Wind turbine generator remote intelligent access control system based on two-ticket linkage and control method

Abstract

The invention provides a wind turbine generator remote intelligent access control system based on two-ticket linkage and a control method. The system comprises a cloud centralized control center, an edge end access control terminal and an execution end, the cloud centralized control center receives and verifies the relevance and validity of the two tickets, and generates a dynamic door opening voucher based on the successfully verified information of the two tickets, the operator information and a preset safety rule; the edge end access control terminal acquires authentication information of the operating personnel; the cloud centralized control center performs matching verification on the authentication information and the dynamic door opening voucher, and sends an encrypted door opening instruction to the execution end when the verification is passed; the execution end unlocks the access control of the target unit; the edge end access control terminal gives an alarm when detecting an abnormal event; after the operation is finished, the cloud centralized control center updates the state of the electronic work ticket and triggers the access control to lock, so that the dynamic access control authority, the remote access control operation and the closed loop of the operation flow and access control are realized, and the safety and the management efficiency of the remote intelligent access control system of the wind turbine generator are improved.

Description

Technical Field

[0001] This invention relates to the field of wind turbine safety management technology, and in particular to a remote intelligent access control system and control method for wind turbines based on two-ticket linkage. Background Technology

[0002] The wind power industry is developing rapidly, and the number of wind turbine units continues to increase. As these units are mostly located in remote and dispersed areas, on-site safety management faces considerable challenges, and access control systems are a key line of defense to ensure the safety of the equipment and personnel.

[0003] Currently, access control for wind turbine units mostly consists of traditional mechanical locks or simple electronic access control systems. Mechanical locks rely on physical keys, which are prone to loss, have a high risk of being lent out, and have low management efficiency. While simple electronic access control systems support passwords or card swipes for opening doors, their authentication methods are limited, their security is poor, and they cannot dynamically adjust access permissions according to operational needs, often leading to issues such as permission abuse or expiration.

[0004] Furthermore, existing access control systems generally lack remote control capabilities, requiring maintenance personnel to operate and authorize on-site operations, which increases management costs. At the same time, access control status is disconnected from operational processes, making it difficult to provide timely warnings of abnormal situations. Manual locking of the access control system is required after operations are completed, failing to create a closed-loop security control system.

[0005] Therefore, in response to the problems of insufficient security, rigid control, and weak remote collaboration of existing access control systems, there is an urgent need for a remote intelligent access control system for wind turbines that can achieve intelligent control and dynamic authorization in order to improve security and management efficiency. Summary of the Invention

[0006] This invention provides a remote intelligent access control system and control method for wind turbine generators based on two-ticket linkage, which solves the problems of insufficient security, rigid access control and lack of remote collaboration capabilities in existing wind turbine generator access control systems, and realizes dynamic access control and remote intelligent access control management based on two-ticket linkage.

[0007] On one hand, the present invention provides a remote intelligent access control system for wind turbine generators based on two-ticket linkage, which includes: This includes a cloud-based control center, edge access control terminals, and execution terminals; The cloud-based centralized control center is used to receive and verify the correlation and validity of the two tickets. Based on the successfully verified ticket information, operator information, and preset safety rules, it generates a dynamic door opening certificate with time and space constraints. The two tickets include an electronic work ticket and an operation ticket. The edge access control terminal is used to collect the authentication information of the operators and send the authentication information to the cloud-based central control center; The cloud-based centralized control center is also used to match and verify the authentication information with the dynamic door opening credential, and send an encrypted door opening command to the execution terminal when the verification is successful. The execution terminal is used to unlock the access control of the corresponding target unit after receiving the door opening command; The edge access control terminal is also used to monitor abnormal events after the access control is opened, and to issue an alarm when an abnormal event is detected; The cloud-based control center is also used to update the status of the electronic work ticket and trigger access control locking after the work is completed.

[0008] On the other hand, the present invention also provides a method for a remote intelligent access control system for wind turbine generators based on two-ticket linkage, which includes: The cloud-based centralized control center receives and verifies the correlation and validity of the two tickets. Based on the successfully verified ticket information, operator information, and preset safety rules, it generates a dynamic door opening certificate with time and space constraints. The two tickets include an electronic work ticket and an operation ticket. The edge access control terminal collects the authentication information of the operators and sends the authentication information to the cloud-based centralized control center; The cloud-based central control center matches and verifies the authentication information with the dynamic door opening credential, and sends an encrypted door opening command to the execution terminal when the verification is successful. Upon receiving the door opening command, the execution unit unlocks the access control for the corresponding target unit. After the access control terminal opens the door, it monitors for abnormal events and issues an alarm when an abnormal event is detected. After the operation is completed, the cloud-based control center updates the status of the electronic work ticket and triggers the access control lock.

[0009] The wind turbine remote intelligent access control system and control method based on two-ticket linkage provided by this invention generates dynamic credentials with spatiotemporal constraints through a cloud-based centralized control center based on two-ticket information, personnel information, and security rules. The edge terminal collects authentication information and uploads it for verification. After successful verification, the execution terminal unlocks the access control. At the same time, the edge terminal monitors anomalies in real time and issues alarms. After the operation is completed, the cloud updates the ticket status and triggers locking. Ultimately, it realizes dynamic access control permissions, remote access control operations, and closed-loop operation of work processes and access control management, effectively improving the security and management efficiency of the wind turbine remote intelligent access control system. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0011] Figure 1 This is a schematic diagram of the structure of the wind turbine remote intelligent access control system based on two-ticket linkage provided in an embodiment of the present invention; Figure 2 This is a flowchart illustrating the remote intelligent access control system method for wind turbine units based on two-ticket linkage provided in an embodiment of the present invention. Detailed Implementation

[0012] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0013] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this invention, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0014] Specifically, Figure 1 This is a schematic diagram of the structure of a remote intelligent access control system for wind turbines based on two-ticket linkage provided in an embodiment of the present invention.

[0015] like Figure 1 As shown, the wind turbine remote intelligent access control system based on two-ticket linkage provided in this embodiment of the invention may include a cloud-based central control center 11, an edge access control terminal 12, and an execution terminal 13; The cloud-based centralized control center 11 is used to receive and verify the correlation and validity of the two tickets. Based on the successfully verified ticket information, operator information, and preset safety rules, it generates a dynamic door opening certificate with time and space constraints. The two tickets include an electronic work ticket and an operation ticket. Edge access control terminal 12 is used to collect the authentication information of operators and send the authentication information to the cloud control center 11; The cloud-based centralized control center 11 is also used to match and verify the authentication information with the dynamic door opening credential, and when the verification is successful, to send an encrypted door opening command to the execution terminal 13. Execution terminal 13 is used to unlock the access control of the corresponding target unit after receiving the door opening command; The edge access control terminal 12 is also used to monitor abnormal events after the access control is opened, and to issue an alarm when an abnormal event is detected; The cloud-based centralized control center 11 is also used to update the status of the electronic work ticket and trigger access control lock after the work is completed.

[0016] In practical applications, the main function of the cloud-based centralized control center 11 is to perform logical verification and permission generation on the two ticket information. For example, correlation verification can be achieved by comparing the task number or equipment identifier in the two tickets, while validity verification can be completed by checking whether the timestamps of the two tickets meet the requirements of the current work period. Furthermore, the process of generating dynamic access vouchers with time and space constraints can be implemented in various ways, such as generating vouchers based on preset permission templates combined with real-time environmental data, or dynamically generating vouchers by calling external authorization service interfaces. This is mainly to achieve dynamic and refined permission management.

[0017] The edge access control terminal 12 functions to collect authentication information and monitor anomalies. Authentication information collection can be achieved through various technologies, such as fingerprint recognition, facial recognition, or RFID tag reading. Furthermore, anomaly monitoring can be achieved by analyzing deviations between operator behavior patterns and preset standard procedures, such as by statistically analyzing usage frequency or monitoring whether the equipment operation sequence meets expectations. Its primary purpose is to enable timely detection and response to potential risks.

[0018] The function of the execution terminal 13 is to unlock the access control system according to encrypted instructions. The generation of these encrypted instructions can employ various encryption algorithms, such as AES or RSA, to ensure the security of the instructions during transmission. Furthermore, the specific implementation of access control unlocking may include electromagnetic drive of a mechanical lock or signal triggering of an electronic lock, primarily to ensure the reliability and security of the access control operation.

[0019] Specifically, the cloud-based centralized control center 11 receives electronic work orders and operation tickets, and verifies their relevance and validity. The relevance verification ensures the logical consistency of work tasks, the matching degree of equipment operation sequences, and the complementarity of security measures, while the validity verification is based on a timeliness verification model, covering issuance timeliness, execution sequence, and conflict detection. This avoids issues such as permission abuse or expiration, ensuring that access control authorization is strictly bound to legal and compliant work processes.

[0020] Furthermore, after successful verification of both tickets, a dynamic access pass with spatiotemporal constraints is generated by combining the operator's information and preset safety rules. This pass not only includes dynamic constraints such as time windows and geofencing, but can also adaptively adjust according to changes in equipment status and environmental conditions, thereby achieving refined management and control. The edge access control terminal 12 is responsible for collecting the operator's authentication information and sending it to the cloud-based central control center 11. By remotely acquiring biometric or identity data in real time, the management burden of requiring on-site authorization by maintenance personnel is eliminated, significantly improving remote collaboration efficiency.

[0021] Specifically, the cloud-based control center 11 matches and verifies the authentication information against the dynamic access credentials. Because the credentials embed a list of permitted personnel and spatiotemporal parameters, the verification process strictly relies on these dynamic elements to determine the legitimacy of the operation, ensuring that access is only granted to matching personnel during authorized times and locations, significantly enhancing security. After successful verification, an encrypted access command is sent to the execution terminal 13. Upon receiving the command, the execution terminal 13 unlocks the access control for the corresponding target unit. The command encryption mechanism prevents tampering during transmission, ensuring the reliability of the access control operation.

[0022] Furthermore, the edge access control terminal 12 continuously monitors for abnormal events after the access control is opened. By analyzing deviations between the operational behavior sequence and the standardized process, it promptly identifies risks such as abnormal tool handling or deviations in movement trajectory, achieving a shift from passive response to proactive early warning. When an abnormal event is detected, an alarm mechanism is triggered.

[0023] Furthermore, upon completion of the work, the cloud-based control center 11 updates the status of the electronic work ticket and triggers the access control lock. By automatically synchronizing the work progress and access control status, closed-loop safety management can be completed without manual intervention, resolving the management disconnect caused by the need for manual locking of access control after work. Overall, this solution deeply embeds the access control system into the work process, using the linkage between the two tickets as the core to drive dynamic permission generation and verification, transforming security management from rigid and static to intelligent and flexible, effectively improving the protection capabilities and operational efficiency of wind turbine access control.

[0024] In some embodiments, the present invention further proposes a cloud-based centralized control center 11, including a parsing module, a correlation verification module, a validity verification module, an evaluation module, a generation module, and a synchronization module. The parsing module is used to parse the structured data of the two tickets and extract key verification elements. The correlation verification module is used to perform correlation verification on the two tickets based on the key verification elements and a preset ticket correlation rule base; correlation verification includes job task logic consistency verification, equipment operation sequence matching degree verification, and safety measure complementarity verification. The validity verification module is used to perform timeliness validity verification on the two tickets based on a timeliness verification model; timeliness validity verification includes issuance timeliness verification, execution sequence verification, and conflict detection. The evaluation module is used to call the safety rule engine to perform a comprehensive risk assessment by combining equipment status data, environmental monitoring data, and operator qualification information when both correlation and validity verifications pass. The generation module is used to generate a dynamic access voucher with spatiotemporal constraints based on the risk assessment results and the two ticket information. The synchronization module is used to digitally sign and encrypt the generated dynamic access voucher, store it in a distributed voucher database, and synchronize it to the edge access control terminal 12.

[0025] Specifically, the parsing module is a functional unit capable of extracting standardized information from unstructured or semi-structured ticket data. It can be implemented using natural language processing techniques or regular expression matching algorithms, aiming to provide a unified data input source for subsequent verification. The correlation verification module is a component that verifies tickets based on multi-dimensional logical relationships. It can be implemented by building knowledge graphs or rule-based reasoning engines, aiming to ensure the coordination and integrity of work tickets and operation tickets in terms of task objectives, operational steps, and security measures. The validity verification module is a functional unit that dynamically evaluates the time attributes of tickets. It can be implemented using time series analysis models or conflict detection algorithms, aiming to verify the time validity of tickets and their compatibility with other tasks. The evaluation module is a component that integrates multi-source data for risk quantification analysis. It can be implemented using ensemble learning algorithms or multi-factor weighted models, aiming to provide a scientific basis for the generation of dynamic access vouchers. The generation module is a unit that generates permission constraint functions based on risk assessment results. It can be implemented using encoding algorithms or encryption protocols, aiming to ensure the dynamism and timeliness of vouchers. A synchronization module is a functional unit that ensures the security and consistency of data transmission. It can be implemented using blockchain technology or distributed storage protocols, with the aim of improving the security and reliability of credential management.

[0026] Specifically, the parsing module first transforms the data on both tickets into a structured form, providing standardized input for subsequent verification. The correlation verification module, based on extracted key verification elements and a pre-defined ticket correlation rule base, deeply analyzes the logical dependencies between the two tickets. For example, the task logic consistency verification ensures no conflict between the task objectives of the work ticket and the operation ticket; the equipment operation sequence matching verification verifies the temporal consistency between operation steps and equipment status; and the safety measure complementarity verification identifies the completeness of safety measures coverage. The validity verification module, through a timeliness verification model, dynamically evaluates the matching degree between the issuance time and the work plan, the compliance of the execution order of operation steps, and resource conflicts between multiple tasks, thereby preventing operational risks caused by expired tickets or reversed time sequences. After both correlation and validity verifications pass, the evaluation module calls the safety rule engine to conduct a comprehensive risk assessment combining equipment status data, environmental monitoring data, and operator qualification information. This achieves multi-source data fusion analysis, expanding risk assessment from a single dimension to a collaborative judgment of equipment, environment, and personnel. The generation module generates dynamic access vouchers with spatiotemporal constraints based on risk assessment results and two sets of ticket information. By limiting the voucher's usage window and geographical scope, it avoids the rigidity problem of fixed permissions. The synchronization module digitally signs and encrypts the generated dynamic access vouchers, and stores them in a distributed voucher repository. This ensures the integrity and tamper-proof nature of the vouchers during transmission and storage, while also improving the reliability of voucher access.

[0027] In some embodiments, the present invention further provides a generation module, including: The risk assessment mapping unit is used to quantify the risk assessment results into risk levels and determine the corresponding authority constraint strength based on a preset risk and authority mapping table. The spatiotemporal constraint calculation unit is used to dynamically calculate the authorized time window and three-dimensional geofence based on the work plan time period, equipment location coordinates and work radius in the two ticket information, combined with meteorological data and equipment operating status. The dynamic factor generation unit is used to generate time-sensitive dynamic passwords based on the current timestamp, device serial number, and random seed using an encryption algorithm. The credential combination engine is used to combine and encode at least one of the following: permission constraint strength, authorization time window, 3D geofence, dynamic password, and list of allowed operators, to generate dynamic access credentials. The adaptive adjustment unit is used to adjust the authorization time window and three-dimensional geofence based on real-time monitoring of changes in equipment status or sudden changes in weather conditions within the validity period of the credential.

[0028] The risk assessment mapping unit is a functional module that transforms abstract risk assessment results into specific and operable access control parameters. It can be implemented using a hierarchical mapping table or a nonlinear function model, aiming to ensure that access allocation matches the actual risk level. The spatiotemporal constraint calculation unit can be understood as a dynamic boundary calculation tool based on multi-source data fusion. It can be implemented through a geographic information system combined with a real-time meteorological interface or equipment status monitoring platform, aiming to flexibly adapt the validity scope of credentials to the complex environment of wind power sites. The dynamic factor generation unit is a component that uses specific algorithms to generate time-sensitive and unique security verification elements. It can be implemented using a hash algorithm combined with a random number generator or a time synchronization mechanism, aiming to enhance the security and anti-counterfeiting capabilities of credentials. The credential combination engine is a multi-dimensional information integration tool, implemented through a rule engine or encoding protocol, aiming to organically integrate multiple security elements to form a complete credential carrier. The adaptive adjustment unit is a dynamic control module with environmental perception and parameter optimization capabilities. It can be implemented using an event-driven architecture or a real-time feedback control system, aiming to ensure that credential parameters can respond promptly to emergencies.

[0029] Specifically, the risk assessment mapping unit first transforms the comprehensive risk assessment results into specific permission constraint strengths. The spatiotemporal constraint calculation unit, based on multi-dimensional data such as work plans, equipment locations, and weather conditions, accurately calculates the authorization time window and three-dimensional geofence, ensuring a high degree of match between the credential's effective scope and actual operational needs. The dynamic factor generation unit generates a time-sensitive and unique dynamic password by introducing elements such as timestamps, equipment serial numbers, and random seeds, significantly improving credential security. The credential combination engine organically integrates the core security elements generated by the aforementioned units, forming a dynamic access credential containing multi-dimensional information such as risk, spatiotemporal, and identity. The adaptive adjustment unit continuously monitors environmental changes throughout the credential's validity period. When abnormal equipment status or sudden changes in weather conditions are detected, it can promptly adjust authorization parameters to ensure the access control system remains in a secure and controllable state.

[0030] In some embodiments, the present invention further provides an evaluation module, including: The risk quantification unit is used to calculate the risk level, environmental risk level and personnel suitability level based on the standardized data provided by the data aggregation unit through the equipment risk sub-model, environmental risk sub-model and personnel risk sub-model respectively. The fusion assessment engine receives equipment risk level, environmental risk level, and personnel suitability level, calls the built-in weighted fuzzy inference rule base or risk matrix, performs multi-source data fusion calculation, and outputs a comprehensive risk assessment result.

[0031] The risk quantification unit is a component capable of independently processing multi-source data and outputting structured risk levels. It can be implemented using a distributed computing framework or a dedicated algorithm module. The unit is designed to ensure that the assessment processes for equipment, environmental, and personnel risks are highly specialized and do not interfere with each other, thus laying the foundation for subsequent risk fusion. The fusion assessment engine is a component used to integrate multi-dimensional risk data and generate comprehensive assessment results. It can be implemented through embedded intelligent algorithms or cloud-based collaborative computing. The introduction of this engine aims to scientifically allocate the weights of each risk dimension, avoiding assessment distortion caused by simple aggregation, thereby improving the objectivity of risk assessment and its decision support capabilities.

[0032] Specifically, the risk quantification unit, based on standardized data provided by the data aggregation unit, independently calculates risk levels using equipment risk sub-models, environmental risk sub-models, and personnel risk sub-models to output equipment risk level, environmental risk level, and personnel suitability level. The fusion assessment engine receives these risk levels and uses its built-in weighted fuzzy inference rule base or risk matrix to perform multi-source data fusion calculations. Through scientific weight allocation, it effectively integrates the interactive effects of equipment, environmental, and personnel risks, ultimately outputting a comprehensive risk assessment result.

[0033] In some embodiments, the present invention further proposes an equipment risk sub-model comprising: an extraction unit for extracting key operating parameters and fault codes from equipment status data; an analysis unit for comparing key operating parameters with preset safety thresholds and analyzing their short-term trends; and an equipment risk level calculation unit for calculating the equipment risk level by combining the urgency and trend of fault codes with predefined equipment risk assessment rules.

[0034] The extraction unit can be implemented using data acquisition cards, sensor networks, or industrial communication protocols to ensure the comprehensiveness and real-time nature of the risk assessment input data. The analysis unit can identify gradual deviations in parameters using sliding window algorithms, time series analysis, or machine learning models to improve the timeliness of risk warnings. The equipment risk level calculation unit can be implemented using fuzzy logic reasoning, weighted scoring algorithms, or decision tree models to avoid assessment distortion caused by ignoring differences in the impact of faults or state evolution.

[0035] Specifically, the extraction unit extracts key operating parameters and fault codes from equipment status data. The analysis unit not only compares key operating parameters with preset safety thresholds but also focuses on analyzing their short-term trends. This trend analysis can identify gradual deviations in parameters; for example, a continuous upward trend in temperature or vibration parameters may indicate potential faults, thereby improving the timeliness of risk warnings. The equipment risk level calculation unit combines the urgency of fault codes with parameter change trends to calculate the equipment risk level using predefined rules. This comprehensive consideration mechanism makes risk assessment more closely aligned with actual operating conditions, ultimately achieving accurate quantification of equipment risk levels.

[0036] In some embodiments, the present invention further proposes an equipment risk level calculation unit, specifically used for: constructing a fault knowledge base containing fault codes, urgency levels, and weight coefficients, wherein the urgency level is divided based on the immediate impact of the fault on the safe operation of the equipment; receiving and parsing the equipment status data stream from the target wind turbine in real time, extracting the real-time fault code set and key operating parameter sequence from the equipment status data stream; matching the real-time fault code set with the fault knowledge base to map the corresponding urgency level, and calculating the fault dimension risk value based on the weight coefficient; performing sliding window trend analysis on the key operating parameter sequence to identify the magnitude and rate of change of its deviation from the preset safety threshold, and calculating the parameter trend risk value; and weighting and fusing the fault dimension risk value and the parameter trend risk value according to predefined equipment risk assessment rules, and determining the final equipment risk level based on the risk range in which the fusion result is located.

[0037] In practical applications, a fault knowledge base can be implemented using a relational database or a graph database, aiming to provide standardized knowledge support for subsequent fault matching and risk quantification. The urgency level can be a priority indicator based on the degree of impact of the fault on the safety of equipment operation, which can be defined using expert experience or historical data analysis. Specifically, the real-time fault code set refers to the collection of all active fault codes at the current moment extracted from the equipment status data stream, which can be efficiently collected using data stream processing technologies such as Apache Kafka or Spark Streaming. Furthermore, sliding window trend analysis can use a fixed time window or an adaptive window size to capture the changing patterns of key operating parameters and avoid instantaneous anomalies interfering with the evaluation results.

[0038] In detail, firstly, clear urgency levels and weighting coefficients are defined for different types of fault codes, providing a foundation for subsequent risk quantification. Based on this, real-time reception and parsing of equipment status data streams ensures the timeliness of input information and avoids assessment bias caused by data lag. Subsequently, by matching the real-time fault code set with a fault knowledge base and combining the weighting coefficients, the fault dimension risk value is quantified. This process utilizes a predefined knowledge base to transform fault codes into calculable risk indicators, improving the objectivity of the assessment. Simultaneously, by performing sliding window trend analysis on key operating parameter sequences, the magnitude and rate of change of deviations from safety thresholds are identified, and parameter trend risk values ​​are calculated. This step effectively captures the dynamic characteristics of parameters and prevents misjudgments caused by relying solely on instantaneous values. Finally, the fault dimension risk value and parameter trend risk value are weighted and fused using predefined rules. The final risk level is determined based on the risk range of the fused result, thus achieving a comprehensive assessment of multi-source risk values ​​and ensuring that the access control system can make secure authorization decisions based on accurate risk levels.

[0039] In some embodiments, the present invention further proposes an environmental risk sub-model, including: The acquisition unit is used to acquire real-time meteorological data and short-term meteorological forecast data of the location of the target wind turbine. The correction unit is used to call the micro-topography meteorological correction model corresponding to the geographical location of the target wind turbine to correct the real-time meteorological data and forecast data, so as to obtain accurate meteorological information of the turbine location. The environmental risk level calculation unit is used to determine whether wind speed, thunderstorms, and icing factors exceed the safety limits for tower climbing operations based on accurate meteorological information, and to calculate the environmental risk level.

[0040] In a specific implementation, the acquisition unit can extract relevant meteorological information about the location of the target wind turbine from external meteorological data sources or internal databases. This can be achieved through API calls, data crawling, or direct sensor connection, aiming to provide basic data support for subsequent environmental risk assessment. The correction unit can process and correct the raw meteorological data using specific algorithms. This can be achieved through machine learning models, physical simulation algorithms, or empirical formulas, aiming to eliminate the influence of micro-topography on meteorological elements and generate more accurate meteorological information that is closer to reality. The environmental risk level calculation unit is a functional module that performs risk quantification assessment based on the corrected meteorological information. This can be achieved using methods such as threshold judgment, fuzzy reasoning, or risk matrices, aiming to accurately determine whether the current environmental conditions meet the requirements for safe operation.

[0041] Specifically, the system first acquires basic meteorological data on the location of the target wind turbine, including both real-time monitoring data and short-term forecasts, providing comprehensive data support for environmental risk assessment. Based on this, the correction unit processes the raw data using a corresponding micro-topographic meteorological correction model, according to the specific geographical location of the target wind turbine. Finally, the environmental risk level calculation unit, based on the corrected and accurate meteorological information, comprehensively evaluates key factors such as wind speed, thunderstorms, and icing by comparing them with preset safety limits, thus deriving an accurate environmental risk level. This design ensures that the environmental risk assessment results accurately reflect the actual operating scenario under complex terrain conditions, providing a reliable basis for the dynamic authorization decisions of the access control system.

[0042] In some embodiments, the present invention further proposes an environmental risk level calculation unit, specifically used for: Construct a dynamic safety threshold library that includes three dimensions: wind speed, thunderstorm, and icing. The wind speed safety threshold is a piecewise function related to the wind turbine's operating status and operation type, while the thunderstorm and icing safety thresholds are Boolean judgments.

[0043] The precise meteorological information of the unit location is analyzed into real-time data vectors corresponding to wind speed, thunderstorm warning, and icing warning; The real-time data vector is compared with a dynamic safety threshold library: for wind speed, it is determined whether it is within the threshold range that allows climbing the tower; for thunderstorms and icing, it is determined whether the warning signal has been triggered. Based on the comparison results, a risk label is assigned to each dimension, and a comprehensive environmental risk value is calculated according to the pre-set multi-factor risk fusion algorithm. Based on the preset range of environmental risk values, the final environmental risk level is mapped and output.

[0044] Specifically, a dynamic safety threshold library refers to a database used to store safety limit parameters associated with different meteorological conditions. It can be implemented using a distributed or centralized database. The piecewise function of the wind speed safety threshold can be dynamically adjusted according to the wind turbine's operating status (e.g., start-up, shutdown) and the type of operation (e.g., maintenance, repair). Its purpose is to adapt to different operating conditions and avoid potential safety hazards or excessive restrictions that might result from fixed thresholds. The Boolean judgment of thunderstorm and icing safety thresholds can be understood as a binary logic judgment mechanism, aimed at quickly responding to sudden meteorological risks.

[0045] In practical applications, precise meteorological information for generator unit locations refers to accurate meteorological data processed through a micro-topographic meteorological correction model. This data can be generated by collecting raw meteorological data through a sensor network and combining it with the correction model. Real-time data vectors can be in structured data formats, such as JSON or XML, to facilitate systematic processing and subsequent analysis. Multi-factor risk fusion algorithms can employ weighted average methods, fuzzy inference algorithms, or other multi-dimensional data analysis methods. Their purpose is to integrate risk contributions from multiple dimensions, resulting in more comprehensive and accurate assessment results.

[0046] Specifically, the piecewise function design of the wind speed safety threshold can be dynamically adjusted according to the wind turbine's operating status and operation type, thereby improving operational flexibility while ensuring safety. The Boolean judgment mechanism for thunderstorm and icing safety thresholds ensures rapid response to sudden meteorological events. By parsing precise meteorological information from the unit location into real-time data vectors and comparing them with a dynamic safety threshold database, refined management of the continuous variation characteristics of wind speed is achieved, while simultaneously capturing the immediate risks of critical meteorological events such as thunderstorms and icing.

[0047] Building upon this foundation, the application of a multi-factor risk fusion algorithm further enhances the accuracy of environmental risk assessment. By fusing risk indicators from three dimensions—wind speed, thunderstorms, and icing—the risk assessment becomes more comprehensive and reliable. Ultimately, a standardized environmental risk level is output based on the environmental risk value mapping, providing a clear basis for subsequent system decision-making and response.

[0048] In some embodiments, the present invention further proposes a personnel risk sub-model comprising a verification unit, a retrieval unit, a construction unit, and a personnel suitability level calculation unit. The verification unit verifies the matching degree between the operator's qualification certificates, authorized equipment list, and current work tasks; the retrieval unit retrieves the operator's historical work records and safety violation records; the construction unit combines pre-job physiological state testing results to construct a dynamic competency profile; and the personnel suitability level calculation unit calculates the personnel suitability level based on the matching degree, historical records, and the dynamic competency profile.

[0049] Specifically, the verification unit can perform real-time matching and verification of operators' qualification certificates, authorized equipment lists, and current work tasks. This can be achieved using database comparison technology or rule engines, aiming to ensure strict alignment between qualification verification and task requirements, avoiding the risk of qualification mismatch due to task changes. The retrieval unit can extract operators' historical work records and safety violation records from the storage system. This can be achieved using time decay algorithms or weighted scoring mechanisms to quantify the safety performance of historical data, highlighting the weight of recent violations and making historical records more relevant to the current risk situation. The construction unit can dynamically generate competency profiles by collecting physiological indicators such as heart rate, blood pressure, and fatigue levels in real time and combining them with benchmark values. This can be achieved using sensor data fusion technology or machine learning models, aiming to capture the impact of sudden physiological abnormalities before work on safety. The personnel suitability level calculation unit can weightedly fuse qualification matching scores, historical safety scores, and real-time status scores to output a quantitative level. This can be achieved using multi-factor evaluation models or score interval mapping tables, aiming to dynamically reflect changes in personnel's comprehensive competency and provide accurate decision-making basis for access control authorization.

[0050] Specifically, this embodiment uses a verification unit to dynamically verify the coverage of personnel qualifications based on the real-time requirements of specific tasks, rather than relying on a fixed authorization list, thus ensuring strict alignment between qualification verification and task requirements. The retrieval unit quantifies safety performance based on the time decay characteristics of historical data, highlighting the weight of recent violations. The construction unit combines real-time physiological indicators with dynamic comparisons of benchmark values, incorporating the personnel's immediate physical condition into the assessment framework, effectively capturing the impact of sudden physiological abnormalities before work on safety. The personnel suitability level calculation unit weighted and integrated qualification matching scores, historical safety scores, and real-time status scores, mapping and outputting a quantitative level based on a preset score range, rather than simply adding a single factor, enabling the assessment results to dynamically reflect changes in the personnel's comprehensive competence.

[0051] In some embodiments, the present invention further proposes a personnel suitability level calculation unit, specifically used for: constructing a personnel competency-based assessment model, which includes three assessment dimensions: qualification matching degree, historical work safety index, and real-time physiological state, and assigning dynamic weights to each dimension; quantifying the matching degree: calculating a qualification matching score based on the degree of conformity between the operator's qualification certificate level, authorized equipment coverage, and current work task requirements; quantifying historical records: calculating a historical safety score based on the operator's historical work completion rate, historical violation count, and severity using a predefined decay algorithm; quantifying the dynamic competency profile: comparing the heart rate, blood pressure, and fatigue level indicators detected before the job with benchmark values ​​to calculate a real-time status score; inputting the qualification matching score, historical safety score, and real-time status score into the personnel competency-based assessment model, obtaining a comprehensive competency score through weighted calculation, and outputting the final personnel suitability level according to a preset score interval mapping table.

[0052] Specifically, a personnel competency assessment model comprehensively reflects the suitability of operators in terms of qualifications, historical behavior, and real-time status. This can be achieved through a multi-dimensional scoring matrix or a fuzzy logic reasoning system. Dynamic weighting refers to a mechanism that automatically adjusts the importance of each assessment dimension based on the risk priority of different work scenarios, aiming to ensure that the assessment results flexibly adapt to environmental changes. The qualification matching score measures the degree to which the operator's qualifications match the task requirements, and can be calculated using the analytic hierarchy process (AHP) or a rule engine. The historical safety score is a safety evaluation indicator generated based on the operator's past performance, and can be achieved using a time-weighted average algorithm or an exponential decay function. The real-time status score is a quantitative value reflecting whether the operator's current physiological condition is suitable for performing the task, and can be obtained through standardized difference calculation or threshold determination methods.

[0053] In detail, firstly, the personnel competency assessment model integrates three dimensions: qualification matching degree, historical work safety index, and real-time physiological state. Through a dynamic weight allocation mechanism, the weight ratio of each dimension can be flexibly adjusted according to the actual work scenario. When quantifying matching degree, a qualification matching score is generated based on the degree of conformity between the qualification certificate level, authorized equipment coverage, and task requirements, transforming abstract qualification requirements into quantifiable values ​​and improving the objectivity of the assessment. The quantification of historical records employs a predefined decay algorithm, assigning higher weight to recent behaviors, effectively suppressing the time-related decay of historical data and highlighting the current safety behavior trend of personnel. When quantifying the dynamic competency profile, physiological parameters such as heart rate, blood pressure, and fatigue level are compared with benchmark values ​​to generate a real-time status score, avoiding the influence of pre-work physiological fluctuations. Finally, a comprehensive competency score is formed by weighted calculation and fusion of the qualification matching score, historical safety score, and real-time status score. Based on a preset score range mapping table, an adaptation level is output, providing reliable input for hierarchical authorization in the access control system. This process not only solves the problem of the lack of a refined and quantitative mechanism for personnel suitability assessment, but also enhances the adaptability of the assessment results through a dynamic weight allocation mechanism, thereby supporting the security rule engine to generate accurate dynamic access credentials.

[0054] In some embodiments, the present invention further proposes a specific implementation method for monitoring abnormal events using the edge access control terminal 12. A behavior sequence prediction unit is used to continuously collect the work behavior sequence of the operator after the access control is opened. The behavior sequence includes tool retrieval records, in-cabin movement trajectories, and equipment operation actions. A dynamic risk assessment unit is used to compare the behavior sequence with a pre-stored standardized work procedure model in real time, and calculate the deviation between the current behavior and the expected work process using a hidden Markov model; when the deviation continuously exceeds a dynamic threshold, it is determined to be a behavioral abnormality event. A predictive alarm unit is used to initiate a three-level response after determining a behavioral abnormality event: first, a local voice reminder is issued to the operator; if the deviation does not decrease after the reminder, a warning message is sent to the on-site safety officer; if the deviation continues to rise and reaches a high-risk threshold, an emergency alarm is generated and the relevant equipment operation permissions are simultaneously forcibly locked.

[0055] Specifically, the behavior sequence prediction unit can collect and process multi-dimensional behavioral data during wind turbine maintenance. This can be achieved using sensor networks combined with data fusion algorithms, aiming to fully reconstruct the operational chain of workers and provide a foundation for fine-grained behavior monitoring. The dynamic risk assessment unit can be implemented using machine learning algorithms or probabilistic graphical models, aiming to accurately identify progressive deviations in the operational process. The predictive alarm unit can be implemented using a rule engine combined with dynamic threshold judgment, aiming to customize the response intensity according to the risk evolution path, avoiding excessive intervention while ensuring timely interruption of the accident chain.

[0056] In detail, the behavior sequence prediction unit continuously collects multi-dimensional behavioral data, including tool usage records, cabin movement trajectories, and equipment operation actions of the workers, to reflect the highly procedural nature of wind turbine maintenance operations. The dynamic risk assessment unit uses a hidden Markov model to analyze the collected behavior sequences in real time. This model effectively captures the time dependence and state transition characteristics of behavior, and by comparing it with a standardized operating procedure model, it can accurately quantify the degree of deviation from the norm. The predictive alarm unit dynamically adjusts the response level based on the changing trend of the deviation, forming a closed-loop control mechanism from early warning to intervention.

[0057] In some embodiments, the present invention further proposes that the system also includes a digital twin mapping module, a virtual simulation and deduction unit, and an adaptive defense decision-making unit. The digital twin mapping module is used to construct a virtual access control mirror corresponding to the physical access control system in the cloud-based central control center 11, synchronizing the physical access control's status data, environmental data, and personnel behavior data in real time. The virtual simulation and deduction unit is used to perform multi-dimensional security situation deduction in the virtual access control mirror based on the current system state and abnormal behavior characteristics when receiving an alarm for abnormal behavior events, predicting the potential equipment risk chain caused by abnormal behavior. The adaptive defense decision-making unit is used to match the optimal handling plan from a preset strategy library based on the security situation deduction results. The handling plan includes generating targeted equipment isolation instructions, dynamically adjusting the three-dimensional geofence range, or issuing specific security enhancement operation guidelines to the edge access control terminal 12.

[0058] In practical applications, the digital twin mapping module can be implemented using IoT sensing technology, real-time data acquisition technology, and data fusion algorithms, aiming to provide a high-fidelity data foundation for subsequent risk simulations. The virtual simulation simulation unit can be implemented by combining machine learning algorithms, fault propagation models, and multi-dimensional data analysis methods, aiming to predict the cascading failure paths of equipment that may be triggered by abnormal behavior. Specifically, the adaptive defense decision-making unit can be implemented using rule engines, policy matching algorithms, and dynamic optimization techniques, aiming to ensure that the response measures are highly adapted to the specific risk scenario.

[0059] In detail, the digital twin mapping module constructs a virtual access control mirror in the cloud and synchronizes the physical access control's status data, environmental data, and personnel behavior data in real time, thus providing a unified data foundation for subsequent simulations. Based on this, upon receiving an anomaly alarm, the virtual simulation unit performs a multi-dimensional security posture simulation within the virtual access control mirror, based on the current system state and anomaly behavior characteristics. By combining real-time anomaly characteristics with system state to dynamically predict risk chains, rather than relying on a static rule base, the system can simulate the cascading failure paths that anomaly behavior may trigger. Finally, the adaptive defense decision unit matches the optimal handling plan from a preset strategy library based on the simulation results. This includes generating targeted device isolation commands, dynamically adjusting the 3D geofence range, or issuing specific security enhancement operation guidelines to the edge access control terminal 12, thereby achieving human-machine collaborative intervention.

[0060] Based on the same general inventive concept, this invention also protects a method for a remote intelligent access control system for wind turbines based on two-ticket linkage. The method for a remote intelligent access control system for wind turbines based on two-ticket linkage provided by this invention will be described below. The method for a remote intelligent access control system for wind turbines based on two-ticket linkage described below can be referred to in correspondence with the method for a remote intelligent access control system for wind turbines based on two-ticket linkage described above.

[0061] Figure 2 This is a flowchart illustrating a method for a remote intelligent access control system for wind turbines based on two-ticket linkage, provided in an embodiment of the present invention. The method is applied to the control device within the remote intelligent access control system for wind turbines based on two-ticket linkage. Figure 2 As shown, the remote intelligent access control system method for wind turbine generators based on two-ticket linkage in this embodiment includes the following steps: 201. The cloud-based centralized control center receives and verifies the correlation and validity of the two tickets. Based on the successfully verified information of the two tickets, the operator information, and the preset safety rules, it generates a dynamic door opening certificate with time and space constraints. The two tickets include an electronic work ticket and an operation ticket. 202. The edge access control terminal collects the authentication information of the operators and sends the authentication information to the cloud-based centralized control center; 203. The cloud-based centralized control center matches and verifies the authentication information with the dynamic door opening credential, and sends an encrypted door opening command to the execution terminal when the verification is successful; 204. Upon receiving the door opening command, the execution unit unlocks the access control for the corresponding target unit; 205. After the access control terminal opens the door, it monitors for abnormal events and issues an alarm when an abnormal event is detected. 206. After the operation is completed, the cloud-based centralized control center updates the status of the electronic work ticket and triggers the access control lock.

[0062] It should be noted that all relevant information that may be involved in the various embodiments of the present invention is processed in strict accordance with the requirements of laws and regulations, following the principles of legality, legitimacy, and necessity, based on the reasonable purpose of the business scenario, and is information that users actively provide or generate during the use of the product / service, as well as information obtained with user authorization.

[0063] The information processed by this invention may vary depending on the specific product / service scenario and should be based on the specific scenario in which the user uses the product / service. This may involve user account information, device information, or other related information. This invention will handle the relevant information and its processing with the utmost diligence.

[0064] This invention places great emphasis on the security of relevant information and has adopted reasonable and feasible security protection measures that comply with industry standards to protect user information and prevent unauthorized access, public disclosure, use, modification, damage or loss of relevant information.

[0065] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0066] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A remote intelligent access control system for wind turbine units based on two-ticket linkage, characterized in that, This includes a cloud-based control center, edge access control terminals, and execution terminals; The cloud-based centralized control center is used to receive and verify the correlation and validity of the two tickets. Based on the successfully verified ticket information, operator information, and preset safety rules, it generates a dynamic door opening certificate with time and space constraints. The two tickets include an electronic work ticket and an operation ticket. The edge access control terminal is used to collect the authentication information of the operators and send the authentication information to the cloud-based central control center; The cloud-based centralized control center is also used to match and verify the authentication information with the dynamic door opening credential, and send an encrypted door opening command to the execution terminal when the verification is successful. The execution terminal is used to unlock the access control of the corresponding target unit after receiving the door opening command; The edge access control terminal is also used to monitor abnormal events after the access control is opened, and to issue an alarm when an abnormal event is detected; The cloud-based control center is also used to update the status of the electronic work ticket and trigger access control locking after the work is completed.

2. The remote intelligent access control system for wind turbine units based on two-ticket linkage as described in claim 1, characterized in that, The cloud-based centralized control center includes: The parsing module is used to parse the structured data of the two tickets and extract the key verification elements of the two tickets; The correlation verification module is used to perform correlation verification on two tickets based on key verification elements and a preset ticket correlation rule base; the correlation verification includes job task logic consistency verification, equipment operation sequence matching degree verification, and safety measure complementarity verification. The validity verification module is used to perform validity verification on two tickets based on the timeliness verification model; the validity verification includes issuance timeliness verification, execution sequence verification and conflict detection. The assessment module is used to call the safety rule engine when both the correlation and validity checks pass, and to conduct a comprehensive risk assessment by combining equipment status data, environmental monitoring data, and operator qualification information. The generation module is used to generate dynamic door opening vouchers with time and space constraints based on risk assessment results and two ticket information. The synchronization module is used to digitally sign and encrypt the generated dynamic access vouchers, store them in a distributed voucher database, and synchronize them to the edge access control terminal.

3. The remote intelligent access control system for wind turbine units based on two-ticket linkage as described in claim 2, characterized in that, The generation module includes: The risk assessment mapping unit is used to quantify the risk assessment results into risk levels and determine the corresponding authority constraint strength based on a preset risk and authority mapping table. The spatiotemporal constraint calculation unit is used to dynamically calculate the authorized time window and three-dimensional geofence based on the work plan time period, equipment location coordinates and work radius in the two ticket information, combined with meteorological data and equipment operating status. The dynamic factor generation unit is used to generate time-sensitive dynamic passwords based on the current timestamp, device serial number, and random seed using an encryption algorithm. The credential combination engine is used to combine and encode at least one of the following: permission constraint strength, authorization time window, three-dimensional geofence, dynamic password, and list of allowed operators, to generate the dynamic door opening credential. An adaptive adjustment unit is used to adjust the authorization time window and the three-dimensional geofence based on real-time monitoring of changes in equipment status or sudden changes in weather conditions within the validity period of the credential.

4. The remote intelligent access control system for wind turbine generators based on two-ticket linkage as described in claim 2, characterized in that, The evaluation module includes: The risk quantification unit is used to calculate the risk level, environmental risk level and personnel suitability level based on the standardized data provided by the data aggregation unit through the equipment risk sub-model, environmental risk sub-model and personnel risk sub-model respectively. The fusion assessment engine receives the equipment risk level, environmental risk level, and personnel suitability level, calls the built-in weighted fuzzy inference rule base or risk matrix, performs multi-source data fusion calculation, and outputs a comprehensive risk assessment result.

5. The remote intelligent access control system for wind turbine generators based on two-ticket linkage as described in claim 4, characterized in that, The equipment risk sub-model includes: The extraction unit is used to extract key operating parameters and fault codes from the equipment status data; The analysis unit is used to compare the key operating parameters with preset safety thresholds and analyze their short-term change trends. The equipment risk level calculation unit is used to calculate the equipment risk level by combining the urgency of the fault code with the trend of change and by using predefined equipment risk assessment rules.

6. The remote intelligent access control system for wind turbine units based on two-ticket linkage as described in claim 5, characterized in that, The equipment risk level calculation unit is specifically used for: Construct a fault knowledge base that includes fault codes, urgency levels, and weight coefficients, wherein the urgency levels are classified based on the degree of immediate impact of the fault on the safe operation of the equipment; Real-time reception and parsing of equipment status data streams from the target wind turbine, extracting real-time fault code sets and key operating parameter sequences from the equipment status data streams; The real-time fault code set is matched with the fault knowledge base to obtain the corresponding emergency level, and the fault dimension risk value is calculated based on the weight coefficient. Sliding window trend analysis is performed on the key operating parameter sequence to identify the magnitude and rate of change of its deviation from the preset safety threshold, and the parameter trend risk value is calculated; By using predefined equipment risk assessment rules, the fault dimension risk value and the parameter trend risk value are weighted and fused together, and the final equipment risk level is determined based on the risk range in which the fusion result is located.

7. The remote intelligent access control system for wind turbine generators based on two-ticket linkage as described in claim 4, characterized in that, The environmental risk sub-model includes: The acquisition unit is used to acquire real-time meteorological data and short-term meteorological forecast data of the location of the target wind turbine. The correction unit is used to call the micro-topography meteorological correction model corresponding to the geographical location of the target wind turbine to correct the real-time meteorological data and forecast data, so as to obtain accurate meteorological information of the turbine location. The environmental risk level calculation unit is used to determine whether wind speed, thunderstorms, and icing factors exceed the safety limits for tower climbing operations based on the accurate meteorological information, and to calculate the environmental risk level.

8. The remote intelligent access control system for wind turbine generators based on two-ticket linkage as described in claim 7, characterized in that, The environmental risk level calculation unit is specifically used for: A dynamic safety threshold library is constructed, which includes three dimensions: wind speed, thunderstorm, and icing. The wind speed safety threshold is a piecewise function related to the wind turbine's operating status and operation type, while the thunderstorm and icing safety thresholds are Boolean judgments. The precise meteorological information of the unit locations is parsed into real-time data vectors corresponding to wind speed, thunderstorm warnings, and icing warnings; The real-time data vector is compared with the dynamic safety threshold library: for wind speed, it is determined whether it is within the threshold range that allows climbing the tower; for thunderstorms and icing, it is determined whether the warning signal has been triggered. Based on the comparison results, risk labels are assigned to each dimension, and a comprehensive environmental risk value is calculated according to a pre-set multi-factor risk fusion algorithm. Based on the preset range of environmental risk values, the final environmental risk level is mapped and output.

9. The remote intelligent access control system for wind turbine units based on two-ticket linkage as described in claim 4, characterized in that, The personnel risk sub-model includes: The verification module is used to verify the matching degree between the operator's qualification certificate, authorized equipment list and the current work task; The retrieval module is used to retrieve the historical work records and safety violation records of operators. The module is used to build a dynamic competency profile by combining the results of pre-employment physiological status testing; The personnel suitability level calculation module is used to calculate the personnel suitability level based on the matching degree, historical records, and dynamic competency profile.

10. A control method for a remote intelligent access control system for wind turbine generators based on two-ticket linkage, characterized in that, include: The cloud-based centralized control center receives and verifies the correlation and validity of the two tickets. Based on the successfully verified ticket information, operator information, and preset safety rules, it generates a dynamic door opening certificate with time and space constraints. The two tickets include an electronic work ticket and an operation ticket. The edge access control terminal collects the authentication information of the operators and sends the authentication information to the cloud-based centralized control center; The cloud-based central control center matches and verifies the authentication information with the dynamic door opening credential, and sends an encrypted door opening command to the execution terminal when the verification is successful. Upon receiving the door opening command, the execution unit unlocks the access control for the corresponding target unit. After the access control terminal opens the door, it monitors for abnormal events and issues an alarm when an abnormal event is detected. After the operation is completed, the cloud-based control center updates the status of the electronic work ticket and triggers the access control lock.

Images