CN111523522A - Intelligent operation and maintenance management method and management system for equipment - Google Patents
Intelligent operation and maintenance management method and management system for equipment Download PDFInfo
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- CN111523522A CN111523522A CN202010601754.8A CN202010601754A CN111523522A CN 111523522 A CN111523522 A CN 111523522A CN 202010601754 A CN202010601754 A CN 202010601754A CN 111523522 A CN111523522 A CN 111523522A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/41—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items
- G06V20/42—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items of sport video content
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- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
- G06Q10/0833—Tracking
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/46—Extracting features or characteristics from the video content, e.g. video fingerprints, representative shots or key frames
Abstract
The invention discloses an intelligent operation and maintenance management method for equipment, which comprises the steps of tracking and monitoring logistics equipment in operation in a warehouse, acquiring a video image sequence of gait of the logistics equipment, extracting gait features of the logistics equipment from the video image sequence, wherein the gait is posture and/or behavior features of the logistics equipment in operation, generating a first feature state parameter set according to continuous gait feature change of the object taking flow equipment, and judging the operation state of the logistics equipment according to comparative analysis of the first feature state parameter set and a preset state parameter set. The logistics equipment is remotely monitored by the operation and maintenance personnel conveniently, the daily operation and maintenance workload of the operation and maintenance personnel is reduced, and the overall operation and maintenance efficiency of the material equipment is improved.
Description
Technical Field
The invention relates to the field of intelligent warehouse logistics, in particular to an intelligent operation and maintenance management method and system applied to warehouse logistics equipment.
Background
With the development of domestic economy, especially the rapid advance of logistics, more and more enterprises are undergoing the process of the development from the traditional flat warehouse to the stereoscopic warehouse. The intelligent warehousing system has the characteristics of high space utilization rate, strong warehousing and ex-warehouse capacity, contribution to enterprise implementation of modern management by adopting a computer for control management and the like, and becomes an indispensable warehousing technology for enterprise logistics and production management. Meanwhile, intelligent warehousing plays an important role in the whole logistics link, and in a supply chain system, warehousing is an important transfer link connecting upstream manufacturing and downstream distribution and is an indispensable link in the whole system. In the intelligent warehousing management, a plurality of advanced concepts and technical means are integrated, so that the intelligent warehousing management system is gradually developed into a modern warehousing system integrating mechanization, automation, integration and intelligence from the initial manual warehousing management.
With the improvement of the automation degree of the intelligent warehousing system, more and more related operating devices are provided, and how to use and manage the devices is a problem which cannot be ignored. At present, the operation and maintenance mode that domestic enterprise adopted mostly uses regularly to patrol and examine as the main, and equipment operation and maintenance work requires higher to operation and maintenance personnel, and operation and maintenance personnel need very long training cycle just can post, and operation and maintenance personnel flow in addition greatly, lead to that operation and maintenance input cost is higher, and operation and maintenance time span is big, and the human resource input is surplus, a great deal of problem such as whole operation and maintenance efficiency is not high. In addition, in the existing intelligent warehousing system, when equipment fails, manual item-by-item monitoring devices are required to be checked, one of the equipment fails, each piece of equipment needs to be checked item by item, the locating efficiency of the failed equipment is low, the checking time is long, and the working efficiency of the intelligent warehousing system is seriously influenced.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides an intelligent operation and maintenance management method for equipment, which can be used for warehouse logistics equipment and comprises the following steps:
s1, tracking and monitoring the logistics equipment in the warehouse;
s2, acquiring a video image sequence of the gait of the logistics equipment, and extracting the gait characteristics of the logistics equipment from the video image sequence, wherein the gait is the posture and/or behavior characteristics of the logistics equipment during operation;
s3, generating a first characteristic state parameter set according to the continuous gait characteristic change of the logistics equipment;
and S4, judging the operation state of the logistics equipment according to the comparison analysis of the first characteristic state parameter set and a preset state parameter set.
Preferably, step S2 specifically includes: and identifying the composition of each mechanical part of the logistics equipment in the video image sequence, and calculating the posture and/or behavior characteristics of each mechanical part.
Preferably, step S2 specifically includes:
s21, identifying logistics equipment identity information in the video image sequence;
s22, acquiring the corresponding mechanical component composition, the identification characteristics and the detection parameters of each mechanical component in a database according to the logistics equipment identity information;
and S23, screening the corresponding mechanical parts in the video image sequence according to the identification features, and measuring and acquiring the detection parameters of the mechanical parts.
Preferably, the mechanical parts of the logistics apparatus include, but are not limited to, a pallet, a fork, a lift pallet, or a walking device.
Preferably, the detection parameter is a swing angle of the mechanical component with respect to a vertical direction.
Preferably, the walking device is a sky rail or a ground rail, and the detection parameter includes, but is not limited to, a relative position between the shelf and the sky rail, a relative position between the shelf and the ground rail, or a tilt angle of the shelf.
Preferably, the step S3 includes: and generating a plurality of first characteristic state parameter sets according to the relative position of the goods shelf and the sky rail, the relative position of the goods shelf and the ground rail or the inclination angle of the goods shelf of each acquisition time acquired from the video image sequence, wherein the first characteristic state parameter sets comprise a change curve of the relative position of the goods shelf and the sky rail, a change curve of the relative position of the goods shelf and the ground rail or a change curve of the inclination angle of the goods shelf.
Preferably, the step S4 further includes: and judging the operating state of the logistics equipment according to the comparison analysis of a second characteristic state parameter set and a preset state parameter set, wherein the second characteristic state parameter set comprises the operating speed of the logistics equipment in each acquisition time.
The invention also discloses an intelligent operation and maintenance management system for equipment, which is used for the warehouse logistics equipment and comprises the following components: the image acquisition device is used for acquiring video images of logistics equipment in operation in the warehouse; the monitoring device comprises a memory, a processor and a computer program which is stored in the memory and can run on the processor, wherein the processor realizes the steps of any one of the above equipment intelligent operation and maintenance management methods when executing the computer program.
The invention also discloses a computer readable storage medium, which stores a computer program, and the computer program realizes the steps of the intelligent operation and maintenance management method of the equipment when being executed by the processor.
The method comprises the steps of tracking and monitoring logistics equipment in operation in a warehouse by using image monitoring equipment to obtain a video image sequence of the gait of the logistics equipment, then extracting the gait characteristics of the logistics equipment from the video image sequence, and generating a first characteristic state parameter set according to the continuous gait characteristic change of the logistics equipment; and comparing and analyzing the first characteristic state parameter set and a preset state parameter set to judge the operation state of the logistics equipment, and acquiring whether the operation of the related logistics equipment has a fault or does not operate according to a preset state. Instruct fortune dimension personnel in time to maintain logistics equipment, the fortune dimension personnel of being convenient for carry out remote monitoring to logistics equipment, have reduced the daily fortune dimension's of fortune dimension personnel work load, have improved the efficiency of whole fortune dimension, and on the other hand has got rid of personnel's discernment difference through machine identification, has reduced the professional knowledge requirement to daily managers, and fortune dimension personnel need not to carry out long-time training and just can go on duty to stereoscopic warehouse fortune dimension management's cost has been reduced. The problems that most operation and maintenance modes adopted by enterprises at present mainly use periodic inspection, equipment operation and maintenance work has high requirements on operation and maintenance personnel, operation and maintenance input cost is high, operation and maintenance time span is large, human resource input is excessive, and overall operation and maintenance efficiency is not high are solved. Meanwhile, the problems that manual item-by-item monitoring devices are required to be checked when equipment fails in the existing intelligent warehousing system, item-by-item checking needs to be carried out on each piece of equipment when one piece of equipment fails, positioning efficiency of failed equipment is low, and checking time is long are solved.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
fig. 1 is a schematic flow chart of the intelligent operation and maintenance management method for devices disclosed in this embodiment.
Fig. 2 is a schematic flowchart of step S2 disclosed in this embodiment.
Fig. 3 is a schematic block diagram of the intelligent operation and maintenance management system for devices disclosed in this embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the drawings of the embodiments of the present invention. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the described embodiments of the invention without any inventive step, are within the scope of protection of the invention.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", and the like, indicate orientations and positional relationships based on those shown in the drawings, and are used only for convenience of description and simplicity of description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be considered as limiting the present invention.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
In the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," "secured," and the like are to be construed broadly and can, for example, be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In the present invention, unless otherwise expressly stated or limited, "above" or "below" a first feature means that the first and second features are in direct contact, or that the first and second features are not in direct contact but are in contact with each other via another feature therebetween. Also, the first feature being "on," "above" and "over" the second feature includes the first feature being directly on and obliquely above the second feature, or merely indicating that the first feature is at a higher level than the second feature. A first feature being "under," "below," and "beneath" a second feature includes the first feature being directly under and obliquely below the second feature, or simply meaning that the first feature is at a lesser elevation than the second feature.
Unless defined otherwise, technical or scientific terms used herein shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention belongs. The use of "first," "second," and similar terms in the description and claims of the present application do not denote any order, quantity, or importance, but rather the terms are used to distinguish one element from another. Also, the use of the terms "a" or "an" and the like do not denote a limitation of quantity, but rather denote the presence of at least one.
At present, maintenance to all kinds of automatic logistics equipment in the warehouse is mainly based on regular inspection, and this type of mode can lead to the fortune dimension input cost higher, and fortune dimension time span is big, and whole fortune dimension efficiency is not high. In order to more effectively manage the automatic stereoscopic warehouse, the whole operation and maintenance efficiency is improved, and the time and space cost consumed by operation and maintenance personnel in the operation and maintenance process is reduced. The embodiment of the invention provides an intelligent operation and maintenance management method of equipment, which can reasonably utilize limited resources of a warehouse, monitor the operation states of various logistics equipment such as an automatic forklift, an automatic material handling vehicle and a conveying vehicle lamp in real time and provide effective data to realize accurate operation and maintenance in the operation and maintenance process, can be used for various intelligent storage logistics equipment, particularly various stackers and forklifts, and can be widely applied to the fields of intelligent manufacturing, factory digital transformation and industry 4.0. As shown in fig. 1, the intelligent operation and maintenance management method for a device may specifically include:
and step S1, tracking and monitoring the logistics equipment in operation in the warehouse.
And tracking and shooting logistics equipment running in the warehouse through monitoring camera equipment installed in the remote control warehouse. In some embodiments, in this step, the identification and analysis may also be performed according to the appearance or the identification mark of the logistics apparatus in the monitoring graph, so as to determine the identity information of the logistics apparatus.
Step S2, acquiring a video image sequence of the gait of the logistics equipment, and extracting the gait characteristics of the logistics equipment from the video image sequence, wherein the gait characteristics are the posture and/or behavior characteristics of the logistics equipment during operation.
In this embodiment, the gait may specifically include a posture characteristic and a behavior characteristic of the logistics apparatus during operation. Specifically, the logistics equipment drives the logistics equipment through a motor or a servo mechanism to move a series of continuous activities, so that the logistics equipment presents posture characteristics and behavior characteristics in the process of moving along a certain direction.
In specific application, the warehousing operation and maintenance management system can call monitoring camera equipment to track and shoot video image sequences of all logistics equipment running in a warehouse, preprocesses called video images of the logistics equipment through an image algorithm, and extracts gait features of the logistics equipment from the video image sequences. Specifically, the attitude and/or behavior characteristics of each mechanical component of the logistics equipment can be calculated by identifying the composition of each mechanical component in the video image sequence. As shown in fig. 2, the step S2 may specifically include:
and step S21, identifying the logistics equipment identity information in the video image sequence.
The physical distribution equipment appearance in the image can be identified and analyzed by the physical distribution equipment image information acquired in the aforementioned step S1, specific identification information on the physical distribution equipment body is extracted, and the physical distribution equipment database is retrieved according to the identification information to acquire the corresponding physical distribution equipment identity information. The physical characteristics of the logistics equipment can be identified from the monitoring image. The physical distribution equipment appearance characteristic can be a specific appearance characteristic, and the specific appearance characteristic is an area with brightness contrast ratio exceeding a specific threshold value with other peripheral equipment areas or a protrusion and main equipment area part. The physical distribution equipment identity information can be obtained by identifying part of obvious appearance characteristics such as an engine body outline or a specific part such as a bottom walking mechanism or a top mechanism and the like as physical distribution equipment appearance characteristics and comparing and screening in a physical distribution equipment database according to the appearance characteristics. In addition, each monitoring camera device can be arranged on different passing paths of each logistics device, so that different camera devices respectively aim at different logistics devices, the identity information of the logistics devices can be judged and determined according to the camera device information of the specific area shot and captured by the logistics devices, the specific logistics devices are captured by the specific camera devices, the video image sequence tracked and shot by the camera devices can directly correspond to the logistics devices, the early identity recognition and the identity information acquisition of the logistics devices in the video images can be reduced or not needed, the image processing workload is reduced, the problem of identity information recognition errors among the logistics devices with similar shapes is avoided, and therefore the subsequent gait feature recognition errors are caused.
In other embodiments, some salient mechanical component features of the logistics apparatus in the video image can also be identified through image algorithms, and the mechanical component of the logistics apparatus includes, but is not limited to, a shelf, a fork, a lifting platform or a walking device, wherein the walking device can be a sky rail or a ground rail. And identifying the identity information of the logistics equipment to which the monitoring image belongs by identifying the extracted specific mechanical part information from the monitoring image. The identity information of the logistics equipment comprises information such as the name and the model of the logistics equipment.
And step S22, acquiring the corresponding mechanical component composition, the identification characteristics and the detection parameters of each mechanical component in the database according to the logistics equipment identity information.
Specifically, a logistics equipment database is established in the warehouse operation and maintenance management system, and the database contains all information of the warehouse logistics equipment to be monitored. In the database, various parameter labels of each warehouse logistics device are stored, wherein the parameter labels can comprise product models, mechanical component parts, identification characteristics and relative positions of single mechanical component parts and detection parameters of the mechanical component parts. And calling the corresponding mechanical component composition, the identification characteristics of the mechanical components and the detection parameters corresponding to the identification characteristics from the database according to the identification information of the logistics equipment acquired in the previous step. Wherein the mechanical parts of each logistics apparatus can include, but are not limited to, a shelf, a fork, a lift truck, or a walking device. And the walking device can be a sky rail or a ground rail.
In some embodiments, the detected parameter of each mechanical component may be a swing angle of the mechanical component relative to the vertical direction, such as a swing angle or an offset angle of a mechanical component such as a rack, a fork, or a lift truck relative to the vertical direction. In addition, some warehouse logistics equipment have a traveling device including a top rail or a bottom rail, and the corresponding detection parameters may also include, but are not limited to, one or more of the relative position of the rack and the top rail, the relative position of the rack and the bottom rail, or the inclination angle of the rack.
And step S23, screening the corresponding mechanical parts in the video image sequence according to the identification features, and measuring and acquiring the detection parameters of the mechanical parts.
The detection parameters include, but are not limited to, the relative position of the shelf and the sky rail, the relative position of the shelf and the ground rail, or the inclination angle of the shelf. Specifically, the positions of the components of the equipment such as the goods shelf, the fork, the lifting goods carrying platform or the walking device can be extracted according to the mechanical components of the logistics equipment. And calculating the kinematic characteristics of each position, such as the swing angle relative to the vertical direction, so as to perform classification and identification of the gait, wherein the classification and identification comprises the comparative analysis of detection parameters such as the change of a sky rail, the change of the inclination angle of the goods shelf in different states of goods and/or goods absence, the horizontal change of a ground rail and the like. In this embodiment, the method may further include: screening corresponding cargo carrying platforms in the video image sequence, wherein the cargo carrying platforms are goods shelves, forks or lifting cargo carrying platforms, and judging whether goods exist above the cargo carrying platforms or not; and respectively acquiring the swinging angles of the cargo platform in the cargo state and the cargo state relative to the vertical direction.
In some embodiments, the image recognition algorithm may screen out the corresponding mechanical component region in the video image sequence according to the identification feature of the mechanical component to be detected of the logistics equipment and the corresponding detection parameter obtained in the database, and then measure and obtain the specific value of the detection parameter from the video image sequence according to the corresponding detection parameter. In the present embodiment, the detection parameter is a swing angle of the mechanical component with respect to the vertical direction. In other specific embodiments, the camera device can also be controlled to perform multi-angle shooting to select a proper view angle picture, and more accurate specific values of the detection parameters required by the mechanical component can be obtained according to an image processing algorithm.
In step S3, a first characteristic state parameter set is generated according to the obtained continuous gait characteristic change of the stream device. The steps may specifically include: and acquiring the relative position of the goods shelf and the sky rail, the relative position of the goods shelf and the ground rail or the inclination angle of the goods shelf at each acquisition time according to the video image sequence to generate a plurality of first characteristic state parameter sets, wherein the first characteristic state parameter sets comprise a change curve of the relative position of the goods shelf and the sky rail, a change curve of the relative position of the goods shelf and the ground rail or a change curve of the inclination angle of the goods shelf.
For example, when the posture characteristic is a rack shift amount, a swing angle of the rack with respect to the vertical direction may be acquired from the video image. In the continuous video image sequence, continuous numerical values of the swing angle of the mechanical component such as the shelf and the like relative to the vertical direction in the time dimension are obtained through the same method, and a graph of the angle change is generated by the numerical values.
Specifically, a video image sequence of the gait is obtained through detection and tracking, and gait features of the logistics equipment are extracted through preprocessing analysis to form a curve graph. Namely, gait movement in the image sequence is subjected to key processing in the early stage of gait recognition, such as movement detection, operation and maintenance segmentation, feature extraction and the like. And obtaining gait characteristics through a gait recognition algorithm. For example, motion and dynamics based methods aim at constructing a 2D or 3D model of the moving structure of the logistics apparatus, characterizing the gait pattern of the logistics apparatus by extracting image features and mapping them onto the model structure. Such as acquiring gait characteristics from frequency components of the tilt angle signal thereof. Some basic changes of the logistics equipment are detected according to the kinematic parameters to form a graph. Including temporal parameters, distance parameters, time-space parameters.
And step S4, judging the operation state of the logistics equipment according to the comparison analysis of the first characteristic state parameter set and a preset state parameter set. The first characteristic state parameter set has newly acquired gait characteristics, and the preset state parameter set has the gait characteristics of the normal working state of the logistics equipment stored in the gait database. And comparing and identifying the newly acquired gait features with the gait features of the gait database, displaying the two gait graphs together, and performing pre-alarming or alarming if no match exists. If the matching exists, the monitoring camera equipment continues to carry out gait acquisition. In some embodiments, a certain parameter curve in the first characteristic state parameter set and a corresponding parameter curve in a preset state parameter set may be subjected to fitting analysis according to a related curve fitting function, and a fitting result is output. The fitting result is 0, which indicates the normal operation state of the logistics equipment and no need of maintenance in the near term. The fitting result is 1, which indicates that the logistics equipment is not in a normal operation state and needs to be maintained. In other embodiments, a certain parameter curve in the first characteristic state parameter set and a corresponding parameter curve in a preset state parameter set are subjected to fitting analysis, and a fitting result is output. The fitting result may be in other forms. And according to the fitting result, corresponding to a plurality of states of the logistics equipment. The plurality of conditions include full normal operation, substantially normal operation, recent need for service, immediate decommissioning, and the like.
Wherein the step S4 may further include: and judging the operating state of the logistics equipment according to the comparison analysis of a second characteristic state parameter set and a preset state parameter set, wherein the second characteristic state parameter set comprises the operating speed of the logistics equipment in each acquisition time. The preset state parameter set comprises a corresponding running speed range of the logistics equipment in a normal working state. And when the running speed of the logistics equipment at the acquisition time exceeds the running speed range in the preset state parameter set, carrying out early warning or alarming operation.
The method comprises the steps of tracking and monitoring logistics equipment in operation in a warehouse by using image monitoring equipment to obtain a video image sequence of the gait of the logistics equipment, then extracting the gait characteristics of the logistics equipment from the video sequence, and generating a first characteristic state parameter set according to the continuous gait characteristic change of the logistics equipment; and comparing and analyzing the first characteristic state parameter set and a preset state parameter set to judge the operation state of the logistics equipment, and acquiring whether the operation of the related logistics equipment has a fault or does not operate according to a preset state. Instruct fortune dimension personnel in time to maintain logistics equipment, the fortune dimension personnel of being convenient for carry out remote monitoring to logistics equipment, have reduced the daily fortune dimension's of fortune dimension personnel work load, have improved the efficiency of whole fortune dimension, and on the other hand has got rid of personnel's discernment difference through machine identification, has reduced the professional knowledge requirement to daily managers, and fortune dimension personnel need not to carry out long-time training and just can go on duty to stereoscopic warehouse fortune dimension management's cost has been reduced. The problems that most operation and maintenance modes adopted by enterprises at present mainly use periodic inspection, equipment operation and maintenance work has high requirements on operation and maintenance personnel, operation and maintenance input cost is high, operation and maintenance time span is large, human resource input is excessive, and overall operation and maintenance efficiency is not high are solved. Meanwhile, the problems that manual item-by-item monitoring devices are required to be checked when equipment fails in the existing intelligent warehousing system, item-by-item checking needs to be carried out on each piece of equipment when one piece of equipment fails, positioning efficiency of failed equipment is low, and checking time is long are solved. In particular to operation, maintenance and management of a traditional stacker, which tracks the stacker through a camera and then obtains an angle change track of the stacker during operation from a tracking result as a key index of dynamic characteristics for operation, maintenance and management. Therefore, the effect of immediately maintaining the stacker is achieved.
In other embodiments, as shown in fig. 3, an embodiment of the present invention further discloses an operation and maintenance management system for warehouse logistics equipment, including: the image acquisition device 2 is used for acquiring video images of logistics equipment in operation in the warehouse; the monitoring apparatus 1 includes a memory 11, a processor 12, and a computer program stored in the memory 11 and executable on the processor, and the processor executes the computer program to implement the steps of the device intelligent operation and maintenance management method described in the embodiments.
The warehouse logistics equipment operation and maintenance management device can include, but is not limited to, a processor and a memory. It will be understood by those skilled in the art that the schematic diagram is merely an example of the operation and maintenance management device of the warehouse logistics equipment, and does not constitute a limitation on the operation and maintenance management device of the warehouse logistics equipment, and may include more or less components than those shown in the figure, or combine some components, or different components, for example, the operation and maintenance management device of the warehouse logistics equipment may further include an input and output device, a network access device, a bus, etc.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor, and the processor is a control center of the warehouse logistics equipment operation and maintenance management device, and various interfaces and lines are used to connect various parts of the whole warehouse logistics equipment operation and maintenance management device.
The memory can be used for storing the computer program and/or the module, and the processor realizes various functions of the warehouse logistics equipment operation and maintenance management device equipment by running or executing the computer program and/or the module stored in the memory and calling data stored in the memory. The memory may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function, and the like, and the memory may include a high speed random access memory, and may further include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a flash memory Card (FlashCard), at least one magnetic disk storage device, a flash memory device, or other volatile solid state storage device.
The data management method of the warehouse logistics equipment operation and maintenance management device can be stored in a computer readable storage medium if the data management method is realized in the form of a software functional unit and is sold or used as an independent product. Based on such understanding, all or part of the flow in the method according to the above embodiments may also be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of the above embodiments of the method for intelligent operation and maintenance management of each device. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
In summary, the above-mentioned embodiments are only preferred embodiments of the present invention, and all equivalent changes and modifications made in the claims of the present invention should be covered by the claims of the present invention.
Claims (10)
1. An intelligent operation and maintenance management method for equipment is used for warehouse logistics equipment, and is characterized by comprising the following steps:
s1, tracking and monitoring the logistics equipment in the warehouse;
s2, acquiring a video image sequence of the gait of the logistics equipment, and extracting the gait characteristics of the logistics equipment from the video image sequence, wherein the gait is the posture and/or behavior characteristics of the logistics equipment during operation;
s3, generating a first characteristic state parameter set according to the continuous gait characteristic change of the logistics equipment;
and S4, judging the operation state of the logistics equipment according to the comparison analysis of the first characteristic state parameter set and a preset state parameter set.
2. The intelligent operation and maintenance management method for equipment according to claim 1, wherein: the step S2 specifically includes:
and identifying the composition of each mechanical part of the logistics equipment in the video image sequence, and calculating the posture and/or behavior characteristics of each mechanical part.
3. The method for intelligent operation and maintenance management of equipment according to claim 2, wherein the step S2 specifically includes:
s21, identifying logistics equipment identity information in the video image sequence;
s22, acquiring the corresponding mechanical component composition, the identification characteristics and the detection parameters of each mechanical component in a database according to the logistics equipment identity information;
and S23, screening the corresponding mechanical parts in the video image sequence according to the identification features, and measuring and acquiring the detection parameters of the mechanical parts.
4. The intelligent operation and maintenance management method for equipment according to claim 3, wherein: the mechanical parts of the logistics apparatus include, but are not limited to, a pallet, a fork, a lifting platform or a walking device.
5. The intelligent operation and maintenance management method for equipment according to claim 4, wherein: the detection parameter is a swing angle of the mechanical part relative to the vertical direction.
6. The intelligent operation and maintenance management method for equipment according to claim 4, wherein: the walking device is a sky rail or a ground rail, and the detection parameter includes, but is not limited to, a relative position between the shelf and the sky rail, a relative position between the shelf and the ground rail, or a shelf inclination angle.
7. The intelligent operation and maintenance management method for equipment according to claim 6, wherein the step S3 includes:
and generating a plurality of first characteristic state parameter sets according to the relative position of the goods shelf and the sky rail, the relative position of the goods shelf and the ground rail or the inclination angle of the goods shelf of each acquisition time acquired from the video image sequence, wherein the first characteristic state parameter sets comprise a change curve of the relative position of the goods shelf and the sky rail, a change curve of the relative position of the goods shelf and the ground rail or a change curve of the inclination angle of the goods shelf.
8. The intelligent operation and maintenance management method for equipment according to claim 7, wherein the step S4 further includes:
and judging the operating state of the logistics equipment according to the comparison analysis of a second characteristic state parameter set and a preset state parameter set, wherein the second characteristic state parameter set comprises the operating speed of the logistics equipment in each acquisition time.
9. The utility model provides an equipment intelligence operation and maintenance management system for storage logistics equipment which characterized in that includes:
the image acquisition device is used for acquiring video images of logistics equipment in operation in the warehouse;
monitoring device comprising a memory, a processor and a computer program stored in said memory and executable on said processor, said processor implementing the steps of the method according to any of claims 1-8 when executing said computer program.
10. A computer-readable storage medium storing a computer program, characterized in that: the computer program realizing the steps of the method according to any of claims 1-8 when executed by a processor.
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