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CN-122022441-A - Monitoring method suitable for wooden furniture production line

CN122022441ACN 122022441 ACN122022441 ACN 122022441ACN-122022441-A

Abstract

The invention discloses a monitoring method suitable for a wooden furniture production line, which relates to the technical field of wooden furniture production monitoring and comprises the steps of S1, deploying modularized monitoring nodes, deploying a plurality of modularized monitoring nodes with sensing, processing and communication functions at each key station of processing equipment, generating unique identification information for each monitoring node, generating the identification information by a preset rule, and sending a registration request containing identity information, node type and equipment state through a network. The method comprises the steps of arranging monitoring nodes to send automatic registration capability, realizing binding unique identification to workpieces, collecting and recording state information of the whole process, constructing a complete product record chain, facilitating quality tracing and problem positioning, introducing knowledge graph modeling and graph structure reasoning methods, realizing early identification of potential faults, executing multi-target linkage control according to risk levels, and improving real-time performance and accuracy of control through cooperative response of standard interfaces, equipment and an alarm system.

Inventors

  • YE YONGZHEN
  • LI NING

Assignees

  • 海太欧林集团股份有限公司

Dates

Publication Date
20260512
Application Date
20251208

Claims (10)

  1. 1. The monitoring method suitable for the wooden furniture production line is characterized by comprising the following steps of: s1, deploying modularized monitoring nodes, deploying a plurality of modularized monitoring nodes with sensing, processing and communication functions at each key station of processing equipment, generating unique identification information for each monitoring node, wherein the identification information is generated by a preset rule, and sending a registration request containing identity information, node type and equipment state through a network; s2, automatically identifying and constructing a flow, automatically sending registration information to a central monitoring platform through a network after a monitoring node is electrified, wherein the registration information comprises a node unique identifier, a type, functional configuration and the like, automatically configuring tasks of each node according to the registration information by the central monitoring platform, constructing a production line monitoring flow chart, and updating the production line monitoring flow chart in real time when the monitoring node is changed; s3, tracking the process of the workpiece, namely, attaching identification information to the workpiece, and recording state, parameter and event information related to the workpiece through each monitoring node to realize overall process tracking and data binding of the workpiece among different procedures; s4, knowledge graph modeling and reasoning, wherein the central monitoring platform builds a knowledge graph model based on the process flow, the equipment state, the historical fault information, the workpiece features and the environmental data, and builds an association relation of the monitoring nodes for expressing the association mode of the potential faults; S5, risk prediction, namely after the central monitoring platform cleans and standardizes the real-time monitoring data uploaded by each monitoring node, performing feature matching or knowledge graph reasoning with the knowledge graph, judging whether potential risks exist or not, and generating an early warning signal; S6, linkage control, wherein if a fault is detected, early warning information is generated and a downstream control system is linked to execute control actions, the control actions comprise stop control and alarm prompt, and meanwhile, a maintenance task list is generated and the early warning information and related workpieces are bound and archived.
  2. 2. The monitoring method for the wood furniture production line according to claim 1, wherein the modularized monitoring node comprises a sensing unit, a monitoring unit and a monitoring unit, wherein the sensing unit is used for acquiring information such as images, temperature and humidity, vibration, current and the like related to a workpiece or equipment; the communication unit is used for carrying out data interaction with the central monitoring platform in a wired or wireless mode; And the processing unit is used for carrying out preliminary analysis on the acquired data and packaging the acquired data into registration request or monitoring data.
  3. 3. The monitoring method for the wood furniture production line according to claim 1, wherein the unique identification information consists of a factory burning number, a MAC address or a two-dimensional code identification of the monitoring node, and the unique identification is automatically read and a registration request is sent when the monitoring node is powered on or connected to the network for the first time.
  4. 4. The method for monitoring a wood furniture production line according to claim 1, wherein the registration information includes a unique identifier of a monitoring node, a node type, a station position, a current firmware version, a supported sensor type and a collection frequency parameter thereof; After receiving the registration information, the central monitoring platform automatically distributes corresponding task configuration for the monitoring nodes according to a preset task template library, wherein the task configuration comprises a data acquisition period, an uploading path, an early warning threshold value and processing logic.
  5. 5. The monitoring method for the wood furniture production line according to claim 1, wherein the central monitoring platform automatically generates a monitoring flow chart representing the process flow of the production line through a graph structure algorithm according to the registration sequence, the station position and the node function of each monitoring node, the flow chart is a directed graph, the nodes represent process units, and the edges represent the process sequence or the data flow direction; The flow chart is stored and maintained through a chart database or a topology management module, and when a monitoring node is newly added, disconnected or replaced by faults, the operation of newly adding, replacing or deleting the flow chart node is automatically carried out.
  6. 6. The monitoring method for the wooden furniture production line according to claim 1, wherein the identification information of the workpieces is a two-dimensional code tag, an RFID electronic tag or an outline feature code extracted by image recognition, which is used for identifying each workpiece, the identification information of each workpiece is consistent in the process of process circulation, the central monitoring platform integrates the workpiece state data, environmental parameters, event records and the like uploaded by each monitoring node in time sequence, forms the monitoring data of each workpiece to generate a time stamp and node information, and stores the time stamp and node information in a workpiece history database for subsequent quality analysis and calling.
  7. 7. The monitoring method suitable for the wooden furniture production line according to claim 1 is characterized in that the central monitoring platform performs rule matching or map traversal on paths, node types and attribute combinations in a knowledge map to achieve reasoning analysis on potential fault occurrence reasons and risk points, and the central monitoring platform automatically extracts common fault modes based on historical monitoring data when constructing the knowledge map and performs knowledge map reasoning through a graph structure for subsequent real-time data comparison and fault early warning triggering.
  8. 8. The monitoring method for the wooden furniture production line according to claim 1, wherein the knowledge graph reasoning comprises rule reasoning and relation path reasoning, the rule reasoning is based on a logic relation defined in a graph, the path reasoning is based on logic strength calculation of a node relation chain and is used for mining potential fault causal links, and if the knowledge graph reasoning or feature matching judges that potential risks exist, the central monitoring platform generates an early warning data packet containing risk grades, predicted fault types, influencing procedures and related workpiece numbers and synchronously sends the early warning data packet to a human-computer interface and a control system.
  9. 9. The method for monitoring a wooden furniture production line according to claim 1, wherein the linkage control is implemented by a preset control rule base, the rule base comprises a plurality of "condition-action" pairs, and when a risk level, a fault type or a station number contained in the early warning information meets a certain rule condition, the corresponding control action is automatically executed.
  10. 10. The method for monitoring the production line of the wooden furniture according to claim 9, wherein the linkage control action is transferred through an edge control gateway to realize localized response, and the edge control gateway can perform specific actions after receiving a control instruction from a central monitoring platform and performing caching, confirmation and secondary verification locally.

Description

Monitoring method suitable for wooden furniture production line Technical Field The invention relates to the technical field of wood furniture production monitoring, in particular to a monitoring method suitable for a wood furniture production line. Background With the rapid development of the furniture manufacturing industry to the intelligent and automatic directions, the requirements for safety monitoring and operation management of the wooden furniture production line are increasingly improved. The problems of equipment abnormality, workpiece defects, environmental risks and the like possibly occurring in the production process are extremely easy to cause chain reaction if the problems are not found and treated in time, and the product quality and personnel safety are affected. Therefore, the construction of efficient, intelligent, and scalable production line monitoring systems is an important topic in the industry. In the prior art, a partition type monitoring method for a wooden furniture production line is proposed by a public patent CN106919130a, a production site is divided into a plurality of independent partitions, a detection device, an alarm device and an isolation device are deployed in each partition, and a control system is constructed by a processor, so that state monitoring and isolation control of a local area are realized. The scheme has the advantages of simple structure, quick triggering, strong regional control capability and the like, and has certain effect in the aspect of improving the stability and the safety of the system. However, the traditional partition type monitoring method including the scheme still has the defects that the monitoring systems of each partition are relatively independent, a cooperative mechanism is lacked among the systems, deployment and logic configuration cannot be flexibly adjusted according to the change of a production line structure, most monitoring events depend on sensor overrun or alarm after faults occur, potential risks or trend anomalies cannot be prejudged in advance, regional state monitoring is focused, state tracking and quality data recording of a single workpiece among a plurality of working procedures cannot be realized, the requirement control response of product-level quality tracing is difficult to meet based on a preset program, self-adaptive judgment and multi-target linkage are difficult to realize, the data storage and management of each partition are scattered, information islands exist, and full-line-level data analysis and optimization decision support are difficult. In summary, the existing monitoring technology is not attractive when facing flexible manufacturing, complex process chains and high frequency variation scenarios. What is needed is a novel monitoring method with modular deployment capability, automatic identification and configuration support, overall process tracking of workpieces, abnormal intelligent prediction and multi-target coordinated control functions, so as to better meet the comprehensive requirements of modern wooden furniture production lines on intelligent, safe and flexible monitoring. Disclosure of Invention The invention aims to provide a monitoring method suitable for a wooden furniture production line, so as to solve the defects in the prior art. In order to achieve the above object, the present invention provides the following technical solutions: A monitoring method suitable for a wooden furniture production line, the method comprising the steps of: s1, deploying modularized monitoring nodes, deploying a plurality of modularized monitoring nodes with sensing, processing and communication functions at each key station of processing equipment, generating unique identification information for each monitoring node, wherein the identification information is generated by a preset rule, and sending a registration request containing identity information, node type and equipment state through a network; S2, automatically identifying and constructing a flow, automatically sending registration information to a central monitoring platform through a network after the monitoring node is electrified, wherein the registration information comprises unique node identifiers, types, functional configurations and the like, automatically configuring tasks of each node according to the registration information by the central monitoring platform, constructing a production line monitoring flow chart, and updating the production line monitoring flow chart in real time when the monitoring node is changed; s3, tracking the process of the workpiece, namely, attaching identification information to the workpiece, and recording state, parameter and event information related to the workpiece through each monitoring node to realize overall process tracking and data binding of the workpiece among different procedures; s4, knowledge graph modeling and reasoning, wherein the central monitoring platform builds a knowledge graph m