CN111736556A - Warehousing operation and maintenance management system applied to intelligent manufacturing - Google Patents
Warehousing operation and maintenance management system applied to intelligent manufacturing Download PDFInfo
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Abstract
The invention discloses a warehousing operation and maintenance management system applied to intelligent manufacturing, which is characterized in that a monitoring server is used for collecting motion control pulse values output by a PLC (programmable logic controller) of logistics equipment in real time, corresponding motion direction pulse curve graphs are respectively generated according to the motion directions of the logistics equipment, the generated specific motion direction pulse curve graphs are compared with preset pulse curves of the motion directions, and an alarm is given if the generated specific motion direction pulse curve graphs deviate from the preset pulse curve specific threshold values. The system can simultaneously monitor a plurality of logistics devices in the large warehouse in real time, and quickly and accurately discover the logistics devices in abnormal working states.
Description
Technical Field
The invention relates to the field of intelligent warehouse logistics, in particular to a warehouse operation and maintenance management system applied to intelligent manufacturing.
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 a warehousing operation and maintenance management system applied to intelligent manufacturing, which comprises: the system comprises at least one logistics device working in a specific area and provided with a PLC controller, and a monitoring server connected with the PLC controller of each logistics device; the monitoring server is configured to collect motion control pulse values output by a PLC (programmable logic controller) of the logistics equipment in real time, respectively generate corresponding motion direction pulse curve graphs according to the motion directions of the logistics equipment, compare the generated specific motion direction pulse curve graphs with preset pulse curves of the motion directions, and give an alarm if the generated specific motion direction pulse curve graphs deviate from the preset pulse curve specific threshold.
Preferably, the logistics equipment is logistics equipment.
Preferably, the monitoring server is configured to extract motion control pulse values of the traveling mechanism, the fork mechanism and/or the lifting mechanism respectively according to the mechanical composition of the logistics equipment, wherein the motion control pulse values are values generated in the process of driving the logistics equipment to move along a specific direction through a motor or a servo mechanism; and respectively storing the collected motion control pulse values into each motion part data group in a database according to the mechanical composition class.
Preferably, the motion control pulse values comprise pulse values at a start position of the direction of motion and/or pulse values at all valid cargo spaces between the start position and an end position.
Preferably, the motion control pulse value further includes an acceleration generated along the motion direction, and/or a total time of the operation in the motion direction.
Preferably, the monitoring server is configured to compare the generated motion direction pulse curve with a preset pulse curve of the motion direction, divide the generated motion direction pulse curve into a first state and a second state according to a deviation value of the generated motion direction pulse curve and the preset pulse curve, and send a corresponding notification when the generated motion direction pulse curve and the preset pulse curve are judged to be in the second state.
Preferably, the system further comprises a video monitoring device connected with the monitoring server, wherein the video monitoring device is used for acquiring video images of the logistics equipment working in a specific area; the monitoring server is configured to acquire a video image sequence from the video monitoring device in a working area of the logistics equipment when pulse value data of one movement direction of the logistics equipment is in a second state, extract gait features of the logistics equipment from the video sequence, generate a first feature state parameter set according to continuous gait feature changes of the logistics equipment, and judge the operation state of the logistics equipment according to comparative analysis of the first feature state parameter set and a preset state parameter set, wherein the gait is the posture and/or behavior features of the logistics equipment during operation;
preferably, the monitoring server is configured to identify the composition of each mechanical component of the logistics equipment in the video image sequence, and calculate the posture and/or behavior characteristics of each mechanical component.
Preferably, the monitoring server is configured to identify the logistics equipment identity information in the video image sequence, obtain the corresponding mechanical component composition and the identification characteristics and detection parameters of each mechanical component in the database according to the logistics equipment identity information, obtain the corresponding mechanical component in the video image sequence according to the identification characteristics, and measure and obtain the detection parameters of the corresponding mechanical component.
The warehousing operation and maintenance management system applied to intelligent manufacturing uses the monitoring server to collect motion control pulse values output by the PLC of the logistics equipment in real time, respectively generates corresponding motion direction pulse curve graphs according to the motion directions of the logistics equipment, compares the generated specific motion direction pulse curve graphs with preset pulse curves of the motion directions, and gives an alarm if the generated specific motion direction pulse curve graphs deviate from the preset pulse curve specific threshold. The instant monitoring and maintenance condition is achieved according to the change of the curve diagram track, the simultaneous real-time monitoring on a plurality of logistics devices in a large warehouse can be achieved, the logistics devices in abnormal working states can be found quickly and accurately, then operation and maintenance personnel are guided to maintain the logistics devices in time, the operation and maintenance personnel can carry out remote monitoring on the logistics devices conveniently, the daily operation and maintenance workload of the operation and maintenance personnel is reduced, and the overall operation and maintenance efficiency is improved.
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 structural diagram of a warehousing operation and maintenance management system applied to intelligent manufacturing according to the 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 a warehousing operation and maintenance management system which can reasonably utilize limited resources of a warehouse and is applied to intelligent manufacturing, can be applied to various intelligent warehousing 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 warehousing operation and maintenance management system applied to intelligent manufacturing comprises at least one logistics device 2 working in a specific area and provided with a PLC controller, and a monitoring server 1 connected with the PLC controller of each logistics device 2; the monitoring server 1 is configured to collect motion control pulse values output by the PLC controllers of the logistics devices 2 in real time, generate corresponding motion direction pulse curve graphs according to the motion directions of the logistics devices 2, compare the generated specific motion direction pulse curve graphs with preset pulse curves of the motion directions, and alarm if the generated specific motion direction pulse curve graphs deviate from the preset pulse curve specific threshold.
Specifically, in this embodiment, the logistics device is a logistics device, and may be other logistics devices installed with a PLC controller. The monitoring server collects the motion control pulse value output by the logistics equipment in real time through interaction with a PLC in the logistics equipment in operation. In the intelligent monitoring method of the logistics equipment, a monitoring server or other upper computers are connected with controllers in the logistics equipment through industrial networks such as a wireless network and the like. The controllers of the logistics devices can adopt PLCs, and the PLCs of the logistics devices exchange information with the upper computer and other intelligent devices through an industrial network to form a unified whole and realize the decentralized and centralized control. When the intelligent monitoring method of the logistics equipment is implemented, the motion control pulse values output by the PLC of each logistics equipment are collected in real time through interaction of the monitoring server or other upper computers and the PLC in each logistics equipment in operation.
Specifically, the monitoring server is configured to respectively extract motion control pulse values of the walking mechanism, the fork mechanism and/or the lifting mechanism according to the mechanical composition of the logistics equipment, wherein the motion control pulse values are values generated in the process that the logistics equipment is driven by a motor or a servo mechanism to move along a specific direction; and respectively storing the collected motion control pulse values into each motion part data group in a database according to the mechanical composition class.
Furthermore, the monitoring server extracts the pulse value data collected in the database in real time, and generates corresponding motion direction pulse curve graphs according to the motion directions of the logistics equipment respectively. Wherein the motion control pulse values may comprise pulse values at a start position of the direction of motion and/or pulse values at all valid cargo levels between the start position and an end position. Or the motion control pulse value may also include the resulting acceleration along the direction of motion, and/or the total time of the run for the direction of motion.
The monitoring server is also configured to compare the generated pulse curve graph with a preset pulse curve of the motion direction, and alarm if the generated pulse curve graph deviates from an original preset pulse curve specific threshold value. Specifically, the monitoring server is further configured to compare the generated motion direction pulse curve with a preset pulse curve of the motion direction, divide the generated motion direction pulse curve into a first state and a second state according to the deviation value of the generated motion direction pulse curve and the preset pulse curve, and send a corresponding notification when the motion direction pulse curve is judged to be in the second state. The deviation degree of the two curves can be divided into three levels, such as a normal state, an early warning state and a state needing maintenance, and specifically, a first specific threshold and a second specific threshold can be set, the logistics equipment is judged to be in the normal state when the deviation value is smaller than the first specific threshold, the logistics equipment is judged to be in the early warning state when the deviation value is larger than the first specific threshold and smaller than the second specific threshold, and the logistics equipment is judged to be in the state needing maintenance when the deviation value is larger than the second specific threshold. The first specific threshold value may be a maximum deviation value from a normal pulse value, which is allowed when the stacking apparatus is operated in each movement direction in a good working state and in a maintenance-free state, and the maximum deviation value may be determined manually according to daily maintenance experience of each apparatus. The second specific threshold value may be a maximum deviation value from a normal pulse value, which is allowed when the stacking apparatus operates in each moving direction under a normal operating condition, and when the deviation value is exceeded, it indicates that the stacking apparatus is in a state where there is an apparatus failure and maintenance is required immediately, and the maximum deviation value may be artificially determined according to daily maintenance experience of each apparatus. The first state is a normal state, and the second state can be an early warning state and a state needing maintenance. Or the first state can be set to be a normal state and an early warning state, the second state is a maintenance-required state, and only the logistics equipment sends out an alarm signal when entering the maintenance-required state.
The warehousing operation and maintenance management system applied to intelligent manufacturing uses the monitoring server to collect motion control pulse values output by the PLC of the logistics equipment in real time, respectively generates corresponding motion direction pulse curve graphs according to the motion directions of the logistics equipment, compares the generated specific motion direction pulse curve graphs with preset pulse curves of the motion directions, and gives an alarm if the generated specific motion direction pulse curve graphs deviate from the preset pulse curve specific threshold. This system is through reaching the real-time supervision maintenance condition according to the change of curve chart orbit, can realize carrying out simultaneous real time monitoring to a plurality of logistics equipment in the large-scale warehouse simultaneously to quick accurate discovery wherein is in the logistics equipment of abnormal operating condition, then instructs fortune dimension personnel in time to carry out maintenance to logistics equipment, and the fortune dimension personnel of being convenient for carry out remote monitoring to logistics equipment, have reduced the work load of the daily fortune dimension of fortune dimension personnel, have improved the efficiency of whole fortune dimension.
In other embodiments, the warehousing operation and maintenance management system applied to intelligent manufacturing further comprises a video monitoring device 3 connected to the monitoring server, wherein the video monitoring device 3 is used for acquiring video images of logistics equipment working in a specific area; the monitoring server is configured to acquire a video image sequence from the video monitoring device in a working area of the logistics equipment when pulse value data of one movement direction of the logistics equipment is in a second state, extract gait features of the logistics equipment from the video sequence, generate a first feature state parameter set according to continuous gait feature changes of the logistics equipment, and judge the operation state of the logistics equipment according to comparative analysis of the first feature state parameter set and a preset state parameter set, wherein the gait is the posture and/or behavior features of the logistics equipment during operation. The gait may specifically include a posture characteristic and a behavior characteristic of the logistics apparatus while operating. 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. Specifically, the logistics equipment running in the warehouse is tracked and shot 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.
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 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. Further, the monitoring server of the warehousing operation and maintenance management system is also configured to identify the logistics equipment identity information in the video image sequence. The appearance of the logistics equipment in the image can be identified and analyzed through the acquired image information of the logistics equipment, specific identification information on the logistics equipment body is extracted, and the corresponding logistics equipment identity information is acquired by retrieving the logistics equipment database according to the identification 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, the monitoring server may also identify some salient mechanical component features of the logistics apparatus in the video image through an image algorithm, 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 may 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.
In this embodiment, the monitoring server is configured to identify physical distribution equipment identity information in a video image sequence, obtain a mechanical component composition corresponding to the physical distribution equipment identity information and identification features and detection parameters of each mechanical component in a database according to the physical distribution equipment identity information, obtain a corresponding mechanical component in the video image sequence according to the identification features, and measure and obtain the detection parameters of the corresponding mechanical component. 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.
The monitoring server is also configured to screen the corresponding mechanical parts in the video image sequence according to the identification features, and measure and acquire 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 monitoring server may screen out, according to the identification features of the mechanical components to be detected of the logistics equipment and the corresponding detection parameters obtained in the database, the corresponding mechanical component regions in the video image sequence through an image identification algorithm, and then measure and obtain specific values of the detection parameters from the video image sequence according to the corresponding detection parameters. 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.
The monitoring server is further configured to generate a first characteristic state parameter set according to the continuous gait characteristic change of the logistics equipment, and determine 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. Specifically, the monitoring server is configured to obtain the relative position between the shelf and the sky rail, the relative position between the shelf and the ground rail, or the inclination angle of the shelf at each acquisition time according to the video image sequence, and generate a plurality of first characteristic state parameter sets, where the first characteristic state parameter sets include a variation curve of the relative position between the shelf and the sky rail, a variation curve of the relative position between the shelf and the ground rail, or a variation curve of the inclination angle of the 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 collected video 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 by the same method, and a graph of the angle change is generated by the numerical values. Specifically, a video sequence of 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.
In addition, in a specific embodiment, the operating state of the logistics apparatus is determined by performing comparative analysis on the first characteristic state parameter set and a preset state parameter set, wherein the first characteristic state parameter set has a newly acquired gait feature, and the preset state parameter set has a gait feature of a normal working state of the logistics apparatus, which is stored in a 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.
Further, the monitoring server is configured to determine the operation state of the logistics equipment according to a comparison analysis of a second characteristic state parameter set and a preset state parameter set, wherein the second characteristic state parameter set comprises the operation speed of the logistics equipment at 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 warehousing operation and maintenance management system applied to intelligent manufacturing disclosed by the embodiment acquires a video image sequence of the gait of the logistics equipment by adding the image monitoring equipment and tracking and monitoring the logistics equipment in operation in the warehouse by means of the image monitoring equipment, extracts the gait feature of the logistics equipment from the video sequence and generates a first feature state parameter set according to the continuous gait feature 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 warehouse management 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.
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 (8)
1. A warehousing operation and maintenance management system applied to intelligent manufacturing is characterized by comprising:
the system comprises at least one logistics device working in a specific area and provided with a PLC controller, and a monitoring server connected with the PLC controller of each logistics device;
the monitoring server is configured to collect motion control pulse values output by a PLC (programmable logic controller) of the logistics equipment in real time, respectively generate corresponding motion direction pulse curve graphs according to the motion directions of the logistics equipment, compare the generated specific motion direction pulse curve graphs with preset pulse curves of the motion directions, and give an alarm if the generated specific motion direction pulse curve graphs deviate from the preset pulse curve specific threshold.
2. The warehousing operation and maintenance management system according to claim 1, wherein: the logistics equipment is stacking equipment.
3. The warehousing operation and maintenance management system according to claim 2, wherein: the monitoring server is configured to respectively extract motion control pulse values of the walking mechanism, the pallet fork mechanism and/or the lifting mechanism according to the mechanical composition of the logistics equipment, wherein the motion control pulse values are values generated in the process that the logistics equipment is driven to move along a specific direction through a motor or a servo mechanism; and respectively storing the collected motion control pulse values into each motion part data group in a database according to the mechanical composition class.
4. The warehousing operation and maintenance management system according to claim 3, wherein: the motion control pulse values include a pulse value at a start position in the direction of motion and/or a pulse value for all valid cargo spaces between the start position and an end position.
5. The warehousing operation and maintenance management system according to claim 4, wherein: the monitoring server is configured to compare the generated motion direction pulse curve with a preset pulse curve of the motion direction, divide the generated motion direction pulse curve into a first state and a second state according to a deviation value of the generated motion direction pulse curve and the preset pulse curve, and send a corresponding notification when the motion direction pulse curve is judged to be in the second state.
6. The warehousing operation and maintenance management system according to claim 5, wherein: the system also comprises a video monitoring device connected with the monitoring server, wherein the video monitoring device is used for acquiring video images of the logistics equipment working in a specific area;
the monitoring server is configured to acquire a video image sequence from the video monitoring device in a working area of the logistics equipment when pulse value data of one movement direction of the logistics equipment is in a second state, extract gait features of the logistics equipment from the video sequence, generate a first feature state parameter set according to continuous gait feature changes of the logistics equipment, and judge the operation state of the logistics equipment according to comparative analysis of the first feature state parameter set and a preset state parameter set, wherein the gait is the posture and/or behavior features of the logistics equipment during operation.
7. The warehousing operation and maintenance management system according to claim 6, wherein: the monitoring server is configured to identify the composition of each mechanical part of the logistics equipment in the video image sequence, and calculate the posture and/or behavior characteristics of each mechanical part.
8. The warehousing operation and maintenance management system according to claim 7, wherein: the monitoring server is configured to identify logistics equipment identity information in a video image sequence, acquire corresponding mechanical component components and identification characteristics and detection parameters of all the mechanical components in a database according to the logistics equipment identity information, acquire corresponding mechanical components in the video image sequence according to the identification characteristics, and measure and acquire the detection parameters of the corresponding mechanical components.
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