CN114357262A - Method, processor and server for engineering equipment - Google Patents
Method, processor and server for engineering equipment Download PDFInfo
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Abstract
The invention relates to the technical field of engineering machinery and discloses a method, a processor and a server for engineering equipment. The method comprises the following steps: receiving fault phenomenon classification determined by a terminal or determining fault phenomenon classification corresponding to fault phenomenon description information in a fault phenomenon classification set; determining historical fault cause information classified according to fault phenomena in a historical fault database, wherein the historical fault cause information comprises the probability of occurrence of each fault cause; and determining a fault maintenance scheme based on the historical fault reason information, wherein the fault maintenance scheme comprises a fault troubleshooting sequence determined based on the probability of occurrence of each fault reason, and the fault maintenance scheme is a maintenance scheme which is compiled in advance in a historical fault database for fault phenomenon classification. The invention can quickly position the fault point for the service personnel, provides the optimal troubleshooting step and improves the working efficiency and the fault overhauling reliability of the field service personnel.
Description
Technical Field
The invention relates to the technical field of engineering machinery, in particular to a method, a processor and a server for engineering equipment.
Background
Engineering equipment may be in failure in the using process, for example, the engineering equipment is a crane, the crane refers to a multi-action crane for vertically lifting and horizontally carrying heavy objects within a certain range, and the types of the crane are various, for example, the crane includes: tire cranes, bridge cranes, truck cranes, crawler cranes, and the like. The operator may find some faults during the operation of the crane and describe the faults, such as: the amplitude variation action is slow, the arm support cannot be extended and contracted normally, and the like. After the faults of the engineering equipment are found, the faults are checked and repaired mainly by the personal experience of engineers at present, the personal ability of the engineers is excessively depended, and the reliability is low.
Disclosure of Invention
In order to overcome the defects in the prior art, embodiments of the present invention provide a method, a processor, and a server for engineering equipment.
In order to achieve the above object, a first aspect of the present invention provides a method for an engineering apparatus, comprising:
receiving fault phenomenon classification determined by a terminal or determining fault phenomenon classification corresponding to fault phenomenon description information in a fault phenomenon classification set;
determining historical fault cause information classified according to fault phenomena in a historical fault database, wherein the historical fault cause information comprises the probability of occurrence of each fault cause;
and determining a fault maintenance scheme based on the historical fault reason information, wherein the fault maintenance scheme comprises a fault troubleshooting sequence determined based on the probability of occurrence of each fault reason, and the fault maintenance scheme is a maintenance scheme which is compiled in advance in a historical fault database for fault phenomenon classification.
In the embodiment of the invention, the establishment mode of the historical fault database comprises the following steps:
receiving input fault phenomenon description information;
performing semantic analysis on the fault phenomenon description information;
and clustering the fault phenomenon description information according to the semantic analysis result to form a corresponding relation between the fault phenomenon description information and the fault phenomenon classification.
In the embodiment of the present invention, determining the classification of the fault phenomenon corresponding to the fault phenomenon description information includes:
calculating the fault phenomenon description information by using a pre-trained text data classification model;
and determining fault phenomenon classifications corresponding to the fault phenomenon description information, wherein the fault phenomenon classifications correspond to the classification numbers one to one.
In the embodiment of the invention, each fault reason comprises a fault component in the engineering equipment and a fault type of the component, the probability comprises a probability of component fault classified according to fault phenomena and a probability of the fault type, and the troubleshooting sequence comprises a troubleshooting sequence determined according to the probability of the component fault and the probability of the fault type and aiming at the component.
In an embodiment of the present invention, the method further comprises:
historical processor information for fault phenomenon classification is determined in a historical fault database, and the historical processor information comprises names and contact information of processors and frequency of processing fault phenomenon classification of the processors.
In an embodiment of the invention, the troubleshooting plan includes a respective troubleshooting plan for a respective cause of failure.
In an embodiment of the invention, the troubleshooting plan includes a troubleshooting plan for the component and the fault category, the troubleshooting plan including: replacing the component or directing the repair of the component according to the type of failure.
In the embodiment of the present invention, the overhaul scheme further includes:
compiling personnel names and contact ways of the maintenance schemes; and
at least one of a suitable vehicle type, a suitable tonnage grade, a suitable product platform, and a suitable engineering equipment type for the overhaul scheme.
In the embodiment of the present invention, the historical failure cause information further includes the frequency of occurrence of each failure cause.
In the embodiment of the present invention, the description information of the fault phenomenon includes model information of the engineering equipment in which the fault phenomenon occurs, and the method further includes:
matching model information in a historical fault database;
matching tonnage level information corresponding to the model information in a historical fault database under the condition that the model information is not matched;
matching product platform information corresponding to tonnage grade information in a historical fault database under the condition that the tonnage grade information is not matched;
and matching the engineering equipment type information corresponding to the product platform information in the historical fault database under the condition that the product platform information is not matched.
In an embodiment of the present invention, the method further comprises:
under the condition that the model information is matched in the historical fault database, determining the number of fault phenomenon classifications under the model information in the historical fault database;
under the condition that tonnage level information is matched in the historical fault database, determining the number of fault phenomenon classifications under the tonnage level information in the historical fault database;
under the condition that the product platform information is matched in the historical fault database, determining the quantity of fault phenomenon classifications under the product platform information in the historical fault database;
and under the condition that the type information of the engineering equipment is matched in the historical fault database, determining the number of fault phenomenon classifications under the type information of the engineering equipment in the historical fault database.
A second aspect of the invention provides a processor configured to perform the above-described method for engineering equipment.
A third aspect of the invention provides a server comprising the processor described above.
A fourth aspect of the invention provides a machine-readable storage medium having stored thereon instructions for causing a machine to perform the above-described method for an engineering machine.
In the technical scheme, after a service person discovers a fault of engineering equipment (such as a crane), the fault is described to form fault phenomenon description information. The service personnel can select corresponding fault phenomenon classification at the terminal according to the fault phenomenon description information, then the terminal sends the fault phenomenon classification to the historical fault database, or the service personnel inputs the fault phenomenon description information to a server corresponding to the historical fault database, the historical fault database can calculate the fault phenomenon description information, and the fault phenomenon classification corresponding to the fault phenomenon description information is determined in the fault phenomenon classification set.
After the fault classification is determined, historical fault cause information for the fault classification in the past records can be determined in the historical fault database according to the stored historical data, and the probability of occurrence of each fault cause of the fault classification can be determined in the past records. The method and the system have the advantages that a large amount of historical data in the historical fault database is used as a support, and service personnel can perform troubleshooting based on the probability of each fault reason, for example, the fault reason with the higher probability is preferably debugged, so that compared with the prior art that troubleshooting and maintenance are performed on the fault mainly by depending on personal experience of engineers, in the embodiment of the invention, fault points can be quickly positioned for the service personnel, the optimal troubleshooting step is provided, and the working efficiency of field service personnel is improved. In addition, the historical fault database also comprises a fault maintenance scheme which is compiled in advance according to historical fault reason information, and after the service personnel determine fault phenomenon classification, the service personnel can directly refer to the maintenance scheme in the historical fault database to perform maintenance, so that the reliability and the working efficiency of fault maintenance are further improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the embodiments of the invention without limiting the embodiments of the invention. In the drawings:
fig. 1 schematically shows a flow chart of a method for engineering equipment according to an embodiment of the invention;
FIG. 2 schematically illustrates a block diagram of a fault pre-diagnosis according to an embodiment of the present invention;
fig. 3 schematically shows a schematic diagram of service docking according to an embodiment of the invention.
Detailed Description
The following detailed description of embodiments of the invention refers to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating embodiments of the invention, are given by way of illustration and explanation only, not limitation.
It should be noted that, if directional indications (such as up, down, left, right, front, and rear … …) are referred to in the embodiments of the present application, the directional indications are only used to explain the relative positional relationship between the components, the movement situation, and the like in a specific posture (as shown in the drawings), and if the specific posture is changed, the directional indications are changed accordingly.
In addition, if there is a description of "first", "second", etc. in the embodiments of the present application, the description of "first", "second", etc. is for descriptive purposes only and is not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In addition, technical solutions between the various embodiments can be combined with each other, but must be realized by a person skilled in the art, and when the technical solutions are contradictory or cannot be realized, such a combination should not be considered to exist, and is not within the protection scope of the present application.
Fig. 1 schematically shows a flow chart of a method for engineering equipment according to an embodiment of the invention. As shown in fig. 1, in an embodiment of the present invention, there is provided a method for engineering equipment, including the steps of:
and 103, determining a fault maintenance scheme based on the historical fault reason information, wherein the fault maintenance scheme comprises a fault troubleshooting sequence determined based on the probability of each fault reason, and the fault maintenance scheme is a maintenance scheme which is compiled in advance for fault phenomenon classification in a historical fault database.
After finding out the fault of the engineering equipment, the service personnel describe the fault to form fault phenomenon description information. Taking engineering equipment as an example of a crane, the fault phenomenon description information may be, for example: the amplitude variation action is slower, and the arm support can not be extended normally. The historical fault database may be located in the smart service cloud platform. In the embodiment of the invention, the service request can be understood as that equipment faults occur in the field operation process of the crane, a user describes the fault phenomenon and the problem to be solved through a service telephone, and a customer service staff records the request description in a service desk system, and the process is called as the service request. The fault pre-diagnosis can be understood as that based on the service request, the troubleshooting priority sequence of the fault is intelligently pushed through the analysis of the intelligent service cloud platform, and the problem of the service request is rapidly positioned and solved by combining a fault expert knowledge base.
The fault phenomenon description information and the fault phenomenon classification are in corresponding relation, for example, the variable amplitude action is slower than the fault phenomenon description information, and the corresponding fault phenomenon classification is slow variable amplitude action; the 'arm support can not be extended normally' is fault phenomenon description information, and the corresponding fault phenomenon classification is 'arm support extension fault'. The service personnel can select corresponding fault phenomenon classification at the terminal (which can be a client APP) according to the fault phenomenon description information, then the terminal sends the fault phenomenon classification to the historical fault database, or the service personnel inputs the fault phenomenon description information to a server corresponding to the historical fault database, the historical fault database can calculate the fault phenomenon description information, and the fault phenomenon classification corresponding to the fault phenomenon description information is determined in the fault phenomenon classification set.
After the current fault phenomenon classification is determined, the historical fault database may determine historical fault cause information for the fault phenomenon classification, taking the current fault phenomenon classification as "amplitude variation action slow" as an example, please refer to table 1.
TABLE 1
The service personnel determine that the fault phenomenon description information of the crane at this time is that amplitude variation motion is slow, the historical fault database determines that the corresponding fault phenomenon is classified as slow amplitude variation motion, and then based on the service request of slow amplitude variation motion, the historical fault database can display the information shown in the table 1 to the service personnel. The service personnel can know from the table 1 that in the use process of the traditional crane, 500 times of slow amplitude variation action caused by internal leakage of the main oil pump occurs, 300 times of slow amplitude variation action caused by oil leakage of the amplitude variation balance valve occurs, and 200 times of slow amplitude variation action caused by blockage of the amplitude variation balance valve occurs. That is, the historical failure cause information also includes the frequency with which the respective failure causes occurred. It can be understood that the historical fault reasons correspond to the internal leakage of the main oil pump, the oil leakage of the variable amplitude balance valve and the blockage of the variable amplitude balance valve.
The service personnel can also know from table 1 that in the historical fault database, when the fault phenomenon classification is 'amplitude variation slow motion', the past data statistics show that 50% of the probability is caused by the internal leakage of the main oil pump, 30% of the probability is caused by the oil leakage of the amplitude variation balance valve, and 20% of the probability is caused by the blockage of the amplitude variation balance valve. Therefore, after finding the fault that the amplitude variation action is slow, service personnel can preferentially check the problem of the internal leakage of the main oil pump and then sequentially check the problems of the oil leakage of the amplitude variation balance valve and the blockage of the amplitude variation balance valve based on historical data in a historical fault database. Therefore, faults are not required to be checked and overhauled completely by the personal experience of engineers, the personal ability of the engineers is not required to be excessively depended, even if the service personnel are novice service personnel, the faults can be checked based on the troubleshooting sequence suggested in the historical fault database, fault points can be quickly located for the service personnel, the optimal checking step is provided, and the working efficiency of field service personnel and the reliability of fault overhauling are improved. And (4) rapidly positioning the fault corresponding to the service request in a flow, process and system manner to obtain an optimized solution path.
The service personnel can also know from the table 1 that in the historical fault database, the past data statistics show that the crane luffing motion is slow due to the fault of the main oil pump by 50% of probability, and the crane luffing motion is slow due to the fault of the luffing balance valve by 50% of probability. Therefore, after finding the fault that the amplitude variation action is slow, the service personnel can preferentially check the main oil pump and the amplitude variation balance valve. If the main oil pump and the amplitude variation balance valve have no problems, service personnel determine other fault reasons causing 'slow amplitude variation action' in the troubleshooting, at the moment, the newly found fault reasons can be recorded by the historical fault database, the fault phenomenon of 'slow amplitude variation action' is classified correspondingly, the fault reasons serve as data bases of the later troubleshooting, the increase, deletion and modification of support data in the historical fault database are realized, and the construction of the database content is a long-term and continuous process.
In one embodiment, historical processor information for a classification of a fault phenomenon is determined in a historical fault database, the historical processor information including names of processors, contact addresses, and frequencies of processing of the classification of the fault phenomenon by the processors.
TABLE 2
Referring to table 2, in the historical fault database, the past data statistics shows that the fault phenomenon classification of amplitude variation slow action is performed by Zhang three times for 20 times, the fault phenomenon classification of amplitude variation slow action is performed by Liquan for 10 times, and the fault phenomenon classification of amplitude variation slow action is performed by Wang five times for 2 times. Therefore, after the service personnel find that the amplitude variation action is slow, the service personnel can consult Zhang III and Lile IV preferentially and consult Wang V. Because the historical fault database shows that the processing experience of Zhang three and Lile four is the most for the fault phenomenon classification of 'amplitude variation action slow'. Therefore, by consulting Zhang III, Li IV and Wang V, the troubleshooting efficiency of the field service personnel can be improved.
In an embodiment, the troubleshooting plan includes a respective troubleshooting plan for a respective cause of failure.
In this way, when a service person finds that the amplitude variation action is slow, the service person can inquire historical fault reason information and can inquire various pre-programmed maintenance schemes for various fault reasons, and the reliability and the working efficiency of fault maintenance are improved for the service person.
In an embodiment, the troubleshooting scheme includes a troubleshooting scheme for the component and the fault category, the troubleshooting scheme including: replacing the component or directing the repair of the component according to the type of failure.
With reference to the above examples, the troubleshooting schemes include a troubleshooting scheme for the main oil pump and the luffing balance valve. The fault maintenance scheme comprises a maintenance scheme aiming at internal leakage of the main oil pump, oil leakage of the variable amplitude balance valve and blockage of the variable amplitude balance valve. The maintenance scheme comprises the following steps: failure cause analysis (analysis of the likelihood of causing the failure), failure resolution steps (disassembly sequence and inspection of part specifications), and failure resolution advice (maintenance guidance process or replacement of parts).
In an embodiment, the service plan further comprises:
compiling personnel names and contact ways of the maintenance schemes; and
at least one of a suitable vehicle type, a suitable tonnage grade, a suitable product platform, and a suitable engineering equipment type for the overhaul scheme.
In one embodiment, the historical failure database is established in a manner that includes:
receiving input fault phenomenon description information;
performing semantic analysis on the fault phenomenon description information;
and clustering the fault phenomenon description information according to the semantic analysis result to form a corresponding relation between the fault phenomenon description information and the fault phenomenon classification.
The historical fault database can adopt a text semantic clustering analysis technology to realize structured processing on service request data, such as k-means, Affinity prediction and other clustering algorithms, to form a service request dictionary set, which can also be called a fault phenomenon classification set. Exemplarily, the unified clustering of "luffing motion is somewhat slow", "luffing motion is not fast enough" and "luffing too slow" is classified as "luffing motion slow". And uniformly clustering and classifying the boom extension fault, the boom failure to extend normally and the boom failure to extend into the boom extension fault. It can be understood that the "variable amplitude motion is a little slower", "variable amplitude motion is not fast enough", "variable amplitude is too slow", "boom extension has a point fault", "boom cannot normally extend", and "boom cannot extend", which are service request data (i.e. fault phenomenon description information), and belong to unstructured data. The variable amplitude action is slow, and the boom extension fault is structured data which is subjected to structured processing, and the structured data can form a service request dictionary set (namely a fault phenomenon classification set).
In the embodiment of the invention, the structured processing of the service request data is realized by adopting a text semantic clustering analysis technology to form a service request dictionary set. And making service request solution information by using a data statistical analysis development technology. The method comprises the steps of building an overhaul scheme expert database data system corresponding to a component-fault type in service request solution information through a relational database development technology, organically combining the service request solution information and an overhaul scheme expert database, deploying the service request solution information and the overhaul scheme expert database on an intelligent service cloud platform, and applying the service E-pass (which can be understood as a client terminal APP) to a carried application mode for field service personnel.
In one embodiment, determining the classification of the phenomena corresponding to the phenomena-of-failure description information includes:
calculating the fault phenomenon description information by using a pre-trained text data classification model;
and determining fault phenomenon classifications corresponding to the fault phenomenon description information, wherein the fault phenomenon classifications correspond to the classification numbers one to one.
The method comprises the steps of training and analyzing text data of a service request field in historical data by adopting a deep neural network learning technology to obtain a corresponding text data classification model, sequentially calculating service request text data (namely fault phenomenon description information) in each record by applying the trained classification model to obtain a number corresponding to a service request, wherein the number at the moment is the number corresponding to fault phenomenon classification and belongs to structured data.
In one embodiment, the fault phenomenon description information includes model information of the engineering equipment in which the fault phenomenon occurs, and the method further includes:
matching model information in a historical fault database;
matching tonnage level information corresponding to the model information in a historical fault database under the condition that the model information is not matched;
matching product platform information corresponding to tonnage grade information in a historical fault database under the condition that the tonnage grade information is not matched;
and matching the engineering equipment type information corresponding to the product platform information in the historical fault database under the condition that the product platform information is not matched.
Historical fault cause information and maintenance schemes corresponding to fault phenomenon classifications of cranes of different models may be different. Therefore, after determining the failure description information, the service person needs to input the model information of the failed vehicle (such as the vehicle VIN code), and the VIN code of the vehicle can be understood as the ID of the vehicle. The historical fault database can be preferentially matched with the model information of the fault vehicle, and if the model information is not matched, the historical fault database temporarily does not record the fault phenomenon classification under the model information. At the moment, the historical fault database is matched with tonnage level information corresponding to the model information, so that the data matched by the historical fault database is as close as possible to the information of the fault vehicle. The classification of the product platform information may include: three-bridge cranes, four-bridge cranes or five-bridge cranes, etc., that is to say, the three-bridge cranes and the four-bridge cranes belong to different product platforms. The classification of the engineering device type information may include: tire cranes, bridge cranes, truck cranes, crawler cranes, and the like.
Illustratively, assuming that a vehicle found to be in fault by a service person is a vehicle a, the fault phenomenon classification is 'amplitude variation slow motion', and the historical fault database stores historical fault cause information and fault overhaul schemes for the 'amplitude variation slow motion' vehicle B, the vehicle a and the vehicle B are preferably of the same vehicle type, so that the information about the vehicle B in the historical fault database has the most reference value. If the A vehicle and the B vehicle are not of the same model, the A vehicle and the B vehicle are preferably of the same tonnage class. If the A and B vehicles are not of the same tonnage class, then the A and B vehicles are preferably the same product platform, e.g., the A and B vehicles are both four-axle cranes. If the A vehicle and the B vehicle are not the same product platform, then the A vehicle and the B vehicle are preferably the same construction equipment type, such as the A vehicle and the B vehicle are both tire hoists.
In an embodiment, the method further comprises:
under the condition that the model information is matched in the historical fault database, determining the number of fault phenomenon classifications under the model information in the historical fault database;
under the condition that tonnage level information is matched in the historical fault database, determining the number of fault phenomenon classifications under the tonnage level information in the historical fault database;
under the condition that the product platform information is matched in the historical fault database, determining the quantity of fault phenomenon classifications under the product platform information in the historical fault database;
and under the condition that the type information of the engineering equipment is matched in the historical fault database, determining the number of fault phenomenon classifications under the type information of the engineering equipment in the historical fault database.
Referring to the above example, the a vehicle is a vehicle in which a service person finds a fault, and the B vehicle is a vehicle to which the historical fault database is matched according to the fault phenomenon classification. If the vehicle A and the vehicle B are of the same model, the historical fault database can count the frequency of 'slow amplitude variation action' of the vehicle B under the model information, and service personnel of the vehicle A can inquire and refer to the frequency. If the model of the vehicle B is not matched with the model of the vehicle A, and the vehicle B and the vehicle A belong to the same tonnage class, the historical fault database can count the frequency of amplitude variation slow action of the vehicle B under the tonnage class information, and service personnel of the vehicle A can inquire and refer to the frequency. Exemplarily, assuming that the vehicle A is a four-bridge crane, the historical fault database can count the frequency and probability of the occurrence of the fault of 'slow luffing motion' of the former four-bridge crane. Assuming that the vehicle A is a tire crane, the historical fault database can count the frequency and the probability of the conventional tire crane having the fault of slow amplitude variation.
Counting the number of the component-fault types corresponding to the service request from the historical CRM records, counting the service engineer information corresponding to the service request, and making solution information of the service request:
(1) classifying the vehicle types in a historical fault database, and then counting the following information of each vehicle type according to the number of the service request (namely the number corresponding to the fault phenomenon classification):
1) the number of each service request;
2) the name and telephone of the service engineer who has solved the service request, and the number of times each service engineer has solved the problem;
3) the number of "component-failure categories" to which the service request corresponds, and thus the probability that each "component-failure mode" causes this "service request" for that vehicle model is calculated.
(2) According to the calculation result in the item (1), calculating the following information of each tonnage grade:
1) the number of each service request;
2) the name and telephone of the service engineer who has solved the service request, and the number of times each service engineer has solved the problem;
3) the number of "component-fault classes" to which the service request corresponds, and thus the probability that each "component-fault class" causes this "service request" for that tonnage class.
(3) Calculating the following information of each product platform according to the calculation result in the item (2):
1) the number of each service request;
2) the name and telephone of the service engineer who has solved the service request, and the number of times each service engineer has solved the problem;
3) the number of "component-failure classes" to which the service request corresponds, and thus the probability that each "component-failure class" causes such a "service request" for the product platform is calculated.
(4) Similarly, the information on each type of crane is calculated from the calculation result in item (3), and the crane types include: automobile cranes, tire cranes, crawler cranes, and the like. Thus, the fault pre-diagnosis system based on the service request can be established for various streaming cranes such as automobile cranes, crawler cranes, tire cranes and the like.
When the service personnel determine that the vehicle A (taking engineering equipment as an example of the vehicle) has a fault, the fault is slow in amplitude variation action, and the model information of the vehicle A is determined. At this time, the historical fault database may present the following report to the service personnel of the a vehicle to assist the service personnel in resolving the fault of the a vehicle. See table 3.
TABLE 3
Service personnel and historical fault database (server) can utilize client APP (client can understand the terminal) to interact, after service personnel inputs the model information and the fault phenomenon classification of A vehicle (can understand the service request) at client APP, the server just shows the information as shown in table 3 to service personnel through client APP, according to past data record and statistics in the historical fault database, assists service personnel to fix a position the fault point fast, provides the optimal troubleshooting step, improves on-the-spot service personnel's work efficiency. The names and contact modes of the personnel writing the maintenance plan are also included in the table 3, and if the places in question of the maintenance plan are in question, the personnel writing the maintenance plan can be directly contacted by telephone. The information of the service engineer who has solved the service request in the past is also included in table 3, and the service person of the vehicle a can directly go to the telephone to consult zhang and lie si, thereby solving the fault of the vehicle a more quickly. The information shown in table 3 is a pre-diagnosis report for the vehicle failure a given according to past data records and statistics in the historical failure database, and is referred by the service staff.
Fig. 2 is a block diagram schematically illustrating a structure of a fault pre-diagnosis according to an embodiment of the present invention, and may refer to fig. 2. The fault pre-diagnosis model runs regularly (for example, runs once a month), and the accumulated CRM data is analyzed and mined, and the following data is output: in order to solve the problem of the service request (crane fault phenomenon), it is necessary to sequentially search the optimal sequence of different "component-fault modes", and output the name of the service engineer who has solved the service request problem and a telephone list, and these output information are stored in a database. Through the interactive interface of the overhaul scheme expert database system, the overhaul scheme corresponding to the component-fault category can be edited and then stored in the database. The database provides data support for fault diagnosis.
The service personnel inputs 'service request' and the VIN code of trouble vehicle at customer end APP, and the customer end sends these information to the cloud end of wisdom service center platform, and the cloud end can carry out following operation: (1) inquiring the model of the vehicle with the fault according to the vehicle VIN code; (2) inquiring a service engineer information list from a database according to the vehicle model and the service request; (3) inquiring an information list of 'component-fault types' from a database according to the vehicle model and the service request; (4) inquiring a specific maintenance scheme of each component-fault type from a maintenance scheme database according to the serial number of each component-fault type and the vehicle model in the information list of the component-fault types; (5) and generating a fault diagnosis report according to the information, which can be referred to as table 3. And displaying the fault diagnosis report generated by the cloud on the client APP, and maintaining the fault diagnosis report on site by service personnel according to the steps and the maintenance scheme in the fault diagnosis report.
In a fault pre-diagnosis module of a client APP, a service request input box has an association input function, and when characters are input, similar items are associated from a standard service request dictionary to serve as a service request input list for service personnel to select. After the service personnel inputs the complete service request characters, the background calculates the complete service request characters through a classification model algorithm to obtain a service request number corresponding to the service request. Then, according to the service request number, relevant information is inquired from the service request solution database and the component-fault type solution database, a fault pre-diagnosis report is displayed, and details of the solution can be checked. See table 4.
TABLE 4
The intelligent service platform and the fault pre-diagnosis function module in the client APP can be developed by adopting the Internet application technology, for example: python, Java, jsp, html, and the like. Database techniques may be employed to develop a service plan expert library, such as: a relational database development method, a distributed database development method and the like. In addition, fig. 3 schematically shows a schematic diagram of service docking according to an embodiment of the present invention.
Compared with the working mode that service personnel mainly rely on field experience and remote video troubleshooting and maintenance in the prior art, the embodiment of the invention provides the pre-diagnosis information by establishing the fault pre-diagnosis system based on the crane service request, and the application mode of the APP carried on the client is used by the field service personnel.
In the embodiment of the invention, the service request data recorded by the CRM of the crane is automatically classified and analyzed by applying an artificial intelligent natural language processing technology; the working process of the solution for analyzing and processing the CRM service request of the crane is designed, and the automatic fault pre-diagnosis analysis system is realized; a fault pre-diagnosis model of the service request based on CRM data mining is designed, and intelligent recommendation of a solution of the service request is realized; a maintenance scheme database system of 'component-fault type' is designed, and application and maintenance operation of database information is convenient.
In the technical scheme, after a service person discovers a fault of engineering equipment (such as a crane), the fault is described to form fault phenomenon description information. The service personnel can select corresponding fault phenomenon classification at the terminal according to the fault phenomenon description information, then the terminal sends the fault phenomenon classification to the historical fault database, or the service personnel inputs the fault phenomenon description information to a server corresponding to the historical fault database, the historical fault database can calculate the fault phenomenon description information, and the fault phenomenon classification corresponding to the fault phenomenon description information is determined in the fault phenomenon classification set.
After the fault classification is determined, historical fault cause information for the fault classification in the past records can be determined in the historical fault database according to the stored historical data, and the probability of occurrence of each fault cause of the fault classification can be determined in the past records. The method and the system have the advantages that a large amount of historical data in the historical fault database is used as a support, and service personnel can perform troubleshooting based on the probability of each fault reason, for example, the fault reason with the higher probability is preferably debugged, so that compared with the prior art that troubleshooting and maintenance are performed on the fault mainly by depending on personal experience of engineers, in the embodiment of the invention, fault points can be quickly positioned for the service personnel, the optimal troubleshooting step is provided, and the working efficiency of field service personnel is improved. In addition, the historical fault database also comprises a fault maintenance scheme which is compiled in advance according to historical fault reason information, and after the service personnel determine fault phenomenon classification, the service personnel can directly refer to the maintenance scheme in the historical fault database to perform maintenance, so that the reliability and the working efficiency of fault maintenance are further improved.
An embodiment of the present invention provides a processor configured to execute any one of the above-described embodiments of the method for engineering equipment.
In particular, the processor may be configured to:
receiving fault phenomenon classification determined by a terminal or determining fault phenomenon classification corresponding to fault phenomenon description information in a fault phenomenon classification set;
determining historical fault cause information classified according to fault phenomena in a historical fault database, wherein the historical fault cause information comprises the probability of occurrence of each fault cause;
and determining a fault maintenance scheme based on the historical fault reason information, wherein the fault maintenance scheme comprises a fault troubleshooting sequence determined based on the probability of occurrence of each fault reason, and the fault maintenance scheme is a maintenance scheme which is compiled in advance in a historical fault database for fault phenomenon classification.
In an embodiment of the invention, the processor is configured to:
the historical fault database establishing method comprises the following steps:
receiving input fault phenomenon description information;
performing semantic analysis on the fault phenomenon description information;
and clustering the fault phenomenon description information according to the semantic analysis result to form a corresponding relation between the fault phenomenon description information and the fault phenomenon classification.
In an embodiment of the invention, the processor is configured to:
determining the classification of the phenomena corresponding to the phenomena-of-failure description information includes:
calculating the fault phenomenon description information by using a pre-trained text data classification model;
and determining fault phenomenon classifications corresponding to the fault phenomenon description information, wherein the fault phenomenon classifications correspond to the classification numbers one to one.
In an embodiment of the invention, the processor is configured to:
each fault cause comprises a component with a fault in the engineering equipment and a fault type of the component, the probability comprises a probability of component fault classified according to fault phenomena and a probability of the fault type, and the troubleshooting sequence comprises a troubleshooting sequence determined according to the probability of the component fault and the probability of the fault type and aiming at the component.
In an embodiment of the invention, the processor is further configured to:
historical processor information for fault phenomenon classification is determined in a historical fault database, and the historical processor information comprises names and contact information of processors and frequency of processing fault phenomenon classification of the processors.
In an embodiment of the invention, the processor is configured to:
the troubleshooting plan includes individual troubleshooting plans for individual causes of failure.
In an embodiment of the invention, the processor is configured to:
the troubleshooting scheme includes a troubleshooting scheme for components and fault categories, the troubleshooting scheme including: replacing the component or directing the repair of the component according to the type of failure.
In an embodiment of the invention, the processor is configured to:
the maintenance scheme still includes:
compiling personnel names and contact ways of the maintenance schemes; and
at least one of a suitable vehicle type, a suitable tonnage grade, a suitable product platform, and a suitable engineering equipment type for the overhaul scheme.
In an embodiment of the invention, the processor is configured to:
the historical fault cause information also includes the frequency with which the respective fault causes occurred.
In an embodiment of the invention, the processor is configured to:
the malfunction-phenomenon-description information includes model information of the engineering equipment in which the malfunction occurs,
matching model information in a historical fault database;
matching tonnage level information corresponding to the model information in a historical fault database under the condition that the model information is not matched;
matching product platform information corresponding to tonnage grade information in a historical fault database under the condition that the tonnage grade information is not matched;
and matching the engineering equipment type information corresponding to the product platform information in the historical fault database under the condition that the product platform information is not matched.
In an embodiment of the invention, the processor is further configured to:
under the condition that the model information is matched in the historical fault database, determining the number of fault phenomenon classifications under the model information in the historical fault database;
under the condition that tonnage level information is matched in the historical fault database, determining the number of fault phenomenon classifications under the tonnage level information in the historical fault database;
under the condition that the product platform information is matched in the historical fault database, determining the quantity of fault phenomenon classifications under the product platform information in the historical fault database;
and under the condition that the type information of the engineering equipment is matched in the historical fault database, determining the number of fault phenomenon classifications under the type information of the engineering equipment in the historical fault database.
An embodiment of the present invention provides a server, including the processor described above.
The embodiment of the invention provides a machine-readable storage medium, wherein the machine-readable storage medium is stored with instructions, and the instructions are used for enabling a machine to execute the method for engineering equipment.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (13)
1. A method for use with engineering equipment, comprising:
receiving fault phenomenon classification determined by a terminal or determining the fault phenomenon classification corresponding to the fault phenomenon description information in a fault phenomenon classification set;
determining historical fault cause information classified for the fault phenomenon in a historical fault database, wherein the historical fault cause information comprises the probability of occurrence of each fault cause;
and determining a fault maintenance scheme based on the historical fault reason information, wherein the fault maintenance scheme comprises a fault troubleshooting sequence determined based on the probability of occurrence of each fault reason, and the fault maintenance scheme is a maintenance scheme which is compiled in advance in the historical fault database aiming at the fault phenomenon classification.
2. The method of claim 1, wherein the historical failure database is established in a manner that includes:
receiving the input fault phenomenon description information;
performing semantic analysis on the fault phenomenon description information;
and clustering the fault phenomenon description information according to the semantic analysis result to form a corresponding relation between the fault phenomenon description information and the fault phenomenon classification.
3. The method of claim 1, wherein the determining the classification of the phenomena corresponding to the phenomena-descriptive information comprises:
calculating the fault phenomenon description information by using a pre-trained text data classification model;
and determining fault phenomenon classifications corresponding to the fault phenomenon description information, wherein the fault phenomenon classifications correspond to classification numbers one to one.
4. The method of claim 1, wherein the fault causes comprise a component that fails in the engineering equipment and a fault category of the component, the probabilities comprise probabilities of component failure and the fault category classified for the fault phenomena, and the troubleshooting order comprises a troubleshooting order for the component determined based on the probability of the component failure and the probability of the fault category.
5. The method of claim 1, further comprising:
determining historical handler information for the fault phenomenon classification in the historical fault database, wherein the historical handler information comprises names and contact information of handlers and frequency of handling of the fault phenomenon classification by the handlers.
6. The method of claim 1, wherein the troubleshooting plan comprises a respective troubleshooting plan for the respective failure cause.
7. The method of claim 4, wherein the troubleshooting plan comprises a troubleshooting plan for the component and the fault category, the troubleshooting plan comprising: replacing the component or directing repair of the component according to the fault category.
8. The method of claim 7, wherein the service plan further comprises:
compiling the names and contact ways of the personnel of the maintenance scheme; and
at least one of a suitable vehicle type, a suitable tonnage class, a suitable product platform, and a suitable engineering equipment type for the overhaul scheme.
9. The method of claim 1, wherein the historical fault cause information further comprises a frequency with which the respective fault causes occurred.
10. The method of claim 1, wherein the malfunction-description information includes model information of the malfunctioning engineering equipment, the method further comprising:
matching the model information in the historical fault database;
matching tonnage grade information corresponding to the model information in the historical fault database under the condition that the model information is not matched;
matching product platform information corresponding to the tonnage grade information in the historical fault database under the condition that the tonnage grade information is not matched;
and matching the engineering equipment type information corresponding to the product platform information in the historical fault database under the condition that the product platform information is not matched.
11. The method of claim 10, further comprising:
determining the number of fault phenomenon classifications under the model information in the historical fault database under the condition that the model information is matched in the historical fault database;
determining the number of fault phenomenon classifications under the tonnage level information in the historical fault database under the condition that the tonnage level information is matched in the historical fault database;
determining the number of the fault phenomenon classifications under the product platform information in the historical fault database under the condition that the product platform information is matched in the historical fault database;
and under the condition that the engineering equipment type information is matched in the historical fault database, determining the quantity of the fault phenomenon classifications under the engineering equipment type information in the historical fault database.
12. A processor configured to perform the method for engineering equipment according to any one of claims 1 to 10.
13. A server, characterized in that it comprises a processor according to claim 12.
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