A method and system for port machinery equipment predictive maintenance decision making

Abstract

The application discloses a kind of port machinery equipment predictive maintenance decision method and system, it is related to fault prediction technical field.The method obtains the abnormal operating state of several port machinery equipment in preset time window in work area, determines effective abnormal operating state according to occurrence position, duration and accompanying equipment quantity;Generate abnormal watermark mark and place into port machine work plane to form watermark chart;Determine its watermark distribution form, generate regional prediction maintenance instruction or public system review instruction when external induction form, generate the component prediction maintenance instruction of corresponding equipment when single machine degradation form.The application solves the problem that multiple port machinery equipment abnormalities lack correlation analysis, it is difficult to distinguish external induction and single machine degradation caused by mismaintenance.

Description

Technical Field

[0001] This invention relates to the field of fault prediction technology, and in particular to a predictive maintenance decision-making method and system for port machinery equipment. Background Technology

[0002] Port machinery refers to large mechanical equipment used in port loading and unloading operations, such as quay container cranes, rail-mounted gantry cranes, and loading and unloading bridges. Several port machinery units are usually arranged side by side in the same working area. Each port machinery unit operates along the same track and serves the same vessel being loaded or unloaded. They are interconnected in terms of track, power supply, control, and communication.

[0003] Existing predictive maintenance solutions for port machinery typically deploy independent monitoring of operating parameters on each machine. When a certain operating parameter exceeds a threshold, a maintenance task is generated specifically for that machine. This approach handles anomalies independently on a per-machine basis, lacking analysis of the correlations between anomalies across multiple machines within the work area. For example, Chinese Patent Publication No. CN122046032A discloses a port equipment fault early warning method and related equipment based on multi-source heterogeneous data. This method, in the field of port equipment fault early warning, constructs a collaborative fusion mechanism for multi-source heterogeneous data, synchronously associating and jointly modeling sensor time-series data, work task data, maintenance log text, and equipment image data. This overcomes the shortcomings of existing technologies that suffer from incomplete fault characteristic representation due to the isolated use of a single data source.

[0004] However, when an anomaly is actually triggered by external public factors, similar anomalies are often triggered simultaneously or successively on several port machinery equipment. The existing solution, because it handles each machine independently, assigns component maintenance tasks to several port machinery equipment separately. This not only fails to locate the real external cause, but also causes a large number of incorrect maintenance of individual machine components, increasing maintenance costs and reducing operational efficiency. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art, which handles anomalies independently on a per-unit basis, lacks anomaly correlation analysis, and is difficult to distinguish between external inducements and single-unit degradation leading to erroneous maintenance. The invention provides a predictive maintenance decision-making method and system for port machinery equipment to improve the accuracy of maintenance decisions.

[0006] To achieve the above objectives, in a first aspect, the present invention provides a predictive maintenance decision-making method for port machinery equipment, comprising the following steps:

[0007] The abnormal operating status of several port machinery equipment in the work area within a preset time window is obtained, and the valid abnormal operating status is determined according to the location, duration and number of accompanying equipment corresponding to the abnormal operating status. An abnormal watermark identifier is generated based on the valid abnormal operating status, and each abnormal watermark identifier is placed on the port machinery operating plane according to the corresponding operating position of the port machinery equipment to form an abnormal watermark map; wherein, the abnormal watermark identifier is used to at least indicate the port machinery equipment to which the abnormality belongs, the location where the abnormality occurred, and the order in which the abnormality occurred; Determine the watermark distribution pattern corresponding to the abnormal watermark map. If the abnormal watermark identifier forms a continuous distribution along the port machinery track direction, the wind direction, the ship side operation boundary, or the public control area, determine that the watermark distribution pattern is an externally induced pattern, and generate a regional predictive maintenance instruction or a public system review instruction. If the abnormal watermark is distributed from a single port machinery device to related parts, the watermark distribution pattern is determined to be a single machine degradation pattern, and a component predictive maintenance instruction for the port machinery device is generated. If an abnormal operating state occurs only within one collection cycle and does not form an accompanying abnormality in an adjacent part of the same port machinery equipment or in an adjacent port machinery equipment, then the abnormal operating state will be excluded from the abnormal watermark image. If an abnormal operating state occurs sequentially among several related parts of the same port machinery equipment, or occurs continuously among several port machinery equipment according to their operating positions, or occurs together in several port machinery equipment within the same time window, then the abnormal operating state is determined to be a valid abnormal operating state.

[0008] As a preferred technical solution for predictive maintenance decision-making methods for port machinery equipment, the process of determining the externally induced morphology includes: If several abnormal watermarks are arranged continuously along the same port machinery track section, and the abnormal occurrence location corresponding to each abnormal watermark includes at least one of the trolley traveling mechanism, trackside power supply component or track support component, the watermark distribution pattern is determined to be a track-induced pattern, and the track foundation, track joint or trackside power supply structure corresponding to the track section is identified as a regional predictive maintenance object. If several abnormal watermarks are transferred to adjacent track sections as the port machinery moves along the track, the track-induced state is converted into a single-machine degradation pending determination state, and the abnormal watermark image is re-determined according to the single-machine degradation state determination rules.

[0009] As a preferred technical solution for predictive maintenance decision-making methods for port machinery equipment, the process of determining the externally induced morphology further includes: If several abnormal watermarks are distributed on the same wind-affected side of several port machinery equipment, and the order of appearance of the abnormal watermarks on the windward side is earlier than the order of appearance on the leeward side, the watermark distribution pattern is determined to be a wind-induced pattern, and crosswind disturbance, salt spray adhesion, or swaying of the spreader are identified as regional predicted maintenance events. If the abnormal watermark in the wind-induced pattern remains at the same location of the same port machinery within a preset duration for which the wind direction change is not less than a preset angle threshold, then the wind-induced pattern will be converted into a single-machine degradation pattern.

[0010] As a preferred technical solution for predictive maintenance decision-making methods for port machinery equipment, the process of determining the externally induced morphology further includes: If several abnormal watermarks are continuously distributed along the shipside operation boundary, hatch boundary, or loading / unloading hold boundary of the vessel being loaded / unloaded, and the abnormal watermarks shift synchronously with the changes in the loading / unloading hold, the watermark distribution pattern is determined to be a shipside operation-induced pattern, and abnormal ship attitude, hatch obstruction, spreader off-center loading, or loading / unloading rhythm is identified as an operation-induced maintenance event. If the abnormal watermark does not change with the loading and unloading position and is fixed at the hoisting part, luffing part or trolley running part of a single port machinery, then the ship-side operation-induced state will be converted into a single-machine degradation state.

[0011] As a preferred technical solution for predictive maintenance decision-making methods for port machinery equipment, the process of determining the public system review instructions includes: If several port machinery equipment form abnormal watermarks with the same abnormal location and the same abnormal occurrence order within the same time window, and the abnormal watermarks do not change with the change of the port machinery equipment's operating position, the watermark distribution pattern is determined to be a common control-induced pattern. In response to the aforementioned public control triggering mode, a verification instruction for the public power supply system, control command link, or regional communication link is generated, and each port machinery equipment is restricted from generating individual component predictive maintenance instructions based on the abnormal operating status within the time window.

[0012] As a preferred technical solution for predictive maintenance decision-making methods for port machinery equipment, the process of determining the degradation mode of the individual machine includes: If the abnormal watermark identifier corresponding to the target location in a single port machinery equipment appears earlier than the abnormal watermark identifiers corresponding to several related locations, and the abnormal watermark identifiers corresponding to the several related locations form a diffuse distribution around the target location, the watermark distribution pattern is determined to be a single-machine degradation pattern. The target location is one of the following: hoisting mechanism, wire rope system, gearbox, brake, trolley traveling mechanism or trolley traveling mechanism; the associated location is a location that has a transmission connection, load-bearing connection or control connection with the target location.

[0013] As a preferred technical solution for predictive maintenance decision-making methods for port machinery equipment, the process of generating anomaly watermark identifiers based on the effective abnormal operating states includes: The port machinery equipment number corresponding to the effective abnormal operating status is determined as the equipment location identifier; The location corresponding to the effective abnormal operating state is identified as the location identifier; The order in which the valid abnormal operating states appear within the preset time window is determined as a sequence identifier; The abnormal watermark identifier is formed by the device location identifier, part identifier, and sequence identifier.

[0014] As a preferred technical solution for predictive maintenance decision-making methods for port machinery equipment, the process of placing various abnormal watermark markers into the port machinery operating plane includes: The location of the port machinery equipment on the track, on the side of the ship, or in the yard within the operating area is used as the location for inserting the corresponding abnormal watermark mark. For several abnormal watermarks generated by the same port machinery equipment within the same preset time window, each abnormal watermark is placed sequentially into the adjacent display area of ​​the corresponding position of the port machinery equipment in the order of abnormal occurrence, so as to form a local watermark segment corresponding to the port machinery equipment.

[0015] On the other hand, the present invention also provides a predictive maintenance decision-making system for port machinery equipment, comprising: The anomaly screening module is used to obtain the abnormal operating status of several port machinery equipment in the working area within a preset time window, and to determine the valid abnormal operating status based on the location, duration and number of accompanying equipment corresponding to the abnormal operating status. The watermark generation module is used to generate abnormal watermark identifiers based on the effective abnormal operating status, and to place each abnormal watermark identifier into the port machinery operating plane according to the corresponding operating position of the port machinery equipment to form an abnormal watermark image. The morphology determination module is used to determine the watermark distribution morphology corresponding to the abnormal watermark image. If the abnormal watermark is continuously distributed along the port machinery track direction, the wind direction, the ship side operation boundary, or the public control area, the watermark distribution morphology is determined to be an externally induced morphology. If the abnormal watermark is diffused from a single port machinery device to related parts, the watermark distribution morphology is determined to be a single-machine degradation morphology. The maintenance decision module is used to generate regional predictive maintenance instructions or public system review instructions when the watermark distribution pattern is an externally induced pattern, and to generate corresponding component predictive maintenance instructions for port machinery equipment when the watermark distribution pattern is a single-machine degradation pattern. Specifically, the anomaly screening module excludes an abnormal operating state from the abnormal watermark map when a single abnormal operating state appears only within one collection cycle and does not form an accompanying anomaly in an adjacent part of the same port machinery or in adjacent port machinery; when a single abnormal operating state appears sequentially among several related parts of the same port machinery, or appears continuously among several port machinery according to the working position, or appears together in several port machinery within the same time window, the abnormal operating state is determined as a valid abnormal operating state.

[0016] As a preferred technical solution for a predictive maintenance decision-making system for port machinery equipment, the system also includes an equipment-end acquisition unit, an area edge unit, and a maintenance command output unit, which are set up corresponding to several port machinery equipment. The device-side acquisition unit is used to acquire the abnormal operating status of the corresponding port machinery equipment and send the abnormal operating status to the area edge unit; The region edge unit is used to collect abnormal operating states within the same work area and send the corresponding abnormal operating states to the abnormal screening module. The maintenance instruction output unit is used to send maintenance tasks to the corresponding port machinery equipment, regional maintenance terminal or public system maintenance terminal according to the regional predictive maintenance instruction, public system review instruction or component predictive maintenance instruction generated by the maintenance decision module. When the maintenance instruction output unit receives a public system review instruction, it restricts the generation of component predictive maintenance tasks for a single port machinery device within the corresponding time window based on the same abnormal operating state.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows: First, the present invention no longer handles anomalies in isolation on a single port machinery equipment basis, but instead generates anomaly watermarks for the effective abnormal operating status of several port machinery equipment within a preset time window and places them on the same port machinery operating plane. This allows for correlation analysis of anomalies of several port machinery equipment on the same plane, enabling the discovery of cross-equipment anomaly correlations that cannot be discovered by monitoring a single piece of equipment.

[0018] In particular, by determining the watermark distribution pattern corresponding to the abnormal watermark image, the present invention classifies the causes of abnormalities into two categories: external inducement and single-machine degradation. The external inducement pattern is further subdivided into sub-patterns such as track inducement, wind direction inducement, ship-side operation inducement and public control inducement. This enables the generation of regional predictive maintenance instructions or public system review instructions for the true cause of the inducement, avoiding the repeated assignment of single-machine component maintenance tasks to several port machinery equipment and reducing erroneous maintenance.

[0019] Furthermore, this invention sets exclusion and inclusion rules when determining valid abnormal operating states, which can filter out occasional isolated anomalies, reduce false alarms, and improve the accuracy of maintenance decisions and operational efficiency. Attached Figure Description

[0020] The accompanying drawings are provided to further understand the technical solutions of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the technical solutions of the present invention, and do not constitute a limitation on the technical solutions of the present invention.

[0021] Figure 1 A schematic diagram of the overall process of the predictive maintenance decision-making method for port machinery equipment provided in an embodiment of the present invention; Figure 2 A flowchart illustrating the process of determining a valid abnormal operating state provided in an embodiment of the present invention; Figure 3 This is a flowchart illustrating the watermark distribution pattern determination and maintenance decision-making process provided in an embodiment of the present invention. Figure 4 This is a schematic diagram of an abnormal watermark image being inserted into the port machinery operation plane according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the predictive maintenance decision system for port machinery equipment provided in an embodiment of the present invention.

[0022] In the diagram: 901, Anomaly Screening Module; 902, Watermark Generation Module; 903, Morphology Determination Module; 904, Maintenance Decision Module; 905, Device-side Acquisition Unit; 906, Region Edge Unit; 907, Maintenance Command Output Unit. Detailed Implementation

[0023] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0024] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0025] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0026] For ease of understanding, the following explanation will first describe several terms involved in this invention in conjunction with the present invention. An abnormal operating state refers to the operating state of port machinery equipment during operation, where operating parameters such as vibration, temperature, current, torque, or displacement collected by the equipment-end acquisition unit exceed the corresponding warning values ​​(i.e., the equipment issues a warning signal when the operating parameters reach the warning values), or where the control system of the port machinery equipment outputs a fault code. The data originates from sensors installed on each port machinery piece of equipment, and is collected by the equipment-end acquisition unit and then aggregated by the regional edge unit. The regional edge unit can passively receive abnormal operating states reported by the equipment-end acquisition unit, or actively query the equipment-end acquisition unit. The data format is a structured record, and each record includes at least the port machinery equipment number, the location of the abnormality, the start and end timestamps of the abnormality, and the type or parameter value of the abnormality.

[0027] A preset time window is a time interval used to define whether several abnormal operating states fall within the same time range. Its length can be set from minutes to hours, for example, from 5 minutes to 120 minutes, preferably from 10 minutes to 60 minutes, and typically 30 minutes. When the lower end value (e.g., 5 minutes) is used, the preset time window is shorter and more sensitive to changes in anomalies, but it is easy to miss slow-developing degradation trends. When the upper end value (e.g., 120 minutes) is used, the preset time window is longer and the anomaly statistics are more complete, but the timeliness of maintenance decisions decreases. Taking the middle value (e.g., 30 minutes) can achieve a balance between sensitivity and timeliness. The length of the preset time window should at least cover one typical loading and unloading operation cycle of the port machinery equipment and include several data collection cycles. Therefore, it can be set according to the operation rhythm and the scale of the port machinery equipment. For example, when it takes about 30 minutes for a single port machinery equipment to complete a typical loading and unloading operation cycle, the preset time window can be set to 30 minutes accordingly. The preset time window can be a fixed-length sliding window or a variable-length window divided by operation shifts. The acquisition cycle refers to the cycle in which the device-side acquisition unit acquires and reports operating parameters once. It can be set from 1 second to 5 minutes, for example, 60 seconds. The specific setting can be determined according to the rate of change of the monitored operating parameters and the processing capacity of the acquisition unit. A preset time window usually contains several acquisition cycles. The length of the preset time window is preferably an integer multiple of the acquisition cycle and not less than 10 times the acquisition cycle, so as to ensure that there are enough sampling points in each preset time window to determine the duration and order of occurrence of anomalies.

[0028] The number of accompanying equipment refers to the number of other port machinery that are operationally related to the port machinery that is currently experiencing an anomaly and also exhibit the same anomaly within the same preset time window. Operational association refers to equipment located on the same track section, operating on the same vessel being loaded or unloaded, or sharing the same power supply, control, or communication system. Accompanying anomaly refers to an anomaly that occurs in an adjacent part of the same port machinery or in adjacent port machinery within the same preset time window and is related to the current anomaly. It should be noted that the "accompanying" in the number of accompanying equipment and the "accompanying" in accompanying anomaly refer to the same related concept; the former focuses on counting the port machinery that generates the accompanying anomaly, while the latter focuses on the associated anomaly itself. The judgment criteria for both are consistent.

[0029] Adjacent locations refer to locations that have a direct transmission, load-bearing, or control connection with the target location, meaning they are directly related in structure or control, rather than being measured solely by geometric distance. Adjacent port machinery refers to port machinery that is directly related in operational logic, such as port machinery located on the same track section with an operational sequence difference not exceeding a preset number of positions, or port machinery operating together on the same vessel being loaded or unloaded. The preset number of positions can be set from 1 to 5 operational positions, typically 1 operational position. The larger the preset number of positions, the wider the range of operational sequences considered adjacent port machinery, and the more lenient the determination of operational association. The smaller the preset number of positions, the more strictly only port machinery with adjacent operational sequences are considered adjacent, and the determination is more stringent. Therefore, the specific preset number of positions can be set according to the equipment layout spacing in the operational area. For example, when the layout spacing of adjacent port machinery is small, a larger preset number of positions can be used, and when the layout spacing is large, a smaller preset number of positions can be used (such as 1 operational position).

[0030] The following is combined Figure 1 The predictive maintenance decision-making method for port machinery equipment provided in this embodiment of the invention will be described. For example... Figure 1 As shown, the method includes steps S101 to S105.

[0031] Step S101: Obtain the abnormal operating status of several port machinery equipment in the work area within a preset time window, and determine the valid abnormal operating status based on the location, duration and number of accompanying equipment corresponding to the abnormal operating status.

[0032] In this step, after the regional edge unit obtains the abnormal operating states of several port machinery equipment within the operating area within a preset time window as described above, it needs to filter out the valid abnormal operating states to eliminate occasional isolated anomalies and retain anomalies with analytical value, laying the foundation for subsequent correlation analysis. The location of occurrence, duration, and number of accompanying equipment are the three dimensions used for filtering. Based on these three dimensions, this invention forms two specific judgment rules: exclusion rules and inclusion rules, as follows: Figure 2As shown, the determination process is as follows.

[0033] Specifically, if an abnormal operating condition occurs only within one data collection cycle and does not form an accompanying abnormality in adjacent parts of the same port machinery or in adjacent port machinery, then the abnormal operating condition is excluded from the abnormal watermark map. This exclusion rule corresponds to the case where the duration is short and the number of accompanying devices is zero, which is reflected as an occasional isolated abnormality.

[0034] If an abnormal operating condition occurs sequentially among several related parts of the same port machinery, or occurs consecutively among several port machinery according to their operating positions, or occurs simultaneously within the same time window among several port machinery, then the abnormal operating condition is determined to be a valid abnormal operating condition. This inclusion rule corresponds to situations where the duration is extended or the number of accompanying devices is not zero. Therefore, the exclusion and inclusion rules are concrete manifestations of the three dimensions of the location of occurrence, duration, and number of accompanying devices, rather than additional judgment conditions.

[0035] It should be noted that the exclusion rule requires both conditions to be met simultaneously: the condition that the anomaly occurs only within one data collection cycle and that no accompanying anomaly has formed. To avoid conflicts between the exclusion and inclusion rules, this embodiment prioritizes the inclusion rule over the exclusion rule. That is, if an abnormal operating state meets either inclusion condition—for example, if it occurs only within one data collection cycle but has appeared consecutively across several port machinery equipment according to their operating positions—then the abnormal operating state does not meet the second condition of the exclusion rule because it has formed an accompanying anomaly, and should be determined as a valid abnormal operating state rather than excluded. The reason for prioritizing inclusion in this approach is that the occurrence of related anomalies across different locations or equipment often points to common triggering causes, and their analytical value is higher than that of occasional isolated anomalies, so they should be retained.

[0036] Step S102: Generate abnormal watermark identifiers based on valid abnormal operating status, and place each abnormal watermark identifier into the port machinery operating plane according to the corresponding port machinery equipment's operating position to form an abnormal watermark map; wherein, the abnormal watermark identifier is used to at least indicate the port machinery equipment to which the abnormality belongs, the location where the abnormality occurred, and the order in which the abnormality occurred.

[0037] The reason for performing this step after determining the valid abnormal operating status in step S101 is that the valid abnormal operating status itself is a scattered record of structured data, which is difficult to directly reflect the spatial relationship between several port machinery equipment. Therefore, this step converts each valid abnormal operating status into an abnormal watermark identifier with spatial location meaning and places it into a unified port machinery operation plane, so as to present the scattered abnormalities on the same plane, which is convenient for subsequent determination of their distribution pattern.

[0038] Specifically, the process of generating anomaly watermark identifiers includes: determining the port machinery equipment number corresponding to the valid abnormal operating status as the equipment location identifier; determining the location of occurrence corresponding to the valid abnormal operating status as the location identifier; determining the order in which valid abnormal operating statuses appear within a preset time window as the sequence identifier; and forming the anomaly watermark identifier by combining the equipment location identifier, location identifier, and sequence identifier. It should be noted that the order of anomaly occurrence is a global order, meaning it is the order obtained by uniformly sorting all valid abnormal operating statuses within the preset time window according to a unified timestamp for the entire work area, rather than sorting them individually for a single port machinery equipment, to ensure comparability of the chronological relationship between the anomaly watermark identifiers of different port machinery equipment.

[0039] The port machinery operating plane refers to a two-dimensional coordinate plane established based on the layout of the operating area, with its coordinates corresponding one-to-one with the actual operating positions of the port machinery equipment within the operating area. "Insertion" refers to marking and overlaying the abnormal watermark identifier onto the corresponding position on this two-dimensional coordinate plane according to the operating position of the corresponding port machinery equipment. It is an overlay annotation operation, not a replacement of the base map.

[0040] The process of placing abnormal watermarks onto the port machinery operating plane includes: using the track position, ship-side operating position, or yard operating position of the port machinery within the operating area as the placement position for the corresponding abnormal watermark; for several abnormal watermarks generated by the same port machinery within the same preset time window, each abnormal watermark is placed sequentially into the adjacent display area corresponding to the port machinery position in the order of abnormality occurrence, thus forming a local watermark segment corresponding to that port machinery. Adjacent display areas refer to several marked areas arranged sequentially and adjacently to the corresponding position of the port machinery on the port machinery operating plane, for example, arranged sequentially from one side to the other along the port machinery track direction. Figure 4 As shown, port machinery equipment J1, J2, and J3 are arranged sequentially along the port machinery track within the port machinery operating plane. The abnormal watermark markers W11, W12, and W13 corresponding to port machinery equipment J1 are placed in adjacent display areas in the order of abnormality occurrence, thus forming the local watermark segment corresponding to port machinery equipment J1; the local watermark segments corresponding to port machinery equipment J2 and J3 are arranged in the same manner. The local watermark segments corresponding to each port machinery equipment collectively constitute the abnormal watermark map.

[0041] Step S103: Determine the watermark distribution pattern corresponding to the abnormal watermark image.

[0042] After the abnormal watermark map is generated, different causes of abnormalities will result in different spatial arrangement characteristics on the watermark map. Therefore, it is necessary to determine the watermark distribution pattern corresponding to the abnormal watermark map as the basis for generating subsequent maintenance instructions. The watermark distribution pattern is determined by a preset rule matching method. That is, the pattern determination module compares the spatial arrangement and time sequence of the equipment location, part, and sequence marks represented by each abnormal watermark mark in the abnormal watermark map with the preset pattern determination rules one by one, thereby determining whether it belongs to an externally induced pattern or a single-machine degradation pattern, without relying on manual interpretation.

[0043] Continuous distribution refers to the sequential arrangement of several abnormal watermark markers along the port machinery track direction, the direction of wind influence, the ship-side operation boundary, or the public control area, with the interval between the operation positions corresponding to two adjacent abnormal watermark markers not exceeding a preset interval threshold, and the number of abnormal watermark markers involved in the arrangement not less than a preset number. The preset interval threshold can be set, for example, to allow for a difference of no more than 1 to 3 operation positions between adjacent operation positions, typically set to a difference of no more than 1 operation position. This allows for occasional abnormal absences at individual operation positions without disrupting the continuous distribution. A larger preset interval threshold value indicates a higher tolerance for discontinuities in the continuous distribution and a more lenient judgment; a smaller value indicates a more stringent judgment. The preset number can be set, for example, to allow for... The number of watermarks can range from 2 to 10, typically set to 3. These are used to exclude occasional arrangements consisting of only a few abnormal watermarks. The larger the preset number, the more abnormal watermarks are required to determine a continuous distribution, and the more robust the determination, but the lower the sensitivity. The smaller the value, the higher the sensitivity, but the easier it is to make a false judgment. The preset interval threshold corresponds to the equipment layout spacing in the work area. That is, the maximum physical span allowed for continuous distribution is equal to the product of the preset interval threshold and the distance between adjacent work positions. The preset number corresponds to the number of port machinery equipment in the work area and the level of work busyness. When the work is busier and there are more equipment, a larger preset number can be used. Therefore, both can be set according to the equipment layout of the work area.

[0044] like Figure 3As shown, if the abnormal watermark is continuously distributed along the port machinery track direction, the wind direction, the ship's side operating boundary, or the common control area, the watermark distribution pattern is determined to be an externally induced pattern; if the abnormal watermark spreads from a single port machinery device to related parts, the watermark distribution pattern is determined to be a single-machine degradation pattern. It should be noted that a continuous distribution spans several port machinery devices and extends in an external direction, while a diffuse distribution is limited to the interior of a single port machinery device and spreads outward along the internal relationships of the device. The two are distinguished accordingly. In actual working conditions, if an abnormal watermark pattern shows both a continuous distribution across several port machinery devices in an external direction and a spread from a single port machinery device to adjacent devices, this embodiment sets the determination of the externally induced pattern to take precedence over the single-machine degradation pattern, that is, it is preferentially determined to be an externally induced pattern; only when the abnormal watermark is limited to the interior of a single port machinery device, does not span port machinery devices, and does not extend in an external common direction is it determined to be a single-machine degradation pattern. The priority is set in this way because the external triggering mode points to an external cause that is common to several devices. If it is misjudged as a single-machine degradation mode, it will lead to repeated erroneous maintenance of multiple devices.

[0045] Step S104: If the watermark distribution pattern is an externally induced pattern, generate a regional prediction maintenance instruction or a public system review instruction.

[0046] It should be noted that the "or" here refers to a selection based on a specific sub-mode of the externally induced pattern, rather than arbitrarily generating one or two of them. Specifically, when the externally induced pattern is a track-induced pattern, a wind-induced pattern, or a ship-side operation-induced pattern, a regional predictive maintenance instruction is generated; when the externally induced pattern is a common control-induced pattern, a common system review instruction is generated. The common control-induced pattern is one of the lower-level sub-modes of the externally induced pattern. The determination process for each sub-mode is explained below.

[0047] The process of determining the externally induced pattern includes: if several abnormal watermarks are continuously arranged along the same port machinery track segment, and the abnormal occurrence location corresponding to each abnormal watermark includes at least one of the following: trolley traveling mechanism, trackside power supply component, or track support component, the watermark distribution pattern is determined to be a track-induced pattern, and the track foundation, track joint, or trackside power supply structure corresponding to that track segment is identified as a regional predictive maintenance object; if several abnormal watermarks move to adjacent track segments along the port machinery equipment, the track-induced pattern is converted into a single-machine degradation pending determination pattern. Converting to a single-machine degradation pending determination pattern here means modifying the pattern label of the track-induced pattern originally marked on the abnormal watermark map to a single-machine degradation pending determination pattern, and resubmitting the abnormal watermark map into the single-machine degradation pattern determination process for re-determination according to the subsequent diffusion distribution rules, thereby avoiding misjudgment of the abnormality as a track-induced pattern due to equipment movement. This is because if the abnormality moves along with the port machinery equipment, it indicates that the abnormality is more likely to originate from the equipment itself, rather than a fixed track segment.

[0048] The process of determining the externally induced pattern also includes: if several abnormal watermarks are distributed on the same wind-affected side of several port machinery equipment, and the order of appearance of the abnormal watermarks on the windward side is earlier than the order of appearance on the leeward side, the watermark distribution pattern is determined to be a wind-induced pattern, and crosswind disturbance, salt spray adhesion, or swaying of the spreader are identified as regional predictive maintenance objects; if the abnormal watermarks in the wind-induced pattern remain at the same location of the same port machinery equipment within a preset holding time after the wind direction change is not less than the preset angle threshold, the wind-induced pattern is converted into a single-machine degradation pattern. Here, wind direction change refers to a change in wind direction that is not less than a preset angle threshold. The preset angle threshold can be set to, for example, 30 degrees to 180 degrees, preferably 45 degrees to 90 degrees, and typically 45 degrees. The smaller the preset angle threshold, the more sensitive the determination of wind direction change, but it is easy to mistake small fluctuations in wind direction for a change in wind direction. The larger the preset angle threshold, the more strictly the determination is made when there is a significant change in wind direction. Therefore, the specific setting can be based on the meteorological conditions of the operating area. For example, a smaller preset angle threshold can be used for port areas with frequent crosswinds and changeable wind directions. "Maintaining" refers to ensuring that the abnormal watermark remains at the same location on the same port machinery equipment for a preset holding time after a change in wind direction. The preset holding time can be set from 1 to 30 minutes, preferably 5 to 15 minutes, and typically no less than 10 minutes. A shorter preset holding time makes it easier to misjudge residual disturbances caused by a sudden change in wind direction as single-machine degradation. A longer preset holding time makes the judgment more reliable but reduces the timeliness of maintenance decisions. The preset holding time is preferably an integer multiple of the acquisition cycle and does not exceed a preset time window. For example, when the acquisition cycle is 60 seconds, the preset holding time can be set to 10 minutes, approximately 10 acquisition cycles. Therefore, the specific setting can be based on the acquisition cycle. This is because if the magnitude of the wind direction change is not less than a preset angle threshold, and the abnormality remains fixed at the same location on the same equipment within the preset holding time, then the abnormality does not change with the wind direction and is more likely due to degradation of the equipment's own components.

[0049] The process of determining the externally induced pattern also includes: if several abnormal watermarks are continuously distributed along the ship's side operation boundary, hatch boundary, or loading / unloading hold boundary of the vessel being loaded / unloaded, and the abnormal watermarks move synchronously with changes in the loading / unloading hold, the watermark distribution pattern is determined to be a ship-side operation-induced pattern, and abnormal ship attitude, hatch obstruction, spreader off-center loading, or loading / unloading rhythm are identified as operation-induced maintenance events; if the abnormal watermarks do not move with changes in the loading / unloading hold and are fixed at the hoisting part, luffing part, or trolley running part corresponding to a single port machinery, then the ship-side operation-induced pattern is converted into a single-machine degradation pattern. This is because anomalies induced by ship-side operations should move synchronously with changes in the loading / unloading hold. If the anomaly is fixed at a specific part of a single piece of equipment and does not move with the hold, it is more likely to originate from the equipment itself.

[0050] The process of determining the public system review instructions includes: if several port machinery equipment generate abnormal watermarks with the same abnormal location and the same abnormal occurrence order within the same time window, and the abnormal watermarks do not change with the operating position of the port machinery equipment, the watermark distribution pattern is determined to be a public control induced pattern; in response to the public control induced pattern, review instructions for the public power supply system, control command link, or regional communication link are generated, and each port machinery equipment is restricted from generating individual component predictive maintenance instructions based on the abnormal operating status within the time window. The review instructions include instructions for checking the status of the public power supply system, control command link, or regional communication link. The output format is a structured instruction record, which is sent by the maintenance instruction output unit to the public system maintenance terminal and executed by the public system maintenance party. Restricting each port machinery equipment from generating individual component predictive maintenance instructions means that the superior regional edge unit or maintenance instruction output unit shields or suppresses component predictive maintenance instructions based on the same abnormal operating status within the time window, that is, it does not generate them or invalidates them after generation, thereby avoiding the repeated dispatch of single-machine maintenance tasks to multiple port machinery equipment for abnormalities caused by public system reasons. It should be noted that the public control induced form is one of the lower sub-forms of the external induced form, and the corresponding public system review instructions generated are consistent with the above-mentioned review instructions.

[0051] Step S105: If the watermark distribution pattern is a single-machine degradation pattern, generate the corresponding component prediction maintenance instruction for the port machinery equipment.

[0052] The process of determining the single-machine degradation pattern includes: if the abnormal watermark corresponding to the target location in a single port machinery appears earlier than the abnormal watermarks corresponding to several related locations, and the abnormal watermarks corresponding to several related locations form a diffuse distribution around the target location, the watermark distribution pattern is determined to be a single-machine degradation pattern; wherein, the target location is one of the following: hoisting mechanism, wire rope system, gearbox, brake, trolley traveling mechanism, or trolley traveling mechanism, and the related locations are locations that have a transmission connection, load-bearing connection, or control connection with the target location. After determining that it is a single-machine degradation pattern, a component predictive maintenance command is generated for the target location and its related locations of the port machinery, and the maintenance command output unit sends it to the corresponding port machinery or regional maintenance terminal. In the above embodiment, the determination criterion is that the abnormal watermark corresponding to the target location appears earlier than the related locations and diffuses towards the related locations, because single-machine degradation usually occurs from a certain source location and gradually affects the related locations along the transmission, load-bearing, or control connections.

[0053] The following is combined Figure 5 The predictive maintenance decision-making system for port machinery equipment provided in this embodiment of the invention will be described. For example... Figure 5As shown, the system includes an anomaly screening module 901, a watermark generation module 902, a morphology determination module 903, and a maintenance decision module 904.

[0054] The anomaly screening module 901 is used to acquire the abnormal operating states of several port machinery equipment within a preset time window in the work area, and to determine the valid abnormal operating states based on the location, duration, and number of accompanying equipment corresponding to the abnormal operating states. Specifically, the anomaly screening module 901 excludes an abnormal operating state from the abnormal watermark map when a single abnormal operating state occurs only within one acquisition cycle and does not form an accompanying anomaly in an adjacent part of the same port machinery equipment or in adjacent port machinery equipment. When a single abnormal operating state occurs sequentially among several related parts of the same port machinery equipment, or occurs continuously among several port machinery equipment according to the work position, or occurs together in several port machinery equipment within the same time window, the abnormal operating state is determined as a valid abnormal operating state.

[0055] The watermark generation module 902 is used to generate abnormal watermark identifiers based on valid abnormal operating status, and to place each abnormal watermark identifier into the port machinery operating plane according to the corresponding operating position of the port machinery equipment to form an abnormal watermark map.

[0056] The morphology determination module 903 is used to determine the watermark distribution morphology corresponding to the abnormal watermark map. If the abnormal watermark is continuously distributed along the port machinery track direction, the wind direction, the ship side operation boundary, or the public control area, the watermark distribution morphology is determined to be an externally induced morphology. If the abnormal watermark is diffused from a single port machinery equipment to related parts, the watermark distribution morphology is determined to be a single machine degradation morphology.

[0057] The maintenance decision module 904 is used to generate regional predictive maintenance instructions or public system review instructions when the watermark distribution pattern is an externally induced pattern, and to generate corresponding component predictive maintenance instructions for the port machinery equipment when the watermark distribution pattern is a single-machine degradation pattern. The above-mentioned anomaly screening module 901, watermark generation module 902, pattern determination module 903, and maintenance decision module 904 are connected in sequence, and are used to implement steps S101 to S105 in the aforementioned method embodiments, respectively. The specific implementation methods have been described in the aforementioned method embodiments and will not be repeated here.

[0058] The system also includes equipment-side acquisition units 905, area edge units 906, and maintenance command output units 907, each corresponding to a number of port machinery devices. Equipment-side acquisition units 905 acquire abnormal operating states of the corresponding port machinery devices and send these states to area edge units 906. Area edge units 906 aggregate abnormal operating states within the same work area and send the corresponding abnormal operating states to anomaly screening modules 901. Maintenance command output units 907 send maintenance tasks to the corresponding port machinery devices, area maintenance terminals, or public system maintenance terminals based on regional predictive maintenance commands, public system review commands, or component predictive maintenance commands generated by maintenance decision modules 904. When receiving a public system review command, maintenance command output units 907 restrict the generation of component predictive maintenance tasks for a single port machinery device within the corresponding time window based on the same abnormal operating state.

[0059] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0060] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention; various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method of port machinery equipment predictive maintenance decision making, characterized in that, include: The abnormal operating status of several port machinery equipment in the work area within a preset time window is obtained, and the valid abnormal operating status is determined according to the location, duration and number of accompanying equipment corresponding to the abnormal operating status. An abnormal watermark identifier is generated based on the valid abnormal operating status, and each abnormal watermark identifier is placed on the port machinery operating plane according to the corresponding operating position of the port machinery equipment to form an abnormal watermark map; wherein, the abnormal watermark identifier is used to at least indicate the port machinery equipment to which the abnormality belongs, the location where the abnormality occurred, and the order in which the abnormality occurred; Determine the watermark distribution pattern corresponding to the abnormal watermark map. If the abnormal watermark identifier forms a continuous distribution along the port machinery track direction, the wind direction, the ship side operation boundary, or the public control area, determine that the watermark distribution pattern is an externally induced pattern, and generate a regional predictive maintenance instruction or a public system review instruction. If the abnormal watermark is distributed from the target location of a single port machinery equipment to the associated location, the watermark distribution pattern is determined to be a single machine degradation pattern, and a component predictive maintenance instruction for the port machinery equipment is generated; the target location is one of the hoisting mechanism, wire rope system, gearbox, brake, trolley running mechanism or trolley traveling mechanism, and the associated location is a part that has a transmission connection, load-bearing connection or control connection with the target location; If an abnormal operating state occurs only within one collection cycle and does not form an accompanying abnormality in an adjacent part of the same port machinery equipment or in an adjacent port machinery equipment, then the abnormal operating state will be excluded from the abnormal watermark image. If an abnormal operating state occurs sequentially among several related parts of the same port machinery equipment, or occurs continuously among several port machinery equipment according to their operating positions, or occurs together in several port machinery equipment within the same time window, then the abnormal operating state is determined to be a valid abnormal operating state. The process of determining the externally induced morphology includes: If several abnormal watermarks are arranged continuously along the same port machinery track section, and the abnormal occurrence location corresponding to each abnormal watermark includes at least one of the trolley traveling mechanism, trackside power supply component or track support component, the watermark distribution pattern is determined to be a track-induced pattern, and the track foundation, track joint or trackside power supply structure corresponding to the track section is identified as a regional predictive maintenance object. If several abnormal watermarks are transferred to adjacent track sections as the port machinery moves along the track, the track-induced state is converted into a single-machine degradation pending determination state, and the abnormal watermark image is re-determined according to the single-machine degradation state determination rules.

2. The predictive maintenance decision-making method for port machinery equipment according to claim 1, characterized in that, The process of determining the externally induced morphology also includes: If several abnormal watermarks are distributed on the same wind-affected side of several port machinery equipment, and the order of appearance of the abnormal watermarks on the windward side is earlier than the order of appearance on the leeward side, the watermark distribution pattern is determined to be a wind-induced pattern, and crosswind disturbance, salt spray adhesion, or swaying of the spreader are identified as regional predicted maintenance events. If the abnormal watermark in the wind-induced pattern remains at the same location of the same port machinery within a preset duration for which the wind direction change is not less than a preset angle threshold, then the wind-induced pattern will be converted into a single-machine degradation pattern.

3. The predictive maintenance decision-making method for port machinery equipment according to claim 1, characterized in that, The process of determining the externally induced morphology also includes: If several abnormal watermarks are continuously distributed along the shipside operation boundary, hatch boundary, or loading / unloading hold boundary of the vessel being loaded / unloaded, and the abnormal watermarks shift synchronously with the changes in the loading / unloading hold, the watermark distribution pattern is determined to be a shipside operation-induced pattern, and abnormal ship attitude, hatch obstruction, spreader off-center loading, or loading / unloading rhythm is identified as an operation-induced maintenance event. If the abnormal watermark does not change with the loading and unloading position and is fixed at the hoisting part, luffing part or trolley running part of a single port machinery, then the ship-side operation-induced state will be converted into a single-machine degradation state.

4. The predictive maintenance decision-making method for port machinery equipment according to claim 1, characterized in that, The process of determining the public system review instruction includes: If several port machinery equipment form abnormal watermarks with the same abnormal location and the same abnormal occurrence order within the same time window, and the abnormal watermarks do not change with the change of the port machinery equipment's operating position, the watermark distribution pattern is determined to be a common control-induced pattern. In response to the aforementioned public control triggering mode, a verification instruction for the public power supply system, control command link, or regional communication link is generated, and each port machinery equipment is restricted from generating individual component predictive maintenance instructions based on the abnormal operating status within the time window.

5. The predictive maintenance decision-making method for port machinery equipment according to claim 1, characterized in that, The process of determining the single-machine degradation mode includes: If the abnormal watermark corresponding to the target location in a single port machinery appears earlier than the abnormal watermark corresponding to several related locations, and the abnormal watermark corresponding to the several related locations forms a diffuse distribution around the target location, the watermark distribution pattern is determined to be a single-machine degradation pattern.

6. The predictive maintenance decision-making method for port machinery equipment according to claim 1, characterized in that, The process of generating an abnormal watermark identifier based on the valid abnormal operating status includes: The port machinery equipment number corresponding to the effective abnormal operating status is determined as the equipment location identifier; The location corresponding to the effective abnormal operating state is identified as the location identifier; The order in which the valid abnormal operating states appear within the preset time window is determined as a sequence identifier; The abnormal watermark identifier is formed by the device location identifier, part identifier, and sequence identifier.

7. The predictive maintenance decision-making method for port machinery equipment according to claim 1, characterized in that, The process of placing the abnormal watermarks into the port machinery operating plane includes: The location of the port machinery equipment on the track, on the side of the ship, or in the yard within the operating area is used as the location for inserting the corresponding abnormal watermark mark. For several abnormal watermarks generated by the same port machinery equipment within the same preset time window, each abnormal watermark is placed sequentially into the adjacent display area of ​​the corresponding position of the port machinery equipment in the order of abnormal occurrence, so as to form a local watermark segment corresponding to the port machinery equipment.

8. A predictive maintenance decision-making system for port machinery equipment, characterized in that, include: The anomaly screening module is used to obtain the abnormal operating status of several port machinery equipment in the working area within a preset time window, and to determine the valid abnormal operating status based on the location, duration and number of accompanying equipment corresponding to the abnormal operating status. The watermark generation module is used to generate abnormal watermark identifiers based on the effective abnormal operating status, and to place each abnormal watermark identifier into the port machinery operating plane according to the corresponding operating position of the port machinery equipment to form an abnormal watermark image. The morphology determination module is used to determine the watermark distribution morphology corresponding to the abnormal watermark map. If the abnormal watermark is continuously distributed along the port machinery track direction, the wind direction, the ship side operation boundary, or the public control area, the watermark distribution morphology is determined to be an externally induced morphology. If the abnormal watermark is diffused from the target location of a single port machinery device to related locations, the watermark distribution morphology is determined to be a single-machine degradation morphology. The target location is one of the following: hoisting mechanism, wire rope system, gearbox, brake, trolley running mechanism, or trolley traveling mechanism. The related location is a location that has a transmission connection, load-bearing connection, or control connection with the target location. The maintenance decision module is used to generate regional predictive maintenance instructions or public system review instructions when the watermark distribution pattern is an externally induced pattern, and to generate corresponding component predictive maintenance instructions for port machinery equipment when the watermark distribution pattern is a single-machine degradation pattern. The anomaly screening module excludes an abnormal operating state from the abnormal watermark map when a single abnormal operating state appears only within one collection cycle and does not form an accompanying anomaly in an adjacent part of the same port machinery or in adjacent port machinery; when a single abnormal operating state appears sequentially among several related parts of the same port machinery, or appears continuously among several port machinery according to the working position, or appears together in several port machinery within the same time window, the abnormal operating state is determined as a valid abnormal operating state. The process of determining the externally induced morphology includes: If several abnormal watermarks are arranged continuously along the same port machinery track section, and the abnormal occurrence location corresponding to each abnormal watermark includes at least one of the trolley traveling mechanism, trackside power supply component or track support component, the watermark distribution pattern is determined to be a track-induced pattern, and the track foundation, track joint or trackside power supply structure corresponding to the track section is identified as a regional predictive maintenance object. If several abnormal watermarks are transferred to adjacent track sections as the port machinery moves along the track, the track-induced state is converted into a single-machine degradation pending determination state, and the abnormal watermark image is re-determined according to the single-machine degradation state determination rules.

9. The predictive maintenance decision-making system for port machinery equipment according to claim 8, characterized in that, The system also includes a device-end acquisition unit, an area edge unit, and a maintenance command output unit, which are set up corresponding to several port machinery equipment. The device-side acquisition unit is used to acquire the abnormal operating status of the corresponding port machinery equipment and send the abnormal operating status to the area edge unit; The region edge unit is used to collect abnormal operating states within the same work area and send the corresponding abnormal operating states to the abnormal screening module. The maintenance instruction output unit is used to send maintenance tasks to the corresponding port machinery equipment, regional maintenance terminal or public system maintenance terminal according to the regional predictive maintenance instruction, public system review instruction or component predictive maintenance instruction generated by the maintenance decision module. When the maintenance instruction output unit receives a public system review instruction, it restricts the generation of component predictive maintenance tasks for a single port machinery device within the corresponding time window based on the same abnormal operating state.

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