CN117478582A - Oil field production equipment state monitoring and optimizing method based on intelligent link management system - Google Patents
Oil field production equipment state monitoring and optimizing method based on intelligent link management system Download PDFInfo
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Abstract
The invention relates to an oilfield production equipment state monitoring and optimizing method based on an intelligent link management system. Firstly, a main server is used for carrying out periodic link connectivity test on production equipment, and equipment state information is obtained in real time. And secondly, realizing self-learning of the link topology by using an intelligent link management system, and establishing a connection relationship between devices. The transmission efficiency between the devices is then determined by evaluating the link communication capabilities in real time. Further, the key nodes of the link are evaluated, and nodes which have important influence on the overall communication quality are identified. On the basis, a link resource library is established, and the communication characteristics and performance parameters among the devices are recorded. Meanwhile, an adaptation rule is formulated, and the allocation strategy of the link resource is dynamically adjusted according to factors such as the data length, the real-time requirement, the importance degree and the like. By realizing the auto-negotiation of the link communication resources, the system can flexibly configure the communication resources according to actual demands, and the communication efficiency is improved. And finally, carrying out real-time evaluation feedback on the service quality of the link, providing data support for optimization adjustment, and ensuring the stable operation of oilfield production equipment.
Description
Technical Field
The invention belongs to the technical field of industrial automation and network communication. The intelligent link management system is used for realizing the intelligent link management and communication optimization of the oilfield production equipment by establishing a main server.
Background
With the continuous improvement of informatization and automation level of oil wells, detection and control by traditional production equipment cannot meet actual production requirements. In order to more fully master the operation condition of the oilfield production equipment, a more efficient, safe and reliable intelligent link management system is needed for the real-time monitoring and management of the oilfield production equipment.
At present, aiming at an intelligent management system of oilfield production equipment, only monitoring and control of the state of the production equipment are often paid attention to, and the intellectualization of a data transmission link is omitted. This results in limited real-time performance of the conventional monitoring method, and failure to acquire status information of the device in real time, resulting in failure to respond in time when a failure occurs. The connectivity monitoring capability for communication links between production facilities is limited and often the stability of the links cannot be effectively detected. The lack of a comprehensive evaluation mechanism for the quality of service of the link cannot accurately evaluate the performance of the link. Once a fault occurs, it is difficult to locate and take corresponding treatment measures.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides an oil field production equipment state monitoring and optimizing method based on an intelligent link management system, which can realize intelligent communication between a main server and oil field production equipment and is beneficial to real-time monitoring and intelligent management of the oil field production equipment.
The technical scheme adopted by the invention for achieving the purpose is as follows:
the intelligent link management system comprises a main server, a display module and a plurality of sub-production devices, wherein the display module and the sub-production devices are respectively connected with the main server, and the main server comprises:
the link connection periodic test module is used for carrying out connectivity test on each sub-production device and alarming the sub-production devices which do not pass the connectivity test;
the link communication real-time detection and evaluation module is used for sending test requests to each sub-production device at regular time according to a set period and evaluating the communication real-time of the link of the sub-production device according to response data;
the link topology self-learning module is used for automatically identifying and finding the connection relation between the production devices and generating a graphical topological structure;
the link key node evaluation module is used for acquiring node data in the topological structure, selecting key nodes according to the node data and evaluating the key nodes regularly;
the link communication resource library module is used for storing nodes and link data in the topology;
the link communication resource negotiation module is used for detecting the communication resource utilization condition of each link in the topology in real time and dynamically adjusting and optimizing the communication resource utilization condition;
and the link service quality evaluation feedback module is used for monitoring the performance index of the link in the topology in real time and evaluating the link.
The method comprises the following steps:
the link connection periodic test module performs connectivity test on each sub-production device and alarms on sub-production devices which do not pass the connectivity test;
the link communication real-time detection and evaluation module sends test requests to each sub-production device at regular time according to a set period, and evaluates the communication real-time of the link of the sub-production device according to response data;
the link topology self-learning module automatically identifies and discovers the connection relation between the production devices and generates a graphical topological structure;
the link key node evaluation module acquires node data in the topological structure, selects key nodes according to the node data, and evaluates the key nodes regularly;
the link communication resource library module stores nodes and link data in the topology;
the link communication resource source negotiation module detects the communication resource utilization condition of each link in the topology in real time and dynamically adjusts and optimizes the communication resource utilization condition;
and the link service quality evaluation feedback module monitors the performance index of the link in the topology in real time and evaluates the link.
The link connectivity periodicity test module performs the steps of:
after initializing the tested parameters by the system, sending connectivity test requests to each sub-production device one by one, and waiting for the response of each sub-device;
recording the test result after receiving the response of the sub-production equipment, if the response of a certain sub-production equipment is not received, sending a second connectivity test request to the sub-production equipment, and if the response is not received yet, sending alarm information;
and (5) until all the sub-production devices are traversed, completing connectivity test.
The link communication real-time detection and evaluation module performs the following steps:
setting an evaluation period and a parameter threshold before detection, configuring detection parameters, and selecting detection indexes;
sending test data packets to each sub-production device at regular time according to the evaluation period, waiting for the response of the sub-devices, and recording the real-time detection result;
judging whether the parameters detected in the response data exceed an index threshold value, and giving alarm information if the parameters are detected in the response data exceed the index threshold value.
The link topology self-learning module performs the steps of:
acquiring the connection relation between each sub-production device and each device in the network by monitoring and analyzing the link data in real time;
scanning each sub-production device, acquiring device information, and matching with the configuration information stored in the main server;
analyzing the collected data by using a graph theory algorithm, generating a topological structure of the system according to the source address and the target address, and updating in real time;
detecting whether a loop exists in the communication link according to the collected data, if the loop exists, discarding the data packet by the system to reduce the duration of the loop, sending an error message notice, displaying error detailed information, tracking the specific position of the loop, determining which device paths cause the loop and adjusting the topology structure of the link.
The link key node evaluation module performs the steps of:
collecting data of each node in the network topology, wherein the data comprises the type, the model, the IP address, the MAC address, the network traffic, the load and the delay of the node;
determining an evaluation index for evaluating the importance of the node, and distributing weights to each index, wherein the indexes comprise the load condition, the communication frequency and the connection number of the node;
according to the evaluation index and the weight, calculating the score of each node;
and taking the node with the score meeting the threshold value as a key node, updating and evaluating the key node periodically, and adjusting the weight, the index and the threshold value according to the result of evaluating the key node.
The score of each node is calculated, specifically:
the following three factors need to be considered in the evaluation of the critical nodes: connectivity factor C, data traffic factor F, and failure impact factor I, wherein:
c represents the number and quality of nodes connected to other nodes, using a score of 0 to 1, where 1 represents perfect connectivity and 0 represents no connection, calculated by:
c= (number of connections of node/maximum possible number of connections) connectivity weight w_c;
f represents the data traffic passing over the node, calculated using the percentage of the data traffic actually passing over the node:
f= (data traffic actually passing through the node/total data traffic) ×data traffic weight w_f;
i represents the influence degree of the node fault on the network, if the node fault can cause the interruption of the whole network, the score of the factor is 1, otherwise, the factor is 0, and the specific steps are as follows:
finally, the composite score S of the node is obtained by weighted averaging of three factors:
S＝(w_c*C)+(w_f*F)+(w_i*I)。
the link communication resource library module performs the steps of:
storing the link resource information, the link attribute, the topological structure and the production equipment information which need to be stored in a database, and simultaneously establishing a resource index;
setting and storing a link resource library management strategy, wherein the strategy comprises link resource allocation and scheduling;
setting a permission control mechanism and a periodic updating mechanism of a link resource library.
The link communication resource source negotiation module performs the following steps:
acquiring a communication request, identifying whether available communication resources exist in a link communication resource library module, if so, sending a link resource negotiation request to the other party by one party requesting communication, otherwise, rejecting the negotiation request and sending prompt information, wherein the link resource negotiation request comprises a preferred value of communication parameters and communication requirements;
after receiving the negotiation request, the other party responds to the negotiation response, wherein the response comprises the acceptance, rejection or modification of the negotiation request and corresponding parameters, and the two parties verify the response parameters, and if the parameters are not matched or supported, the negotiation fails; when the link communication parameters of both parties agree, the negotiation is completed;
the two communication parties exchange respective preferred values or requirements and determine final negotiation parameters by using a negotiation algorithm, wherein the preferred values comprise the negotiation parameters;
and adapting communication resources, and simultaneously, automatically optimizing communication resource allocation according to the real-time monitored data length, the loads of links and nodes and response time.
The link service quality evaluation feedback module performs the following steps:
obtaining performance index data of each link in the topology, wherein the performance index data comprises: delay, packet loss rate, bandwidth utilization;
and evaluating the performance of the link based on a preset quality of service standard, and triggering an alarm mechanism when the quality of service of the link is lower than a set threshold.
The invention has the following beneficial effects and advantages:
1. compared with the traditional oilfield production equipment management which focuses on data acquisition and monitoring, the real-time evaluation and optimization of the communication quality between the equipment are realized.
2. Compared with the traditional network topology maintenance and updating which requires manual intervention, the self-learning of the link topology structure is realized, and the device can be better adapted to the frequent change of the device in the oilfield environment.
3. Compared with the traditional link state monitoring which usually relies on manual inspection or fixed-period testing, the real-time link optimization and resource allocation are realized.
4. In the aspect of communication resource matching, the method for dynamically matching and optimizing the communication resources is realized according to the data characteristics and the real-time requirements.
Drawings
FIG. 1 is a block diagram of an intelligent management system for oilfield production equipment links of the present invention.
Fig. 2 is a flow chart of the link connectivity periodicity test of the present invention.
Fig. 3 is a flow chart of the link connection real-time detection of the present invention.
Fig. 4 is a flow chart of the self-learning of the link topology of the present invention.
Fig. 5 is a flow chart of link critical node state evaluation of the present invention.
Fig. 6 is a flow chart of the link resource negotiation of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
The invention relates to oil field production equipment based on an intelligent link management system, and a system frame diagram is shown in fig. 1. The system mainly comprises: display module, main server and branch production facility.
The display module is connected with the main server through a corresponding interface, has a certain interaction function and supports the design of a user interface.
The main server integrates a plurality of modules such as a network communication module, a link connection periodicity testing module, a link communication real-time detection and evaluation module, a link key node evaluation module, a link communication resource negotiation module, a link topology self-learning module, an alarm module, a link service quality evaluation feedback module and the like. As the core of the system. The main server is equipped with necessary hardware such as a high-performance processor, a large-capacity memory, a high-speed network interface, a storage device and the like, so that the high-efficiency and stable operation of the system is ensured. The main server also has high reliability, stability and security, and has a remote management function so that an administrator can remotely monitor and manage the state and configuration of the system. In addition, the main server has a certain expansibility, so that additional hardware modules or expansion functions can be added when needed.
The main server is connected with petroleum production equipment distributed in various places through an industrial internet through a bus. The production equipment realizes the transmission of sensor data and the control of the actuator in a wireless mode.
In order to achieve intelligent management of the communication links, the required functions are implemented in a modular form. The implementation flow chart of the link connection periodic test module is shown in fig. 2, and the system initializes the parameters of the test, and connects the main server with each production device in a bus and wireless manner through the industrial internet. And then sending a connectivity test request, waiting for the response of each piece of equipment, recording the test result after receiving the response of the piece of equipment, sending a second connectivity test request to the piece of equipment if the corresponding response is not received, and sending alarm information if the response is not received yet. And (3) completing connectivity test until all the sub-devices are traversed, and then automatically testing according to a preset time interval. The module can independently execute the test flow without manual intervention. The link state between each production equipment can be monitored in real time, and the link state comprises information such as connection state, data transmission rate and the like. Once the link connectivity is found abnormal, an alarm signal can be generated in time.
The flow chart of the link communication real-time detection evaluation module is shown in fig. 3, the system is started, and the system parameters are initialized. Setting an evaluation period and a parameter threshold before detection, configuring detection parameters, and selecting detection indexes. And starting a link real-time detection program, sending a test data packet to the sub-equipment by the main server, waiting for the response of the sub-equipment, and recording the real-time detection result. Judging whether the detected parameters exceed a threshold value, and giving alarm information if the detected parameters exceed the threshold value. The link communication real-time detection evaluation module tests according to a set period, periodically collects real-time detection data, and analyzes the data to know the real-time performance of the link. Reports are generated periodically for assessing communication timeliness, analyzing communication quality and providing real-time feedback. And according to the real-time detection result, adopting corresponding measures to perform optimization, wherein the optimization may comprise equipment adjustment, network topology adjustment and the like.
The flow chart of the link topology and self-learning module is shown in fig. 4, after the system is started, the main server establishes connection with the sub-equipment through the previous steps, the main server discovers the equipment in the network through scanning, collects the relevant information of the equipment, matches with the configuration information stored in the main server, and ensures that the main server and the equipment are correctly connected to analyze the topology information. Devices in the network and their connection relationships are automatically identified and discovered by listening and parsing the link data. Analyzing and processing the collected data, and generating the topological structure of the system according to the source address and the target address by using a graph theory algorithm. The system updates the system topology structure in real time according to the real-time communication condition, the link load condition and the like and supports the multi-level topology. Meanwhile, the module can automatically learn loop detection through a time-to-live mechanism, a recursive path inspection and the like, and can detect and process loops possibly existing in a topological structure, so that the occurrence of data packet circulation or communication dead circulation is avoided. Taking the security of the topology into account, corresponding security measures are provided, and a firewall is arranged to protect the topology information from unauthorized access. In addition, the module can map the automatic learning update link topological structure into a graphical topological structure, so that the connection condition between devices can be intuitively known. The topology structure can be dynamically updated in real time to reflect the change of the connection state such as the addition and removal of the devices.
The flow chart of the link key node evaluation module is shown in fig. 5, and after the system establishes the overall topology structure of the network and the connection relation between the nodes, data about each node is collected, including data of the type, the model, the IP address, the MAC address, the network traffic, the load, the delay and the like of the node. Indicators for evaluating the importance of the node are determined, including the load condition of the node, the communication frequency, the number of connections, and the like. Each evaluation index is assigned a respective weight in order to reflect their relative importance in the node importance evaluation. And applying corresponding evaluation indexes and weights to each node, and calculating the score of each node. And setting a threshold value, and screening out key nodes of the link according to the node score. And analyzing communication data, detecting whether the communication state of the key node is abnormal, and if the communication state of the key node is abnormal, switching the standby node according to the link resource library and the link resource source negotiation module to ensure the communication state of the system. And simultaneously sending an alarm signal and displaying the specific information of the node. And updating the evaluation regularly to generate an evaluation report. And automatically adjusting weights, indexes and thresholds according to the result of the evaluation of the key nodes so as to ensure the accuracy and rationality of the evaluation.
And the link communication resource library module is established to collect communication link data including detailed information such as the model, manufacturer, communication interface and the like of terminal production equipment, bandwidth, delay and other key parameters. The communication resource condition of each device is recorded, including information of IP address, MAC address, port, etc. for subsequent configuration and management. And providing a description of the physical connection relation between links, including information such as connection modes, topological structures and the like between the devices. And then storing the collected data into a database to ensure the accuracy and the integrity of the information. And sort the stored information for quick search and management. To facilitate the retrieval and lookup of the resource library, a corresponding resource index needs to be established. And (3) formulating a link resource library management strategy according to specific requirements, wherein the strategy comprises link resource allocation, scheduling and the like. When there is a communication demand, the link resource library module can cooperate with the link communication resource auto-negotiation module to select and allocate optimal communication link resources from the resource library. The use condition of the resources is recorded, the use condition of the resources is monitored in real time, the use condition of the resources comprises the occupation condition of the resources, the running state, the CPU, the memory use rate performance index and the like, and the normal use of the link resources is ensured. After the communication is completed, the allocated resources are timely recovered and released so that other equipment can use the resources, and when the use of the resources reaches a certain threshold or an abnormal condition occurs, an alarm mechanism is triggered. The security of the link resource library is considered, the corresponding authority control mechanism is set, and only authorized users can access and modify the information in the link resource library and set an encryption or authentication mechanism at the same time, so that the integrity and confidentiality of the link resource library are protected. In order to reflect the latest state and configuration information of the device, the link resource library may be updated periodically, and a mechanism for updating the link resource library periodically is set.
Link communication resources negotiation module a flow chart is shown in fig. 6, and when the system is started, and a communication request of the device is acquired, the available communication resources are identified through the link resource library. Judging whether available link resources exist or not, if not, rejecting the negotiation request and sending prompt information; if link resources are available, a link resource negotiation request is sent. Communication parameters are negotiated according to the communication requirements and the resource characteristics. After receiving negotiation responses of other devices, analyzing the responses to determine optimal link negotiation communication parameters. And adapting communication resources, and simultaneously, automatically optimizing communication resource allocation according to the real-time monitored data length, the loads of links and nodes and response time. The link communication resource source negotiation module can detect the communication resource utilization condition of each link in real time. And analyzing the communication requirements among production equipment, including requirements on data length, real-time performance requirements, importance degree and the like. And an intelligent algorithm and a strategy are adopted, and communication resources are automatically allocated and adjusted according to the communication requirements, the real-time performance, the priority and the real-time resource condition. The method optimizes the communication performance of the links, has the capability of dynamically adjusting resource allocation, realizes load balancing among a plurality of links, and avoids performance degradation caused by excessive utilization of certain link resources. The self-adaptive fault processing can adaptively select a resource allocation strategy according to the change of a communication environment and the requirement of equipment, and can timely adjust the resource allocation when a link or a node fails.
Determination of negotiation parameters: first, the communication parties are required to exchange preference values, and first, the communication parties exchange respective preference values or requirements. These preference values typically include various parameters negotiated such as encryption algorithm, data transfer rate, compression algorithm, etc. The two parties to the communication use a negotiation algorithm to determine the final negotiation parameters. The algorithm needs to consider the preference values of both parties and select parameters supported by both parties. Parameters with sufficient security are selected to meet the security requirements of the communication, taking into account the security of the link communication. Parameters that provide good performance under given network conditions are selected taking into account the performance of the link communication. Priority of link communication: if multiple parameters are selected, the final communication parameters can be determined based on the priority, and in the communication process, the two parties can periodically update the negotiated parameters according to indexes such as bandwidth of the link communication resource, delay condition of data transmission, packet loss rate, availability and safety of the link communication resource, bandwidth utilization rate of the link communication resource, fault tolerance of the link communication resource and the like to determine the optimal link negotiation communication parameters.
The link service quality evaluation feedback module can monitor the performance index of the link in real time, such as delay, packet loss rate, bandwidth utilization rate and the like. The performance of the link can be evaluated based on a pre-set quality of service criterion or threshold. The method has the capability of feeding back the service quality evaluation result of the link to the control center in real time. Can identify problems or faults that may exist in the link and provide relevant diagnostic information. When the service quality of the link is lower than a set threshold value, an alarm mechanism can be triggered to inform related personnel in time. The historical data of the link quality of service can be recorded and stored for subsequent analysis and comparison.
Examples
Link connectivity periodicity test module: the timing test device has a timing test function, and can automatically test at preset time intervals. The automatic test program is provided, and the test flow can be independently executed without manual intervention. The method comprises the following steps of real-time monitoring of the link state: the link state between each production equipment can be monitored in real time, and the link state comprises information such as connection state, data transmission rate and the like. The system has a fault detection and alarm mechanism, and can generate an alarm signal or inform related personnel in time once the link connectivity abnormality is found. The method has the advantages of recording and counting results of each connectivity test, including test time, link state and other information, so as to facilitate subsequent analysis and reference. The method has flexible configuration parameters, and can flexibly configure test parameters such as test intervals, test time periods and the like according to requirements so as to adapt to different practical application scenes.
The following steps are performed:
step 1: when the equipment is connected to the main server for the first time, a registration request is sent to the main server or a registration page is provided on the main server, the main server acquires relevant information of the equipment, including id, MAC address and geographic position information of the equipment, and configuration information is stored in the main server;
step 2: setting a link connection detection period according to the link connection condition;
step 3: the method comprises the steps that a total server sends a test data packet in a bus+star mode, and the connectivity condition of links between the main server and each device is tested;
step 4: the master server performs daily polling on each piece of equipment in a bus+star communication mode, and detects the link connection condition with each piece of equipment and the state of each piece of equipment. Detecting the transmission condition of a data packet, recording response time, and updating the link state;
step 5: the main server detects that a certain link or node is abnormal, and other available communication links or communication nodes are actively switched by utilizing modules such as link resource auto-negotiation, link topology self-learning, link resource library and the like and related adaptation rules, and meanwhile, related data in each module is updated to ensure the communication state of the equipment;
step 6: aiming at a link or a node with abnormal communication, the main server sends a test data packet again, and if the communication state is still abnormal, the main server sends out alarm information, displays abnormal information and prompts a manager to maintain.
Link communication real-time detection and evaluation module: after the main server and the sub-equipment are successfully communicated, the real-time performance of the link communication needs to be detected and evaluated. The following steps are performed:
step 1: setting an evaluation period;
step 2: configuring monitoring parameters: the method comprises the steps of monitoring target equipment or nodes, monitoring modes and the like;
step 3: selecting monitoring indexes: including delay, packet loss rate, bandwidth utilization, etc.;
step 4: setting an alarm and a threshold value, wherein when certain indexes exceed the set range, the system can automatically give out the alarm so as to take measures in time;
step 5: and starting a link real-time detection program to test according to a set period. Periodically collecting real-time detected data, and analyzing the data to know the real-time performance of the link;
step 6: recording the real-time detection result, and periodically generating a report for evaluating the communication real-time performance, analyzing the communication quality and providing real-time feedback;
step 7: and according to the real-time detection result, adopting corresponding measures to perform optimization, wherein the optimization may comprise equipment adjustment, network topology adjustment and the like.
Link topology and self-learning module: the module can automatically identify and discover the connection relation between oilfield production equipment without manual configuration. A multi-level topology may be implemented. Taking the security of the topology into account, corresponding security measures are provided, and a firewall is arranged to protect the topology information from unauthorized access. In addition, the module can automatically learn and update the link topology structure, and map the discovered equipment and the connection relationship into a graphical topology structure, so that the connection condition among the equipment can be intuitively known. The topology structure can be dynamically updated in real time to reflect the change of the connection state such as the addition and removal of the devices. The following steps are performed:
step 1: establishing a correct connection between the device and the main server;
step 2: the equipment information and the topological structure are obtained by monitoring and analyzing the link data to automatically identify and discover the equipment in the network and the connection relation of the equipment;
step 3: starting scanning and discovering equipment in a network, collecting equipment related information, and matching with configuration information stored in a main server to ensure correct connection between the main server and the equipment;
step 4: analyzing topology information, and constructing a topology structure of the system according to the source address and the target address by using a graph theory algorithm. Providing relevant attribute information of each device, such as device type, IP address, MAC address, etc. to facilitate identification and management;
step 5: the system updates the system topology according to the real-time communication conditions. Meanwhile, the module can automatically learn loop detection, can detect and process loops possibly existing in a topological structure, and avoids the occurrence of data packet circulation or communication dead circulation;
link key node evaluation module: the module is capable of identifying critical nodes in the link. Each node can be assigned a respective weight to reflect its degree of importance in the communication network. When the key node fails, the system has the capability of automatically detecting the failure and switching to the standby node. The following steps are mainly executed:
step 1: the method comprises the steps of defining the overall topological structure of a network and the connection relation between all nodes, including directly adjacent nodes and the communication mode between the nodes;
step 2: collecting data about each node, including data of the type, model, IP address, MAC address, network traffic, load, delay, etc. of the node;
step 3: determining indexes for evaluating the importance of the node, including the load condition, communication frequency, connection number and the like of the node;
step 4: assigning a corresponding weight to each evaluation index to reflect their relative importance in the node importance evaluation;
step 5: applying corresponding evaluation indexes and weights to each node, and calculating the score of each node;
step 6: ranking according to node scores, from high to low, to determine which nodes are considered critical nodes;
step 7: setting a threshold value and screening key nodes;
step 8: updating and evaluating regularly, and automatically adjusting weights, indexes and thresholds according to the result of evaluating the key nodes so as to ensure the accuracy and rationality of the evaluation;
a link communication resource library module: the system can collect detailed information of various production devices, including key parameters such as model, manufacturer, communication interface, bandwidth and the like. The communication resource condition of each device is recorded, including information of IP address, MAC address, port, etc. for subsequent configuration and management. And providing a description of the physical connection relation between links, including information such as connection modes, topological structures and the like between the devices. And recording the state information of the equipment, such as running state, CPU, memory utilization rate and other performance indexes, so as to monitor and evaluate the equipment in real time. And (3) carrying out historical record and storage on the data of the link resource library so as to facilitate subsequent data analysis, fault investigation and other works. Encryption or authentication mechanisms are provided to protect the integrity and confidentiality of the link resource library in view of the security of the data. The link resource library may be updated periodically to reflect the latest state and configuration information of the device. The execution steps comprise:
step 1: the method comprises the steps of collecting detailed information of production equipment in an oil field, wherein the information comprises key parameters such as equipment model, manufacturer, communication interface, IP address, MAC address and the like;
step 2: recording the communication resource condition of each device, including IP address, MAC address, port and other information, so as to facilitate subsequent configuration and management;
step 3: establishing a database for storing device information and communication resource data;
step 4: the collected equipment information and communication resource data are input into a database, so that the accuracy and the integrity of the information are ensured;
step 5: setting a corresponding authority control mechanism to ensure that only authorized users can access and modify information in a link resource library;
step 6: setting a mechanism for periodically updating a link resource library to reflect the latest state and configuration information of the equipment;
the link communication resources are derived from a negotiation module: the real-time resource detection can detect the utilization condition of the communication resources of each link in real time, including indexes such as bandwidth, delay and the like. And analyzing the communication requirements among production equipment, wherein the requirements comprise data length, real-time requirements, importance degree and the like. The communication resource intelligent allocation is automatically negotiated, and the communication resource allocation and adjustment are automatically carried out according to the communication requirements, the real-time performance, the priority and the real-time resource condition by adopting an intelligent algorithm and a strategy. The method optimizes the communication performance of the links, has the capability of dynamically adjusting resource allocation, realizes load balancing among a plurality of links, and avoids performance degradation caused by excessive utilization of certain link resources. The self-adaptive fault processing can adaptively select a resource allocation strategy according to the change of a communication environment and the requirement of equipment, and can timely adjust the resource allocation when a link or a node fails. The specific steps of the method comprise:
step 1: a resource identification step of identifying available communication resources according to current communication requirements and available resources;
step 2: negotiating communication parameters, and negotiating optimal communication parameters according to communication requirements and resource characteristics;
step 3: adapting communication resources, applying the negotiated parameters to data transmission, and ensuring high efficiency and stability of communication;
step 4: communication resource optimization, namely automatically optimizing communication resource allocation according to the data length, the loads of links and nodes and response time monitored in real time;
link quality of service assessment feedback module: the module can monitor the performance index of the link in real time, such as delay, packet loss rate, bandwidth utilization rate and the like. The performance of the link can be evaluated based on a pre-set quality of service criterion or threshold. The method has the capability of feeding back the service quality evaluation result of the link to the control center in real time. Can identify problems or faults that may exist in the link and provide relevant diagnostic information. When the service quality of the link is lower than a set threshold value, an alarm mechanism can be triggered to inform related personnel in time. The historical data of the link quality of service can be recorded and stored for subsequent analysis and comparison.
The production equipment comprises a sensor and an actuator which are connected through a wireless network.
The system realizes the high-efficiency communication between the production equipment and the main server by establishing an intelligent main server as a brain core, providing a high-performance processor, a real-time data processing engine, a communication module and a data storage unit, and simultaneously combines the advanced data analysis technology to realize the functions of self-learning of link topology, real-time evaluation of link capacity, establishment of a link resource library, formulation of an adaptation rule and the like.
Claims (10)
1. The intelligent link management system comprises a main server, a display module and a plurality of sub-production devices, wherein the display module and the sub-production devices are respectively connected with the main server, and the intelligent link management system is characterized in that the main server comprises:
the link connection periodic test module is used for carrying out connectivity test on each sub-production device and alarming the sub-production devices which do not pass the connectivity test;
the link communication real-time detection and evaluation module is used for sending test requests to each sub-production device at regular time according to a set period and evaluating the communication real-time of the link of the sub-production device according to response data;
the link topology self-learning module is used for automatically identifying and finding the connection relation between the production devices and generating a graphical topological structure;
the link key node evaluation module is used for acquiring node data in the topological structure, selecting key nodes according to the node data and evaluating the key nodes regularly;
the link communication resource library module is used for storing nodes and link data in the topology;
the link communication resource negotiation module is used for detecting the communication resource utilization condition of each link in the topology in real time and dynamically adjusting and optimizing the communication resource utilization condition;
and the link service quality evaluation feedback module is used for monitoring the performance index of the link in the topology in real time and evaluating the link.
2. The oil field production equipment state monitoring and optimizing method based on the intelligent link management system is characterized by comprising the following steps of:
the link connection periodic test module performs connectivity test on each sub-production device and alarms on sub-production devices which do not pass the connectivity test;
the link communication real-time detection and evaluation module sends test requests to each sub-production device at regular time according to a set period, and evaluates the communication real-time of the link of the sub-production device according to response data;
the link topology self-learning module automatically identifies and discovers the connection relation between the production devices and generates a graphical topological structure;
the link key node evaluation module acquires node data in the topological structure, selects key nodes according to the node data, and evaluates the key nodes regularly;
the link communication resource library module stores nodes and link data in the topology;
the link communication resource source negotiation module detects the communication resource utilization condition of each link in the topology in real time and dynamically adjusts and optimizes the communication resource utilization condition;
and the link service quality evaluation feedback module monitors the performance index of the link in the topology in real time and evaluates the link.
3. The intelligent link management system-based oilfield production equipment status monitoring and optimization method of claim 2, wherein the link connectivity periodicity testing module performs the steps of:
after initializing the tested parameters by the system, sending connectivity test requests to each sub-production device one by one, and waiting for the response of each sub-device;
recording the test result after receiving the response of the sub-production equipment, if the response of a certain sub-production equipment is not received, sending a second connectivity test request to the sub-production equipment, and if the response is not received yet, sending alarm information;
and (5) until all the sub-production devices are traversed, completing connectivity test.
4. The intelligent link management system-based oilfield production equipment status monitoring and optimization method of claim 2, wherein the link communication real-time detection and assessment module performs the following steps:
setting an evaluation period and a parameter threshold before detection, configuring detection parameters, and selecting detection indexes;
sending test data packets to each sub-production device at regular time according to the evaluation period, waiting for the response of the sub-devices, and recording the real-time detection result;
judging whether the parameters detected in the response data exceed an index threshold value, and giving alarm information if the parameters are detected in the response data exceed the index threshold value.
5. The intelligent link management system-based oilfield production equipment status monitoring and optimization method of claim 2, wherein the link topology self-learning module performs the following steps:
acquiring the connection relation between each sub-production device and each device in the network by monitoring and analyzing the link data in real time;
scanning each sub-production device, acquiring device information, and matching with the configuration information stored in the main server;
analyzing the collected data by using a graph theory algorithm, generating a topological structure of the system according to the source address and the target address, and updating in real time;
detecting whether a loop exists in the communication link according to the collected data, if the loop exists, discarding the data packet by the system to reduce the duration of the loop, sending an error message notice, displaying error detailed information, tracking the specific position of the loop, determining which device paths cause the loop and adjusting the topology structure of the link.
6. The intelligent link management system-based oilfield production equipment status monitoring and optimization method of claim 2, wherein the link key node assessment module performs the steps of:
collecting data of each node in the network topology, wherein the data comprises the type, the model, the IP address, the MAC address, the network traffic, the load and the delay of the node;
determining an evaluation index for evaluating the importance of the node, and distributing weights to each index, wherein the indexes comprise the load condition, the communication frequency and the connection number of the node;
according to the evaluation index and the weight, calculating the score of each node;
and taking the node with the score meeting the threshold value as a key node, updating and evaluating the key node periodically, and adjusting the weight, the index and the threshold value according to the result of evaluating the key node.
7. The method for monitoring and optimizing the state of oilfield production equipment based on the intelligent link management system according to claim 6, wherein the calculating the score of each node is specifically as follows:
the following three factors need to be considered in the evaluation of the critical nodes: connectivity factor C, data traffic factor F, and failure impact factor I, wherein:
c represents the number and quality of nodes connected to other nodes, using a score of 0 to 1, where 1 represents perfect connectivity and 0 represents no connection, calculated by:
c= (number of connections of node/maximum possible number of connections) connectivity weight w_c;
f represents the data traffic passing over the node, calculated using the percentage of the data traffic actually passing over the node: f= (data traffic actually passing through the node/total data traffic) ×data traffic weight w_f;
i represents the influence degree of the node fault on the network, if the node fault can cause the interruption of the whole network, the score of the factor is 1, otherwise, the factor is 0, and the specific steps are as follows:
finally, the composite score S of the node is obtained by weighted averaging of three factors:
S＝(w_c*C)+(w_f*F)+(w_i*I)。
8. the intelligent link management system-based oilfield production equipment status monitoring and optimization method of claim 2, wherein the link communication resource library module performs the steps of:
storing the link resource information, the link attribute, the topological structure and the production equipment information which need to be stored in a database, and simultaneously establishing a resource index;
setting and storing a link resource library management strategy, wherein the strategy comprises link resource allocation and scheduling;
setting a permission control mechanism and a periodic updating mechanism of a link resource library.
9. The intelligent link management system-based oilfield production equipment status monitoring and optimization method of claim 2, wherein the link communication resource negotiation module performs the following steps:
acquiring a communication request, identifying whether available communication resources exist in a link communication resource library module, if so, sending a link resource negotiation request to the other party by one party requesting communication, otherwise, rejecting the negotiation request and sending prompt information, wherein the link resource negotiation request comprises a preferred value of communication parameters and communication requirements;
after receiving the negotiation request, the other party responds to the negotiation response, wherein the response comprises the acceptance, rejection or modification of the negotiation request and corresponding parameters, and the two parties verify the response parameters, and if the parameters are not matched or supported, the negotiation fails; when the link communication parameters of both parties agree, the negotiation is completed;
the two communication parties exchange respective preferred values or requirements and determine final negotiation parameters by using a negotiation algorithm, wherein the preferred values comprise the negotiation parameters;
and adapting communication resources, and simultaneously, automatically optimizing communication resource allocation according to the real-time monitored data length, the loads of links and nodes and response time.
10. The intelligent link management system-based oilfield production equipment status monitoring and optimization method of claim 2, wherein the link quality of service assessment feedback module performs the steps of:
obtaining performance index data of each link in the topology, wherein the performance index data comprises: delay, packet loss rate, bandwidth utilization;
and evaluating the performance of the link based on a preset quality of service standard, and triggering an alarm mechanism when the quality of service of the link is lower than a set threshold.
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