Maintenance strategy generation method, device, computer equipment and readable storage medium

Abstract

The present invention relates to a maintenance strategy generation method, device, computer equipment and readable storage medium. The method comprises acquiring operation data of engineering machinery equipment and full maintenance cycle data of engineering machinery equipment; inputting the operation data into a first decision tree model to obtain a maintenance analysis result based on the operation data; the first decision tree model is a decision tree model established based on the operation data; inputting the full maintenance cycle data into a second decision tree model to obtain a maintenance analysis result based on the full maintenance cycle data; the second decision tree model is a decision tree model established based on the full maintenance cycle data; generating a maintenance strategy for engineering machinery equipment according to the maintenance analysis result based on the operation data and the maintenance analysis result based on the full maintenance cycle data. The method can timely update the maintenance strategy for engineering machinery equipment, and solves the problem of untimely updating of the maintenance strategy for engineering machinery equipment in traditional technologies.

Description

Technical Field

[0001] The present invention relates to the field of Internet of Things applications, and in particular to a maintenance strategy generation method, device, computer equipment and readable storage medium. Background Art

[0002] With the increase in the use of construction machinery and equipment in my country, in order to further improve construction efficiency and quality, the repair and maintenance of construction machinery and equipment has also received attention. Good repair and maintenance of construction machinery and equipment can effectively reduce unnecessary losses of construction machinery and equipment and extend the service life of construction machinery and equipment.

[0003] In traditional technology, the maintenance strategy for construction machinery equipment is mainly based on different product production lines of construction machinery equipment, and different maintenance strategies are generated. For example, the maintenance strategy generated for the installed machine is that the front frame, rear frame, boom, and VRT gearbox are warrantied for 2 years or 5,000 hours; the maintenance strategy generated for excavators greater than or equal to 36 tons is that the key parts and structural parts are warrantied for 3 years or 10,000 hours.

[0004] However, the traditional maintenance strategy for construction machinery equipment has the problem of untimely updating of the maintenance strategy for construction machinery equipment. Summary of the invention

[0005] Based on this, it is necessary to provide a maintenance strategy generation method, device, computer equipment and readable storage medium to address the problem of untimely updating of maintenance strategies for traditional engineering machinery equipment.

[0006] In a first aspect, an embodiment of the present invention provides a maintenance strategy generation method, the method comprising:

[0007] Obtaining operation data of engineering machinery and equipment and full-cycle maintenance data of the engineering machinery and equipment;

[0008] Inputting the operation data into a first decision tree model to obtain a maintenance analysis result based on the operation data; the first decision tree model is a decision tree model established based on the operation data;

[0009] Inputting the full maintenance cycle data into a second decision tree model to obtain a maintenance analysis result based on the full maintenance cycle data; the second decision tree model is a decision tree model established based on the full maintenance cycle data;

[0010] A maintenance strategy for the engineering machinery equipment is generated according to the maintenance analysis result based on the operation data and the maintenance analysis result based on the full maintenance cycle data.

[0011] In one embodiment, the maintenance analysis result based on the operating data includes maintenance extended service or non-extension service based on the operating data; the maintenance analysis result based on the full maintenance cycle data includes maintenance extended service or maintenance non-extension service based on the full maintenance cycle data.

[0012] In one embodiment, generating a maintenance strategy for the construction machinery equipment according to the maintenance analysis result based on the operation data and the maintenance analysis result based on the maintenance cycle data includes:

[0013] If the maintenance analysis result based on the operation data is the maintenance extension service based on the operation data, and the maintenance analysis result based on the maintenance cycle data is the maintenance extension service based on the maintenance cycle data, then the maintenance strategy of the construction machinery equipment is determined to be the implementation of the extended maintenance strategy;

[0014] If the maintenance analysis result based on the operating data is that the maintenance service is not extended based on the operating data, and the maintenance analysis result based on the full maintenance cycle data is that the maintenance service is not extended based on the full maintenance cycle data, then the maintenance strategy of the construction machinery equipment is determined to be not implementing the maintenance extension strategy.

[0015] In one embodiment, the method further comprises:

[0016] If any one of the maintenance analysis result based on the operation data and the maintenance analysis result based on the maintenance cycle data is that the maintenance service is not extended, a prompt is provided to determine the maintenance strategy of the construction machinery equipment offline.

[0017] In one embodiment, the operating data includes at least one of the average monthly workload of the engineering machinery equipment and the average monthly startup time, average daily startup times, startup fuel consumption change rate, current location of the engineering machinery equipment, and distance to a maintenance point.

[0018] In one embodiment, the full maintenance cycle data includes at least one of the monthly repair frequency of the engineering machinery equipment, the monthly maintenance frequency of the engineering machinery equipment, the major component replacement frequency, and the average monthly service profit outside the warranty period.

[0019] In one embodiment, before inputting the operation data into a first decision tree model to obtain a maintenance analysis result based on the operation data, the method further includes:

[0020] Determining whether the engineering machinery equipment is in a heavy load condition;

[0021] If not, the step of inputting the operating data into the first decision tree model to obtain a maintenance analysis result based on the operating data is executed;

[0022] If so, it is determined that the maintenance strategy for the engineering machinery equipment is not to implement the extended maintenance strategy.

[0023] In one embodiment, before inputting the full maintenance cycle data into a second decision tree model to obtain a maintenance analysis result based on the full maintenance cycle data, the method further includes:

[0024] Determining whether the engineering machinery and equipment has been maintained on time;

[0025] If yes, the step of inputting the full maintenance cycle data into the second decision tree model to obtain a maintenance analysis result based on the full maintenance cycle data is executed;

[0026] If not, it is determined that the maintenance strategy of the engineering machinery equipment is not to implement the extended maintenance strategy.

[0027] In a second aspect, an embodiment of the present invention provides a maintenance strategy generating device, the device comprising:

[0028] An acquisition module, used to acquire operation data of engineering machinery equipment and full-cycle maintenance data of the engineering machinery equipment;

[0029] A first analysis module, used for inputting the operation data into a first decision tree model to obtain a maintenance analysis result based on the operation data; the first decision tree model is a decision tree model established based on the operation data;

[0030] A second analysis module is used to input the full maintenance cycle data into a second decision tree model to obtain a maintenance analysis result based on the full maintenance cycle data; the second decision tree model is a decision tree model established based on the full maintenance cycle data;

[0031] A generation module is used to generate a maintenance strategy for the engineering machinery equipment according to the maintenance analysis result based on the operation data and the maintenance analysis result based on the maintenance full cycle data.

[0032] In a third aspect, an embodiment of the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0033] Acquire operation data of the engineering machinery equipment and the full maintenance cycle data of the engineering machinery equipment after the maintenance cycle data is processed;

[0034] Inputting the operation data into a first decision tree model to obtain a maintenance analysis result based on the operation data; the first decision tree model is a decision tree model established based on the operation data;

[0035] Inputting the full maintenance cycle data into a second decision tree model to obtain a maintenance analysis result based on the full maintenance cycle data; the second decision tree model is a decision tree model established based on the full maintenance cycle data;

[0036] A maintenance strategy for the engineering machinery equipment is generated according to the maintenance analysis result based on the operation data and the maintenance analysis result based on the full maintenance cycle data.

[0037] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0038] Obtaining operation data of engineering machinery and equipment and full-cycle maintenance data of the engineering machinery and equipment;

[0039] Inputting the operation data into a first decision tree model to obtain a maintenance analysis result based on the operation data; the first decision tree model is a decision tree model established based on the operation data;

[0040] Inputting the full maintenance cycle data into a second decision tree model to obtain a maintenance analysis result based on the full maintenance cycle data; the second decision tree model is a decision tree model established based on the full maintenance cycle data;

[0041] A maintenance strategy for the engineering machinery equipment is generated according to the maintenance analysis result based on the operation data and the maintenance analysis result based on the full maintenance cycle data.

[0042] In the maintenance strategy generation method, device, computer device and readable storage medium provided in the above embodiments, the computer device obtains the operation data of the engineering machinery equipment and the maintenance cycle data of the engineering machinery equipment; the operation data is input into a first decision tree model to obtain a maintenance analysis result based on the operation data; the first decision tree model is a decision tree model established based on the operation data; the maintenance cycle data is input into a second decision tree model to obtain a maintenance analysis result based on the maintenance cycle data; the second decision tree model is a decision tree model established based on the maintenance cycle data; according to the maintenance analysis result based on the operation data and the maintenance analysis result based on the maintenance cycle data, the maintenance strategy is generated. Maintenance strategy for construction machinery equipment. In this method, a computer device first obtains operation data of the construction machinery equipment and data of the entire maintenance cycle of the construction machinery equipment, inputs the operation data into a first decision tree model to obtain a maintenance analysis result based on the operation data, inputs the entire maintenance cycle data into a second decision tree model to obtain a maintenance analysis result based on the entire maintenance cycle data, and generates a maintenance strategy for the construction machinery equipment based on the maintenance analysis results based on the operation data and the maintenance analysis results based on the entire maintenance cycle data. The maintenance strategy for the construction machinery equipment can be updated in a timely manner based on the operation data of the construction machinery equipment and the data of the entire maintenance cycle of the construction machinery equipment, thereby solving the problem of untimely updating of maintenance strategies for construction machinery equipment in traditional technologies. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A schematic diagram of the internal structure of a computer device provided by an embodiment;

[0044] Figure 2 A flowchart of a maintenance strategy generation method provided by an embodiment;

[0045] Figure 3 A schematic diagram of a maintenance strategy generation method provided by an embodiment;

[0046] FIG4( a) is a schematic diagram of a first decision tree model provided by an embodiment;

[0047] FIG4( b) is a schematic diagram of a second decision tree model provided by an embodiment;

[0048] Figure 5 A schematic diagram of a maintenance strategy generation method provided in another embodiment;

[0049] Figure 6 A schematic diagram of a maintenance strategy generation method provided in another embodiment;

[0050] Figure 7 A schematic diagram of the structure of a maintenance strategy generating device provided in an embodiment. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0052] The maintenance strategy generation method provided in the embodiment of the present application can be applied to Figure 1 The computer device shown. The computer device includes a processor and a memory connected by a system bus, and a computer program is stored in the memory. When the processor executes the computer program, the steps of the following method embodiment can be executed. Optionally, the computer device may also include a network interface, a display screen and an input device. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory, and the non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. Optionally, the computer device can be a server, a personal computer, a personal digital assistant, or other terminal devices, such as a tablet computer, a mobile phone, etc., or a cloud or remote server. The embodiment of the present application does not limit the specific form of the computer device.

[0053] It should be noted that the maintenance strategy generation method provided in the embodiment of the present application may be executed by a maintenance strategy generation device, which may be implemented as part or all of a computer device through software, hardware, or a combination of software and hardware. In the following method embodiments, the execution subject is a computer device as an example for explanation.

[0054] The following specific embodiments are used to describe in detail the technical solution of the present invention and how the technical solution of the present invention solves the above technical problems. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0055] Figure 2 The flowchart of the maintenance strategy generation method provided by an embodiment. This embodiment relates to the specific implementation process of a computer device generating a maintenance strategy for an engineering machinery device based on the operation data of the engineering machinery device and the maintenance cycle data of the engineering machinery device. Figure 2 As shown, the method may include:

[0056] S201, obtaining operation data of construction machinery equipment and full-cycle maintenance data of construction machinery equipment.

[0057] Specifically, the computer device obtains the operation data of the engineering machinery equipment and the maintenance cycle data of the engineering machinery equipment. Among them, the engineering machinery equipment refers to the mechanical equipment used in the process of large-scale infrastructure construction, such as loaders, cranes, installers and graders. Optionally, the operation data of the engineering machinery equipment can be the average monthly workload, average monthly startup time, average daily startup times, etc. of the engineering machinery equipment. Optionally, the maintenance cycle data of the engineering machinery equipment can be the monthly repair times, monthly maintenance times, major component replacement times, etc. of the engineering machinery equipment. Optionally, the computer device can obtain the operation data of the engineering machinery equipment through the smart IoT box. Optionally, the computer device can obtain the maintenance cycle data of the engineering machinery equipment through the enterprise resource planning (Enterprise Resource Planning, ERP), customer relationship management system (Customer Relationship Management, CRM) self-built information system. Optionally, the computer device can obtain the operation data of the engineering machinery equipment and the maintenance cycle data of the engineering machinery equipment at preset time intervals. For example, the operation data of the engineering machinery equipment and the maintenance cycle data of the engineering machinery equipment can be collected every 10 minutes. Optionally, the computer device can perform aggregation processing, slicing processing or block processing on the operation data of the engineering machinery equipment and the maintenance cycle data of the engineering machinery equipment. Aggregation processing refers to generating a single value for the operation data or the maintenance cycle data, that is, generating a single value for the same type of data in the operation data or generating a single value for the same type of data in the maintenance cycle data; slicing processing and block processing on the operation data or the maintenance cycle data of the engineering machinery equipment means that the amount of the operation data or the maintenance cycle data of the engineering machinery equipment obtained is large, and the computer device only needs to obtain part of the data, then the computer device can select values ​​on a part of the preset dimensions, and determine the distribution of the operation data or the maintenance cycle data obtained on the remaining dimensions. If the distribution of the operation data or the maintenance cycle data on the remaining dimensions is two-dimensional, the operation data or the maintenance cycle data is sliced ​​to obtain the required part of the data; if the distribution of the operation data or the maintenance cycle data on the remaining dimensions is three-dimensional or more, the operation data or the maintenance cycle data is block processed to obtain the required part of the data.

[0058] S202, inputting the operation data into a first decision tree model to obtain a maintenance analysis result based on the operation data; the first decision tree model is a decision tree model established based on the operation data.

[0059] Specifically, the computer device inputs the operation data of the above-mentioned engineering machinery equipment into a decision tree model established based on the operation data of the engineering machinery equipment, and obtains a maintenance analysis result based on the above-mentioned operation data. Optionally, the maintenance analysis result based on the operation data includes a maintenance extension service or a non-extension service based on the operation data. For example, the computer device inputs the monthly average workload in the operation data of the engineering machinery equipment into the first decision tree model. If the monthly average workload is greater than the preset monthly average workload threshold, the maintenance analysis result based on the above-mentioned operation data is determined to be a maintenance non-extended service. If the monthly average workload is less than the preset monthly average workload threshold, the maintenance analysis result based on the above-mentioned operation data is determined to be a maintenance extension service. Exemplarily, the monthly average workload in the operation data of the obtained engineering machinery equipment is 150 hours, the preset monthly average workload threshold is 120 hours, and the monthly average workload is greater than the preset monthly average workload threshold, then the maintenance analysis result based on the monthly average workload of 150 hours is determined to be a maintenance non-extended service.

[0060] S203, inputting the full maintenance cycle data into a second decision tree model to obtain a maintenance analysis result based on the full maintenance cycle data; the second decision tree model is a decision tree model established based on the full maintenance cycle data.

[0061] Specifically, the computer device inputs the maintenance cycle data of the above-mentioned engineering machinery equipment into the second decision tree model to obtain the maintenance analysis result based on the above-mentioned maintenance cycle data. Optionally, the maintenance analysis result based on the maintenance cycle data includes maintenance extension service or non-extension service based on the maintenance cycle data. For example, the computer device inputs the monthly repair number in the maintenance cycle data of the engineering machinery equipment into the second decision tree model. If the monthly repair number is greater than the preset monthly repair number threshold, the maintenance analysis result based on the above-mentioned maintenance cycle data is determined to be maintenance non-extended service. If the monthly repair number is less than the preset monthly repair number threshold, the maintenance analysis result based on the above-mentioned maintenance cycle data is determined to be maintenance extended service. Exemplarily, the monthly repair number in the obtained maintenance cycle data of the engineering machinery equipment is 8 times, the preset monthly repair number threshold is 4 times, and the monthly repair number is greater than the preset monthly repair number threshold, then the maintenance analysis result based on the monthly repair number of 4 times is determined to be maintenance non-extended service.

[0062] S204: Generate a maintenance strategy for the construction machinery equipment according to the maintenance analysis results based on the operation data and the maintenance analysis results based on the maintenance cycle data.

[0063] Specifically, the computer device generates a maintenance strategy for the construction machinery equipment according to the above-mentioned maintenance analysis results based on the operation data and the maintenance analysis results based on the maintenance cycle data. Optionally, the maintenance analysis results based on the operation data can be a maintenance extension service or a maintenance non-extension service, and the maintenance analysis results based on the maintenance cycle data can be a maintenance extension service or a maintenance non-extension service. The computer device can generate a maintenance strategy for the construction machinery equipment according to the analysis results of the two, that is, the generated maintenance strategy for the construction machinery equipment can be a maintenance extension service or a maintenance non-extension service.

[0064] In this embodiment, the computer device first obtains the operating data of the engineering machinery equipment and the full maintenance cycle data of the engineering machinery equipment, inputs the operating data into the first decision tree model, and obtains the maintenance analysis results based on the operating data, and inputs the full maintenance cycle data into the second decision tree model, and obtains the maintenance analysis results based on the full maintenance cycle data. According to the maintenance analysis results based on the operating data and the maintenance analysis results based on the full maintenance cycle data, a maintenance strategy for the engineering machinery equipment can be generated, and the maintenance strategy of the engineering machinery equipment can be updated in time according to the operating data of the engineering machinery equipment and the full maintenance cycle data of the engineering machinery equipment, which solves the problem of untimely updating of the maintenance strategy of the engineering machinery equipment in traditional technologies.

[0065] Figure 3 A schematic diagram of a maintenance strategy generation method provided in an embodiment. This embodiment relates to a specific implementation process of generating a maintenance strategy for construction machinery equipment by a computer device based on the maintenance analysis results of operation data and the maintenance analysis results based on the maintenance cycle data. Figure 3 As shown, on the basis of the above embodiment, as an optional implementation mode, the above S204 includes: if the maintenance analysis result based on the operating data is the maintenance extension service based on the operating data, and the maintenance analysis result based on the full maintenance cycle data is the maintenance extension service based on the full maintenance cycle data, then the maintenance strategy of the construction machinery equipment is determined to be the implementation of the extended maintenance strategy; if the maintenance analysis result based on the operating data is the maintenance non-extended service based on the operating data, and the maintenance analysis result based on the full maintenance cycle data is the maintenance non-extended service based on the full maintenance cycle data, then the maintenance strategy of the construction machinery equipment is determined to be not to implement the maintenance extension strategy.

[0066] Specifically, if the maintenance analysis result based on the above operation data of the computer equipment is a maintenance extension service based on the operation data, and the maintenance analysis result based on the above maintenance cycle data is a maintenance extension service based on the maintenance cycle data, then Figure 3 As shown, the computer equipment determines that the maintenance strategy of the engineering machinery equipment is to implement the extended maintenance strategy, that is, Figure 3As shown in area A; if the maintenance analysis result based on the above operation data of the computer equipment is that the maintenance service based on the operation data is not extended, and the maintenance analysis result based on the above maintenance cycle data is that the maintenance service based on the maintenance cycle data is not extended, then Figure 3 As shown, the computer equipment determines that the maintenance strategy of the engineering machinery equipment is to implement the non-extended maintenance strategy, that is, Figure 3 Optionally, if the computer device obtains any one of the maintenance analysis results based on the above operation data and the maintenance analysis results based on the above maintenance cycle data, that is, the maintenance service will not be extended, then the computer device prompts to determine the maintenance strategy of the construction machinery equipment offline, that is, Figure 3 Shown in areas B and C.

[0067] In this embodiment, after the computer equipment obtains the maintenance analysis results of the engineering machinery equipment based on the operation data and the maintenance analysis results based on the full maintenance cycle data, it can quickly determine the corresponding maintenance strategy of the engineering machinery equipment based on the results of the two, thereby improving the efficiency of determining the maintenance strategy of the engineering machinery equipment and being able to timely update the maintenance strategy of the engineering machinery equipment based on the operation data and full maintenance cycle data of the engineering machinery equipment.

[0068] Figure 4(a) is a schematic diagram of a first decision tree model provided by an embodiment; Figure 4(b) is a schematic diagram of a second decision tree model provided by an embodiment. Based on the above embodiment, as an optional implementation, as shown in Figure 4, the operation data includes at least one of the monthly average workload of the engineering machinery equipment and the monthly average startup time of the engineering machinery equipment, the average daily startup times, the startup fuel consumption change rate, the current location of the engineering machinery equipment, and the distance to the maintenance network. The full maintenance cycle data includes at least one of the monthly repair times of the engineering machinery equipment and the monthly maintenance times of the engineering machinery equipment, the number of major component replacements, and the average monthly service profit outside the warranty period.

[0069] Specifically, as shown in Figure 4(a), the above-mentioned operating data includes the average monthly workload of the engineering machinery equipment and at least one of the average monthly startup time of the engineering machinery equipment, the average daily startup times, the startup fuel consumption change rate, the current location of the engineering machinery equipment, and the distance to the maintenance point. Exemplarily, the computer device first inputs the monthly average workload of the engineering machinery equipment into the first decision tree model to obtain an analysis result. If the input monthly average workload of the engineering machinery equipment is greater than the preset monthly average workload threshold, the maintenance strategy of the engineering machinery equipment is determined to be not extending the maintenance service, and the subsequent maintenance strategy determination and analysis steps are no longer performed; if the input monthly average workload of the engineering machinery equipment is less than the preset monthly average workload threshold, the maintenance strategy of the engineering machinery equipment is determined to be extending the maintenance service, and then the monthly average startup time, daily average startup times, startup fuel consumption change rate, current location of the engineering machinery equipment, and distance from the maintenance point of the engineering machinery equipment are used to further determine the maintenance strategy of the engineering machinery equipment. It can be understood that if any parameter of the monthly average startup time, daily average startup times, startup fuel consumption change rate, current location of the engineering machinery equipment, and distance from the maintenance point of the engineering machinery equipment is input into the first decision tree model, the result obtained is that the maintenance service is not extended, then the subsequent parameters will no longer be used to determine and analyze the maintenance strategy of the engineering machinery equipment.

[0070] As shown in FIG4(b), the above-mentioned maintenance cycle data includes at least one of the monthly repair times of the engineering machinery equipment and the monthly maintenance times of the engineering machinery equipment, the major component replacement times, and the monthly average service profit outside the warranty. Exemplarily, the computer device first inputs the monthly maintenance times of the engineering machinery equipment into the second decision tree model to obtain the analysis result. If the monthly maintenance times of the input engineering machinery equipment are greater than the preset monthly maintenance times threshold, the maintenance strategy of the engineering machinery equipment is determined to be not to extend the maintenance service, and the subsequent maintenance strategy determination and analysis steps are no longer performed; if the monthly maintenance times of the input engineering machinery equipment are less than the preset monthly maintenance times threshold, the maintenance strategy of the engineering machinery equipment is determined to be extended maintenance service, and the major component replacement times of the engineering machinery equipment and the monthly average service outside the warranty are further used to determine the maintenance strategy of the engineering machinery equipment. It can be understood that if the result of inputting any parameter of the major component replacement times of the engineering machinery equipment and the monthly average service outside the warranty into the second decision tree model is that the maintenance service is not extended, then the subsequent parameters will no longer be used to determine and analyze the maintenance strategy of the engineering machinery equipment.

[0071] In this embodiment, the operating data input into the first decision tree model include the average monthly workload of the engineering machinery equipment, as well as the average monthly startup time of the engineering machinery equipment, the average daily startup times, the startup fuel consumption change rate, the current location of the engineering machinery equipment, and at least one of the distances to maintenance outlets; the full maintenance cycle data input into the second decision tree model include the monthly repair times of the engineering machinery equipment, the monthly maintenance times of the engineering machinery equipment, the number of major component replacements, and the average monthly service profit outside the warranty period. When the above parameters are used to generate the maintenance strategy for the engineering machinery equipment, as long as the maintenance strategy determined by any of the parameters is not to extend the maintenance service, the subsequent parameters will no longer be used to analyze and determine the maintenance strategy for the engineering machinery equipment, thereby improving the efficiency of generating the maintenance strategy for the engineering machinery equipment; and when the maintenance strategy determined by any of the parameters is to extend the maintenance service, the subsequent parameters will continue to be used to analyze and determine the maintenance strategy for the engineering machinery equipment, thereby improving the accuracy of the generated maintenance strategy for the engineering machinery equipment.

[0072] Figure 5 This is a schematic diagram of a maintenance strategy generation method provided by another embodiment. This embodiment involves a specific implementation process of a computer device generating a maintenance strategy for an engineering machinery device. Figure 5 As shown, based on the above embodiment, as an optional implementation manner, before the above S202, the above method further includes:

[0073] S501, determining whether the construction machinery equipment is in a heavy load condition.

[0074] Specifically, the computer device can collect the load condition of the above-mentioned engineering machinery equipment through the smart IoT box to determine whether the engineering machinery equipment is in a heavy load condition. If not, execute S502; if so, execute S503. Optionally, the computer device can compare the collected load condition of the engineering machinery equipment with a preset load condition threshold to determine whether the engineering machinery equipment is in a heavy load condition. Exemplarily, the preset load condition threshold is 1200 tons. If the collected load condition of the engineering machinery equipment is 800 tons, it is determined that the engineering machinery equipment is not in a heavy load condition. If the collected load condition of the engineering machinery equipment is 1500 tons, it is determined that the engineering machinery equipment is in a heavy load condition.

[0075] S502, a step of inputting the operation data into a first decision tree model to obtain a maintenance analysis result based on the operation data is executed.

[0076] For details, please refer to the description related to this step in the above embodiment, which will not be repeated in this embodiment.

[0077] S503, determining that the maintenance strategy for the construction machinery equipment is not to implement the extended maintenance strategy.

[0078] Specifically, if the computer device determines that the above-mentioned engineering machinery equipment is in a heavy load condition, the computer device determines that the maintenance strategy of the engineering machinery equipment is not to implement the extended maintenance strategy. It can be understood that if the engineering machinery equipment is in a heavy load condition, the wear and tear of various large parts of the engineering machinery equipment is relatively serious, affecting the performance of the engineering machinery equipment, and it is not necessary to extend the maintenance.

[0079] In this embodiment, the computer device first determines the load condition of the engineering machinery equipment. If it is a heavy load condition, the maintenance strategy of the engineering machinery equipment is determined to not implement the extended maintenance strategy. If it is not a heavy load condition, the operation data is input into the first decision tree model to obtain a maintenance analysis result based on the operation data. When the engineering machinery equipment is in a heavy load condition, there is no need for subsequent analysis and determination, which further improves the efficiency of determining the maintenance strategy of the engineering machinery equipment.

[0080] Figure 6 This is a schematic diagram of a maintenance strategy generation method provided by another embodiment. This embodiment involves a specific implementation process of a computer device generating a maintenance strategy for an engineering machinery device. Figure 6 As shown, based on the above embodiment, as an optional implementation manner, before the above S203, the above method further includes:

[0081] S601, determining whether the construction machinery equipment has been maintained on time.

[0082] Specifically, the computer device can obtain the maintenance data of the engineering machinery equipment through the enterprise resource planning (ERP) and customer relationship management system (CRM) information system built by the enterprise to determine whether the engineering machinery equipment has been maintained on time. If so, execute S602; if not, execute S603. Optionally, the computer device can compare the obtained maintenance data with the expected maintenance data of the engineering machinery equipment to determine whether the engineering machinery equipment has been maintained on time. Exemplarily, the expected maintenance data of the engineering machinery equipment should be 10 times. If the maintenance data of the engineering machinery equipment obtained is 10 times, it is determined that the engineering machinery equipment has been maintained on time. If the maintenance data of the engineering machinery equipment obtained is 8 times, it is determined that the engineering machinery equipment has not been maintained on time.

[0083] S602, a step is performed in which the full maintenance cycle data is input into a second decision tree model to obtain a maintenance analysis result based on the full maintenance cycle data.

[0084] For details, please refer to the description related to this step in the above embodiment, which will not be repeated in this embodiment.

[0085] S603, determining that the maintenance strategy for the construction machinery equipment is not to implement the extended maintenance strategy.

[0086] Specifically, if the computer device determines that the above-mentioned engineering machinery equipment has not been maintained on time, the computer device determines that the maintenance strategy of the engineering machinery equipment is not to implement the extended maintenance strategy. It is understandable that if the engineering machinery equipment is not maintained on time and the major parts of the engineering machinery equipment are not regularly maintained, the performance of the engineering machinery equipment will be affected, and there is no need to extend the maintenance.

[0087] In this embodiment, the computer device first determines whether the construction machinery equipment has been maintained on time. If it has not been maintained on time, the maintenance strategy of the construction machinery equipment is determined to be not to implement the extended maintenance strategy. If it has been maintained on time, the step of inputting the full maintenance cycle data into the second decision tree model is executed to obtain the maintenance analysis results based on the full maintenance cycle data. When the construction machinery equipment has not been maintained on time, there is no need for subsequent analysis and determination, which further improves the efficiency of determining the maintenance strategy of the construction machinery equipment.

[0088] It should be understood that although Figure 2-6 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 2-6 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0089] Figure 7 The following is a schematic diagram of the structure of a maintenance strategy generation device provided by an embodiment. Figure 7 As shown, the device may include: an acquisition module 10, a first analysis module 11, a second analysis module 12 and a generation module 13.

[0090] Specifically, the acquisition module 10 is used to acquire the operation data of the engineering machinery equipment and the maintenance cycle data of the engineering machinery equipment;

[0091] The first analysis module 11 is used to input the operation data into the first decision tree model to obtain the maintenance analysis result based on the operation data; the first decision tree model is a decision tree model established based on the operation data;

[0092] The second analysis module 12 is used to input the full maintenance cycle data into the second decision tree model to obtain a maintenance analysis result based on the full maintenance cycle data; the second decision tree model is a decision tree model established based on the full maintenance cycle data;

[0093] The generation module 13 is used to generate a maintenance strategy for the construction machinery equipment according to the maintenance analysis results based on the operation data and the maintenance analysis results based on the maintenance cycle data.

[0094] Optionally, the maintenance analysis results based on the operating data include maintenance extended service or maintenance non-extension service based on the operating data; the maintenance analysis results based on the full maintenance cycle data include maintenance extended service or maintenance non-extension service based on the full maintenance cycle data.

[0095] Optionally, the operating data includes at least one of the average monthly workload of the engineering machinery equipment and the average monthly startup time of the engineering machinery equipment, the average daily startup times, the startup fuel consumption change rate, the current location of the engineering machinery equipment, and the distance to a maintenance point.

[0096] Optionally, the full maintenance cycle data includes at least one of the monthly number of repair reports for engineering machinery equipment, the monthly number of repairs for engineering machinery equipment, the number of major component replacements, and the average monthly service profit outside warranty.

[0097] The maintenance strategy generation device provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, which will not be repeated here.

[0098] On the basis of the above embodiment, the maintenance analysis result based on the operation data includes maintenance extension service or non-extension service based on the operation data; optionally, the above generation module 13 includes: a first determination unit and a second determination unit.

[0099] Specifically, the first determination unit is used to determine that the maintenance strategy of the construction machinery equipment is to implement the extended maintenance strategy if the maintenance analysis result based on the operation data is the maintenance extension service based on the operation data and the maintenance analysis result based on the maintenance cycle data is the maintenance extension service based on the maintenance cycle data;

[0100] The second determination unit is used to determine that the maintenance strategy for the construction machinery equipment is not to implement the maintenance extension strategy if the maintenance analysis result based on the operating data is that the maintenance service based on the operating data is not extended, and the maintenance analysis result based on the full maintenance cycle data is that the maintenance service based on the full maintenance cycle data is not extended.

[0101] The maintenance strategy generation device provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, which will not be repeated here.

[0102] On the basis of the above embodiment, optionally, the above generation module 13 further includes: a third determination unit.

[0103] Specifically, the third determination unit is used to prompt offline determination of the maintenance strategy for the construction machinery equipment if any one of the maintenance analysis results based on the operation data and the maintenance analysis results based on the full maintenance cycle data is that the maintenance service will not be extended.

[0104] The maintenance strategy generation device provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, which will not be repeated here.

[0105] On the basis of the above embodiment, optionally, the above device further includes: a second judgment module, a second execution module and a second determination module.

[0106] Specifically, the second judgment module is used to judge whether the engineering machinery equipment has been maintained on time;

[0107] The second execution module is used to input the full maintenance cycle data into the second decision tree model to obtain the maintenance analysis result based on the full maintenance cycle data when the engineering machinery equipment is maintained on time;

[0108] The second determination module is used to determine that the maintenance strategy of the engineering machinery equipment is not to implement the extended maintenance strategy when the engineering machinery equipment is not maintained on time.

[0109] The maintenance strategy generation device provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, which will not be repeated here.

[0110] For the specific definition of the maintenance strategy generation device, please refer to the definition of the maintenance strategy generation method above, which will not be repeated here. The various modules in the above-mentioned maintenance strategy generation device can be implemented in whole or in part by software, hardware and their combination. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0111] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0112] Obtain the operation data of construction machinery and equipment and the full maintenance cycle data of construction machinery and equipment;

[0113] Inputting the operation data into the first decision tree model to obtain a maintenance analysis result based on the operation data; the first decision tree model is a decision tree model established based on the operation data;

[0114] Input the full maintenance cycle data into the second decision tree model to obtain a maintenance analysis result based on the full maintenance cycle data; the second decision tree model is a decision tree model established based on the full maintenance cycle data;

[0115] Based on the maintenance analysis results based on operation data and the maintenance analysis results based on full maintenance cycle data, a maintenance strategy for construction machinery equipment is generated.

[0116] The implementation principle and technical effect of the computer device provided in the above embodiment are similar to those of the above method embodiment, and will not be repeated here.

[0117] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0118] Obtain the operation data of construction machinery and equipment and the full maintenance cycle data of construction machinery and equipment;

[0119] Inputting the operation data into the first decision tree model to obtain a maintenance analysis result based on the operation data; the first decision tree model is a decision tree model established based on the operation data;

[0120] Input the full maintenance cycle data into the second decision tree model to obtain a maintenance analysis result based on the full maintenance cycle data; the second decision tree model is a decision tree model established based on the full maintenance cycle data;

[0121] Based on the maintenance analysis results based on operation data and the maintenance analysis results based on full maintenance cycle data, a maintenance strategy for construction machinery equipment is generated.

[0122] The computer-readable storage medium provided in the above embodiment has similar implementation principles and technical effects as those of the above method embodiment, and will not be described in detail here.

[0123] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0124] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0125] The above-mentioned embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A maintenance strategy generation method, characterized in that: The method comprises: Acquire operation data of the engineering machinery equipment and full-cycle maintenance data of the engineering machinery equipment; the operation data includes at least one of the monthly average workload of the engineering machinery equipment and the monthly average startup time of the engineering machinery equipment, the daily average startup times, the startup fuel consumption change rate, the current location of the engineering machinery equipment, and the distance to the maintenance network; the full-cycle maintenance data includes at least one of the monthly repair times of the engineering machinery equipment and the monthly maintenance times of the engineering machinery equipment, the number of major component replacements, and the average monthly service profit outside the warranty period; Determine whether the engineering machinery equipment is in a heavy load condition; if not, input the operating data into a first decision tree model to obtain a maintenance analysis result based on the operating data; the first decision tree model is a decision tree model established based on the operating data; the maintenance analysis result based on the operating data includes a maintenance extension service or a non-extension service based on the operating data; if so, determine that the maintenance strategy of the engineering machinery equipment is not to implement an extended maintenance strategy; input any type of operating data into the first decision tree model, and if the maintenance analysis result based on the operating data is not to extend the maintenance service, then no other operating data is used to analyze the maintenance strategy of the engineering machinery equipment; Determine whether the construction machinery equipment has been maintained on time; if so, input the full maintenance cycle data into a second decision tree model to obtain a maintenance analysis result based on the full maintenance cycle data; the second decision tree model is a decision tree model established based on the full maintenance cycle data; the maintenance analysis result based on the full maintenance cycle data includes a maintenance extension service or a maintenance non-extended service based on the full maintenance cycle data; if not, determine that the maintenance strategy of the construction machinery equipment is not to implement an extended maintenance strategy; input any type of full maintenance cycle data into the second decision tree model, and if the maintenance analysis result based on the full maintenance cycle data is that the maintenance service is not to be extended, then no other full maintenance cycle data is used to analyze the maintenance strategy of the construction machinery equipment; A maintenance strategy for the construction machinery equipment is generated based on the maintenance analysis results based on the operation data and the maintenance analysis results based on the full maintenance cycle data; the maintenance strategy for the construction machinery equipment includes extended maintenance service and non-extended maintenance service.

2. The method according to claim 1, characterized in that Generating a maintenance strategy for the construction machinery equipment according to the maintenance analysis result based on the operation data and the maintenance analysis result based on the maintenance cycle data includes: If the maintenance analysis result based on the operation data is the maintenance extension service based on the operation data, and the maintenance analysis result based on the maintenance cycle data is the maintenance extension service based on the maintenance cycle data, then the maintenance strategy of the construction machinery equipment is determined to be the implementation of the extended maintenance strategy; If the maintenance analysis result based on the operating data is that the maintenance service is not extended based on the operating data, and the maintenance analysis result based on the full maintenance cycle data is that the maintenance service is not extended based on the full maintenance cycle data, then the maintenance strategy of the construction machinery equipment is determined to be not implementing the maintenance extension strategy.

3. The method according to claim 2, characterized in that The method further comprises: If any one of the maintenance analysis result based on the operation data and the maintenance analysis result based on the maintenance cycle data is that the maintenance service is not extended, a prompt is provided to determine the maintenance strategy of the construction machinery equipment offline.

4. The method according to claim 1, characterized in that: The determining whether the engineering machinery equipment is in a heavy load condition includes: The load condition of the engineering machinery equipment is compared with a preset load condition threshold of the engineering machinery equipment to determine whether the engineering machinery equipment is in a heavy load condition.

5. The method according to claim 1, characterized in that: The determining whether the engineering machinery equipment has been maintained on time includes: The maintenance data of the engineering machinery equipment is compared with the expected maintenance data of the engineering machinery equipment to determine whether the engineering machinery equipment has been maintained on time.

6. The method according to claim 1, characterized in that The method further comprises: The operation data of the engineering machinery equipment and the full-cycle maintenance data of the engineering machinery equipment are acquired at preset time intervals.

7. The method according to claim 1, characterized in that The method further comprises: The acquired operation data of the engineering machinery equipment and the full-cycle maintenance data of the engineering machinery equipment are subjected to any one of aggregation processing, slicing processing or dicing processing.

8. A maintenance strategy generating device, characterized in that: The device comprises: An acquisition module is used to acquire operation data of engineering machinery equipment and full-cycle maintenance data of the engineering machinery equipment; the operation data includes at least one of the monthly average workload of the engineering machinery equipment and the monthly average startup time, the daily average startup times, the startup fuel consumption change rate, the current location of the engineering machinery equipment, and the distance to the maintenance network; the full-cycle maintenance data includes at least one of the monthly repair times of the engineering machinery equipment and the monthly maintenance times of the engineering machinery equipment, the number of major component replacements, and the average monthly service profit outside the warranty period; The first analysis module is used to determine whether the engineering machinery equipment is in a heavy load condition; if not, the operation data is input into a first decision tree model to obtain a maintenance analysis result based on the operation data; the first decision tree model is a decision tree model established based on the operation data; the maintenance analysis result based on the operation data includes a maintenance extension service or a non-extension service based on the operation data; if so, the maintenance strategy of the engineering machinery equipment is determined to be not to implement an extended maintenance strategy; any type of operation data is input into the first decision tree model, and if the maintenance analysis result based on the operation data is obtained to be not to extend the maintenance service, then other operation data is no longer used to analyze the maintenance strategy of the engineering machinery equipment; The second analysis module is used to determine whether the engineering machinery equipment has been maintained on time; if so, the maintenance cycle data is input into the second decision tree model to obtain a maintenance analysis result based on the maintenance cycle data; the second decision tree model is a decision tree model established based on the maintenance cycle data; the maintenance analysis result based on the maintenance cycle data includes an extended maintenance service or a non-extended maintenance service based on the maintenance cycle data; if not, the maintenance strategy of the engineering machinery equipment is determined to be a non-extended maintenance strategy; any type of maintenance cycle data is input into the second decision tree model, and if the maintenance analysis result based on the maintenance cycle data is a non-extended maintenance service, then other maintenance cycle data is no longer used to analyze the maintenance strategy of the engineering machinery equipment; A generation module is used to generate a maintenance strategy for the engineering machinery equipment according to the maintenance analysis results based on the operation data and the maintenance analysis results based on the maintenance cycle data; the maintenance strategy for the engineering machinery equipment includes maintenance extension service and maintenance non-extension service.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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