CN115601327B - Fault detection method and system for main propulsion diesel engine unit - Google Patents

Fault detection method and system for main propulsion diesel engine unit Download PDF

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CN115601327B
CN115601327B CN202211270031.XA CN202211270031A CN115601327B CN 115601327 B CN115601327 B CN 115601327B CN 202211270031 A CN202211270031 A CN 202211270031A CN 115601327 B CN115601327 B CN 115601327B
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CN115601327A (en
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吴子俊
夏俊
佘小龙
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Shanghai Yuyou Ship Technology Co ltd
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Abstract

The application provides a fault detection method and a fault detection system for a main propulsion diesel engine set, which relate to the technical field of computers and are applied to a diesel engine set of target equipment, wherein the method comprises the following steps: acquiring a detection image of a part to be detected in the diesel engine unit; determining the working scene of the component to be detected according to the detection image; acquiring a corresponding fault detection model according to the working scene; and according to the fault detection model, combining the detection image and the working scene corresponding to the detection image, and determining the state of the part to be detected. The application can improve the efficiency and accuracy of fault detection of the parts of the main propulsion diesel engine unit.

Description

Fault detection method and system for main propulsion diesel engine unit
Technical Field
The application relates to the technical field of computers, in particular to a fault detection method and system of a main propulsion diesel engine set.
Background
In a state judging system of a main propulsion diesel engine set in traditional ship equipment and the like, an image of a part to be detected is generally obtained, and then the state of the part to be detected is judged by combining human experience.
However, this approach is too dependent on the experience and ability of the inspector, and it is difficult to ensure failure detection efficiency and accuracy of the main propulsion diesel unit. Therefore, a fault detection method and system for a main propulsion diesel engine set are needed to solve the technical problem.
Disclosure of Invention
The embodiment of the application aims to provide a fault detection method and system for a main propulsion diesel engine unit, and the embodiment of the application can obviously improve the accuracy and efficiency of the state detection of the diesel engine unit. The specific technical scheme is as follows:
in a first aspect of an embodiment of the present application, a method for detecting a fault of a main propulsion diesel engine set is provided, applied to a diesel engine set of a target device, the method including:
acquiring a detection image of a part to be detected in the diesel engine unit;
determining the working scene of the component to be detected according to the detection image;
acquiring a corresponding fault detection model according to the working scene;
and according to the fault detection model, combining the detection image and the working scene corresponding to the detection image, and determining the state of the part to be detected.
Optionally, the working scene includes a common scene, a standby scene, and an emergency scene.
Optionally, determining the working scene of the component to be detected according to the detection image includes:
performing interference elimination processing on the detection image to obtain an intermediate detection image;
identifying the part factor and an environmental factor in the intermediate detection image;
and determining the working scene according to the component factors and the environment factors.
Optionally, the determining the working scenario according to the component factor and the environment factor includes:
feature fusion is carried out on the component factors and the environment factors, so that fusion features are obtained;
inputting the fusion characteristics into a working scene detection model, and outputting a target value;
and determining the working scene corresponding to the target value according to the mapping relation between the target value and the working scene.
Optionally, the determining, according to the fault detection model, the state of the component to be detected in combination with the detection image and the working scene corresponding to the detection image includes:
acquiring a current working value and a first analysis result of the part to be detected according to the detection image;
determining a second analysis result according to the current working scene;
and processing the first analysis result and the second analysis result to determine the state of the part to be detected.
Optionally, the obtaining a second analysis result according to the current working scenario includes:
according to the working scene, obtaining a standard working value of the part to be detected;
and comparing the current working value with the standard working value to obtain the second analysis result.
Optionally, the method further comprises:
if the state of the part to be detected is abnormal, acquiring a correction value of the current working value;
and replacing the current working value with the correction value to correct the fault of the part to be detected.
In yet another aspect of an embodiment of the present application, there is provided a fault detection system for a main propulsion diesel engine set, for a diesel engine set of a target device, the system comprising:
the detection image acquisition module is used for acquiring detection images of components to be detected in the diesel engine set;
the working scene determining module is used for determining the working scene of the component to be detected according to the detection image;
the model acquisition module is used for acquiring a corresponding fault detection model according to the working scene;
and the state detection module is used for determining the state of the part to be detected according to the fault detection model and combining the detection image and the working scene corresponding to the detection image.
In a further aspect of the embodiments of the present application, there is provided a computer readable storage medium having stored thereon a computer program which when executed implements the steps of the method as described above.
In yet another aspect of the embodiments of the present application, a computer device is provided, comprising a processor, a memory and a computer program stored on the memory, the processor implementing the steps of the method as described above when executing the computer program.
From the above, the embodiment of the application can determine the working scene of the component to be detected through the detection image of the component to be detected, and determine the corresponding fault detection model according to the working scene, so as to accurately and efficiently detect the state of the component to be detected by combining the image of the component to be detected and the working scene according to the adaptive fault monitoring, thereby remarkably improving the efficiency and accuracy of detecting the state of the main propulsion diesel unit.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is an application scenario schematic diagram of a fault detection system of a main propulsion diesel engine set provided by an embodiment of the present application;
FIG. 2 is a flow chart of a method for fault detection of a main propulsion diesel unit provided by an embodiment of the present application;
FIG. 3 is a schematic diagram of a fault detection system for a main propulsion diesel unit provided by an embodiment of the present application;
fig. 4 is an internal structural diagram of a computer device according to an embodiment of the present application.
Detailed Description
In order to more clearly illustrate the technical solutions of the embodiments of the present specification, the drawings that are required to be used in the description of the embodiments will be briefly described below. It is apparent that the drawings in the following description are only some examples or embodiments of the present specification, and it is possible for those of ordinary skill in the art to apply the present specification to other similar situations according to the drawings without inventive effort. Unless otherwise apparent from the context of the language or otherwise specified, like reference numerals in the figures refer to like structures or operations.
It will be appreciated that "system," "unit," and/or "module" as used herein is one method for distinguishing between different components, elements, parts, portions, or assemblies at different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.
As used in this specification and the claims, the terms "a," "an," "the," and/or "the" are not specific to a singular, but may include a plurality, unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that the steps and elements are explicitly identified, and they do not constitute an exclusive list, as other steps or elements may be included in a method or apparatus.
A flowchart is used in this specification to describe the operations performed by the system according to embodiments of the present specification. It should be appreciated that the preceding or following operations are not necessarily performed in order precisely. Rather, the steps may be processed in reverse order or simultaneously. Also, other operations may be added to or removed from these processes.
FIG. 1 is a schematic diagram of an exemplary primary propulsion diesel unit fault detection system 100 associated with a vessel (FIG. 1 is an example of a marine diesel unit) shown in accordance with some embodiments of the application. In some embodiments, the fault detection system 100 of the main propulsion diesel unit may include a server 110, a network 120, a vessel 130, and a memory 140.
In some embodiments, the server 110 may be a single server or a group of servers. The server farm may be centralized or distributed (e.g., server 110 may be a distributed system). In some embodiments, server 110 may be local or remote. For example, server 110 may access information and/or data stored in vessel 130 and/or memory 140 via network 120. As another example, server 110 may be directly connected to vessel 130 and/or memory 140 to access stored information and/or data. In some embodiments, the server 110 may be implemented on a cloud platform or on-board computer. For example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi-layer cloud, or the like, or any combination thereof. In some embodiments, server 110 may execute on a computing device 200 described in FIG. 2 that includes one or more components in the present application.
In some embodiments, server 110 may include a processing engine 112. The processing engine 112 may process information and/or data associated with the travel information of the vessel 130 to perform one or more functions described herein. For example, the processing engine 112 may obtain travel information for the vessel 130 and determine control parameters that may be used to control the vessel 130 based on the travel information. In some embodiments, the processing engine 112 may include one or more processing engines (e.g., a single chip processing engine or a multi-chip processing engine). By way of example only, the processing engine 112 may include a central processing unit (centralprocessing unit, CPU), an application-specific integrated circuit (ASIC), a special-purpose instruction set processor (ASIP), a graphics processing unit (graphics processing unit, GPU), a physical arithmetic processor (physics processingunit, PPU), a digital signal processor (digital signal processor, DSP), a field programmable gate array (fieldprogrammable gate array, FPGA), a programmable logic device (programmable logic device, PLD), a controller, a microcontroller unit, a reduced instruction set computer (reduced instruction-set computer, RISC), a microprocessor, or the like, or any combination thereof.
In some embodiments, the server 110 may be connected to the network 120 to communicate with one or more components of the fault detection system 100 of the main propulsion diesel unit (e.g., the vessel 130 and the memory 140). In some embodiments, the server 110 may be directly connected to or in communication with one or more components of the fault detection system 100 (e.g., the vessel 130 and the memory 140) of the main propulsion diesel train. In some embodiments, the server 110 may be integrated in the vessel 130.
The network 120 may facilitate the exchange of information and/or data. In some embodiments, one or more components in the fault detection system 100 of the main propulsion diesel unit (e.g., the server 110, the vessel 130, or the memory 140) may send information and/or data to other components in the fault detection system 100 of the main propulsion diesel unit via the network 120. For example, the server 110 may obtain/acquire travel information of the vessel 130 via the network 120. In some embodiments, network 120 may be any form of wired or wireless network, or any combination thereof. By way of example only, the network 120 may include a cable network, a wired network, a fiber optic network, a telecommunications network, an intranet, the internet, a local area network (local area network, LAN), a wide area network (wide area network, WAN), a wireless local area network (wireless local area network, WLAN), a metropolitan area network (metropolitan areanetwork, MAN), a public switched telephone network (public telephone switched network, PSTN), a bluetooth network, a zigbee network, a near field communication (near field communication, NFC) network, and the like, or any combination of the above. In some embodiments, network 120 may include one or more network access points. For example, the network 120 may include a wired or wireless network access point through which one or more components of the fault detection system 100 of the main propulsion diesel unit may connect to the network 120 to exchange data and/or information.
The vessel 130 may include the structure of a conventional vessel, such as a chassis, suspension, steering wheel, drive train components, engine, etc. The vessel 130 may also include at least two sensors (e.g., a distance sensor 131, a speed sensor 132, a position sensor 133, etc.), a braking device 134, an accelerator (not shown), etc. In some embodiments, the at least two sensors may detect travel information of the vessel 130. For example, the position sensor 133 may periodically (e.g., every 20 ms) detect the current position of the vessel 130. For another example, the distance sensor 131 may detect a distance between a current location of the vessel 130 and a defined location (e.g., the destination 150). As another example, the distance sensor 131 may detect a distance between the current position of the vessel 130 and other vessels in the vicinity. As yet another example, the speed sensor 132 may detect an instantaneous speed of the vessel 130.
In some embodiments, the distance sensor 131 may include radar, lidar, infrared sensors, or the like, or a combination thereof. The speed sensor 132 may comprise a hall sensor. In some embodiments, the at least two sensors may also include an acceleration sensor (e.g., an accelerometer), a steering angle sensor (e.g., a tilt sensor), a traction related sensor (e.g., a force sensor), and/or any sensor configured to detect information associated with the dynamic condition of the vessel 130.
The braking device 134 may be configured to control a braking process of the vessel 130. For example, the braking device 134 may adjust the actual acceleration of the vessel based on instructions including the target acceleration obtained from the processing engine 112. The accelerator may be configured to control the acceleration process of the vessel 130.
Memory 140 may store data and/or instructions. In some embodiments, the memory 140 may store data obtained from the vessel 130, such as travel information obtained by the at least two sensors. In some embodiments, memory 140 may store data and/or instructions used by server 110 to perform or use the exemplary methods described herein. In some embodiments, memory 140 may include mass storage, removable storage, volatile read-write memory, read-only memory (ROM), and the like, or any combination thereof. Exemplary mass storage devices may include magnetic disks, optical disks, solid state disks, and the like. Exemplary removable memory may include flash drives, floppy disks, optical disks, memory cards, compact disks, tape, and the like. Exemplary volatile read-write memory can include random access memory (random access memory, RAM). Exemplary RAM may include Dynamic RAM (DRAM), double data rate synchronous dynamic RAM (double date rate synchronous dynamic RAM, DDR SDRAM), static RAM (SRAM), thyristor RAM (T-RAM), zero-capacitance RAM (Z-RAM), and the like. Exemplary read-only memory may include Mask ROM (MROM), programmable ROM (PROM), erasable programmable ROM (PEROM), electrically erasable programmable ROM (programmableROM, EEPROM), compact disk ROM (CD-ROM), digital versatile disk ROM, and the like. In some embodiments, the memory 140 may be implemented on a cloud platform. For example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi-layer cloud, or the like, or any combination thereof.
In some embodiments, memory 140 may be connected to network 120 to communicate with one or more components of fault detection system 100 of the main propulsion diesel unit (e.g., server 110 and vessel 130). One or more components in the fault detection system 100 of the main propulsion diesel unit may access data or instructions stored in the memory 140 via the network 120. In some embodiments, the memory 140 may be directly connected to or in communication with one or more components of the fault detection system 100 (e.g., the server 110 and the vessel 130) of the main propulsion diesel train. In some embodiments, memory 140 may be part of server 110.
Fig. 2 is a schematic flow chart of a fault detection method and system for a main propulsion diesel engine set according to an embodiment of the present application, where, as shown in fig. 2, the fault detection method and system for a main propulsion diesel engine set includes the following steps:
step 201, obtaining a detection image of a part to be detected in the diesel engine set.
The detection image may be an image including a component to be detected, and may be obtained by an image acquisition device such as a video camera or a camera.
Step 202, determining the working scene of the component to be detected according to the detection image.
The working scene may include a common scene, a standby scene, and an emergency scene, among others.
The common scenario refers to a scenario in which target equipment (for example, a ship, a vessel, etc.) carrying a main propulsion diesel engine set uses the diesel engine set under normal working conditions. The standby scene refers to a scene that the target equipment uses the diesel engine set under the limiting working condition, such as a scene of limiting electricity, limiting power and the like. The emergency scene refers to a scene that the target equipment uses the diesel engine set under the fault working condition.
Optionally, step 202 may further include the steps of:
performing interference elimination processing on the detection image to obtain an intermediate detection image;
identifying the part factor and an environmental factor in the intermediate detection image;
and determining the working scene according to the component factors and the environment factors.
In some embodiments, the de-interference process may include removing brightness interference in the detected image. Specifically, the method can be realized by the following calculation modes:
wherein the pixel size of the detected image is P.Q, and P is more than Q and X is assumed to be P i For the pixel value of the ith pixel point (i e 0, p q]) P and Q are the width and height of the image,for the average value of the pixels in each detection image, α is a correction factor, and a is a correction value.
Further, the pixel value of each pixel point is subtractedThe brightness disturbance in the detection image is removed in such a manner that the de-averaging processing of the detection image is realized. It will be appreciated that the function of equation (1) is to average the whole pixels of the detected image, but the operation of directly performing the de-averaging process by only averaging the average value may not ensure the accuracy of obtaining the intermediate detected image, so that a predetermined correction value may be further introduced and the value of the correction factor α may be defined as the correction valueThe proportion of A is used for correcting the average value of the pixels or is understood to be used for fine adjustment of the average value of the pixels so as to further ensure the accuracy of the interference elimination result.
Optionally, the step of determining the working scenario according to the component factor and the environmental factor includes:
feature fusion is carried out on the component factors and the environment factors, so that fusion features are obtained;
inputting the fusion characteristics into a working scene detection model, and outputting a target value;
and determining the working scene corresponding to the target value according to the mapping relation between the target value and the working scene.
Specifically, the feature of the part factor may be a pixel in the detection image that displays the part itself to be detected, and the feature of the environmental factor may be a pixel in the detection image other than the part factor. In the calculation, the two features can be fused to obtain a fused feature, and the fused feature is input into a working scene detection model, wherein the working scene detection model can be a common neural network model, such as RNN, CNN, DNN. After the function calculation mapping inside the model is carried out to the target, the range of the value corresponding to the working scene in which the target value is located is determined through the mapping relation of the target value. For example, if the target value is 10 and the range of the corresponding value of the common scene is 1-20, the target value falls into the range, and the working scene of the component to be detected is determined to be the common scene.
Alternatively, the calculation function of the environmental factor may be expressed as:
wherein T is 1 And T 2 Respectively the different working time lengths of the parts to be detected, r 1 And r 2 Respectively T 1 、T 2 Quantized value of corresponding working data, c is r 1 And r 2 Obtaining an average confidence of accuracy, y being the degree of freedom [ r ] 1 ,r 2 ,(1-c)]A distribution function of time.
It can be understood that, through the activation functions in the E and the working scene detection model, the feature value, i.e. the target value, after the fusion of the environmental factor and the component factor can be mapped accurately, so as to calculate the working scene corresponding to the component to be detected accurately.
Step 203, obtaining a corresponding fault detection model according to the working scene;
it can be understood that in the application, three fault detection models with different detection functions can be respectively corresponding to a common scene, a standby scene and an emergency scene, and different types of fault detection models can be corresponding to different calculation functions, structures, the number of convolution layers and the like, so that accurate judgment on the states of the components to be detected in different working scenes can be realized.
And 204, according to the fault detection model, combining the detection image and the working scene corresponding to the detection image, and determining the state of the part to be detected.
Optionally, step 204 may further include the steps of:
acquiring a current working value and a first analysis result of the part to be detected according to the detection image;
determining a second analysis result according to the current working scene;
and processing the first analysis result and the second analysis result to determine the state of the part to be detected.
Optionally, the step of "obtaining the second analysis result according to the current working scenario" may include:
according to the working scene, obtaining a standard working value of the part to be detected;
and comparing the current working value with the standard working value to obtain the second analysis result.
The working value of the component to be detected can be working data related to the operation of the component to be detected. For example, assuming that the component to be detected is a diesel engine in a main propulsion diesel engine group, the operating value may be a value corresponding to operating data such as a crankshaft mounting angle, a connecting rod temperature, a cooling system water injection amount, and the like. When the image to be detected is acquired, the current or historical working data of the part to be detected can be directly read from a server or a database according to the acquisition time of the image to be detected.
The first analysis result is a fault detection model, and the surface of the part to be detected is directly identified through an image identification technology, so that whether a certain fault or fault risk exists in the appearance of the part to be detected is represented.
Specifically, for the calculation process of the second analysis result, the current operation value of the component to be detected may be compared with the standard operation value. It can be understood that under different working scenarios, there are different standards for the working value of the component to be detected, and the fault detection model can judge the comparison result of the current working value and the standard working value according to different working scenarios by using different preset thresholds. For example, the current working value is 1, the standard working value is 2, the difference value between the current working value and the standard working value is 1, whether the difference value 1 exceeds a preset threshold value is judged, and if the difference value exceeds the preset threshold value, the model judges that the part to be detected fails.
Further, combining the first analysis result and the second analysis result, finally determining whether the component to be detected has a fault or not, and locking the position, time and reason of the fault according to the detected image. For example, the values mapped by the first analysis result and the second analysis result are respectively 3 and 4, and the value is 7, and the model can also judge that the component to be detected fails according to another preset threshold value which is preset, for example, the sum value of the two values is greater than 5, and the component to be detected does not fail and is not greater than 5.
Optionally, the method of the embodiment of the present application may further include:
if the state of the part to be detected is abnormal, acquiring a correction value of the current working value;
and replacing the current working value with the correction value to correct the fault of the part to be detected.
In some embodiments, the correction value for the current operating value may be expressed as:
wherein m in the formula (3) is the mth working data, X m Beta is an auxiliary correction factor, and B is an auxiliary correction factor.
It can be understood that the current working value of the part to be detected corresponding to the abnormal state can be replaced by the similar data of the adjacent time before and after the abnormal state, and the auxiliary correction factor and the auxiliary correction value pair correction value X preset in the same type can be relied on m And (5) making secondary correction to ensure the accuracy of the replacement result.
From the above, the embodiment of the application can determine the working scene of the component to be detected through the detection image of the component to be detected, and determine the corresponding fault detection model according to the working scene, so as to accurately and efficiently detect the state of the component to be detected by combining the image of the component to be detected and the working scene according to the adaptive fault monitoring, thereby remarkably improving the efficiency and accuracy of detecting the state of the main propulsion diesel unit.
In order to implement the above method embodiments, the embodiment of the present application further provides a fault detection system of a main propulsion diesel engine unit, and fig. 3 shows a schematic structural diagram of the fault detection system of the main propulsion diesel engine unit, where the fault detection system is applied to a diesel engine unit of a target device, and the system includes:
a detection image acquisition module 301, configured to acquire a detection image of a component to be detected in the diesel engine set;
a working scene determining module 302, configured to determine a working scene of the component to be detected according to the detection image;
the model obtaining module 303 is configured to obtain a corresponding fault detection model according to the working scenario;
and the state detection module 304 is configured to determine, according to the fault detection model, a state of the component to be detected in combination with the detection image and the working scenario corresponding to the detection image.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working processes of the modules/units/sub-units/components in the above-described system may refer to corresponding processes in the foregoing method embodiments, which are not described herein again.
As can be seen from the above, when the embodiment of the application detects the state of the diesel engine unit, the sensor data of each sub-device of the diesel engine unit can be cleaned and complemented, so that the state erroneous judgment caused by the sensor fault or the data loss of a certain point location can be avoided, and the mutual influence among the collected data of each sub-device can be calculated in the detection process, so that the state trend of a certain sub-device and the whole device of the diesel engine unit is prejudged, and the efficiency and the effect of detecting the state of the diesel engine unit can be greatly improved.
In some embodiments, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 4. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing relevant data of the image acquisition device. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, implements a method and system for fault detection of a main propulsion diesel unit.
In some embodiments, a computer device is provided, which may be a terminal, and the internal structure of which may be as shown in fig. 4. The computer device includes a processor, a memory, a communication interface, a display screen, and an input system connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. 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 computer programs in the non-volatile storage media. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless mode can be realized through WIFI, an operator network, NFC (near field communication) or other technologies. The computer program, when executed by a processor, implements a fault detection method and system for a main propulsion diesel unit. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input system of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by persons skilled in the art that the architecture shown in fig. 4 is merely a block diagram of some of the architecture relevant to the present inventive arrangements and is not limiting as to the computer device to which the present inventive arrangements are applicable, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In some embodiments, there is also provided a computer device comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the method embodiments described above when the computer program is executed.
In some embodiments, a computer readable storage medium is provided, storing a computer program which, when executed by a processor, implements the steps of the method embodiments described above.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, or the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
In summary, the fault detection method of the main propulsion diesel engine set provided by the application is applied to the diesel engine set of the target equipment, and the method comprises the following steps:
acquiring a detection image of a part to be detected in the diesel engine unit;
determining the working scene of the component to be detected according to the detection image;
acquiring a corresponding fault detection model according to the working scene;
and according to the fault detection model, combining the detection image and the working scene corresponding to the detection image, and determining the state of the part to be detected.
In the embodiments provided herein, it should be understood that the disclosed systems and methods may be implemented in other ways. The system embodiments described above are merely illustrative, e.g., the division of the elements is merely a logical functional division, and there may be additional divisions in actual implementation, and e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, system or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown 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 may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments provided in the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method 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, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
It should be noted that: like reference numerals and letters in the following figures denote like items, and thus once an item is defined in one figure, no further definition or explanation of it is required in the following figures, and furthermore, the terms "first," "second," "third," etc. are used merely to distinguish one description from another and are not to be construed as indicating or implying relative importance.
Finally, it should be noted that: the above examples are only specific embodiments of the present application, and are not intended to limit the scope of the present application, but it should be understood by those skilled in the art that the present application is not limited thereto, and that the present application is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the corresponding technical solutions. Are intended to be encompassed within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims (7)

1. A method of fault detection of a main propulsion diesel unit, characterized by a diesel unit applied to a target device, the method comprising:
acquiring a detection image of a part to be detected in the diesel engine unit;
determining the working scene of the component to be detected according to the detection image;
acquiring a corresponding fault detection model according to the working scene;
according to the fault detection model, combining the detection image and the working scene corresponding to the detection image, and determining the state of the part to be detected;
wherein, according to the detection image, determining the working scene of the component to be detected includes:
performing interference elimination processing on the detection image to obtain an intermediate detection image;
identifying a component factor and an environmental factor in the intermediate detection image;
determining the working scene according to the component factors and the environment factors;
wherein said determining said working scenario according to said component factor and said environmental factor comprises:
feature fusion is carried out on the component factors and the environment factors to obtain fusion features, wherein the calculation function of the environment factors can be expressed asT 1 And T 2 Respectively the different working time lengths of the parts to be detected, r 1 And r 2 Respectively T 1 、T 2 Quantized value of corresponding working data, c is r 1 And r 2 Obtaining an average confidence of accuracy, y being the degree of freedom [ r ] 1 ,r 2 ,(1-c)]A distribution function of time;
inputting the fusion characteristics into a working scene detection model, and outputting a target value;
determining a working scene corresponding to the target value according to the mapping relation between the target value and the working scene;
wherein, according to the fault detection model, combining the detection image and the working scene corresponding to the detection image, determining the state of the component to be detected includes:
acquiring a current working value and a first analysis result of the part to be detected according to the detection image;
determining a second analysis result according to the working scene;
processing the first analysis result and the second analysis result to determine the state of the part to be detected;
the method for performing interference elimination processing on the detection image to obtain an intermediate detection image comprises the following steps:
calculating an average of pixels in each of the detected imagesValue of Detecting the pixel size of the image to be P.Q, assuming P > Q, X i For the pixel value of the ith pixel point (i e 0, p q]) P and Q are the width, height, < >>For the average value of the pixels in each detection image, alpha is a correction factor, and A is a correction value;
and subtracting the average value of the pixels from the pixel value of each detection image to obtain the intermediate detection image.
2. The fault detection method of a main propulsion diesel unit according to claim 1, wherein the working scenario includes a common scenario, a standby scenario, and an emergency scenario.
3. The fault detection method of a main propulsion diesel engine unit according to claim 1, wherein the obtaining a second analysis result according to the working scenario includes:
according to the working scene, obtaining a standard working value of the part to be detected;
and comparing the current working value with the standard working value to obtain the second analysis result.
4. A method of fault detection of a main propulsion diesel unit according to any one of claims 1-3, wherein the method further comprises:
if the state of the part to be detected is abnormal, acquiring a correction value of the current working value;
and replacing the current working value with the correction value to correct the fault of the part to be detected.
5. A fault detection system for a main propulsion diesel unit, the system comprising:
the detection image acquisition module is used for acquiring detection images of components to be detected in the diesel engine set;
the working scene determining module is used for determining the working scene of the component to be detected according to the detection image;
the model acquisition module is used for acquiring a corresponding fault detection model according to the working scene;
the state detection module is used for determining the state of the part to be detected according to the fault detection model and combining the detection image and the working scene corresponding to the detection image;
the working scene determining module is further specifically configured to:
performing interference elimination processing on the detection image to obtain an intermediate detection image;
identifying a component factor and an environmental factor in the intermediate detection image;
determining the working scene according to the component factors and the environment factors;
the working scene determining module is further specifically configured to:
feature fusion is carried out on the component factors and the environment factors to obtain fusion features, wherein the calculation function of the environment factors can be expressed asT 1 And T 2 Respectively the different working time lengths of the parts to be detected, r 1 And r 2 Respectively T 1 、T 2 Quantized value of corresponding working data, c is r 1 And r 2 Obtaining an average confidence of accuracy, y being the degree of freedom [ r ] 1 ,r 2 ,(1-c)]A distribution function of time;
inputting the fusion characteristics into a working scene detection model, and outputting a target value;
determining a working scene corresponding to the target value according to the mapping relation between the target value and the working scene;
wherein, the state detection module is further specifically configured to:
acquiring a current working value and a first analysis result of the part to be detected according to the detection image;
determining a second analysis result according to the working scene;
processing the first analysis result and the second analysis result to determine the state of the part to be detected;
the working scene determining module is further specifically configured to:
calculating the average value of pixels in each detected image Detecting the pixel size of the image to be P.Q, assuming P > Q, X i For the pixel value of the ith pixel point (i e 0, p q]) P and Q are the width, height, < >>For the average value of the pixels in each detection image, alpha is a correction factor, and A is a correction value;
and subtracting the average value of the pixels from the pixel value of each detection image to obtain the intermediate detection image.
6. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when executed, implements the steps of the method according to any one of claims 1-4.
7. A computer device comprising a processor, a memory and a computer program stored on the memory, characterized in that the processor implements the steps of the method according to any of claims 1-4 when the computer program is executed.
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