CN111487075A - Fault detection method, device, equipment and medium for construction equipment - Google Patents
Fault detection method, device, equipment and medium for construction equipment Download PDFInfo
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Abstract
The application provides a fault detection method, a fault detection device, equipment and a medium of construction equipment, and relates to the technical field of fault detection. The method can comprise the following steps: acquiring construction data from at least one construction device, wherein the construction data of each construction device comprises various data generated by each construction device in construction operation; adopting a fault analysis model corresponding to each construction device, carrying out fault analysis on the construction data of each construction device, and obtaining a fault analysis result of each construction device, wherein the fault analysis result comprises: information indicating whether there is a malfunction of each construction equipment. By applying the embodiment of the application, the fault detection precision of the construction equipment can be improved.
Description
Technical Field
The application relates to the technical field of fault detection, in particular to a fault detection method, a fault detection device, a fault detection equipment and a fault detection medium for construction equipment.
Background
The fault detection of the construction equipment plays a vital role in modern industry, and along with the rapid development of science and technology, the fault detection can be carried out by collecting data generated by the construction equipment in the operation process.
Currently, in fault detection of construction equipment, fault detection is performed based on only one type of collected data of the construction equipment in construction work.
However, it is difficult to detect a failure of the construction equipment in time by performing failure detection only with one type of data, and the accuracy of failure detection of the construction equipment is not high.
Disclosure of Invention
An object of the present invention is to provide a method, an apparatus, a device, and a medium for detecting a failure of a construction equipment, which can improve the accuracy of detecting a failure of a construction equipment.
In order to achieve the above purpose, the technical solutions adopted in the embodiments of the present application are as follows:
in a first aspect, an embodiment of the present application provides a method for detecting a fault of a construction device, where the method includes:
acquiring construction data from at least one construction device, wherein the construction data of each construction device comprises various data generated by each construction device in construction operation;
adopting a fault analysis model corresponding to each construction device, and carrying out fault analysis on the construction data of each construction device to obtain a fault analysis result of each construction device, wherein the fault analysis result comprises: information indicating whether there is a failure in each of the construction equipment.
Optionally, if there is a failure of the construction equipment in the at least one piece of construction equipment, the failure analysis result further includes: a fault type; the method further comprises the following steps:
determining a processing mode corresponding to the fault type as a fault processing mode corresponding to the construction equipment with the fault according to the fault type and a pre-stored corresponding relation between the fault type and the processing mode;
and displaying the fault processing mode.
Optionally, if there is a failure of the construction equipment in the at least one construction equipment, the method further includes:
and generating a prompt early warning signal, wherein the prompt early warning signal is used for indicating that the construction equipment fails.
Optionally, if the at least one piece of construction equipment includes a plurality of pieces of construction equipment, and the types of the plurality of pieces of construction equipment are multiple types, the fault analysis model corresponding to each piece of construction equipment is the fault analysis model corresponding to the type of each piece of construction equipment.
Optionally, before performing fault analysis on the construction data of each of the construction devices by using the fault analysis model corresponding to each of the construction devices to obtain a fault analysis result of each of the construction devices, the method further includes:
acquiring historical construction data of each construction device;
and carrying out model training according to the historical construction data to obtain the fault analysis model.
Optionally, if the at least one construction equipment comprises: at least one fracturing truck;
the construction data of each fracturing truck comprises at least two kinds of data as follows:
construction data of a hydraulic system, construction data of a lubricating system and construction data of an engine.
Optionally, if the at least one construction equipment comprises: at least one sand mixing truck;
the construction data of each sand mixing truck comprises at least two kinds of data as follows:
suction construction data, discharge construction data, construction data of a hydraulic system, and construction data of an engine.
In a second aspect, an embodiment of the present application further provides a failure detection apparatus for construction equipment, where the apparatus includes:
the construction data acquisition module is used for acquiring construction data from at least one piece of construction equipment, wherein the construction data of each piece of construction equipment comprises various data generated by each piece of construction equipment in construction operation;
the analysis module is used for performing fault analysis on the construction data of each construction device by adopting a fault analysis model corresponding to each construction device to obtain a fault analysis result of each construction device, wherein the fault analysis result comprises: information indicating whether there is a failure in each of the construction equipment.
Optionally, if there is a failure of the construction equipment in the at least one piece of construction equipment, the failure analysis result further includes: a fault type; the device further comprises:
the determining module is used for determining the processing mode corresponding to the fault type as the fault processing mode corresponding to the construction equipment with the fault according to the fault type and the corresponding relation between the pre-stored fault type and the processing mode;
and the display module is used for displaying the fault processing mode.
Optionally, if there is a failure of the construction equipment in the at least one construction equipment, the apparatus further includes:
the generating module is used for generating a prompt early warning signal, and the prompt early warning signal is used for indicating that the construction equipment fails.
Optionally, if the at least one piece of construction equipment includes a plurality of pieces of construction equipment, and the types of the plurality of pieces of construction equipment are multiple types, the fault analysis model corresponding to each piece of construction equipment is the fault analysis model corresponding to the type of each piece of construction equipment.
Optionally, before the analysis module, the apparatus further includes:
the first acquisition module is used for acquiring historical construction data of each piece of construction equipment;
and the training module is used for carrying out model training according to the historical construction data to obtain the fault analysis model.
Optionally, if the at least one construction equipment comprises: at least one fracturing truck;
the construction data of each fracturing truck comprises at least two kinds of data as follows:
construction data of a hydraulic system, construction data of a lubricating system and construction data of an engine.
Optionally, if the at least one construction equipment comprises: at least one sand mixing truck;
the construction data of each sand mixing truck comprises at least two kinds of data as follows:
suction construction data, discharge construction data, construction data of a hydraulic system, and construction data of an engine.
In a third aspect, an embodiment of the present application provides a fault detection device, including: the fault detection device comprises a processor, a storage medium and a bus, wherein the storage medium stores machine readable instructions executable by the processor, when the fault detection device runs, the processor and the storage medium communicate through the bus, and the processor executes the machine readable instructions to execute the steps of the fault detection method of the construction device of the first aspect.
In a fourth aspect, the present application provides a storage medium, and the computer program is executed by a processor to execute the steps of the method for detecting a failure of a construction equipment in the first aspect.
The beneficial effect of this application is:
the embodiment of the application provides a fault detection method, a fault detection device, equipment and a medium for construction equipment, wherein the method comprises the following steps: acquiring construction data from at least one construction device, wherein the construction data of each construction device comprises various data generated by each construction device in construction operation; adopting a fault analysis model corresponding to each construction device, carrying out fault analysis on the construction data of each construction device, and obtaining a fault analysis result of each construction device, wherein the fault analysis result comprises: information indicating whether there is a malfunction of each construction equipment. By adopting the fault detection method for the construction equipment, provided by the embodiment of the application, the multiple construction data of each construction equipment can be comprehensively analyzed through the pre-trained fault analysis model, the possibility that each data influences the construction equipment to generate faults is considered, the fault detection of the construction equipment by using only single data is avoided, and the accuracy of the fault detection result of the construction equipment is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 is a schematic flowchart of a fault detection method for construction equipment according to an embodiment of the present disclosure;
fig. 2 is a schematic flowchart of another fault detection method for construction equipment according to an embodiment of the present disclosure;
fig. 3 is a schematic flowchart of a fault analysis model training method according to an embodiment of the present disclosure;
FIG. 4 is a schematic structural diagram of an oil and gas field mining scenario provided by an embodiment of the present application;
fig. 5 is a schematic structural diagram of a fault detection device of construction equipment according to an embodiment of the present disclosure;
fig. 6 is a schematic structural diagram of another fault detection device for construction equipment according to an embodiment of the present disclosure;
fig. 7 is a schematic structural diagram of a fault analysis model training apparatus according to an embodiment of the present application;
fig. 8 is a schematic structural diagram of a fault detection device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments.
Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
Fig. 1 is a schematic flowchart of a fault detection method for construction equipment according to an embodiment of the present disclosure, where the fault detection method is applied to a construction equipment monitoring system, and the construction equipment monitoring system may include: the construction equipment comprises fault detection equipment and at least one construction equipment, wherein the fault detection equipment can be in communication connection with each construction equipment. The fault detection device can be provided with a device management system, and can realize the fault detection method provided by each embodiment of the application through the device management system, a specific product system of the fault detection device can be a computer, a processor and other devices capable of performing a fault detection function, and in a possible application scene, the fault detection device can be arranged on a detection instrument vehicle, so that the detection instrument vehicle can realize fault detection of construction equipment. When the fault detection equipment is arranged on the detection instrument vehicle, the detection instrument vehicle can also be called an intelligent instrument vehicle. As shown in fig. 1, the method may include:
s101, construction data from at least one construction device is obtained.
Wherein the construction data of each construction equipment includes various data generated by each construction equipment during construction. Hardware systems installed on construction equipment, such as an engine, a hydraulic system and the like, can acquire corresponding data according to various sensors arranged at corresponding positions in the construction process, such as a pressure sensor generating a pressure signal, a temperature sensor generating a temperature signal and the like.
Specifically, the construction equipment may include a data processing module, and the data processing module may be configured to convert analog signals collected by the sensors into digital signals, perform preliminary data processing such as filtering, and transmit the digital signals to the fault detection equipment through the digital transmission module.
S102, adopting the fault analysis model corresponding to each construction device to perform fault analysis on the construction data of each construction device to obtain a fault analysis result of each construction device.
Wherein, the fault analysis result comprises: information indicating whether there is a malfunction of each construction equipment. Specifically, the construction data from each construction equipment may be received by the failure detection equipment and stored in a preset format. The number of data that every construction equipment produced in the work progress can be the same, also can be different, sets up according to the actual demand in the work progress, and under the general condition, the construction equipment of the same kind type has a plurality of construction data of the same kind, and the construction equipment of different grade type has a plurality of construction data of different kinds because of the difference of its function. For example, the construction data corresponding to the same type of construction equipment may include: pressure data x1Temperature data x2Oil consumption data x3And engine speed data x4For example, at time N, the temperature data of the construction equipment No. 1, which is also the type a, may be 60 degrees, and the temperature data of the construction equipment No. 2 may be 80 degrees.
After the fault detection device receives the construction data of the construction equipment, the construction data of each construction equipment can be input into a corresponding pre-trained fault analysis model, the fault analysis model inputs the construction data of the construction equipment with the reference number of A1 into the fault analysis model corresponding to the construction equipment with the reference number of A1, inputs the construction data of the construction equipment with the reference number of A2 into the fault analysis model corresponding to the construction equipment with the reference number of A2, inputs the construction data of the construction equipment with the reference number of B1 into the fault analysis model corresponding to the construction equipment with the reference number of B1, and so on, the fault analysis result of each construction equipment can be obtained. The fault detection device may also include a network module (e.g., a 4G/5G network module), and the network module may send the fault analysis result to a mobile terminal (e.g., a mobile phone). The working personnel can inquire the fault analysis result of the construction equipment to be known at any time and any place by opening the matched application software on the mobile terminal, so that the working personnel can obtain the fault analysis result of the construction equipment in various ways.
To sum up, in the method for detecting a fault of a construction device, first, construction data from at least one construction device is obtained, where the construction data of each construction device includes various data generated by each construction device in a construction operation; adopting a fault analysis model corresponding to each construction device, carrying out fault analysis on the construction data of each construction device, and obtaining a fault analysis result of each construction device, wherein the fault analysis result comprises: information indicating whether there is a malfunction of each construction equipment. By adopting the fault detection method for the construction equipment, provided by the embodiment of the application, the multiple construction data of each construction equipment can be comprehensively analyzed through the pre-trained fault analysis model, the possibility that each data influences the construction equipment to generate faults is considered, the fault detection of the construction equipment by using only a single data class is avoided, and the accuracy of the fault detection result of the construction equipment is improved.
Fig. 2 is a schematic flow chart of another method for detecting a failure of construction equipment according to an embodiment of the present disclosure, and as shown in fig. 2, optionally, if a failure occurs in at least one construction equipment, the failure analysis result further includes: the method may further comprise:
s201, according to the fault type and the corresponding relation between the pre-stored fault type and the processing mode, determining that the processing mode corresponding to the fault type is the fault processing mode corresponding to the construction equipment with the fault.
And S202, displaying the fault processing mode.
Specifically, whether the construction equipment breaks down or not can be analyzed through a pre-trained fault analysis model, and a specific corresponding fault type when the construction equipment breaks down can be analyzed, if so, the type is that the engine is broken. Generally, the cause of a fault generated by construction equipment is recorded in a fault manual in advance, and a corresponding processing mode is provided, so that an operator can search the content in the fault manual and store the processing mode corresponding to the type of the generated fault in advance. The staff can also change the processing mode corresponding to the prestored fault type according to experience, add a new processing mode possibly corresponding to the fault type, or delete a useless processing mode, and release more storage space.
For example, processing manners corresponding to 3 fault types (fault type 1, fault type 2, and fault type 3) are stored in advance, where the processing manner corresponding to the fault type 1 may include: when the specific corresponding fault type is the fault type 1 when the construction equipment is analyzed to be faulty through the pre-trained fault analysis model, it is equivalent to know which specific processing modes are available for the fault type, and the processing modes corresponding to the fault type can be displayed on the display screen according to the priority order of the processing modes.
And S203, generating a prompt early warning signal, wherein the prompt early warning signal is used for indicating that the construction equipment has a fault.
Specifically, when the fault handling mode is displayed, a prompt early warning signal can be generated, the prompt early warning signal can be used for indicating that the construction equipment has the fault in a voice mode, and can also indicate that the construction equipment has the fault in an alarm lamp mode. Therefore, the phenomenon that the construction equipment has faults can be timely found out under the condition that the worker does not see the display screen.
The working personnel can know which construction equipment is failed specifically in a voice mode, can know the specific failure type, and can also add other broadcast contents according to actual requirements, such as failure time, wherein the failure time is not limited.
Optionally, if at least one piece of construction equipment includes multiple pieces of construction equipment, and the types of the multiple pieces of construction equipment are multiple types, the fault analysis model corresponding to each piece of construction equipment is the fault analysis model corresponding to the type of each piece of construction equipment.
Specifically, when a project is large, a plurality of pieces of construction equipment may be required, and the types of the plurality of pieces of construction equipment may be identical or may not be identical. When the types of the plurality of construction equipment are not consistent, each type of construction equipment corresponds to one fault analysis model, and construction data of the construction equipment of the same type can be input into the corresponding fault analysis model to obtain a fault analysis result of the construction equipment.
For example, construction equipment utilized in a project may include two types, such as a type a construction equipment and a type B construction equipment, with 3 construction equipment belonging to the type a construction equipment and 2 construction equipment belonging to the type B construction equipment. The A-type construction equipment corresponds to the fault analysis model 1, and the B-type construction equipment corresponds to the fault analysis model 2. The construction data of the 3 construction equipment belonging to the type a construction equipment can be analyzed by using the fault analysis model 1 to obtain the fault analysis results of the 3 construction equipment, respectively. Similarly, the fault analysis model 2 can be used to analyze the construction data of the 2 pieces of construction equipment belonging to the B-type construction equipment, and the fault analysis results of the 2 pieces of construction equipment are obtained respectively. Because the same type of construction equipment can adopt one fault analysis model for fault analysis, the condition that a plurality of fault analysis models exist is avoided, and the storage space is saved.
The fault analysis model in fig. 1 may be trained in the following manner, and of course, may also be trained in other manners, which is only described as an example, and a specific training process may be shown in fig. 3. Fig. 3 is a schematic flow chart of a fault analysis model training method provided in an embodiment of the present application, and as shown in fig. 3, optionally, before step S102 in fig. 1, the method may further include:
s301, obtaining historical construction data of each construction device.
And S302, performing model training according to the historical construction data to obtain a fault analysis model.
Specifically, the historical construction data of each construction device in the preset time can be acquired in the database or the historical construction data can be acquired according to the number of the preset data groups. The historical construction data may be stored in a database in the form of, for example, (x)1，x2，x3，……，xnY), wherein xnMay represent specific construction data acquired through a sensor, such as pressure data, temperature data, etc., and y may represent an operation state of the construction equipment, and when y is equal to 0, it represents that the construction equipment is not faulty; when y is equal to 1, it represents that the construction equipment is faulty, of course, the numerical values 1, 2 and 3 … … may also be used to represent the specific fault type corresponding to the faulty construction equipment, and the specific representation form of y may also be other, and is specifically set according to the actual requirement, which is not limited here.
The acquired multiple groups of historical construction data are preprocessed, abnormal data values can be filtered, for example, the data values are 0 or infinite values, so that the obtained fault analysis model is more accurate, and the influence of the abnormal data is avoided. Taking part of the preprocessed multi-group data as a training sample, training a pre-established neural network model, wherein the neural network can be a Back Propagation (BP) neural network, inputting the training sample into the pre-established neural network model, and stopping training the pre-established neural network model when the pre-established neural network model meets a preset stopping condition. The preset stop condition may be that the loss function value is minimized, or that the number of iterations reaches a preset value (e.g., 5000). And then, evaluating the neural network model meeting the preset stop condition by using the other part of the preprocessed multi-group data, judging whether the neural network model has an over-fitting phenomenon or an under-fitting phenomenon, if so, continuously optimizing the neural network model until the neural network model has good generalization capability, and taking the neural network model at the moment as a fault analysis model.
Optionally, if at least one construction equipment comprises: at least one fracturing truck; the construction data of each fracturing truck comprises at least two kinds of data as follows: construction data of a hydraulic system, construction data of a lubricating system and construction data of an engine.
Specifically, a specific application scenario (oil and gas field exploitation) is taken as an example to describe the fault detection method of the construction equipment, and fig. 4 is a schematic structural diagram of the oil and gas field exploitation scenario provided by the embodiment of the present application. Firstly, some concepts in oil and gas field exploitation are simply introduced, fracturing is a core technology for increasing yield of a conventional oil and gas field and exploiting unconventional oil and gas resources such as shale gas, shale oil, coal bed gas and the like, and is an important construction process or link of exploration and development engineering of medium and low permeability oil fields. As can be seen from fig. 4, the fracturing truck set in the fracturing operation process mainly comprises a fracturing truck, a fracturing blender truck, an instrument truck and other construction equipment, wherein the fracturing truck mainly has the functions of injecting high-pressure and large-discharge fracturing fluid into an oil-gas well, fracturing the stratum by injecting pressure into a stratum pump fluid, and extruding the fracturing fluid into the fracture, so that the permeability of the oil-gas layer and the recovery ratio of oil and gas wells are improved. In an actual oil and gas field exploitation site, at least one fracturing truck CAN be included, the fracturing truck CAN be identified by using a label, such as the fracturing truck 1 and the fracturing truck 2 … …, the fracturing truck mainly comprises a hydraulic system, a lubricating system, an engine and other parts, during the construction process of the fracturing truck, construction data (pressure, oil supplementing pressure, temperature, fan oil pressure and oil level sensor) of the hydraulic system and construction data (temperature and pressure) of the lubricating system CAN be collected by the sensors on the fracturing truck, the collected data is transmitted to an instrument truck through a data transmission module, meanwhile, construction data (water temperature, oil temperature and load rate) of the engine CAN be obtained through an Electronic Control Unit (ECU), and the data is also transmitted to the instrument truck through a data transmission module through a Controller Area Network (CAN) bus, the instrument vehicle can carry out fault detection on a plurality of fracturing vehicles according to various received data, and when faults exist, the instrument vehicle can give out early warning signals and corresponding processing modes.
Furthermore, the oil and gas field exploitation site can also at least comprise one sand mixing truck, the main function of the sand mixing truck is to form fracturing fluid from various materials, and the fracturing fluid is supplied to the fracturing truck, and the construction data generated by the sand mixing truck in the construction process can comprise suction construction data (suction flow and pressure), discharge construction data (discharge flow and pressure), construction data (pressure and vibration frequency) of a hydraulic system, construction data (water temperature, oil temperature and load rate) of an engine and the like. The suction construction data, the discharge construction data and the construction of the hydraulic system CAN be collected through sensors on the suction construction data, the collected data are transmitted to the instrument truck through a data transmission module, meanwhile, the construction data of the engine CAN be obtained through an Electronic Control Unit (ECU), the data are also transmitted to the instrument truck through a Controller Area Network (CAN) bus through the data transmission module, the instrument truck CAN carry out fault detection on the sand mixing truck according to the received various data, and when a fault exists, the instrument truck CAN give out early warning signals and corresponding processing modes. And, the instrument vehicle may include a network module (e.g. 4G/5G network module), and the network module may transmit the fault analysis result to a terminal device (e.g. mobile phone). The staff can open supporting application software on the terminal equipment, inquire the fault analysis result of the construction equipment that wants to know anytime and anywhere, and can make the staff obtain the fault analysis result of the construction equipment through multiple modes.
Fig. 5 shows an execution device corresponding to the method in fig. 1, where fig. 5 is a schematic structural diagram of a fault detection device for construction equipment according to an embodiment of the present application, where the fault detection device may include:
an obtaining module 501 is configured to obtain construction data from at least one construction device.
The analysis module 502 is configured to perform fault analysis on the construction data of each construction device by using the fault analysis model corresponding to each construction device, so as to obtain a fault analysis result of each construction device.
Fig. 6 shows an execution device corresponding to the method in fig. 2, and fig. 6 is a schematic structural diagram of another fault detection device for construction equipment provided in an embodiment of the present application, and as shown in fig. 6, optionally, if a construction equipment fault occurs in at least one construction equipment, the fault analysis result further includes: the fault type, the apparatus may further comprise:
the determining module 601 is configured to determine, according to the fault type and the pre-stored correspondence between the fault type and the processing manner, that the processing manner corresponding to the fault type is a fault processing manner corresponding to the faulty construction equipment.
A displaying module 602, configured to display the failure handling manner.
The generating module 603 is configured to generate a prompt and early warning signal, where the prompt and early warning signal is used to indicate that a failure occurs in the construction equipment.
Optionally, if at least one piece of construction equipment includes multiple pieces of construction equipment, and the types of the multiple pieces of construction equipment are multiple types, the fault analysis model corresponding to each piece of construction equipment is the fault analysis model corresponding to the type of each piece of construction equipment.
Fig. 7 shows an execution device corresponding to the method in fig. 3, and fig. 7 is a schematic structural diagram of a fault analysis model training device provided in an embodiment of the present application, and as shown in fig. 7, the device may include:
the first obtaining module 701 is configured to obtain historical construction data of each construction device.
And the training module 702 is configured to perform model training according to the historical construction data to obtain a fault analysis model.
Optionally, if at least one construction equipment comprises: at least one fracturing truck; the construction data of each fracturing truck comprises at least two kinds of data as follows: construction data of a hydraulic system, construction data of a lubricating system and construction data of an engine.
Optionally, if at least one construction equipment comprises: at least one sand mixing truck; the construction data of each sand mixing truck comprises at least two kinds of data as follows: suction construction data, discharge construction data, construction data of a hydraulic system, and construction data of an engine.
The above-mentioned apparatus is used for executing the method provided by the foregoing embodiment, and the implementation principle and technical effect are similar, which are not described herein again.
These above modules may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuits (ASICs), or one or more microprocessors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs), among others. For another example, when one of the above modules is implemented in the form of a processing element scheduler code, the processing element may be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor capable of calling program code. For another example, these modules may be integrated together and implemented in the form of a system-on-a-chip (SOC).
Fig. 8 is a schematic structural diagram of a fault detection device according to an embodiment of the present disclosure, which may be disposed in the instrument truck in fig. 4. As shown in fig. 8, the fault detection apparatus may include: the fault detection device comprises a processor 801, a storage medium 802 and a bus 803, wherein the storage medium 802 stores machine readable instructions executable by the processor 801, when the fault detection device operates, the processor 801 communicates with the storage medium 802 through the bus 803, and the processor 801 executes the machine readable instructions to execute the steps of the fault detection method of the construction device. The specific implementation and technical effects are similar, and are not described herein again.
Optionally, the present application further provides a storage medium, where a computer program is stored on the storage medium, and the computer program is executed by a processor to perform the steps of the method for detecting a failure of a construction equipment.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to perform some steps of the methods according to the embodiments of the present application. And the aforementioned storage medium includes: a U disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It is noted that, in this document, relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, 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 a process, method, article, or apparatus that comprises the element.
Claims (10)
1. A method of detecting a failure of construction equipment, the method comprising:
acquiring construction data from at least one construction device, wherein the construction data of each construction device comprises various data generated by each construction device in construction operation;
adopting a fault analysis model corresponding to each construction device, and carrying out fault analysis on the construction data of each construction device to obtain a fault analysis result of each construction device, wherein the fault analysis result comprises: information indicating whether there is a failure in each of the construction equipment.
2. The method of claim 1, wherein if there is a failure of a construction equipment in the at least one construction equipment, the failure analysis result further comprises: a fault type; the method further comprises the following steps:
determining a processing mode corresponding to the fault type as a fault processing mode corresponding to the construction equipment with the fault according to the fault type and a pre-stored corresponding relation between the fault type and the processing mode;
and displaying the fault processing mode.
3. The method of claim 1, wherein if there is a construction equipment failure in the at least one construction equipment, the method further comprises:
and generating a prompt early warning signal, wherein the prompt early warning signal is used for indicating that the construction equipment fails.
4. The method of claim 1, wherein if the at least one construction equipment comprises a plurality of construction equipments, and the types of the plurality of construction equipments are multiple types, the fault analysis model corresponding to each of the construction equipments is a fault analysis model corresponding to each of the types of the construction equipments.
5. The method of claim 1, wherein before performing fault analysis on the construction data of each of the construction devices by using the fault analysis model corresponding to each of the construction devices to obtain the fault analysis result of each of the construction devices, the method further comprises:
acquiring historical construction data of each construction device;
and carrying out model training according to the historical construction data to obtain the fault analysis model.
6. The method of any one of claims 1-5, wherein if the at least one construction equipment comprises: at least one fracturing truck;
the construction data of each fracturing truck comprises at least two kinds of data as follows:
construction data of a hydraulic system, construction data of a lubricating system and construction data of an engine.
7. The method of any one of claims 1-5, wherein if the at least one construction equipment comprises: at least one sand mixing truck;
the construction data of each sand mixing truck comprises at least two kinds of data as follows:
suction construction data, discharge construction data, construction data of a hydraulic system, and construction data of an engine.
8. A failure detection device of construction equipment, characterized in that the device comprises:
the construction data acquisition module is used for acquiring construction data from at least one piece of construction equipment, wherein the construction data of each piece of construction equipment comprises various data generated by each piece of construction equipment in construction operation;
the analysis module is used for performing fault analysis on the construction data of each construction device by adopting a fault analysis model corresponding to each construction device to obtain a fault analysis result of each construction device, wherein the fault analysis result comprises: information indicating whether there is a failure in each of the construction equipment.
9. A fault detection device, comprising: a processor, a storage medium and a bus, the storage medium storing machine-readable instructions executable by the processor, the processor and the storage medium communicating via the bus when the fault detection apparatus is operated, the processor executing the machine-readable instructions to perform the steps of the fault detection method of the construction apparatus as claimed in any one of claims 1 to 7.
10. A storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method of detecting a failure of construction equipment according to any one of claims 1 to 7.
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