Intelligent construction equipment management and control method and system based on object model

Abstract

The invention relates to the technical field of Internet of Things equipment management, in particular to an intelligent construction equipment management and control method and system based on a physical model, and the method comprises the steps: defining the physical model; in response to the heterogeneous device access request, verifying the digital certificate or the identity information, and allocating a data access permission and a control permission according to the function role of the heterogeneous device; when authorized heterogeneous equipment uploads a non-standard data packet, analyzing a communication protocol type, and mapping the non-standard data packet into a standardized data stream according to an equipment attribute field library; distributing the standardized data stream to a storage node, and when it is detected that the standardized data stream deviates from a preset anomaly detection threshold, generating a dynamic early warning signal; and according to the control authority distributed in the authentication stage, executing control command packaging and issuing, and feeding back the current state of the heterogeneous equipment and a dynamic early warning signal to a user interface in real time. According to the invention, the problem of how to realize unified management and control and real-time risk closed-loop control of massive heterogeneous equipment in an intelligent construction scene is effectively solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of Internet of Things equipment management, and in particular to an intelligent construction equipment management method and system based on a physical model. BACKGROUND

[0002] In the field of intelligent construction equipment management, a technical system for the whole life cycle management of various mechanical equipment on the construction site is implemented through Internet of Things technology, and remote instruction issuing is implemented based on a permission control mechanism, so that automatic intervention and safety protection of the equipment are finally realized.

[0003] However, the prior art relies on a customized protocol analysis module to realize equipment access, and an adaptive interface needs to be developed independently for each newly added type of equipment, which not only greatly increases the system complexity, but also causes confusion in data semantic expression, that is, the naming rules of the same physical parameter fields are different for different devices, resulting in a lack of unified basis for subsequent data analysis and collaborative control; the prior art usually uses a fixed threshold to determine the abnormal state of the equipment, completely ignoring the inherent risk level difference of different types of equipment; and the early warning system and the execution system adopt a separate architecture, and the control instruction can be triggered only after a manual confirmation link, which causes the critical risk response delay to be far beyond the safety time window, and the permission control mechanism is missing, which cannot dynamically match the operation permission according to the real-time risk level, further amplifying the risk of misoperation. The above defects easily form a vicious cycle, causing a long-term problem in the field of intelligent construction equipment management.

[0004] The information disclosed in this BACKGROUND section is only for the purpose of enhancing the understanding of the general background of the disclosure and should not be taken as admitting or in any form implying that the information forms the prior art known to those skilled in the art. SUMMARY

[0005] The present application provides an intelligent construction equipment management method and system based on a physical model, which can effectively solve the problems in the background art.

[0006] In order to achieve the above purpose, the technical solution adopted by the present application is: An intelligent construction equipment management method based on a physical model, the method comprising: defining a dynamically scalable physical model in the kernel layer, the physical model comprising a device attribute field library, an access authentication rule set and a data forwarding rule tree; in response to a heterogeneous device access request, verifying the digital certificate or identity information submitted by the heterogeneous device based on the access authentication rule set, and assigning data access permission and control permission according to the functional role of the heterogeneous device; when the authorized heterogeneous device uploads a non-standard data packet, analyzing the communication protocol type, and mapping the non-standard data packet to a standardized data stream according to the device attribute field library; distributing the standardized data stream to storage nodes based on the data forwarding rule tree, and generating a dynamic early warning signal when detecting that the standardized data stream deviates from a preset abnormality detection threshold; executing control command encapsulation delivery according to the control permissions allocated in the authentication phase, and feeding back the current state of the heterogeneous device and the dynamic early warning signal to a user interface in real time.

[0007] Further, a dynamically scalable object model is defined, including: The device attribute field library is dynamically constructed based on a field definition template, and the field definition template includes data type, unit, protocol identifier, and scalable field label; The access authentication rule set is loaded according to a rule configuration interface, wherein a first security level device authentication path forcibly verifies the issuing authority of the digital certificate, and a second security level device authentication path verifies the update period of the identity information; The data forwarding rule tree is stored in a tree structure, and the nodes of the data forwarding rule tree include storage node addresses, forwarding priorities, and condition-triggered branch paths.

[0008] Further, the digital certificate or identity information submitted by the heterogeneous device is verified based on the access authentication rule set, including: If it is the first security level device, it is verified whether the issuing authority of the corresponding digital certificate exists in a preset CA list and checks the validity of the certificate chain; If it is the second security level device, it is verified whether the hash value of the identity information matches, and whether the identity information update period is less than a security day; When the authentication is passed, the device unique identifier and the corresponding permission policy are registered in the object model.

[0009] Further, data access permissions and control permissions are allocated according to the functional roles of the heterogeneous device, including: The functional role of the heterogeneous device is obtained based on the device unique identifier; If it is the first security level device, the control instruction set is activated according to the corresponding functional role; If it is the second security level device, the data access range is allocated according to the corresponding functional role; When the functional role of each device changes, the permission policy in the object model is dynamically updated and synchronized to all the storage nodes.

[0010] Further, the non-standard data packet is mapped to a standardized data stream according to the device attribute field library, including: Resolving a protocol identifier from a header of the non-standard data packet, and matching a corresponding protocol resolver based on the protocol identifier; Obtaining payload data in the non-standard data packet according to a field structure predefined in the device attribute field library; Converting the payload data into a unit uniformization, encapsulating the payload data into a standardized data stream in a JSON format, and injecting the standardized data stream into a corresponding device unique identifier field in the physical model.

[0011] Further, obtaining the payload data in the non-standard data packet comprises: Loading a corresponding data acquisition template according to the protocol identifier, the data acquisition template comprising a field position index and a data type definition; Positioning a start bit and an end bit of the payload data based on a valid data position index predefined in the device attribute field library; If it is detected that the payload data adopts a segmented storage structure, recombining the payload data according to an offset parameter in the field structure; Real-time decrypting the encrypted payload data and decrypting the encrypted payload data using a key bound to the protocol identifier; Verifying a check code of the recombined payload data, deleting the non-standard data packet with a failed check, and generating an error log.

[0012] Further, distributing the standardized data stream to a storage node based on the data forwarding rule tree comprises: Traversing a root node to a leaf node path of the data forwarding rule tree, wherein the root node selects a branch according to a device type field in the standardized data stream, an intermediate node matches a storage strategy according to data sensitivity, and a leaf node is associated with a storage node address; When the standardized data stream carries a real-time control instruction, preferentially distributing the standardized data stream to an edge computing node and performing local storage; For non-real-time monitoring data, selecting to distribute the non-real-time monitoring data to a cloud storage center or to perform the local storage according to the data sensitivity; Real-time monitoring a load of the leaf node during the distribution process, and dynamically switching to a leaf node with a low load when a response delay of the leaf node exceeds an upper limit of the delay.

[0013] Further, when it is detected that the standardized data stream deviates from a preset abnormality detection threshold, a dynamic early warning signal is generated, comprising: Obtaining a device state parameter from the standardized data stream; Obtaining a device risk level predefined in the physical model according to the device type field associated with the leaf node of the data forwarding rule tree; According to the device risk level selection corresponding abnormal detection threshold value, when the device state parameter continuously exceeds the abnormal detection threshold value, the dynamic early warning signal is triggered; Based on the data access permission distributed in the access authentication rule set, a set of early warning receivers is determined; According to the data forwarding rule tree, the dynamic early warning signal is distributed to the set of early warning receivers.

[0014] An intelligent construction equipment management and control system based on a physical model, the system comprises: A physical model definition module defines a dynamically scalable physical model in the kernel layer, the physical model includes a device attribute field library, an access authentication rule set and a data forwarding rule tree; An identity verification module, in response to a heterogeneous device access request, verifies the digital certificate or identity information submitted by the heterogeneous device based on the access authentication rule set, and allocates data access permission and control permission according to the functional role of the heterogeneous device; A standard mapping module parses the communication protocol type when the authorized heterogeneous device uploads a non-standard data packet, and maps the non-standard data packet to a standardized data stream according to the device attribute field library; A dynamic early warning module, based on the data forwarding rule tree, distributes the standardized data stream to the storage node, and generates a dynamic early warning signal when it is detected that the standardized data stream deviates from the preset abnormal detection threshold value; A packaging and issuing module executes control command packaging and issuing according to the control permission allocated in the authentication stage, and feeds back the current state of the heterogeneous device and the dynamic early warning signal to the user interface in real time.

[0015] Further, the standard mapping module comprises: An identifier analysis unit analyzes the protocol identifier from the header of the non-standard data packet, and matches the corresponding protocol parser based on the protocol identifier; A payload unit acquires the payload data in the non-standard data packet according to the field structure predefined in the device attribute field library; A field matching unit performs unit uniformization conversion on the payload data, encapsulates it into a standardized data stream in JSON format, and injects it into the corresponding device unique identifier field in the physical model.

[0016] Through the technical scheme of the present application, the following technical effects can be achieved: The problem of how to realize unified management and control and real-time risk closed-loop control of a large number of heterogeneous devices in an intelligent construction scene is effectively solved.

[0017] The above description is only a summary of the technical solutions of the present application. In order to enable the technical means of the present application to be more clearly understood, and to be implemented according to the content of the description, and in order to enable the above and other purposes, characteristics and advantages of the present application to be more apparent and easy to understand, the following specific embodiments of the present application are described. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are only some embodiments described in the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0019] Figure 1 It is a flowchart of a kind of intelligent construction equipment control method based on object model; Figure 2 It is a structural schematic diagram of object model; Figure 3 It is a flowchart of standardization data stream mapping process; Figure 4 It is a flowchart of storage node distribution. DETAILED DESCRIPTION

[0020] The technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the description of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the present application. As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0022] Embodiment one; As Figure 1 shown, the present application provides a kind of intelligent construction equipment control method based on object model, method includes: S10: defining dynamic scalable object model in kernel layer, object model includes device attribute field library, access authentication rule set and data forwarding rule tree; S20: in response to heterogeneous device access request, based on access authentication rule set, verify the digital certificate or identity information submitted by heterogeneous device, and according to the function role of heterogeneous device, data access authority and control authority are distributed; S30: parsing the communication protocol type when the authorized heterogeneous device uploads a non-standard data packet, and mapping the non-standard data packet to a standardized data stream according to the device attribute field library; S40: distributing the standardized data stream to a storage node based on a data forwarding rule tree, and generating a dynamic early warning signal when it is detected that the standardized data stream deviates from a preset abnormality detection threshold; S50: executing a control command encapsulation and issuing according to the control authority allocated in the authentication stage, and feeding back the current state of the heterogeneous device and the dynamic early warning signal to the user interface in real time.

[0023] Specifically, first, the physical model in the kernel layer contains a device attribute field library, an access authentication rule set, and a data forwarding rule tree. The physical model adapts to the rapidly changing smart construction needs and access requests of various heterogeneous devices through dynamic scalability. The device attribute field library is used to record the basic attributes and characteristics of the device. In the access stage, the access authentication rule set is used to verify the heterogeneous device that submits a digital certificate or identity information, including verifying the device identification, the validity of the digital certificate, the security features, and the identification of the functional role. After verification, the corresponding data access authority and control authority are allocated according to the functional role of the device, so that the device can only access the resources within its authority range. When the authorized heterogeneous device uploads data, there may be differences in the upload format and communication protocol, i.e., non-standard data packets. The communication protocol type of these data packets is analyzed to identify their data format, and then the device attribute field library is used to map them into standardized data streams that the system can understand. The specific mapping process involves data field reorganization and redefinition to ensure that all data flows through the system in a consistent format. Next, through the data forwarding rule tree, the standardized data stream is distributed to the appropriate storage node. The data forwarding rule tree can determine the data storage path according to factors such as data type, source, and priority to improve data processing efficiency and storage accuracy. In the monitoring process of the data stream, if it is found that the data stream deviates from the preset abnormality detection threshold, such as abnormal data rate and information deviation, a dynamic early warning signal is generated. The dynamic early warning signal and the real-time state of the device are fed back to the user interface together, so that the user can take necessary measures in a timely manner. Finally, encapsulated control commands are issued to the device according to the control authority allocated in the authentication stage. In this way, the device can perform specific operations as needed under control, and the device state and warning signals are monitored in real time.

[0024] Through the technical solution of the present application, the problem of how to realize unified control and real-time risk closed-loop control of a large number of heterogeneous devices in a smart construction scenario is effectively solved.

[0025] Further, as shown in Figure 2 , a dynamically scalable physical model is defined, including: The field definition template includes a data type, a unit, a protocol identifier, and an extensible field label. The access authentication rule set is loaded according to the rule configuration interface, wherein the first security level device authentication path forcibly verifies an issuing authority of a digital certificate, and the second security level device authentication path verifies an update period of identity information. The data forwarding rule tree is stored in a tree structure, and a node of the data forwarding rule tree includes a storage node address, a forwarding priority, and a conditional trigger type branch path.

[0026] As a preferred embodiment of the above embodiment, first, a field definition template is used to dynamically construct a device attribute field library, which determines the structure of the device attribute data. In the preferred embodiment, each field template includes a data type, a unit, a protocol identifier, and an extensible field label. The data type is used to ensure the consistency of the data, such as integer, string, etc. The unit is used to explicitly indicate the physical meaning of the value, such as meters, kilograms, etc. The protocol identifier is used to support communication with other devices or systems. The extensible field label allows the template to be extended and modified according to actual needs. For example, the attributes of a certain building device may need to include its serial number, operating temperature range, and communication protocol, etc. This information can be dynamically defined and obtained through the template. Second, the access authentication rule set is loaded according to the rule configuration interface. The first security level device authentication path needs to forcibly verify the issuing authority of the digital certificate to ensure the reliability and security of the device identity, which can be implemented by setting a white list of verification authorities. The second security level device authentication path is mainly used to verify the update period of the identity information to ensure the synchronization of the dynamic information of the device and avoid the use of expired or lost identity data. A specific preferred embodiment can be that the validity period of the digital certificate and the periodic update mechanism are set to ensure the identity verification of the device in continuous operation. Finally, the data forwarding rule tree is stored and managed by storing the data forwarding rule tree in a tree structure, which can effectively design the data flow path. Each node contains a storage node address, a forwarding priority, and a conditional trigger type branch path. The storage node address is used to explicitly indicate the destination of the data, the forwarding priority is used to determine the preferential flow direction of the data in multiple possible paths, and the conditional trigger type branch path allows the data flow path to be dynamically adjusted according to specific conditions, thereby improving the efficiency and flexibility of data transmission. Preferably, specific conditions such as system load or time period are set to adjust the flow direction of the data to optimize the communication performance.

[0027] Further, the access authentication rule set is used to verify the digital certificate or identity information submitted by the heterogeneous device, including: If it is a first security level device, it is verified whether the issuing authority of the corresponding digital certificate exists in a preset CA list and the validity of the certificate chain is checked. If the second security level device, check whether the hash value of the identity information matches, and verify whether the identity information update period is less than the security days; When the authentication is passed, register the device unique identifier and the corresponding permission policy in the thing model.

[0028] As a preferred embodiment of the above embodiment, first, for the first security level device, the digital certificate submitted by the device is verified to ensure its authenticity and security, specifically, in the implementation, a preset CA list is used as the verification reference to ensure that the certificate issuing authority is in the trusted list, and the certificate chain is checked for validity to ensure that the certificate has not been tampered with or forged. In the preferred embodiment, after receiving the digital certificate of the device, the device management system first matches the certificate issuing authority with the preset CA list to ensure that the authority is within the trusted range, and then verifies the certificate chain level by level to ensure that each level of certificate is valid and not expired. For example, a building device may have a certificate issued by a well-known manufacturer, and its authentication can be verified by checking the information of the manufacturer in the CA list to ensure that the certificate chain is complete and valid. Secondly, for the second security level device, the confirmation of the identity information is based on the matching of the hash value, which ensures that the identity information provided by the device has not been modified. In the specific implementation, a secure hash function is used to generate a hash value of the identity information, which is compared with the hash value submitted by the device to confirm the consistency of the information. At the same time, the update period of the device identity information needs to be monitored to ensure that it is less than the preset safe days, thereby effectively avoiding the use of expired information. In the preferred embodiment, the identity information submitted by the device is matched through the system's hash verification mechanism. If the hash value of the identity information is consistent with the database record and the update period is within the safe range, it is considered to pass the verification. The identity information of the device may include its manufacturer information and device model. Regularly updating the hash value of these information can ensure the continuous security authentication of the device. Finally, when the device passes the authentication, the unique identifier of the device and the corresponding permission policy are registered in the thing model. This is done to ensure that the device can operate according to the registered permission in subsequent data interaction, avoiding unauthorized behavior. In the preferred embodiment, a unique identifier is assigned to each device in the thing model, and a permission policy is given according to the device type and functional requirements. For example, some devices may need higher level of operation permission, such as remote diagnosis function of maintenance device, while other devices may only need read permission. Through the implementation of this security verification process, the interaction and data transmission of devices in the intelligent construction environment are ensured to be safe and efficient.

[0029] Further, the data access permission and control permission are allocated according to the functional roles of the heterogeneous devices, including: Obtaining the functional role of the heterogeneous device based on the unique identifier of the device; If it is a first security level device, activate the control instruction set according to the corresponding function role; If it is a second security level device, assign a data access range according to the corresponding function role; When the function role of each device changes, dynamically update the permission policy in the thing model and synchronize to all storage nodes.

[0030] As a preferred embodiment of the above embodiment, first, the function role of the heterogeneous device is obtained based on the unique identifier of the device. In specific implementation, the current function role information of the device can be obtained by querying the unique identifier of the device through the thing model database. The function role can include whether the device is used for monitoring, performing specific building operations, or data acquisition, etc. The clear role helps subsequent permission allocation; for the first security level device, in the specific implementation, the control instruction set is activated according to the function role. The process needs the system to first identify the function role of the device. For example, the control type device can need to have the control instruction permissions of starting, pausing, and calibrating, etc. In the preferred embodiment, after determining the device role, the corresponding control instruction set is automatically activated through the preset association between the function role and the control instruction set. For example, for a crane device, when its function role is a hoisting operation device, the start, operation angle adjustment, and other control instructions of its console will be automatically activated to ensure the safety and accuracy of its operation. For the second security level device, in the specific implementation, the data access range is assigned according to the function role. The system needs to associate the function role with the data access permission. For example, the sensor type device can be assigned the permission to read the environmental data in a specific range, such as temperature, humidity, etc. In the preferred embodiment, after the function role is identified, the data access permission is correspondingly limited. For example, some monitoring type devices are only allowed to read but not modify data to ensure data security and integrity; when the function role of the device changes, the permission policy in the thing model needs to be dynamically updated and synchronized to all storage nodes, which can ensure that after the role changes, the device operation and data access still comply with the security policy. In specific implementation, by listening to the changes of the device role, when the change is detected, the permission policy is automatically adjusted and synchronized to all related nodes through the network protocol to ensure the real-time update and coordination of the system.

[0031] Further, as shown in Figure 3 The non-standard data packet is mapped into a standardized data stream according to the device attribute field library, including: The protocol identifier is parsed from the header of the non-standard data packet, and the corresponding protocol parser is matched based on the protocol identifier; The payload data in the non-standard data packet is obtained according to the field structure predefined in the device attribute field library; The payload data is uniformly converted, encapsulated into a standardized data stream in JSON format, and injected into the corresponding device unique identifier field in the thing model.

[0032] As a preferred embodiment of the above-mentioned embodiment, firstly, the header analysis of the non-standard data packet is involved, and the preferred embodiment of the step includes using the analysis tool to extract the header data of the non-standard data packet to obtain the protocol identifier, through which the corresponding protocol parser can be matched to correctly analyze the data packet content, and the selection of the parser is based on the protocol identifier, because different devices can use different communication protocols, and the parser is responsible for converting the data into a form that the system can understand; Next, the payload data in the non-standard data packet is obtained according to the device attribute field library, and the pre-defined field structure in the field library provides a framework to make the data analysis process more systematic, and in the preferred implementation step, the parser extracts the payload from the non-standard data packet, classifies and organizes the data according to the pre-defined field name, for example, extracts the temperature, pressure and other device data, and corresponds them with the standard field, in this way, even if the original data is in different formats, it can also be mapped into a unified format; The unit conversion of the payload data is part of the standardization, and in the case of gathering data from different devices, the measurement units can be different, therefore, the preferred implementation scheme includes converting the units to ensure that all data is stored and processed under the same unit standard, and the process to achieve this includes applying conversion rules to each data entry to convert it into a system standard unit, for example, converting Celsius temperature to Kelvin, or converting English units to metric units; Finally, the standardized data stream is packaged in JSON format, and the JSON format is widely used due to its structure and human readability, and is selected to package the standardized data in this scheme, and in this process, the device unique identifier is injected into it to ensure the clear attribution of the data stream, and in the preferred embodiment, the device unique identifier is attached to each standardized data stream as part of the metadata, ensuring that in the thing model, the source device of the data can be quickly located, supporting subsequent data management and analysis.

[0033] Further, the payload data in the non-standard data packet is obtained, including: Loading the corresponding data acquisition template according to the protocol identifier, the data acquisition template including field position index and data type definition; Based on the pre-defined effective data position index in the device attribute field library, locating the start bit and end bit of the payload data; If it is detected that the payload data adopts a segmented storage structure, reorganizing the payload data according to the offset parameter in the field structure; Real-time decryption of encrypted payload data and decryption using the key bound to the protocol identifier; Verifying the check code of the reorganized payload data, deleting the non-standard data packet with failed verification and generating an error log.

[0034] As a preferred embodiment of the above embodiment, the corresponding data acquisition template is loaded by the protocol identifier first, which contains the field position index and data type definition, which helps to accurately parse the data of different protocols. In specific implementation, after receiving the data packet, the corresponding field information such as field position and data type is obtained from the pre-created template by using the protocol identifier, so as to guide the accurate positioning and parsing of data; then, based on the valid data position index predefined in the device attribute field library, the start bit and the end bit of the payload data can be quickly located, and the information of the field library provides the structural framework of the data, so that the content of the data packet can be effectively navigated. In the preferred embodiment, the position index in the field library is used to help the system directly extract the data, and different attribute fields of different devices are supported by corresponding predefined positions, so as to ensure that no data is missed or misread; when it is detected that the payload data adopts a segmented storage structure, the offset in the field structure needs to be handled, and the data is reorganized using the offset parameter to ensure that each data segment can be correctly connected and form a complete output. A practical embodiment can include that the scattered segmented data is correctly spliced together according to the offset parameter of each field, thereby improving the reliability of the analysis of complex data storage structure; the encrypted payload data is decrypted in real time, which requires the use of a key bound to the protocol identifier. Through this binding mechanism, it is ensured that each device data packet can be quickly matched to the appropriate key. In the preferred implementation, the protocol identifier and the key are mapped based on a security policy, any data encryption protection is not tampered with, and the data privacy is effectively protected. When it is identified that the data packet is in encrypted format, the appropriate decryption algorithm is automatically called to restore the data; finally, the check code of the reorganized payload data is verified, thereby ensuring that the data is not damaged or tampered with during transmission. Whether the check code verification is successful or not determines whether the data packet will be further processed. If the verification fails, the non-standard data packet that fails the verification is deleted and an error log is generated for subsequent analysis. In specific applications, by setting a detailed log system, the team can quickly respond when problems occur and take corrective measures to continuously improve the stability of the data processing system.

[0035] Further, as shown in Figure 4 the standardized data stream is distributed to the storage nodes based on the data forwarding rule tree, including: traversing the root node to the leaf node path of the data forwarding rule tree, wherein the root node selects a branch according to the device type field in the standardized data stream, the intermediate node matches the storage strategy according to the data sensitivity, and the leaf node is associated with the storage node address; when the standardized data stream carries real-time control instructions, it is preferentially distributed to the edge computing node and executes local storage; for non-real-time monitoring data, it is distributed to the cloud storage center or executes local storage according to the data sensitivity; Real-time monitoring of leaf node load during distribution, dynamic switching to low-load leaf node when leaf node response delay exceeds upper limit of delay.

[0036] As a preferred embodiment of the above, at the root node of the data forwarding rule tree, the branch path is determined by analyzing the device type field in the standardized data stream, as each device may have different storage needs, thereby ensuring adaptability, in specific implementation, the root node can quickly distribute the data stream to the corresponding branch path according to the device type, ensuring the accuracy of the data flow direction; as the depth of traversal deepens, the intermediate node is responsible for matching the storage strategy according to the data sensitivity, which is a key factor in defining data storage methods, in specific embodiments, the appropriate storage strategy is selected through the data sensitivity information identified in the data stream, for example, high-sensitive data needs to select a higher security storage solution, while low-sensitive data may prefer a storage node with better performance, the strategy matching of the intermediate node ensures the safety and efficiency of the data stream during storage; when reaching the leaf node, the data forwarding rule tree associates the standardized data stream to the specific storage node address, which is based on the final decision of the data storage location after the previous few layers of decision, in the preferred embodiment, through the pre-set storage node address and leaf node management mechanism, it ensures that each data stream is directed to the appropriate storage unit, such as designated cloud storage or specific edge node, the result is to improve the accuracy and performance of data storage; if the standardized data stream contains real-time control instructions, it is preferentially distributed to the edge computing node and executed locally, this processing method is derived from the need for fast response of control instructions, local storage reduces network delay, in actual implementation, the content of the data stream is identified, and after it is found that it carries real-time control instructions, it is automatically classified to the edge computing node for fast processing, ensuring the efficiency and real-time response capability of the system; for non-real-time monitoring data, the data sensitivity determines the selection of the storage location, sensitive data is preferentially distributed to the cloud storage center, while general data may select local storage, through this strategy, optimal allocation and utilization of resources are achieved, one preferred embodiment is that when the data stream enters, its sensitivity level is judged and a suitable storage solution is selected accordingly, ensuring that it is both safe and efficient to be stored; during data distribution, the load of the leaf node also needs to be monitored in real time, in order to avoid data transmission delay caused by overload, in specific implementation, the response time of each leaf node is continuously tracked, if it is found that the response delay of a certain node exceeds the set upper limit, it is dynamically switched to other low-load node, which improves the robustness through real-time load monitoring and switching mechanism.

[0037] Further, a dynamic early warning signal is generated when it is detected that the standardized data stream deviates from the pre-set abnormality detection threshold, including: Based on the device state parameters obtained in the standardized data stream; According to the device type field associated with the leaf node of the data forwarding rule tree, the device risk level predefined in the physical model is obtained; According to the device risk level, the corresponding abnormal detection threshold is selected, and when the device state parameter continuously exceeds the abnormal detection threshold, a dynamic early warning signal is triggered; Based on the data access permission distributed in the access authentication rule set, the early warning receiver set is determined; According to the data forwarding rule tree, the dynamic early warning signal is distributed to the early warning receiver set.

[0038] As a preferred embodiment of the above embodiment, first, the device state parameters are parsed from the standardized data stream, which may include device operating temperature, pressure and other key indicators, to ensure that the obtained state parameters can accurately reflect the current working state of the device; Next, through the leaf node of the data forwarding rule tree, the device type field is associated and the device risk level predefined in the physical model is obtained, and the risk level is the core basis for evaluating the potential failure or danger of the device. In specific implementation, the leaf node accesses the risk data in the physical model to provide a basis for setting corresponding monitoring standards for different device types, and the device risk level directly affects how the system sets the abnormal detection threshold to identify and handle potential problems in advance; According to the device risk level, the corresponding abnormal detection threshold is selected, which provides a clear monitoring benchmark for the device state parameters reflected in the standardized data stream. When the device state parameter continuously exceeds the abnormal detection threshold, a dynamic early warning signal is triggered to deal with possible device failure or abnormal situation, for example, for a high-risk level device, after the temperature is measured to exceed the safety threshold for several times in succession, an early warning signal is generated in real time to immediately take preventive measures; Once the early warning signal is triggered, the data access permission in the access authentication rule set is relied on to determine the early warning receiver set, which ensures that the early warning information is only sent to personnel or systems with relevant permissions. In specific implementation, the permission setting information in the authentication rule set is matched with the device early warning signal to ensure the safe and accurate transmission of information and prevent unnecessary influence or interference caused by information miscommunication; Finally, through the data forwarding rule tree, the dynamic early warning signal is distributed to the early warning receiver set, which ensures that the early warning signal is transmitted to the correct operator or management system within the effective time, thereby promoting rapid response and processing. In the preferred embodiment, the data forwarding rule is used to realize the timely distribution of the early warning signal through the preset forwarding path, and the information can be quickly received and acted upon by both internal nodes and external personnel.

[0039] Embodiment two; Based on the same inventive concept as the intelligent construction equipment management method based on the physical model in the foregoing embodiments, the present application also provides an intelligent construction equipment management system based on the physical model, which comprises: A physical model definition module defines a dynamically scalable physical model in a kernel layer, the physical model including a device attribute field library, an access authentication rule set and a data forwarding rule tree; An identity verification module verifies digital certificates or identity information submitted by the heterogeneous device based on the access authentication rule set in response to an access request of the heterogeneous device, and allocates data access rights and control rights to the heterogeneous device according to a functional role of the heterogeneous device; A standard mapping module parses a communication protocol type when the authorized heterogeneous device uploads a non-standard data packet, and maps the non-standard data packet into a standardized data stream according to the device attribute field library; A dynamic early warning module distributes the standardized data stream to a storage node based on the data forwarding rule tree, and generates a dynamic early warning signal when it is detected that the standardized data stream deviates from a preset abnormality detection threshold; A packaging and issuing module executes a control command packaging and issuing according to the control rights allocated in the authentication stage, and feeds back a current state of the heterogeneous device and the dynamic early warning signal to a user interface in real time.

[0040] The above adjustment system in the application can effectively realize an intelligent construction device management and control method based on a physical model, and the technical effects thereof are as described in the above embodiments, which will not be repeated here.

[0041] Further, the standard mapping module includes: An identifier parsing unit parses a protocol identifier from a header of the non-standard data packet, and matches a corresponding protocol parser based on the protocol identifier; A payload unit acquires payload data in the non-standard data packet according to a field structure predefined in the device attribute field library; A field matching unit performs unit uniform conversion on the payload data, encapsulates the payload data into a standardized data stream in a JSON format, and injects the standardized data stream into a corresponding device unique identifier field in the physical model.

[0042] Similarly, the above optimization scheme of the system can also correspondingly realize the optimization effects of the method in Embodiment One, which will not be repeated here.

[0043] Although the present application is described in conjunction with specific features and embodiments thereof, it is obvious that various modifications and combinations can be made thereto without departing from the spirit and scope of the present application. Accordingly, the present specification and drawings are merely illustrative of the exemplary embodiments of the present application and are to be regarded as covering all modifications, variations, combinations or equivalents that are within the scope of the present application. Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the present application and its equivalents, the present application is intended to include these modifications and variations.

Claims

1. A method for intelligent construction equipment management and control based on a physical model, characterized in that, The method includes: A dynamically extensible object model is defined at the kernel layer, which includes a device attribute field library, an access authentication rule set, and a data forwarding rule tree; In response to a heterogeneous device access request, the system verifies the digital certificate or identity information submitted by the heterogeneous device based on the access authentication rule set, and assigns data access permissions and control permissions according to the functional roles of the heterogeneous device. When the authorized heterogeneous device uploads a non-standard data packet, the communication protocol type is parsed, and the non-standard data packet is mapped into a standardized data stream according to the device attribute field library; Based on the data forwarding rule tree, the standardized data stream is distributed to the storage node, and a dynamic early warning signal is generated when the standardized data stream deviates from the preset anomaly detection threshold. Control commands are encapsulated and issued according to the control permissions assigned during the authentication phase, and the current status of the heterogeneous device and the dynamic early warning signal are fed back to the user interface in real time.

2. The intelligent construction equipment management and control method based on object model according to claim 1, characterized in that, Define a dynamically extensible object model, including: The device attribute field library is dynamically constructed based on field definition templates, which include data types, units, protocol identifiers, and extensible field tags. The access authentication rule set is loaded according to the rule configuration interface, wherein the first security level device authentication path forcibly verifies the issuing authority of the digital certificate, and the second security level device authentication path verifies the update cycle of the identity information; The data forwarding rule tree is stored in a tree structure, and the nodes of the data forwarding rule tree include the storage node address, forwarding priority, and condition-triggered branch path.

3. The intelligent construction equipment management and control method based on a material model according to claim 2, characterized in that, Verifying the digital certificate or identity information submitted by the heterogeneous device based on the access authentication rule set includes: If it is a device of the first security level, verify whether the issuing authority of the corresponding digital certificate exists in the preset CA list and check the validity of the certificate chain; If it is a device of the second security level, verify whether the hash value of the identity information matches, and verify whether the update cycle of the identity information is less than the number of security days; When authentication is successful, a unique device identifier and corresponding permission policy are registered in the object model.

4. The intelligent construction equipment management and control method based on a material model according to claim 3, characterized in that, Data access permissions and control permissions are assigned according to the functional roles of the heterogeneous devices, including: The functional role of the heterogeneous device is obtained based on the device's unique identifier; If it is a device of the first security level, activate the control instruction set according to the corresponding functional role; If it is a device of the second security level, data access scope shall be allocated according to the corresponding functional role; When the functional roles of each device change, the permission policy in the object model is dynamically updated and synchronized to all storage nodes.

5. The intelligent construction equipment management and control method based on a material model according to claim 1, characterized in that, Mapping the non-standard data packets to a standardized data stream according to the device attribute field library includes: The protocol identifier is parsed from the header of the non-standard data packet, and the corresponding protocol parser is matched based on the protocol identifier; According to the predefined field structure in the device attribute field library, the payload data in the non-standard data packet is obtained; The payload data is converted to a unified unit, encapsulated into a standardized data stream in JSON format, and injected into the corresponding device unique identifier field in the object model.

6. The intelligent construction equipment management and control method based on a material model according to claim 5, characterized in that, Obtaining the payload data from the non-standard data packet includes: The corresponding data acquisition template is loaded according to the protocol identifier. The data acquisition template includes field position index and data type definition. Based on the predefined valid data location index in the device attribute field library, locate the start and end positions of the payload data; If the payload data is detected to be stored in a segmented structure, the payload data is reassembled according to the offset parameter in the field structure. The encrypted payload data is decrypted in real time using a key bound to the protocol identifier; Verify the checksum of the recombined payload data, delete the non-standard data packets that failed the verification, and generate an error log.

7. The intelligent construction equipment management and control method based on a material model according to claim 1, characterized in that, Based on the data forwarding rule tree, the standardized data stream is distributed to the storage nodes, including: Traverse the path from the root node to the leaf node of the data forwarding rule tree, wherein the root node selects a branch according to the device type field in the standardized data stream, the intermediate nodes match the storage strategy according to the data sensitivity, and the leaf nodes are associated with the storage node address; When the standardized data stream carries real-time control commands, it is preferentially distributed to edge computing nodes and stored locally. For non-real-time monitoring data, the data is selected to be distributed to the cloud storage center or local storage is executed based on the data sensitivity. The load of the leaf node is monitored in real time during the distribution process, and when the response delay of the leaf node exceeds the delay limit, the system dynamically switches to the leaf node with a lower load.

8. The intelligent construction equipment management and control method based on a material model according to claim 7, characterized in that, When the standardized data stream is detected to deviate from a preset anomaly detection threshold, a dynamic early warning signal is generated, including: Device status parameters are obtained from the standardized data stream; Based on the device type field associated with the leaf node of the data forwarding rule tree, obtain the predefined device risk level in the object model; Select the corresponding anomaly detection threshold according to the equipment risk level, and trigger the dynamic early warning signal when the equipment status parameter continuously exceeds the anomaly detection threshold; Based on the data access permissions centrally allocated according to the access authentication rules, determine the set of early warning recipients; The dynamic early warning signal is distributed to the set of early warning receivers according to the data forwarding rule tree.

9. A smart construction equipment control system based on a physical model, characterized in that, The system includes: The object model definition module defines a dynamically extensible object model at the kernel layer. The object model includes a device attribute field library, an access authentication rule set, and a data forwarding rule tree. The identity verification module responds to heterogeneous device access requests, verifies the digital certificates or identity information submitted by the heterogeneous devices based on the access authentication rule set, and assigns data access permissions and control permissions according to the functional roles of the heterogeneous devices. The standard mapping module parses the communication protocol type when an authorized heterogeneous device uploads a non-standard data packet, and maps the non-standard data packet into a standardized data stream according to the device attribute field library. The dynamic early warning module distributes standardized data streams to storage nodes based on a data forwarding rule tree. When a standardized data stream deviates from a preset anomaly detection threshold, a dynamic early warning signal is generated. The encapsulation and distribution module executes and distributes control commands according to the control permissions assigned during the authentication phase, and feeds back the current status of heterogeneous devices and dynamic early warning signals to the user interface in real time.

10. The intelligent construction equipment management and control system based on a material model according to claim 9, characterized in that, The standard mapping module includes: The identifier resolution unit parses the protocol identifier from the header of non-standard data packets and matches the corresponding protocol parser based on the protocol identifier; The payload unit retrieves payload data from non-standard data packets based on the predefined field structure in the device attribute field library. The field matching unit performs unit standardization conversion on the payload data, encapsulates it into a standardized data stream in JSON format, and injects it into the corresponding device unique identifier field in the object model.

Images