the controller data receiving module is used for receiving the working data of the controller end uploaded by the main controller, wherein the main controller is an engineering machinery main controller;
the cloud data acquisition module is used for acquiring cloud work data;
the cloud verification module is used for verifying cloud working data according to the working data of the controller end and the cloud working data.
In some embodiments of the present disclosure, the main controller is configured to perform operations for implementing the work machine work data verification method according to any one of the embodiments described above.
According to another aspect of the present disclosure, there is provided a cloud server, including:
The cloud storage is used for storing the instructions;
and the cloud processor is used for executing the instruction, so that the main controller executes the operation of realizing the working data verification method of the engineering machinery according to any one of the embodiments.
According to another aspect of the disclosure, a work machine work data verification system is provided, including a master controller as described in any of the above embodiments.
In some embodiments of the disclosure, the work machine work data verification system further includes a cloud server as described in any one of the embodiments above.
According to another aspect of the present disclosure, there is provided a work machine work data verification system, including:
the main controller is used for uploading working data of the controller end to the cloud server;
the cloud server is the cloud server according to any one of the above embodiments.
According to another aspect of the present disclosure, there is provided a work machine including a main controller as described in any one of the above embodiments.
According to another aspect of the disclosure, a computer readable storage medium is provided, wherein the computer readable storage medium stores computer instructions that, when executed by a processor, implement a work machine work data verification method as described in any of the embodiments above.
According to the data verification method and the data verification device, through the master controller double-storage-area working hour meter verification mechanism, the data accuracy is improved, and the error risk is reduced.
Drawings
In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present disclosure, and other drawings may be obtained according to these drawings without inventive effort to a person of ordinary skill in the art.
Fig. 1 is a schematic diagram of some embodiments of a method for verifying working data of a construction machine according to the present disclosure.
Fig. 2 is a schematic diagram of other embodiments of a method for verifying working data of a construction machine according to the present disclosure.
FIG. 3 is a schematic diagram of another embodiment of a work machine work data verification method of the present disclosure.
FIG. 4 is a schematic diagram of still further embodiments of the work machine work data verification method of the present disclosure.
Fig. 5 is a schematic diagram of still another embodiment of a method for verifying work data of a construction machine according to the present disclosure.
Fig. 6 is a schematic diagram of some embodiments of a master controller of the present disclosure.
Fig. 7 is a schematic diagram of other embodiments of a master controller of the present disclosure.
Fig. 8 is a schematic diagram of some embodiments of a cloud server of the present disclosure.
Fig. 9 is a schematic diagram of other embodiments of a cloud server according to the disclosure.
FIG. 10 is a schematic diagram of some embodiments of a work machine work data verification system of the present disclosure.
Detailed Description
The following description of the technical solutions in the embodiments of the present disclosure will be made clearly and completely with reference to the accompanying drawings in the embodiments of the present disclosure, and it is apparent that the described embodiments are only some embodiments of the present disclosure, not all embodiments. The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the disclosure, its application, or uses. Based on the embodiments in this disclosure, all other embodiments that a person of ordinary skill in the art would obtain without making any inventive effort are within the scope of protection of this disclosure.
The relative arrangement of the components and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present disclosure unless it is specifically stated otherwise.
Meanwhile, it should be understood that the sizes of the respective parts shown in the drawings are not drawn in actual scale for convenience of description.
Techniques, methods, and apparatus known to one of ordinary skill in the relevant art may not be discussed in detail, but should be considered part of the specification where appropriate.
In all examples shown and discussed herein, any specific values should be construed as merely illustrative, and not a limitation. Thus, other examples of the exemplary embodiments may have different values.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further discussion thereof is necessary in subsequent figures.
Fig. 1 is a schematic diagram of some embodiments of a method for verifying working data of a construction machine according to the present disclosure. Preferably, the present embodiment may be performed by the work machine work data verification system of the present disclosure or the master controller of the present disclosure. The method may comprise steps 11 and 12, wherein:
and 11, storing working data of the engineering machinery in a first storage area and a second storage area of a main controller, wherein the main controller is the main controller of the engineering machinery.
In some embodiments of the present disclosure, the work machine may be a hydraulic excavator or the like.
In some embodiments of the present disclosure, the work data may be work hours of the work machine, work machine times class data, and the like.
For example: the working data may be working hours, wherein the working hours are important data recorded by working conditions of the hydraulic excavator.
And step 12, the main controller performs self-checking on the engineering machinery working data stored in the first storage area and the second storage area to obtain controller-side working data.
In some embodiments of the present disclosure, step 12 may include steps 121-127, wherein:
step 121, the main controller determines whether there is a failure in the first storage area and the second storage area.
Step 122, the main controller takes the first engineering machinery working data stored in the first storage area as the controller end working data and uploads the controller end working data and the second storage area fault alarm information to the cloud server under the condition that the first storage area is not faulty and the second storage area is faulty.
Step 123, the main controller takes the second engineering machinery working data stored in the second storage area as the controller end working data under the condition that the first storage area fails and the second storage area fails, and uploads the controller end working data and the first storage area failure alarm information to the cloud server.
In step 124, the main controller takes the cloud working data as the working data of the controller end and uploads the working data of the controller end, the fault alarm information of the first storage area and the fault alarm information of the second storage area to the cloud server under the condition that the first storage area has a fault and the second storage area has a fault.
And step 125, the main controller uses the first engineering machine working data stored in the first storage area as the controller end working data under the condition that the first storage area has no fault and the second storage area has no fault, and judges whether the absolute value of the difference value of the first engineering machine working data and the second engineering machine working data is larger than a self-checking threshold value.
In step 126, the master controller uploads the controller-side working data to the cloud server when the absolute value of the difference between the first engineering machine working data and the second engineering machine working data is not greater than the self-checking threshold.
And step 127, uploading the working data of the controller end and the verification abnormality alarm information to the cloud server by the main controller under the condition that the absolute value of the difference value of the working data of the first engineering machine and the working data of the second engineering machine is not larger than the self-verification threshold value.
According to the working data verification method of the engineering machinery provided by the embodiment of the disclosure, through a verification mechanism of the working data (such as the working hours of the double storage areas) of the double storage areas of the main controller, the data accuracy is improved, and the error risk is reduced.
Fig. 2 is a schematic diagram of other embodiments of a method for verifying working data of a construction machine according to the present disclosure. Preferably, the present embodiment may be performed by the work machine work data verification system of the present disclosure or the master controller of the present disclosure. Steps 21-22 of the embodiment of fig. 2 are the same as or similar to steps 11 and 12, respectively, of the embodiment of fig. 1. The method of the embodiment of fig. 2 may include steps 21-28, wherein:
step 21, the first storage area and the second storage area of the main controller are both stored with working data of the engineering machinery, wherein the main controller is the main controller of the engineering machinery.
In some embodiments of the present disclosure, the work machine may be a hydraulic excavator or the like.
In some embodiments of the present disclosure, the work data may be work hours of the work machine, work machine times class data, and the like.
For example: the working data may be working hours, wherein the working hours are important data recorded by working conditions of the hydraulic excavator.
Step 22, the main controller performs self-checking on the working data of the engineering machinery stored in the first storage area and the second storage area to obtain working data of the controller end.
Step 23, the main controller sends storage area error alarm information to the client through the cloud server under the condition that the working data self-checking process detects storage area errors.
In the above embodiment of the disclosure, the storage area fault alarm indication can be sent to the client through the cloud end, and the information is quickly transferred, so that the service response efficiency is improved.
In the foregoing embodiments of the present disclosure, the cloud server may be a cloud internet of things platform.
And step 24, the main controller uploads the working data of the controller end to the cloud server.
Step 25, the cloud server receives the work data of the controller end uploaded by the main controller; the cloud server acquires cloud work data.
Step 26, the cloud server performs cloud work data verification according to the controller end work data and the cloud work data.
In some embodiments of the present disclosure, step 26 may include steps 261-265, wherein:
step 261, the cloud server determines whether the difference between the cloud working data and the controller working data is greater than a first threshold, or whether the controller working data is equal to 0;
in step 262, when the difference between the cloud working data and the controller working data is greater than the first threshold, or the controller working data is equal to 0, the cloud server sends the fault abnormal alarm information to the client, and sends the working data change instruction and the cloud working data to the master controller.
In step 263, the cloud server obtains cloud self-counting working data.
In some embodiments of the present disclosure, when the working data is the excavator working hours, the cloud self-counting working data may be a cloud self-counting working hours time_n, where the cloud self-counting working hours refer to when the cloud receives that the excavator stops working, starting timing from a current working hours TIME, increasing a natural TIME T1, and extracting the cloud self-counting working hours time_n=timec+t1 after the next starting-up, where TIMEC is the cloud working hours.
In step 264, the cloud server determines whether the difference between the controller-side working data and the cloud self-calculated working data is greater than a second threshold.
In step 265, when the difference between the working data at the controller end and the cloud self-counting working data is greater than the second threshold, the cloud server takes the cloud self-counting working data as the cloud working data, sends failure abnormality alarm information to the client, and sends a working data changing instruction and the cloud working data to the main controller.
In step 266, the cloud server sends the cloud working data to the master controller when the difference between the controller end working data and the cloud self-counting working data is not greater than the second threshold.
Step 27, the main controller determines whether a working data modification instruction of the cloud server is received.
In step 28, the main controller takes the cloud end working data as the controller end working data under the condition that the working data changing instruction is received.
According to the embodiment of the disclosure, data storage and processing can be performed through the cloud, the accuracy and reliability of the data of the excavator can be improved by means of the IOT (The Internet of Things, internet of things) technology, and the method is an important measure for digital transformation of the excavator.
The embodiment of the disclosure can improve the accuracy and the reliability of the recording in working hours through the self-checking of the double storage areas of the main controller. According to the embodiment of the disclosure, the storage area fault alarm is added, the data transmission is performed through the Internet of things platform, and the fault information and the working hour abnormal information can be quickly pushed to be sent to service personnel for abnormal condition investigation. Meanwhile, the embodiment of the disclosure can verify and automatically calibrate the data of the main controller by means of the cloud internet of things platform data, and a traditional method for changing the hour meter by inputting the field password is changed, so that service efficiency and data communication safety are improved, working hour safety is improved, and risk of manually changing the hour meter is reduced.
FIG. 3 is a schematic diagram of another embodiment of a work machine work data verification method of the present disclosure. Preferably, the present embodiment may be performed by the work machine work data verification system of the present disclosure or the master controller of the present disclosure. Steps 31-34 of the embodiment of fig. 3 are the same as or similar to steps 25-28, respectively, of the embodiment of fig. 2. The method of the embodiment of fig. 3 may include steps 31-34, wherein:
step 31, the cloud server receives the work data of the controller end uploaded by the main controller; the cloud server acquires cloud work data, wherein the main controller is a engineering machinery main controller.
In some embodiments of the present disclosure, the work machine may be a hydraulic excavator or the like.
In some embodiments of the present disclosure, the work data may be work hours of the work machine, work machine times class data, and the like.
For example: the working data may be working hours, wherein the working hours are important data recorded by working conditions of the hydraulic excavator.
Step 32, the cloud server performs cloud work data verification according to the controller end work data and the cloud work data.
In some embodiments of the present disclosure, step 32 may include the aforementioned step 261-step 265.
Step 33, the main controller determines whether a working data modification instruction of the cloud server is received.
In step 34, the main controller takes the cloud end working data as the controller end working data under the condition that the working data changing instruction is received.
According to the embodiment of the disclosure, the IOT technology is utilized, the cloud end and the main controller work hour self-checking is adopted, when the controller is replaced or communication is interrupted for a very long time, the hour meter is automatically calibrated, so that the risk of manually changing the work hour meter is reduced, the main controller is checked through cloud end data processing, abnormal risk alarming of the work hour is carried out, and the statistical accuracy of the work hour is improved.
FIG. 4 is a schematic diagram of still further embodiments of the work machine work data verification method of the present disclosure. Fig. 4 is a flowchart of a control strategy of a main controller according to some embodiments of the present disclosure, and the method for verifying working data of an engineering machine according to the embodiment of fig. 4 may include steps S101 to S113, where:
step S101, the working hours of the first storage area M1 and the second storage area M2 of the main controller memory are read, and the working hours are respectively the first working hours TIME1 and the second working hours TIME2, and the cloud working hours TIME sent by the cloud server is received through a communication terminal such as a GPS terminal.
Step S102, it is determined whether the first memory area M1 is faulty. When the first storage area has the failure E1, step S107 is performed; otherwise, when the first storage area is not faulty, step S103 is performed.
Step S103, the controller end works for hours (the main control program works for hours) TIME, and takes a stored value TIME1 of the first storage area M1; while judging whether the second memory area M2 has a failure E2. When the second storage area M2 has a fault alarm, step S104 is executed; when the second memory area M2 is free from a failure, step S105 is performed.
Step S104, uploading the fault alarm E2 of the second storage area M2 of the main controller to the cloud server.
Step S105, checking the working hours of the dual storage area, and determining whether the absolute VALUE of the difference between the first working hour TIME1 and the second working hour TIME2 is greater than the self-checking threshold t_value1, that is, whether |time1-TIME2| > t_value1 is satisfied, where t_value1 is a determination VALUE set according to the working hour determination criterion, and is used to determine whether there is a statistical error in the working hours of the dual storage area, where the determination VALUE should be set in consideration of a normal error. When the two storage areas are checked in an hour, and the phase difference absolute value is larger than the self-checking threshold value, the step S110 is entered; when the double storage area is checked for hours, the phase difference absolute value is larger than the self-checking threshold, the process proceeds to step S106.
And S106, uploading the double-storage-area hour meter checking abnormal alarm E3 to the cloud server.
Step S107, uploading the failure alarm E1 of the first storage area M1 of the main controller to the cloud server. Judging whether the second storage area M2 has a fault E2 or not; the second memory area M2 has a fault alarm, step S109 is performed, and the second memory area M2 has no fault, step S108 is performed.
In step S108, the controller terminal takes the second memory area M2 area hour meter, TIME: =time 2.
Step S109, uploading a failure alarm E1 of a first storage area M1 of the main controller to a cloud server; the controller end working hour TIME gets the cloud end working hour TIMEC.
Step S110, the master controller uploads the TIME of working hours of the controller end after the double storage areas are checked through the CAN communication network.
In step S111, the main controller receives a cloud server instruction through the communication terminal. Upon receiving the hour meter change instruction, step S112 is executed; no instruction, step S113 is executed;
step S112, the controller terminal works for hours to obtain a cloud hour timer TIMEC;
in step S113, the main controller stores the TIME of the controller end operating hour.
Fig. 5 is a schematic diagram of still another embodiment of a method for verifying work data of a construction machine according to the present disclosure. Fig. 5 is a flowchart of a cloud end server control policy in some embodiments of the present disclosure, and the working data verification method of the engineering machinery in the embodiment of fig. 4 may include steps S201 to S206, where:
In step S201, the cloud server receives the controller end working hour TIME sent by the main controller from the communication terminal, reads the cloud end working hour TIME, reads the cloud end self-timing working hour time_n, wherein time_n is the TIME counted from the current working hour TIME when the cloud end receives the excavator to stop working, increases the natural TIME T1, and extracts time_n=time+t1 after the next startup.
Step S202, performing a first-step working hour check. And judging whether the controller is a new controller or whether the working hour is smaller than the cloud working hour, wherein whether the controller is the new controller is judged by judging whether the working hour TIME is 0, and judging whether the working hour of the main controller is abnormally smaller by judging the difference VALUE between TIMEC and TIME and the first threshold T_VALUE2. When the working hour is abnormally smaller, the working hour is considered to be possibly changed artificially or the main controller is abnormally smaller or the working hour is equal to 0, and the step S206 is performed; otherwise, step S203 is entered.
Step S203, performing a second step of working hour verification. Judging whether the TIME of the working hours of the main controller is larger than the natural timing time_N from the last working hour of the cloud, wherein whether the working hours of the main controller are abnormally large or not is judged through the difference VALUE between the TIME and the time_N and the second threshold T_VALUE3, in actual logic, the cloud stores the time_N as a judging basis according to the natural timing except for storing the working hours TIMEC stored after the last power failure of the main controller in consideration of the condition of GPS communication interruption, namely the cloud server stores the working hours as double-address storage. When the working hour time_n and the working hour TIME are judged and no abnormality exists, the step S204 is entered; otherwise, the process advances to S205.
Step S204, the cloud server normally sends the TIMEC communication terminal of the cloud service hours and sends the TIMEC communication terminal to the main controller through the communication terminal.
In step S205, the cloud server hour timer takes the natural timing time_n.
Step S206, the cloud server sends the abnormal alarm of the working hours to the client, simultaneously sends the change instruction of the working hours and the TIMEC of the working hours to the communication terminal, and the communication terminal transmits the change instruction and the working hours to the main controller to check the control end of the working hours.
The embodiment of the disclosure comprises a main controller control strategy and a cloud server control strategy. The embodiment of the disclosure provides a working hour verification technology suitable for an excavator, which is a strategy for double-end verification based on an internet of things platform and a CAN communication data transmission mechanism. According to the technical scheme, the controller performs self-checking through the data of the double storage areas, provides storage area error alarm, and feeds alarm information back to an information demand party through the cloud. Meanwhile, the embodiment of the disclosure performs verification with cloud data to achieve the purpose of improving accuracy and reliability of working hours.
Fig. 6 is a schematic diagram of some embodiments of a master controller of the present disclosure. As shown in fig. 6, the master controller of the present disclosure may include a first storage area 61, a second storage area 62, and a self-checking module 63, wherein:
The first storage area 61 and the second storage area 62 are used for respectively storing working data of the engineering machinery, wherein the main controller is the engineering machinery main controller.
And the self-checking module 63 is configured to perform self-checking on the working data of the engineering machine stored in the first storage area and the second storage area, so as to obtain working data of the controller.
In some embodiments of the present disclosure, the self-checking module 63 may be used to determine whether there is a failure in the first storage area and the second storage area; under the condition that the first storage area has no fault and the second storage area has a fault, the first engineering machinery working data stored in the first storage area is used as controller end working data, and the controller end working data and the second storage area fault alarm information are uploaded to the cloud server.
In some embodiments of the present disclosure, the self-checking module 63 may be further configured to upload the controller-side working data and the first storage area failure alarm information to the cloud server by using the second work machine working data stored in the second storage area as the controller-side working data when the first storage area fails and the second storage area fails.
In some embodiments of the present disclosure, the self-checking module 63 may be further configured to upload the controller-side working data, the first storage area failure alarm information, and the second storage area failure alarm information to the cloud server by using the cloud working data as the controller-side working data when the first storage area fails and the second storage area fails.
In some embodiments of the present disclosure, the self-checking module 63 may be further configured to determine, when the first storage area has no fault and the second storage area has no fault, whether an absolute value of a difference between the first engineering machine working data and the second engineering machine working data is greater than a self-checking threshold by using the first engineering machine working data stored in the first storage area as the controller-side working data; uploading the working data of the controller end to the cloud server under the condition that the absolute value of the difference value between the working data of the first engineering machine and the working data of the second engineering machine is not greater than a self-checking threshold value; and uploading the working data of the controller and the verification abnormality alarm information to the cloud server under the condition that the absolute value of the difference value between the working data of the first engineering machine and the working data of the second engineering machine is not greater than the self-verification threshold value.
In some embodiments of the present disclosure, the master controller may be further configured to upload controller-side working data to the cloud server, and instruct the cloud server to perform cloud-side working data verification according to the controller-side working data and the cloud-side working data.
In some embodiments of the present disclosure, the master controller may be further configured to determine whether a working data modification instruction of the cloud server is received; and under the condition that a working data changing instruction is received, the cloud working data is used as working data of a controller side.
In some embodiments of the present disclosure, the master controller may be further configured to send, when the working data self-checking process detects a storage area error, storage area error alarm information to the client through the cloud server.
In some embodiments of the present disclosure, the master controller is configured to perform operations to implement the work machine work data verification method described in any of the embodiments described above (e.g., any of fig. 1-2, 4).
Fig. 7 is a schematic diagram of other embodiments of a master controller of the present disclosure. As shown in fig. 7, the master controller of the present disclosure may include a master controller memory 71 and a master controller processor 72, wherein:
a main controller memory 71 for storing instructions.
A main controller processor 72 configured to execute the instructions to cause the main controller to perform operations for implementing the work machine work data verification method described in any of the embodiments (e.g., any of fig. 1-2, 4) above.
Based on the main controller provided by the embodiment of the disclosure, the accuracy and the reliability of the recording in working hours can be improved through the self-checking of the double storage areas of the main controller. According to the embodiment of the disclosure, the storage area fault alarm is added, the data transmission is performed through the Internet of things platform, and the fault information and the working hour abnormal information can be quickly pushed to be sent to service personnel for abnormal condition investigation.
Fig. 8 is a schematic diagram of some embodiments of a cloud server of the present disclosure. As shown in fig. 8, the cloud server of the present disclosure may include a controller data receiving module 81, a cloud data obtaining module 82, and a cloud verification module 83, where:
the controller data receiving module 81 is configured to receive the controller side working data uploaded by the main controller, where the main controller is a engineering machinery main controller.
The cloud data acquisition module 82 is configured to acquire cloud working data.
The cloud verification module 83 is configured to perform cloud working data verification according to the controller end working data and the cloud working data.
In some embodiments of the present disclosure, the cloud verification module 83 may be configured to determine whether a difference between the cloud working data and the controller side working data is greater than a first threshold, or whether the controller side working data is equal to 0; and sending fault abnormal alarm information to the client under the condition that the difference value between the cloud work data and the work data of the controller end is larger than a first threshold value or the work data of the controller end is equal to 0, and sending a work data changing instruction and the cloud work data to the main controller.
In some embodiments of the present disclosure, the cloud verification module 83 may also be configured to obtain cloud self-calculated working data by a cloud server; judging whether the difference value between the working data of the controller end and the cloud self-calculated working data is larger than a second threshold value or not; when the difference value between the working data of the controller and the cloud self-counting working data is larger than a second threshold value, the cloud self-counting working data is used as cloud working data, fault abnormal alarm information is sent to a client, and a working data changing instruction and cloud working data are sent to a main controller; and sending cloud work data to the main controller under the condition that the difference value between the work data of the controller and the cloud self-counting work data is not larger than a second threshold value.
In some embodiments of the present disclosure, the master controller is configured to perform operations for implementing the work machine work data verification method described in any of the embodiments (e.g., any of fig. 3, 5) above.
Fig. 9 is a schematic diagram of other embodiments of a cloud server according to the disclosure. As shown in fig. 9, the cloud server of the present disclosure may include a cloud memory 91 and a cloud processor 92, wherein:
the cloud storage 91 is configured to store instructions.
The cloud processor 92 is configured to execute the instructions, so that the cloud server performs operations for implementing the working data verification method of the working machine according to any one of the embodiments (e.g., any one of fig. 3 and 5).
According to the cloud server provided by the embodiment of the disclosure, the cloud internet of things platform data can be used for checking and automatically calibrating the data of the main controller, and the traditional method for changing the hour meter through on-site password input is changed, so that the service efficiency and the data communication safety are improved, the safety of working hours is improved, and the risk of manually changing the hour meter is reduced.
FIG. 10 is a schematic diagram of some embodiments of a work machine work data verification system of the present disclosure. As shown in fig. 10, the work machine work data verification system of the present disclosure may include a main controller 10, wherein:
The main controller 10 is a program running unit for performing double-storage-area self-checking and storage-area fault diagnosis.
In some embodiments of the present disclosure, the master controller 10 may be the master controller described in any of the embodiments described above (e.g., the fig. 6 or fig. 7 embodiments).
Based on the engineering machinery working data verification system provided by the embodiment of the disclosure, the accuracy and the reliability of the working hour recording can be improved through the self-verification of the double storage areas of the main controller. According to the embodiment of the disclosure, the storage area fault alarm is added, the data transmission is performed through the Internet of things platform, and the fault information and the working hour abnormal information can be quickly pushed to be sent to service personnel for abnormal condition investigation.
In some embodiments of the present disclosure, as shown in fig. 10, the work machine work data verification system may further include a communication terminal 20, a cloud server 30, and a client 40, where:
the communication terminal 20 is used for carrying out communication transmission on the data of the main controller and the data of the cloud server, and the terminal ensures the information communication safety through encryption verification.
In some embodiments of the present disclosure, the communication terminal 20 and the main controller 10 communicate data through a CAN network.
In some embodiments of the present disclosure, the communication terminal 20 may be a GPS terminal.
The client 40 is configured to receive the fault abnormal information of the cloud server 30, learn the site condition, and take measures according to the requirement.
In some embodiments of the present disclosure, the client 40 may be a service person handheld terminal.
The cloud server 30 is configured to receive and store data transmitted by the communication terminal, check the data through the cloud server 30, perform alarm logic judgment, send alarm information to the client 40, and the cloud server 30 may determine according to an abnormal condition, and calibrate the working hours of the main controller 10.
In some embodiments of the present disclosure, the cloud server 30 may be implemented as an internet of things platform server.
In some embodiments of the present disclosure, the communication between the cloud server 30 and the communication terminal 20, and the communication between the cloud server 30 and the client 40 are in a 5G or 4G communication system.
In some embodiments of the present disclosure, the cloud server 30 may be a cloud server as described in any of the embodiments described above (e.g., the embodiment of fig. 8 or 9).
According to the embodiment of the disclosure, the cloud internet of things platform data can be used for checking and automatically calibrating the data of the main controller, and the traditional method for changing the hour meter through on-site password input is changed, so that the service efficiency and the data communication safety are improved, the safety of working hours is improved, and the risk of manually changing the hour meter is reduced.
The embodiment of the disclosure can perform double check of the working hour meter based on the controller double storage areas and the IOT technology, is applied to the hydraulic excavator, is a control technology for improving the statistical accuracy and reliability of the working hour meter of the excavator, and belongs to the technical field of excavator control.
The embodiment of the disclosure can be popularized and applied to the technical fields of engineering machinery time and frequency class data statistics and verification.
According to another aspect of the present disclosure, there is provided a work machine work data verification system that may include a main controller 10 and a cloud server 30, wherein:
the main controller 10 is configured to upload controller-side working data to the cloud server 30.
The cloud server 30 may be any of the cloud servers described in any of the embodiments (e.g., the embodiment of fig. 8 or 9).
According to the embodiment of the disclosure, the IOT technology can be utilized, the working hours of the controller are self-checked through the cloud, and when the controller is replaced or communication is interrupted for a very long time, the hours are automatically calibrated, so that the risk of manually changing the working hours is reduced, the main controller is checked through cloud data processing, abnormal risk alarming of the working hours is carried out, and the statistical accuracy of the working hours is improved.
According to another aspect of the present disclosure, a work machine is provided that includes a main controller as described in any of the embodiments above (e.g., the embodiment of fig. 6 or 7).
In some embodiments of the present disclosure, the engineering machine may further include a communication terminal, where the communication terminal 20 is configured to perform communication transmission between the data of the main controller and the data of the cloud server, and the terminal ensures information communication security through encryption verification, where the communication terminal and the main controller perform data communication through the CAN network.
In some embodiments of the present disclosure, the work machine may be a hydraulic excavator.
Based on the engineering machinery provided by the embodiment of the disclosure, the working hour meter double check is performed based on the controller double storage area and the IOT technology, and the engineering machinery is applied to a hydraulic excavator, is a control technology for improving the statistical accuracy and reliability of the working hour meter of the excavator, and belongs to the technical field of excavator control.
According to the master controller double-storage-area working hour meter checking mechanism, the data accuracy is improved, the error risk is reduced, the storage area fault alarm indication is sent to the client through the cloud, the information is quickly transferred, and the service response efficiency is improved;
According to the embodiment of the disclosure, the IOT technology can be utilized, the cloud end and the main controller 10 can perform work hour self-checking, when the controller is replaced or communication is interrupted for a very long time, the hour meter is automatically calibrated, the risk of manually changing the work hour meter is reduced, the main controller is checked through cloud end data processing, abnormal risk alarming of the work hour is performed, and the statistical accuracy of the work hour is improved.
According to another aspect of the disclosure, a computer readable storage medium is provided, wherein the computer readable storage medium stores computer instructions that, when executed by a processor, implement a work machine work data verification method as described in any of the embodiments (e.g., any of fig. 1-5).
Based on the computer readable storage medium provided by the above embodiments of the present disclosure, the accuracy and reliability of the recording in working hours can be improved by the self-checking of the main controller with double storage areas. According to the embodiment of the disclosure, the storage area fault alarm is added, the data transmission is performed through the Internet of things platform, and the fault information and the working hour abnormal information can be quickly pushed to be sent to service personnel for abnormal condition investigation. Meanwhile, the embodiment of the disclosure can verify and automatically calibrate the data of the main controller by means of the cloud internet of things platform data, and a traditional method for changing the hour meter by inputting the field password is changed, so that service efficiency and data communication safety are improved, working hour safety is improved, and risk of manually changing the hour meter is reduced.
The embodiment of the disclosure provides a working hour verification technology suitable for an excavator, which is a strategy for double-end verification based on an internet of things platform and a CAN communication data transmission mechanism. The technical proposal carries out self-checking through the data of the double storage areas of the controller, provides error warning of the storage areas, feeds back warning information to the information demand party through the cloud,
the embodiment of the disclosure can be verified by the cloud data so as to achieve the purpose of improving the accuracy and the reliability of working hours.
The host controller and cloud server described above may be implemented as general purpose processors, programmable Logic Controllers (PLCs), digital Signal Processors (DSPs), application Specific Integrated Circuits (ASICs), field Programmable Gate Arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or any suitable combination thereof, for performing the functions described herein.
Thus far, the present disclosure has been described in detail. In order to avoid obscuring the concepts of the present disclosure, some details known in the art are not described. How to implement the solutions disclosed herein will be fully apparent to those skilled in the art from the above description.
Those of ordinary skill in the art will appreciate that all or a portion of the steps implementing the above embodiments may be implemented by hardware, or may be implemented by a program indicating that the relevant hardware is implemented, where the program may be stored on a computer readable storage medium, where the storage medium may be a read only memory, a magnetic disk or optical disk, etc.
The description of the present disclosure has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the disclosure in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments were chosen and described in order to best explain the principles of the disclosure and the practical application, and to enable others of ordinary skill in the art to understand the disclosure for various embodiments with various modifications as are suited to the particular use contemplated.
Claims (20)
1. The working data verification method for the engineering machinery is characterized by comprising the following steps of:
the first storage area and the second storage area of the main controller are both stored with working data of the engineering machinery, wherein the main controller is the main controller of the engineering machinery, and the working data is at least one of working hours of the engineering machinery and frequency data of the engineering machinery;
The main controller performs self-checking on the engineering machinery working data stored in the first storage area and the second storage area to obtain controller end working data;
the master controller uploads the working data of the controller end to the cloud server, and instructs the cloud server to check the cloud working data according to the working data of the controller end and the cloud working data;
the cloud server acquires cloud work data;
the cloud server performs cloud work data verification according to the work data of the controller end and the cloud work data;
the cloud server performs cloud work data verification according to the controller end work data and the cloud work data, and the cloud work data verification includes:
the cloud server judges whether the difference value between the cloud work data and the work data of the controller end is larger than a first threshold value;
when the difference value between the cloud end working data and the controller end working data is larger than a first threshold value, the cloud end server sends fault abnormality alarm information to the client end, and sends a working data changing instruction and cloud end working data to the main controller;
under the condition that the difference value between the cloud work data and the work data of the controller end is not greater than a first threshold value, the cloud server acquires cloud self-counting work data;
The cloud server judges whether the difference value between the working data of the controller end and the cloud self-calculated working data is larger than a second threshold value;
when the difference value between the working data of the controller end and the cloud self-counting working data is larger than a second threshold value, the cloud server takes the cloud self-counting working data as cloud working data, sends failure abnormality alarm information to the client, and sends a working data changing instruction and cloud working data to the main controller;
and under the condition that the difference value between the work data of the controller end and the cloud self-counting work data is not greater than a second threshold value, the cloud server sends the cloud work data to the main controller.
2. The work machine work data verification method of claim 1, further comprising:
the main controller judges whether a working data changing instruction of the cloud server is received or not;
and under the condition that the main controller receives the working data changing instruction, the cloud working data are used as working data of the controller end.
3. The construction machine work data verification method according to claim 1 or 2, further comprising:
and the main controller sends storage area error alarm information to the client through the cloud server under the condition that the working data self-checking process detects storage area errors.
4. The method for verifying working data of a construction machine according to claim 1 or 2, wherein the main controller performs self-verification on working data of the construction machine stored in the first storage area and the second storage area, and obtaining working data of a controller side includes:
the main controller judges whether the first storage area and the second storage area have faults or not;
under the condition that the first storage area is free from faults and the second storage area is faulty, the main controller takes the first engineering machinery working data stored in the first storage area as controller end working data, and uploads the controller end working data and the second storage area fault alarm information to the cloud server.
5. The method for verifying working data of a construction machine according to claim 4, wherein the main controller performs self-verification on working data of the construction machine stored in the first storage area and the second storage area, and obtaining working data of a controller side further comprises:
and under the conditions that the first storage area has a fault and the second storage area has no fault, the main controller takes the second engineering machinery working data stored in the second storage area as controller end working data, and uploads the controller end working data and the first storage area fault alarm information to the cloud server.
6. The method for verifying working data of a construction machine according to claim 4, wherein the main controller performs self-verification on working data of the construction machine stored in the first storage area and the second storage area, and obtaining working data of a controller side further comprises:
and the main controller takes the cloud working data as controller end working data under the condition that the first storage area has faults and the second storage area has faults, and uploads the controller end working data, the first storage area fault alarm information and the second storage area fault alarm information to the cloud server.
7. The method for verifying working data of a construction machine according to claim 4, wherein the main controller performs self-verification on working data of the construction machine stored in the first storage area and the second storage area, and obtaining working data of a controller side further comprises:
under the condition that the first storage area has no fault and the second storage area has no fault, the main controller takes the first engineering machinery working data stored in the first storage area as controller end working data, and judges whether the absolute value of the difference value of the first engineering machinery working data and the second engineering machinery working data is larger than a self-checking threshold value;
The method comprises the steps that when the absolute value of the difference value between the first engineering machine working data and the second engineering machine working data is not larger than a self-checking threshold value, the main controller uploads controller end working data to a cloud server;
and uploading the working data of the controller end and the verification abnormality alarm information to the cloud server by the main controller under the condition that the absolute value of the difference value of the working data of the first engineering machine and the working data of the second engineering machine is larger than the self-verification threshold value.
8. The working data verification method for the engineering machinery is characterized by comprising the following steps of:
the cloud server receives controller end working data uploaded by a main controller, wherein the working data is at least one of engineering machinery working hours and engineering machinery frequency data, the main controller is an engineering machinery main controller, and the controller end working data is obtained by self-checking the engineering machinery working data stored in a first storage area and a second storage area by the main controller;
the cloud server acquires cloud work data;
the cloud server performs cloud work data verification according to the work data of the controller end and the cloud work data;
the cloud server performs cloud work data verification according to the controller end work data and the cloud work data, and the cloud work data verification includes:
The cloud server judges whether the difference value between the cloud work data and the work data of the controller end is larger than a first threshold value;
when the difference value between the cloud end working data and the controller end working data is larger than a first threshold value, the cloud end server sends fault abnormality alarm information to the client end, and sends a working data changing instruction and cloud end working data to the main controller;
under the condition that the difference value between the cloud work data and the work data of the controller end is not greater than a first threshold value, the cloud server acquires cloud self-counting work data;
the cloud server judges whether the difference value between the working data of the controller end and the cloud self-calculated working data is larger than a second threshold value;
when the difference value between the working data of the controller end and the cloud self-counting working data is larger than a second threshold value, the cloud server takes the cloud self-counting working data as cloud working data, sends failure abnormality alarm information to the client, and sends a working data changing instruction and cloud working data to the main controller;
and under the condition that the difference value between the work data of the controller end and the cloud self-counting work data is not greater than a second threshold value, the cloud server sends the cloud work data to the main controller.
9. The method for verifying working data of an engineering machine according to claim 8, wherein the cloud server performing cloud working data verification according to the controller side working data and the cloud working data further comprises:
The cloud server judges whether the working data of the controller end is equal to 0;
and under the condition that the working data of the controller end is equal to 0, the cloud server sends fault abnormal alarm information to the client and sends a working data changing instruction and cloud working data to the main controller.
10. A master controller, comprising:
the first storage area and the second storage area are used for respectively storing working data of the engineering machinery, wherein the main controller is the engineering machinery main controller, and the working data is at least one of working hours of the engineering machinery and frequency data of the engineering machinery;
the self-checking module is used for carrying out self-checking on the engineering machinery working data stored in the first storage area and the second storage area to obtain controller end working data;
the main controller is further used for uploading the controller end working data to the cloud server, indicating the cloud server to obtain the cloud working data, and performing cloud working data verification according to the controller end working data and the cloud working data, wherein the cloud server performs cloud working data verification according to the controller end working data and the cloud working data, and the cloud working data verification comprises: the cloud server judges whether the difference value between the cloud work data and the work data of the controller end is larger than a first threshold value; when the difference value between the cloud end working data and the controller end working data is larger than a first threshold value, the cloud end server sends fault abnormality alarm information to the client end, and sends a working data changing instruction and cloud end working data to the main controller; under the condition that the difference value between the cloud work data and the work data of the controller end is not greater than a first threshold value, the cloud server acquires cloud self-counting work data; the cloud server judges whether the difference value between the working data of the controller end and the cloud self-calculated working data is larger than a second threshold value; when the difference value between the working data of the controller end and the cloud self-counting working data is larger than a second threshold value, the cloud server takes the cloud self-counting working data as cloud working data, sends failure abnormality alarm information to the client, and sends a working data changing instruction and cloud working data to the main controller; and under the condition that the difference value between the work data of the controller end and the cloud self-counting work data is not greater than a second threshold value, the cloud server sends the cloud work data to the main controller.
11. The master controller according to claim 10, wherein the master controller is configured to perform operations for implementing the work machine work data verification method according to any one of claims 2-7.
12. A master controller, comprising:
a main controller memory for storing instructions;
a main controller processor for executing the instructions to cause the main controller to perform operations to implement the work machine work data verification method of any one of claims 1-7.
13. A cloud server, comprising:
the controller data receiving module is used for receiving the working data of the controller end uploaded by the main controller, wherein the working data is at least one of working hours of engineering machinery and frequency data of the engineering machinery, the main controller is a main controller of the engineering machinery, and the working data of the controller end is obtained by self-checking the working data of the engineering machinery stored in the first storage area and the second storage area by the main controller;
the cloud data acquisition module is used for acquiring cloud work data;
the cloud verification module is used for verifying cloud working data according to the working data of the controller end and the cloud working data;
The cloud verification module is used for judging whether the difference value between the cloud working data and the working data of the controller end is larger than a first threshold value; under the condition that the difference value between the cloud work data and the work data of the controller end is larger than a first threshold value, sending fault abnormal alarm information to the client end, and sending a work data changing instruction and the cloud work data to the main controller; acquiring cloud self-counting working data under the condition that the difference value between the cloud working data and the working data of the controller end is not greater than a first threshold value; judging whether the difference value between the working data of the controller end and the cloud self-calculated working data is larger than a second threshold value or not; when the difference value between the working data of the controller and the cloud self-counting working data is larger than a second threshold value, the cloud self-counting working data is used as cloud working data, fault abnormal alarm information is sent to a client, and a working data changing instruction and cloud working data are sent to a main controller; and sending cloud work data to the main controller under the condition that the difference value between the work data of the controller and the cloud self-counting work data is not larger than a second threshold value.
14. The cloud server of claim 13, wherein the master controller is configured to perform operations for implementing the work machine work data verification method of claim 9.
15. A cloud server, comprising:
the cloud storage is used for storing the instructions;
the cloud processor is configured to execute the instruction, so that the cloud server executes an operation of implementing the working data verification method of the engineering machine according to claim 8 or 9.
16. A work machine work data verification system comprising a master controller as claimed in any one of claims 10 to 12.
17. The work machine work data verification system of claim 16, further comprising a cloud server according to any one of claims 13-15.
18. An engineering machine tool work data verification system, characterized by comprising:
the main controller is used for uploading working data of the controller end to the cloud server;
cloud server according to any of claims 13-15.
19. A construction machine comprising a main controller according to any one of claims 10-12.
20. A computer readable storage medium storing computer instructions which, when executed by a processor, implement the work machine work data verification method of any one of claims 1-9.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010425612.0A CN111598267B (en) | 2020-05-19 | 2020-05-19 | Engineering machine, working data verification method, device and system thereof and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010425612.0A CN111598267B (en) | 2020-05-19 | 2020-05-19 | Engineering machine, working data verification method, device and system thereof and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111598267A CN111598267A (en) | 2020-08-28 |
| CN111598267B true CN111598267B (en) | 2023-09-29 |
Family
ID=72190382
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010425612.0A Active CN111598267B (en) | 2020-05-19 | 2020-05-19 | Engineering machine, working data verification method, device and system thereof and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111598267B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114280993A (en) * | 2021-12-24 | 2022-04-05 | 徐州徐工挖掘机械有限公司 | Device and method for guaranteeing data safety of engineering machinery |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103246574A (en) * | 2012-02-10 | 2013-08-14 | 阿里巴巴集团控股有限公司 | Verification method and verification device for data accuracy |
| CN105245578A (en) * | 2015-09-11 | 2016-01-13 | 北京金山安全软件有限公司 | Data uploading method, data uploading system and data uploading device |
| CN107483157A (en) * | 2017-09-01 | 2017-12-15 | 郑州云海信息技术有限公司 | A kind of CRC check method and system based on FPGA |
| CN107643882A (en) * | 2017-09-29 | 2018-01-30 | 昂纳信息技术（深圳）有限公司 | The storage and restoration methods of a kind of data reliability, system and storage device |
-
2020
- 2020-05-19 CN CN202010425612.0A patent/CN111598267B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103246574A (en) * | 2012-02-10 | 2013-08-14 | 阿里巴巴集团控股有限公司 | Verification method and verification device for data accuracy |
| CN105245578A (en) * | 2015-09-11 | 2016-01-13 | 北京金山安全软件有限公司 | Data uploading method, data uploading system and data uploading device |
| CN107483157A (en) * | 2017-09-01 | 2017-12-15 | 郑州云海信息技术有限公司 | A kind of CRC check method and system based on FPGA |
| CN107643882A (en) * | 2017-09-29 | 2018-01-30 | 昂纳信息技术（深圳）有限公司 | The storage and restoration methods of a kind of data reliability, system and storage device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111598267A (en) | 2020-08-28 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9709973B2 (en) | Handheld field maintenance tool with improved diagnostics | |
| RU2576588C2 (en) | Detection of sensor performance degradation implemented in transmitter | |
| US11307566B2 (en) | System and method for diagnosing pneumatic control valve online | |
| US20140379302A1 (en) | Apparatus and method for controlling water quality sensor faults | |
| CN113572576B (en) | Sampling data verification method and device, relay protection device and storage medium | |
| CN113157524B (en) | Big data based exception problem solving method, system, equipment and storage medium | |
| CN112630682B (en) | Sensor fault detection method, device and equipment | |
| CN111598267B (en) | Engineering machine, working data verification method, device and system thereof and storage medium | |
| CN104777463B (en) | Selfreparing array system and method | |
| CN111063048A (en) | Method and device for processing equipment inspection information and electronic equipment | |
| CN117664281B (en) | Ultrasonic water meter fault detection and automatic calibration method and system based on Internet of Things | |
| CN104931906A (en) | Integrated circuit test system digit channel transmission delay calibration method and system | |
| CN104716740A (en) | Fixed value calibration method, device and system for relay protection device | |
| CN111581192B (en) | Nuclear power plant reactor important sensitive parameter management method, device, equipment and medium | |
| CN110554940A (en) | Serial port detection tool and method based on electric energy meter communication | |
| US10922412B2 (en) | Automatic tampering detection in networked control systems | |
| CN110493714A (en) | A kind of bluetooth auxiliary positioning returning method and its system | |
| EP2506103A1 (en) | Method and device for automatically detecting erroneous air data on an aircraft | |
| KR102575917B1 (en) | IoT sensor abnormality diagnosing method and system using cloud-based virtual sensor | |
| WO2016136391A1 (en) | Fault point locating device and method, electric power system monitoring system, and facility planning support system | |
| CN112380073B (en) | Fault position detection method and device and readable storage medium | |
| US20190041838A1 (en) | Detection of temperature sensor failure in turbine systems | |
| CN111309584B (en) | Data processing method, device, electronic equipment and storage medium | |
| US11836057B2 (en) | Fault location in a redundant acquisition system | |
| CN114325765B (en) | Integrity detection optimization method and computer-readable storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |