A full-motion flight simulator operating condition monitoring system and method

Abstract

The application discloses a full-motion flight simulator operation state monitoring system and method. The system comprises: a posture acquisition module fixed on a full-motion flight simulator connecting line, used for collecting angle change data and generating a log file containing characteristic angle axis values and transmitting the log file outward; an intelligent log analysis processing module containing a timing scheduling unit, a multi-dimensional log analysis unit and a dynamic threshold operation state judgment unit, used for reading the log file at a fixed time, identifying the format, extracting the characteristic angle axis values and filtering abnormal data, dynamically adjusting the basic threshold based on the historical operation data by using a sliding window iterative optimization mechanism, and judging that the simulator is in an operation state when the extracted values exceed the dynamically adjusted threshold; a data storage module used for storing the log file, data and judgment results; and a display module used for displaying real-time states, historical records and change trends. The application realizes non-intrusive and high-reliability operation state adaptive monitoring.

Description

Technical Field

[0001] This invention belongs to the field of full-motion flight simulator monitoring technology, specifically relating to a full-motion flight simulator operation status monitoring system and method. Background Technology

[0002] Full Flight Simulator (FFS) is a core piece of equipment for civil aviation pilot training, retraining, and type approval. The accurate monitoring of its operational status and the statistics of its runtime are directly related to the operation and maintenance management, training plan scheduling, and equipment life cycle assessment of the simulator.

[0003] Currently, most mainstream full-motion flight simulators in the civil aviation field (such as CAE and Thales brands) adopt a highly closed system architecture. To obtain the simulator's operational status, traditional monitoring solutions typically rely on cracking or deeply interfacing with the simulator's internal black-box interfaces, communication protocols, or data buses to read internal operating parameters in real time. However, this traditional monitoring method has the following significant drawbacks in practical applications: First, it is highly invasive, difficult to access, and poses significant security risks. Since the operating systems and communication protocols of mainstream flight simulators are trade secrets and highly closed (i.e., black boxes), accessing monitoring equipment by cracking interfaces or unauthorized modifications to internal wiring is not only extremely difficult technically, but also easily damages the integrity of the simulator's original system, and may even cause malfunctions or safety hazards in the flight simulator. This fails to meet the extremely high requirements of the civil aviation industry for equipment security and compliance.

[0004] Second, data acquisition is susceptible to transient interference and has low accuracy in judgment. Existing monitoring methods typically use fixed thresholds for status determination after acquiring data from sensors or acquisition devices, lacking an effective filtering mechanism for abnormal interference data. Since flight simulators may generate transient interference data even when not in operation or under slight mechanical vibration, fixed threshold judgment is very likely to misjudge such noisy data as an operational status, resulting in a persistently high false alarm rate in status determination.

[0005] Third, it lacks adaptive adjustment capabilities and has poor scalability and compatibility. Existing monitoring solutions are mostly customized for single specific models or protocols of flight simulators. When adding or replacing flight simulators of different brands or log formats at the maintenance site, it is often necessary to manually rewrite the parsing rules and configure fixed judgment thresholds. This makes it impossible to adapt to the characteristics of the collected signals and data of different devices, resulting in extremely poor system expansion capabilities and unified monitoring capabilities for multiple devices.

[0006] Therefore, how to provide a full-motion flight simulator operation status monitoring system and method that can achieve non-intrusive installation, high-precision data analysis, adaptive dynamic judgment, and rapid expansion of multiple devices without breaking the closed black box system of the simulator is a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0007] The following provides a brief overview of one or more aspects to offer a basic understanding of them. This overview is not an exhaustive summary of all conceived aspects, nor is it intended to identify key or decisive elements of all aspects, nor to define the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form to prepare for the more detailed descriptions that follow.

[0008] The purpose of this invention is to solve the above-mentioned problems and provide a full-motion flight simulator operation status monitoring system and method. This system enables non-intrusive, highly accurate, adaptive dynamic judgment and visual monitoring of the operation status of a full-motion flight simulator without needing to crack the flight simulator's black box system. It also has good multi-device rapid expansion capability and anti-interference ability.

[0009] The technical solution of this invention is as follows: This invention discloses a full-motion flight simulator operation status monitoring system, the system comprising: The attitude acquisition module is fixed to the connection line of the full-motion flight simulator. It is used to collect the angle change data generated during the operation of the full-motion flight simulator, generate a log file containing the characteristic angle axis values, and then transmit the log file to the outside. The intelligent log parsing and processing module, which is communicatively connected to the attitude acquisition module, is configured with a timed scheduling unit, a multi-dimensional log parsing unit, and a dynamic threshold operation status judgment unit. The timed scheduling unit is used to read the log file according to a preset period. The multi-dimensional log parsing unit is used to identify the format of the log file, extract the feature angle axis values, and filter abnormal data. The dynamic threshold operation status judgment unit is used to dynamically fine-tune the base threshold based on a preset feature angle axis base threshold and a sliding window iterative optimization mechanism based on historical operation data to obtain a dynamically adjusted threshold. When the parsed and extracted feature angle axis values ​​exceed the dynamically adjusted threshold, the module determines that the full-motion flight simulator is in operation. The data storage module is communicatively connected to the intelligent log parsing and processing module, and is used to store the log file, the parsed feature angle axis data, and the running status judgment result; The display module is communicatively connected to the data storage module and is used to display the real-time operating status, historical records, and characteristic angle axis change trends of the full-motion flight simulator.

[0010] According to an embodiment of the full-motion flight simulator operation status monitoring system of the present invention, the attitude acquisition module is a commercial sextant acquisition module.

[0011] According to an embodiment of the full-motion flight simulator operation status monitoring system of the present invention, the commercial sextant acquisition module is fixed in the following way: a flexible fastener is selected and passes through the small hole reserved in the commercial sextant to fix the commercial sextant to the connection line of the full-motion flight simulator, and the fixed position avoids the connector and moving parts of the connection line; the flexible fastener includes a flexible strap, a flexible rope or a wear-resistant buckle.

[0012] According to an embodiment of the full-motion flight simulator operation status monitoring system of the present invention, the characteristic angle axis is an angle axis that reflects the pitch or tilt state of the full-motion flight simulator, including the Y-axis, X-axis or Z-axis.

[0013] According to an embodiment of the full-motion flight simulator operation status monitoring system of the present invention, the timing scheduling unit adopts the Quartz scheduling framework to dynamically adjust the reading cycle of the log file based on the log data transmission rate and data volume.

[0014] According to an embodiment of the full-motion flight simulator operation status monitoring system of the present invention, the intelligent log parsing and processing module is further configured with anomaly diagnosis logic, which is used to automatically locate the cause of the anomaly based on the network transmission status and the equipment acquisition status when the log file cannot be read or the characteristic angle axis value exceeds the threshold range.

[0015] According to an embodiment of the full-motion flight simulator operation status monitoring system of the present invention, the multi-dimensional log parsing unit uses a combination of regular expression matching and feature value extraction to identify the text format of the log file and extract the feature angle axis data from the log file; the multi-dimensional log parsing unit is used to filter abnormal data from the extracted feature angle axis values, filtering out invalid characters, missing data, and abnormal feature angle axis values ​​that exceed reasonable ranges or fluctuate too much instantaneously in the log file.

[0016] According to an embodiment of the full-motion flight simulator operation status monitoring system of the present invention, in the basic threshold values ​​of the characteristic angle axis, the upper and lower threshold values ​​correspond to the pitch angle range of the full-motion flight simulator, and the left and right threshold values ​​correspond to the tilt angle range of the full-motion flight simulator.

[0017] According to an embodiment of the full-motion flight simulator operation status monitoring system of the present invention, the dynamic threshold operation status judgment unit is used to acquire multiple sets of continuously collected feature angle axis values, and dynamically allocate weighting coefficients based on data reliability to perform weighted fusion processing, and compare the feature angle axis values ​​after weighted fusion processing with the dynamically adjusted threshold to determine the operation status of the full-motion flight simulator.

[0018] According to an embodiment of the full-motion flight simulator operation status monitoring system of the present invention, the specific logic of the dynamic threshold operation status judgment unit in comparing the weighted fusion processed feature angle axis values ​​with the dynamically adjusted threshold to determine the operation status of the full-motion flight simulator is as follows: For the characteristic angle axes corresponding to the pitch and tilt states, respectively, their weighted fusion values ​​are obtained. and ;when Exceeding the dynamically adjusted upper and lower thresholds, or When the left and right thresholds are exceeded after dynamic adjustment, and this breakthrough state continues for a preset number of operation confirmation frames, the full-motion flight simulator is determined to have entered the operation state, and the operation start timestamp is recorded. ; In running state, when and When all values ​​are below their respective dynamically adjusted thresholds, and the duration of these values ​​remains below the thresholds for a preset stop determination time threshold, the full-motion flight simulator is determined to switch to a stopped state, and a stop timestamp is recorded. And calculate the duration of a single run.

[0019] According to an embodiment of the full-motion flight simulator operation status monitoring system of the present invention, the display module displays the following content: real-time operation status identifiers of one or more full-motion flight simulators, historical operation duration statistics of each full-motion flight simulator, characteristic angle axis change trend curves, dynamic threshold adjustment curves, abnormal status alarm prompts, and algorithm operation status display; it supports querying historical operation records, original log files, dynamic threshold adjustment records, and abnormal data filtering records by time range or simulator number.

[0020] According to an embodiment of the full-motion flight simulator operation status monitoring system of the present invention, the system further includes: The alarm module is communicatively connected to the intelligent log parsing and processing module. When the characteristic angle axis value of the full-motion flight simulator exceeds the threshold range after dynamic adjustment or the log file transmission is interrupted, the alarm module sends an alarm reminder via SMS or WeChat push.

[0021] This invention also discloses a method for monitoring the operational status of a full-motion flight simulator, applied to the full-motion flight simulator operational status monitoring system described above, comprising the following steps: The attitude acquisition module, which is fixed to the connection line of the full-motion flight simulator, collects the angle change data generated during the operation of the full-motion flight simulator, generates a log file containing characteristic angle axis values, and then transmits the log file outward. The log file is read by the timed scheduling unit of the intelligent log parsing and processing module according to a preset period. The intelligent log parsing and processing module identifies the format of the log file through its multi-dimensional log parsing unit, extracts the characteristic angle axis values, and filters out abnormal data. The dynamic threshold operation status judgment unit of the intelligent log parsing and processing module dynamically fine-tunes the basic threshold based on the preset feature angle axis basic threshold and the historical operation data using a sliding window iterative optimization mechanism to obtain the dynamically adjusted threshold; and when the parsed and extracted feature angle axis value exceeds the dynamically adjusted threshold, it is determined that the full-motion flight simulator is in operation. The log file, the parsed feature angle axis data, and the running status judgment results are stored through the data storage module. The display module shows the real-time operating status, historical records, and characteristic angle axis change trends of the full-motion flight simulator.

[0022] Compared with the prior art, the present invention has the following advantages: First, addressing the shortcomings of existing technologies such as high invasiveness, difficulty in access, and high security risks, this invention employs a commercial sextant acquisition module fixed to the connection line of the full-motion flight simulator. This module collects angular change data generated during the simulator's operation and generates a log file containing characteristic angle axis values, which is then transmitted externally. This technical feature achieves non-intrusive data acquisition, completely avoiding the need to hack or deeply integrate into the simulator's closed black-box system or modify internal wiring. While ensuring the integrity and operational safety of the original flight simulator system, it significantly reduces the access difficulty and installation cost of the monitoring system, effectively improving the operational safety and compliance of the equipment.

[0023] Secondly, addressing the shortcomings of existing technologies where data acquisition is susceptible to momentary interference and accuracy is low, this invention utilizes a multi-dimensional log parsing unit to identify the format of the log file, extract feature angle axis values, and filter abnormal data. The dynamic threshold operation status judgment unit dynamically fine-tunes the preset feature angle axis base threshold based on historical operation data using a sliding window iterative optimization mechanism, obtaining a dynamically adjusted threshold. When the extracted feature angle axis value exceeds the dynamically adjusted threshold, the full-motion flight simulator is determined to be in operation. This technical feature effectively eliminates invalid characters, missing data, and momentary interference noise through abnormal data filtering. Simultaneously, the sliding window iterative optimization mechanism allows the judgment threshold to be dynamically and smoothly adjusted based on the device's historical operation data, overcoming the shortcomings of traditional fixed thresholds that are susceptible to false alarms caused by vibration and other interference. This significantly improves the accuracy of flight simulator operation status judgment and the system's anti-interference capability.

[0024] Third, addressing the shortcomings of existing technologies such as lack of adaptive adjustment capabilities and poor scalability and compatibility, this invention employs the Quartz scheduling framework in the timed scheduling unit to dynamically adjust the reading cycle of the log file based on the log data transmission rate and data volume; the multi-dimensional log parsing unit uses a combination of regular expression matching and feature value extraction to identify the text format of the log file and extract the feature angle axis data from the log file; and the system has an automatic expansion configuration function (when a new full-motion flight simulator is connected, the intelligent log parsing and processing module automatically identifies the new device and allocates a reading cycle and calibration threshold, the data storage module automatically creates storage entries and partitions, the display module automatically adds monitoring entries, and the alarm module automatically includes it in the alarm range). These technical features enable the system to adapt to sextant devices of different brands and log text formats, achieving adaptive scheduling reading and rapid parsing of log files, greatly simplifying the configuration process when adding or replacing simulators, realizing rapid access and unified monitoring of multiple full-motion flight simulators of different models, significantly enhancing the system's scalability and compatibility, and further improving management convenience. Attached Figure Description

[0025] The above-described features and advantages of the present invention will be better understood after reading the following detailed description of embodiments of the present disclosure in conjunction with the accompanying drawings. In the drawings, components are not necessarily drawn to scale, and components having similar related characteristics or features may have the same or similar reference numerals.

[0026] Figure 1 A schematic diagram of an embodiment of the full-motion flight simulator operation status monitoring system of the present invention is shown.

[0027] Figure 2 A flowchart of an embodiment of the full-motion flight simulator operation status monitoring method of the present invention is shown.

[0028] Figure 3 A schematic diagram of the fixing method of the commercial sextant in this invention is shown.

[0029] Figure 4 A schematic diagram of the iterative process of dynamic threshold optimization in this invention is shown. Detailed Implementation

[0030] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. It should be noted that the aspects described below with reference to the accompanying drawings and specific embodiments are merely exemplary and should not be construed as limiting the scope of protection of the present invention in any way.

[0031] Figure 1 The principle of an embodiment of the full-motion flight simulator operation status monitoring system of the present invention is illustrated. (Reference) Figure 1The system in this embodiment includes the following modules: attitude acquisition module, intelligent log parsing and processing module, data storage module, and display module.

[0032] The attitude acquisition module and the intelligent log parsing and processing module are connected via network communication: using its own built-in network port (such as an RJ45 network port), the generated log files are transmitted to the intelligent log parsing and processing module.

[0033] The intelligent log parsing and processing module communicates with the data storage module: The intelligent log parsing and processing module transmits the received log files, the parsed and extracted feature angle axis data, and the generated running status judgment results to the data storage module in real time.

[0034] The display module communicates with the data storage module: The display module reads data such as real-time running status, historical records (such as historical running time, original log files), characteristic angle axis change trend curves and dynamic threshold adjustment records stored in the data storage module and displays them visually.

[0035] In addition, preferably, the system also includes an alarm module that is connected in communication with the intelligent log parsing and processing module: when the intelligent log parsing and processing module detects that the value of the characteristic angle axis exceeds the dynamically adjusted threshold range or the log file transmission is interrupted, it triggers and drives the alarm module to send an alarm reminder.

[0036] The attitude acquisition module is used to collect attitude data from the full-motion flight simulator. In this embodiment, the attitude acquisition module is, for example, an external commercial sextant acquisition module, fixed to the connection line of the full-motion flight simulator. It is used to collect angle change data generated during the operation of the full-motion flight simulator, generate a log file containing characteristic angle axis values, and then transmit the log file externally.

[0037] Figure 3 The mounting method of the commercial sextant acquisition module is shown, such as... Figure 3 As shown, a flexible fastener is used to pass through the pre-drilled hole in the commercial sextant and fix it to the connection line of the full-motion flight simulator. The fixed position of the commercial sextant on the connection line is in the straight section of the middle section of the connection line, avoiding the joints at both ends of the connection line and the bending or moving parts of the connection line. The flexible fastener passes through the mounting hole in a loop and wraps around the outer perimeter of the connection line, fixing the base of the commercial sextant to the surface of the connection line. The flexible fastener includes a flexible strap, a flexible rope, or a wear-resistant buckle. In the installed state, the built-in network port of the commercial sextant faces the unobstructed direction for connecting external network transmission cables.

[0038] Characteristic angle axes are angle axes that reflect the pitch or roll state of a full-motion flight simulator, including the Y-axis, X-axis, or Z-axis. Y-axis (or pitch axis): corresponds to the pitch angle change of the full-motion flight simulator (i.e., the nose-up and nose-down movements of the simulator's cabin); X-axis (or roll axis): corresponds to the roll / tilt angle change of the full-motion flight simulator (i.e., the left and right roll movements of the simulator's cabin); Z-axis (yaw axis).

[0039] The intelligent log parsing and processing module communicates with the commercial sextant acquisition module and is equipped with a timed scheduling unit, a multi-dimensional log parsing unit, and a dynamic threshold operation status judgment unit. The intelligent log parsing and processing module is used for timed log reading, multi-dimensional text parsing, abnormal data cleaning, adaptive threshold adjustment, accurate operation status judgment, and system anomaly diagnosis.

[0040] The timing scheduling unit, acting as the time-driven source of the module, periodically reads the log files generated by the commercial sextant acquisition module according to a preset or dynamically adjusted cycle, and transmits the read log files to the multi-dimensional log parsing unit. The multi-dimensional log parsing unit, connected to the data output of the timing scheduling unit, performs text format recognition, feature angle axis value extraction, and abnormal data filtering on the received log files, and transmits the cleaned valid feature angle axis values ​​to the dynamic threshold operation status judgment unit. The dynamic threshold operation status judgment unit, connected to the data output of the multi-dimensional log parsing unit, receives the valid feature angle axis values, and fine-tunes the base threshold based on historical operation data to obtain a dynamically adjusted threshold. By comparing the feature angle axis values ​​with the dynamically adjusted threshold, it outputs the real-time operation status judgment result of the full-motion flight simulator.

[0041] The timed scheduling unit is used to read log files according to a preset period. Specifically, the timed scheduling unit uses the Quartz scheduling framework to dynamically adjust the log file reading period based on the log data transmission rate and data volume. When dynamically adjusting the reading period according to the data transmission rate and data volume, the dynamic fine-tuning range of its scheduling is controlled within a certain range. Within seconds (for example, if the preset period is 10 seconds, the actual reading period will adaptively fluctuate between 8 and 12 seconds). While ensuring the real-time performance of log parsing and runtime status monitoring, it avoids consuming excessive CPU and memory resources due to overly frequent readings, thus achieving a balance between system resource consumption and data timeliness.

[0042] Leveraging the capabilities of the Quartz framework, the timed scheduling unit supports multi-threaded parallel scheduling, enabling the creation of independent jobs and triggers for multiple different full-motion flight simulators (or multiple commercial sextant acquisition modules) simultaneously. When different simulators have different log transmission rates, the timed scheduling unit can allocate independent reading cycles to each device, ensuring no interference between them.

[0043] The timed scheduling unit is the starting point and trigger for the pipeline operation within the entire intelligent log parsing and processing module. After reaching a specified periodic node and reading the latest raw log file, the timed scheduling unit automatically triggers subsequent multi-dimensional log parsing units, and transmits the log file handle or data stream to the parsing units in real time, thereby driving the "reading" process. Analysis Cleaning The chain-like process of "state determination".

[0044] When a log file cannot be read within a preset period due to network fluctuations, sextant transmission interruptions, or file locking, the timed scheduling unit can promptly capture the read anomaly. Upon capturing the anomaly, the timed scheduling unit triggers a preset short-cycle retry mechanism (e.g., 3 consecutive retries). If read failures continue, the anomaly signal is sent to the anomaly diagnosis logic within the module. This logic automatically locates the cause of the anomaly based on network transmission status and device acquisition status, determining whether it is a network disconnection or a device malfunction, and triggers an alarm module to issue an alert.

[0045] Furthermore, when a new full-motion flight simulator is added to the system, the automatic expansion configuration function of the intelligent log parsing and processing module will notify the timing scheduling unit. The timing scheduling unit can automatically identify the new sextant and dynamically allocate initial reading cycles and scheduling tasks to it, without the need for manual restarting of the scheduling engine or modification of the underlying code, achieving "plug-and-play" rapid expansion.

[0046] The multi-dimensional log parsing unit is used to identify the format of log files, extract the characteristic angle axis values, and filter abnormal data.

[0047] In detail, the multi-dimensional log parsing unit uses a combination of regular expression matching and feature value extraction to identify the text format of log files and extract feature angle axis data from them. This unit then filters out abnormal data from the extracted feature angle axis values, removing invalid characters, missing data, and abnormal feature angle axis values ​​that are outside a reasonable range or exhibit excessively large instantaneous fluctuations.

[0048] Because different brands (such as CAE, Thales, etc.) or different models of commercial sextants output log files with different formats and field naming conventions, the multi-dimensional log parsing unit has a built-in keyword and regular expression mapping library. It can automatically recognize different textual expressions such as "Y-axis," "Pitch," or "X-axis," "Roll," and uniformly map and normalize them into the characteristic angle axis data format defined by the system's internal standard, thereby shielding the differences in underlying devices and achieving universal parsing of logs across brands.

[0049] Log files typically contain a large amount of text unrelated to runtime status determination (such as system startup logs, timestamp header information, sensor-irrelevant comments, Z-axis yaw / horizontal rotation data, etc.). When extracting feature angle axes, the multi-dimensional log parsing unit automatically strips and filters out these irrelevant comments and non-target dimension data, retaining only the core feature angle axis values ​​to reduce data processing overhead. During numerical extraction, the system automatically verifies the validity of data types (e.g., whether the extracted string can be legally converted to a floating-point number). If garbled characters, incomplete statements, or non-numeric characters are found, they are directly discarded.

[0050] The judgment logic and corresponding processing methods for filtering abnormal data are as follows: Determination of Exceeding Limits / Reasonable Range: Based on the preset physical limit range of the full-motion flight simulator (such as the reasonable physical range of pitch or tilt angle), the extracted feature angle axis values ​​are checked for boundaries, and outliers that exceed the reasonable physical range (such as distorted data generated by the sextant sensor hardware erroneous acquisition) are automatically removed.

[0051] Instantaneous fluctuation (noise) identification: By combining the data difference between adjacent frames, identify peak / trough noise (i.e., data with "excessive instantaneous fluctuation") caused by environmental micro-vibrations, mechanical collisions, or instantaneous transmission interference of sextant, and remove it or use the adjacent valid frame for smooth replacement.

[0052] The multi-dimensional log parsing unit acts as the intermediate hub for parsing and judgment. Upstream, it receives raw log data from the timed scheduling unit, and downstream, it delivers the cleaned, standardized "feature angle axis values" to the dynamic threshold operation status judgment unit in real time. When the log file is severely corrupted, the text format cannot match the regular expression at all, or the amount of extracted valid feature angle axis data is lower than the preset threshold, the multi-dimensional log parsing unit generates a data parsing anomaly signal and pushes it to the anomaly diagnosis logic within the module for fault cause diagnosis.

[0053] When the system automatically expands to include a new full-motion flight simulator, the multi-dimensional log parsing unit can automatically call a preset standard regular expression template to scan and automatically match the new log format. This allows for adaptive parsing and feature extraction of the new device's log format without rewriting the parsing code.

[0054] The dynamic threshold operation status judgment unit is used to dynamically fine-tune the basic threshold based on the preset feature angle axis basic threshold and the sliding window iterative optimization mechanism based on historical operation data to obtain the dynamically adjusted threshold. When the value of the feature angle axis extracted by parsing exceeds the dynamically adjusted threshold, it is determined that the full-motion flight simulator is in operation.

[0055] In the basic threshold of the characteristic angle axis, the upper and lower thresholds correspond to the pitch angle range of the full-motion flight simulator, and the left and right thresholds correspond to the tilt angle range of the full-motion flight simulator.

[0056] The process for determining whether a full-motion flight simulator is operational is as follows: The dynamic threshold operation status judgment unit is used to acquire multiple sets of continuously collected feature angle axis values, and dynamically allocate weighting coefficients based on data reliability for weighted fusion processing. The weighted fusion process feature angle axis values ​​are compared with the dynamically adjusted threshold to determine the operation status of the full-motion flight simulator.

[0057] In detail, for dynamically fine-tuning the base threshold using a sliding window iterative optimization mechanism, refer to... Figure 4 As shown, the fine-tuning amplitude is strictly controlled within the preset basic threshold. Within a certain range, to prevent the threshold from deviating from a reasonable physical range due to the accumulation of historical abnormal data. The sliding window continuously scrolls forward as new parsed data enters, dynamically updating historical statistical data (such as historical mean and variance) used for fine-tuning the threshold. This allows the dynamic threshold to adapt to minor drifts caused by long-term equipment aging while also possessing strong resistance to severe interference.

[0058] Weighted fusion processing based on dynamically assigned weighting coefficients according to data reliability can be performed in the following manner. Data reliability, used as the basis for adjustment, refers to real-time evaluation based on the stability and fluctuation range of the feature angle axis values. When performing weighted fusion on multiple consecutive sets (multiple frames) of feature angle axis values, the weighting coefficients are allocated according to the stability and fluctuation range of the data: Reduce or remove outlier weights: For outlier data that fluctuates drastically and deviates significantly from the mean of previous and subsequent frames, dynamically reduce their weighting coefficients (or even assign them a weight of 0, i.e., remove them). Increase the weight of smooth and stable data: Assign higher weighting coefficients to continuous, smooth data that conforms to the laws of physical motion.

[0059] It can perform independent adjustments on multiple axes. For example, it can independently and dynamically fine-tune the upper and lower thresholds of the corresponding pitch state (Y-axis); and independently and dynamically fine-tune the left and right thresholds of the corresponding tilt state (X-axis).

[0060] The formula for calculating the feature angle axis values ​​after weighted fusion processing is as follows: : Indicates the first Feature angle axis values ​​extracted from frame parsing Indicates according to the first The dynamic weighting coefficients for assigning data credibility to frame data. This represents the number of consecutively sampled frames. The dynamic weighting coefficient... The allocation logic is as follows: based on the first Frame value The reliability of the data is assessed by evaluating the degree of deviation from the mean or median of the data within the window. Smoothed data with deviations less than a preset tolerance are assigned a higher weighting coefficient, while outlier data with deviations exceeding the preset tolerance are assigned a lower or zero weighting coefficient. Through this weighted fusion calculation, instantaneous mechanical micro-vibrations and transmission noise in non-operating states can be effectively eliminated, improving the accuracy of subsequent state determination.

[0061] As shown in the figure, the feature angle axis values ​​after weighted fusion processing are compared with the dynamically adjusted threshold to determine the operating status of the full-motion flight simulator. The judgment logic can be divided into four dimensions: state triggering (entering the operating state), state maintenance / locking, state release (entering the stop state), and multi-axis collaborative judgment. The specific explanation is as follows.

[0062] 1. Triggering logic for "Running Status" (Startup Detection)

[0063] The system does not trigger its operational state based solely on a single threshold breach; rather, it incorporates threshold breach verification and persistence / multi-frame verification. Judgment criterion: When the feature angle axis value after weighted fusion processing... Exceeding the current dynamically adjusted threshold (Right now )hour; False alarm prevention mechanism (multi-frame continuous verification): When determining whether to enter the running state, continuous verification must be performed. The weighted fusion values ​​of each sampled frame (e.g., 2-3 consecutive periods) all exceed the dynamically adjusted threshold.

[0064] Judgment result and action: The system determines that the full-motion flight simulator is in "operational status"; Mark and record the current time as the start timestamp of a single run. ; The driver display module updates the device status to "Running" and begins to accumulate the runtime in real time.

[0065] 2. Logic for determining the "stopped state" (end determination and duration statistics)

[0066] To address the transition from "running state" back to "stopped state," the following closed-loop logic is established: "below threshold + continuous delay confirmation" (to prevent the simulator from being mistakenly identified as stopped due to temporary stability during operation): Judgment criterion: When the feature angle axis value after weighted fusion processing... Less than or equal to the dynamically adjusted threshold (Right now )hour; Stop Delay Confirmation (Anti-Early Shutdown Mechanism): The system starts a stop timer, requiring that the value below the dynamic threshold must continue for a preset stop judgment time threshold. (For example, 3 seconds to 30 seconds): If the value exceeds the dynamic threshold again within the delay time, the stop timer will be reset and the "running state" will be maintained. If the value remains below the dynamic threshold throughout the entire delay period, it is finally confirmed that the simulator has truly stopped.

[0067] Judgment result and action: The system determined that the full-motion flight simulator had switched to "stopped state"; Mark and record the current time as the end timestamp of a single run. ; Automatically calculate the duration of a single run The system then writes the current run record and the total accumulated duration into the data storage module.

[0068] 3. Collaborative determination logic for multiple feature angle axes (pitch Y-axis and tilt X-axis)

[0069] In actual flight simulation training, the simulator may only perform pitch (head up / down) or roll (side down). The comprehensive judgment of multiple axes adopts a judgment rule that combines "logical OR" and vector synthesis: Channel 1 (Pitch Attitude, Y-axis): Calculates the weighted fused values ​​along the Y-axis. With dynamically adjusted upper and lower thresholds Compare; Channel 2 (Tilt Attitude, X-axis): Calculates the weighted fusion values ​​along the X-axis. , and the dynamically adjusted left and right thresholds Compare; Comprehensive judgment formula:

[0070] The above determination formula shows that as long as the fused value of the pitch angle exceeds its upper and lower dynamic thresholds, or the fused value of the tilt angle exceeds its left and right dynamic thresholds, the system determines that the simulator is in a running state; only when the values ​​of the X-axis and Y-axis remain below their respective dynamic thresholds within the specified stop delay is it determined to be in a stopped state.

[0071] When the system automatically connects to a new full-motion flight simulator, the dynamic threshold operation status judgment unit will complete a "plug-and-play" adaptive matching through a series of mechanisms such as automatic configuration import, initial window construction, basic threshold calibration, and adaptive iterative startup.

[0072] Specifically, when the system automatically expands to include a newly added full-motion flight simulator, the adaptation process of the dynamic threshold operation status judgment unit is as follows: automatically receive the device identifier of the newly added full-motion flight simulator and automatically retrieve the preset feature angle axis basic threshold of the corresponding model; dynamically open an independent sliding window in memory for the newly added full-motion flight simulator and load the initially collected feature angle axis values ​​to establish an initial historical data sequence; start the initial calibration program to eliminate installation bias, and then start the sliding window iterative optimization and weighted fusion calculation for the newly added full-motion flight simulator, and output the dynamically adjusted threshold and operation status judgment results for the newly added device in real time within the fine adjustment range constraint.

[0073] The data storage module communicates with the intelligent log parsing and processing module and is used to store log files, parsed feature angle axis data, and running status judgment results.

[0074] The data storage module does not simply stack data, but adopts a structured partitioned storage design: Raw log file storage area: This area is specifically for archiving and preserving the raw log files transmitted from the commercial sextant, ensuring the originality and traceability of the data for subsequent offline review or troubleshooting. Analysis and Feature Data Storage Area: Stores time-series data extracted and cleaned by the multi-dimensional log analysis unit (such as the Y-axis pitch angle and X-axis tilt angle values ​​corresponding to different timestamps). Status and event log storage area: Stores the results of operation status determination, including the start timestamp, stop timestamp, single run duration, daily / monthly cumulative run duration, and abnormal alarm records for a single run; Configuration and threshold log storage area: records the system's basic thresholds, historical / trend data of dynamically adjusted thresholds generated by sliding window iteration, and configuration parameters of each device.

[0075] The data storage module provides data query and retrieval interfaces for the display module, responds to requests from the display module in real time, and outputs real-time operating status, historical operating curves, characteristic angle axis change trend charts, and dynamic threshold envelope data. When the alarm module is triggered, the data storage module is responsible for receiving and persistently saving alarm logs (such as alarm time, device number, type of out-of-limit value, and fault cause diagnosis results).

[0076] To prevent storage space from being filled with massive amounts of useless logs, the data storage module is configured with management policies for storage capacity and time periods. The data storage module automatically compresses and archives or periodically cleans up expired raw log data (such as data stored for more than 30 or 90 days), while persistently storing the extracted "operational status statistics results" and "daily runtime" for a long time, thus ensuring system storage security while also meeting the needs of long-term data statistics.

[0077] When the system automatically expands to include a new full-motion flight simulator, the data storage module has adaptive expansion capabilities: after receiving the registration instruction for the new device, the data storage module will automatically create an independent storage space, database table structure or storage partition for the newly added full-motion flight simulator, and automatically establish a mapping identifier (ID) for the new device. No manual modification of the database structure is required, realizing plug-and-play automatic storage of the new device's data.

[0078] The display module communicates with the data storage module and is used to display the real-time operating status, historical records, and characteristic angle axis change trends of the full-motion flight simulator.

[0079] The display module displays the following content: real-time operating status indicators of one or more full-motion flight simulators, historical running time statistics for each full-motion flight simulator, characteristic angle axis change trend curves, dynamic threshold adjustment curves, abnormal status alarm prompts, and algorithm operating status displays; it supports querying historical operating records, original log files, dynamic threshold adjustment records, and abnormal data filtering records by time range or simulator number.

[0080] The display module, for example, uses a visual display method to achieve a visual presentation of the interface and the details of layer overlay. The implementation method is as follows.

[0081] Dynamic threshold envelope overlay display: On the time-series trend curve of the characteristic angle axis (pitch Y-axis, tilt X-axis), the display module will simultaneously overlay and display the corresponding dynamic adjustment threshold envelope (Upper / Lower Threshold Envelope) for that characteristic angle axis. Operation and maintenance personnel can intuitively see the waveform trajectory and critical state of the characteristic angle axis value breaking through or falling below the dynamic threshold at different time points.

[0082] Multi-axis simultaneous / split-screen comparison: Supports multi-channel simultaneous display of the Y-axis (pitch) and X-axis (tilt) motion curves of a single simulator; for bases with multiple flight simulators, supports unified display of the real-time status of multiple devices on the main dashboard in the form of matrix cards or lists.

[0083] The display module provides interactive queries and links to original log traceability, and the implementation method is as follows.

[0084] "Trend-Log" Drill-Down Linkage: When displaying waveforms of characteristic angle axes showing filtered abnormal data records or exceeding thresholds, the display module supports interactive drill-down between chart nodes and the original log file. Users can click on a specific time node on the trend chart or abnormal record, and the display module can retrieve and highlight the corresponding time-segment of the original log text from the data storage module, achieving "waveform anomaly" tracking. Quickly locate and verify the original text.

[0085] Data export and report generation functions: Supports exporting historical runtime statistics, equipment utilization analysis, dynamic threshold adjustment history, and abnormal alarm logs into standard format documents (such as CSV, Excel, or PDF statistical reports) for equipment history archiving and utilization auditing by flight training management departments.

[0086] The display module supports multi-terminal adaptation and responsive interaction, and the implementation method is as follows.

[0087] Responsive adaptation for web and mobile devices: The display module is built on a front-end responsive framework and supports remote access via B / S architecture (browser terminal) or mobile devices / monitoring dashboards.

[0088] Real-time data push and refresh-free updates: The display module and data storage module / backend service adopt real-time push mechanisms such as WebSocket or long polling to ensure that the feature angle axis trend curve and running status indicators can be updated in real time without refreshing in milliseconds, reducing monitoring latency.

[0089] In addition, the display module supports "interface adaptive UI expansion" (automatic expansion configuration function) when new devices are connected. When the system automatically expands to connect a new full-motion flight simulator, the display module can receive the system's adaptive expansion command and automatically create and add the monitoring card, trend chart area and alarm status bar of the new simulator on the main monitoring interface. There is no need to manually reconfigure the front-end page components or modify the front-end code, realizing "plug and play" visual expansion.

[0090] Preferably, the system in this embodiment further includes: an alarm module, which is communicatively connected to the intelligent log parsing and processing module; when the characteristic angle axis value of the full-motion flight simulator exceeds the threshold range after dynamic adjustment or the log file transmission is interrupted, the alarm module issues an alarm reminder via SMS push or WeChat push.

[0091] In addition to "value exceeding limits" and "log transmission interruption", alarm triggering conditions have been extended to internal system malfunctions and data anomalies: Severe data parsing anomaly: When the log file is corrupted, the format is completely unable to match the regular expression, or the amount of valid data extracted by the multi-dimensional log parsing unit is lower than the preset threshold, a data parsing anomaly alarm is triggered. Hardware / Network Equipment Fault Diagnosis Alarm: Linked with the abnormal diagnosis logic in the intelligent log parsing and processing module, when the diagnosis logic locates a sextant hardware fault or a network physical link disconnection, it issues a precise hardware / network fault alarm. Threshold fine-tuning anomaly alarm: When the initial threshold calculated by the sliding window iteration is frequently exceeded. When the constraint boundary or the characteristic angle axis value shows a continuous and large outlier jump, the sensor status / environment micro-seismic anomaly prompt is triggered.

[0092] Alarm channels and methods are diverse, including not only SMS and WeChat for Business, but also the following: Local audio-visual / pop-up alerts: A highlighted red box and sound alarm will pop up simultaneously on the display module interface in the monitoring room (local visual / audible alert); Internal system log recording: Detailed information of each alarm event (timestamp, device number, alarm type, abnormal value and diagnostic conclusion) is synchronized to the data storage module in real time to form an alarm history log.

[0093] The alarm module supports alarm classification and anti-harassment (suppression) mechanisms: Alarm classification management: Alarms are classified into different levels according to the severity of the anomaly (such as "general anomaly / notification level", "data interruption / warning level", "equipment failure / critical level"). Different push channels and recipients are triggered for different levels (such as general notifications are only pushed to the front-end interface, while critical failures are triggered simultaneously via SMS and WeChat). Alarm suppression and deduplication (preventing frequent occurrences): For persistent faults (such as log files that cannot be transmitted continuously or exceed limits for a long time), the alarm module has a frequency control and deduplication mechanism. After the first alarm, it enters a cooling-off period or performs periodic merging and push, avoiding sending a large number of duplicate alarm messages to maintenance personnel in a short period of time.

[0094] Alarm response and linkage tracing support one-click jump and fault location: alarm notifications pushed by WeChat or SMS can include fault tracing links / device IDs. Maintenance personnel can click the notification to jump directly to the corresponding device monitoring card in the display module, drill down to retrieve the original logs and waveform curves 5-10 minutes before and after the alarm time for quick troubleshooting.

[0095] When the system automatically expands to connect a new full-motion flight simulator, the alarm module can automatically synchronize the identification and configuration of the new device, and automatically incorporate the transmission status and characteristic angle axis values ​​of the new device into the alarm monitoring logic, without the need to manually rewrite or configure alarm rules for the new device.

[0096] Figure 2 An embodiment of the full-motion flight simulator operation status monitoring method of the present invention is shown. The method of this embodiment is applied to applications such as... Figure 1 The method of the full-motion flight simulator operation status monitoring system shown includes the following steps.

[0097] Step 1: Collect angle change data generated during the operation of the full-motion flight simulator using a commercial sextant acquisition module fixed to the connection line of the full-motion flight simulator, generate a log file containing characteristic angle axis values, and then transmit the log file externally.

[0098] Step 2: The intelligent log parsing and processing module uses a timed scheduling unit to read log files according to a preset cycle.

[0099] Step 3: The multi-dimensional log parsing unit of the intelligent log parsing and processing module identifies the format of the log file, extracts the characteristic angle axis values, and filters out abnormal data.

[0100] Step 4: The dynamic threshold operation status judgment unit of the intelligent log parsing and processing module dynamically fine-tunes the basic threshold based on the preset feature angle axis basic threshold and the historical operation data using a sliding window iterative optimization mechanism to obtain the dynamically adjusted threshold; and when the parsed and extracted feature angle axis value exceeds the dynamically adjusted threshold, it is determined that the full-motion flight simulator is in operation.

[0101] Step 5: Store the log file, parsed feature angle axis data, and running status judgment results through the data storage module.

[0102] Step Six: Display the real-time operating status, historical records, and characteristic angle axis change trends of the full-motion flight simulator through the display module.

[0103] The prior description of this disclosure is provided to enable any person skilled in the art to make or use this disclosure. Various modifications to this disclosure will be apparent to those skilled in the art, and the general principles defined herein may be applied to other variations without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not intended to be limited to the examples and designs described herein, but should be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A monitoring system for the operational status of a full-motion flight simulator, characterized in that, The system includes: The attitude acquisition module is fixed to the connection line of the full-motion flight simulator. It is used to collect the angle change data generated during the operation of the full-motion flight simulator, generate a log file containing the characteristic angle axis values, and then transmit the log file to the outside. The intelligent log parsing and processing module, which is communicatively connected to the attitude acquisition module, is configured with a timed scheduling unit, a multi-dimensional log parsing unit, and a dynamic threshold operation status judgment unit. The timed scheduling unit is used to read the log file according to a preset period. The multi-dimensional log parsing unit is used to identify the format of the log file, extract the feature angle axis values, and filter abnormal data. The dynamic threshold operation status judgment unit is used to dynamically fine-tune the base threshold based on a preset feature angle axis base threshold and a sliding window iterative optimization mechanism based on historical operation data to obtain a dynamically adjusted threshold. When the parsed and extracted feature angle axis values ​​exceed the dynamically adjusted threshold, the module determines that the full-motion flight simulator is in operation. The data storage module is communicatively connected to the intelligent log parsing and processing module, and is used to store the log file, the parsed feature angle axis data, and the running status judgment result; The display module is communicatively connected to the data storage module and is used to display the real-time operating status, historical records, and characteristic angle axis change trends of the full-motion flight simulator.

2. The full-motion flight simulator operation status monitoring system according to claim 1, characterized in that, The attitude acquisition module is a commercial sextant acquisition module.

3. The full-motion flight simulator operation status monitoring system according to claim 1, characterized in that, The commercial sextant acquisition module is fixed by using a flexible fastener that passes through a pre-drilled hole in the commercial sextant to fix it to the connection line of the full-motion flight simulator. The fixed position avoids the connector and moving parts of the connection line. The flexible fastener includes a flexible strap, a flexible rope, or a wear-resistant buckle.

4. The full-motion flight simulator operation status monitoring system according to claim 1, characterized in that, The characteristic angle axis is an angle axis that reflects the pitch or tilt state of the full-motion flight simulator, including the Y-axis, X-axis, or Z-axis.

5. The full-motion flight simulator operation status monitoring system according to claim 1, characterized in that, The timed scheduling unit adopts the Quartz scheduling framework and dynamically adjusts the reading cycle of the log file based on the log data transmission rate and data volume.

6. The full-motion flight simulator operation status monitoring system according to claim 1, characterized in that, The intelligent log parsing and processing module is also configured with anomaly diagnosis logic, which is used to automatically locate the cause of the anomaly based on the network transmission status and device acquisition status when the log file cannot be read or the feature angle axis value exceeds the threshold range.

7. The full-motion flight simulator operation status monitoring system according to claim 1, characterized in that, The multi-dimensional log parsing unit uses a combination of regular expression matching and feature value extraction to identify the text format of the log file and extract the feature angle axis data from the log file. The multi-dimensional log parsing unit is used to filter abnormal data from the extracted feature angle axis values, filtering out invalid characters, missing data, and abnormal feature angle axis values ​​that exceed reasonable ranges or fluctuate too much.

8. The full-motion flight simulator operation status monitoring system according to claim 1, characterized in that, Among the basic threshold values ​​of the characteristic angle axis, the upper and lower threshold values ​​correspond to the pitch angle range of the full-motion flight simulator, and the left and right threshold values ​​correspond to the tilt angle range of the full-motion flight simulator.

9. The full-motion flight simulator operation status monitoring system according to claim 1, characterized in that, The dynamic threshold operation status judgment unit is used to acquire multiple sets of continuously collected feature angle axis values, and dynamically allocate weighting coefficients based on data reliability to perform weighted fusion processing. The feature angle axis values ​​after weighted fusion processing are compared with the dynamically adjusted threshold to determine the operation status of the full-motion flight simulator.

10. The full-motion flight simulator operation status monitoring system according to claim 9, characterized in that, The specific logic of the dynamic threshold operation status determination unit in determining the operation status of the full-motion flight simulator is as follows: The weighted fusion processing of the feature angle axis values ​​is compared with the dynamically adjusted threshold. For the characteristic angle axes corresponding to the pitch and tilt states, respectively, their weighted fusion values ​​are obtained. and ;when Exceeding the dynamically adjusted upper and lower thresholds, or When the left and right thresholds are exceeded after dynamic adjustment, and this breakthrough state continues for a preset number of operation confirmation frames, the full-motion flight simulator is determined to have entered the operation state, and the operation start timestamp is recorded. ; In running state, when and When all values ​​are below their respective dynamically adjusted thresholds, and the duration of these values ​​remains below the thresholds for a preset stop determination time threshold, the full-motion flight simulator is determined to switch to a stopped state, and a stop timestamp is recorded. And calculate the duration of a single run.

11. The full-motion flight simulator operation status monitoring system according to claim 1, characterized in that, The display module displays the following content: real-time operating status indicators of one or more full-motion flight simulators, historical running time statistics for each full-motion flight simulator, characteristic angle axis change trend curves, dynamic threshold adjustment curves, abnormal status alarm prompts, and algorithm operating status displays; it supports querying historical operating records, original log files, dynamic threshold adjustment records, and abnormal data filtering records by time range or simulator number.

12. The full-motion flight simulator operation status monitoring system according to claim 1, characterized in that, The system also includes: The alarm module is communicatively connected to the intelligent log parsing and processing module. When the characteristic angle axis value of the full-motion flight simulator exceeds the threshold range after dynamic adjustment or the log file transmission is interrupted, the alarm module sends an alarm reminder via SMS or WeChat push.

13. A method for monitoring the operational status of a full-motion flight simulator, using the full-motion flight simulator operational status monitoring system as described in any one of claims 1-12, characterized in that, Includes the following steps: The attitude acquisition module, which is fixed to the connection line of the full-motion flight simulator, collects the angle change data generated during the operation of the full-motion flight simulator, generates a log file containing characteristic angle axis values, and then transmits the log file outward. The log file is read by the timed scheduling unit of the intelligent log parsing and processing module according to a preset period. The intelligent log parsing and processing module identifies the format of the log file through its multi-dimensional log parsing unit, extracts the characteristic angle axis values, and filters out abnormal data. The dynamic threshold operation status judgment unit of the intelligent log parsing and processing module dynamically fine-tunes the basic threshold based on the preset feature angle axis basic threshold and the historical operation data using a sliding window iterative optimization mechanism to obtain the dynamically adjusted threshold; and when the parsed and extracted feature angle axis value exceeds the dynamically adjusted threshold, it is determined that the full-motion flight simulator is in operation. The log file, the parsed feature angle axis data, and the running status judgment results are stored through the data storage module. The display module shows the real-time operating status, historical records, and characteristic angle axis change trends of the full-motion flight simulator.

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