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摘要: 为有效解决民用航空器的机载快速存取记录器(QAR)航迹数据中飞行阶段出现错误划分的情况，通过航空器气动构型和垂直运动态势变化提出了飞行阶段重新划分方法，具体分为4个步骤：数据预处理、垂直运动态势划分、飞行状态特征模型构建和飞行阶段重新划分；使用基于DBSCAN的局部遍历聚类方法对气压高度变化趋势进行聚类分析，划分垂直运动态势，并通过设置有效态势最短持续时间解决气压高度的局部抖动问题；考虑不同机型在不同飞行阶段时的襟翼位置和操纵各不相同，场面滑行时的场压抖动以及空速表在低速滑行时数值不准确等因素，根据航空器襟翼位置开关、起落架位置、地速和垂直态势等状态参数建立适合所有机型的飞行状态特征模型，并对QAR航迹划分飞行状态特征段；建立各飞行阶段与飞行状态特征的关系模型，结合起落架空地逻辑将所有飞行状态特征段识别为对应的飞行阶段。以3个典型的样本航班为例，计算结果表明：航班包含复飞在内的所有飞行阶段均被有效识别和划分，并与航空器飞行时的襟翼和起落架状态保持一致, 原QAR数据中的飞行阶段错误划分问题得到有效解决；对272 268个航班的QAR航迹进行了飞行阶段重新划分，成功率为99.7%，起飞、初始爬升、进近和着陆等非光洁构型飞行阶段的平均历时分别为0.6、1.9、6.1和4.0 min，平均距地高度分别为54、3 680、6 030和2 500 ft，符合航班实际运行规律。可见，所建立的飞行阶段重新划分方法可适用于大批量航班，为民用航空器的飞行阶段特征分析提供技术支撑。Abstract: To resolve the flight phase identification errors in the airborne quick access recorder (QAR) trajectory data of civil aircraft, a method of flight phase re-identification was proposed based on the aerodynamic configuration and vertical movements of aircraft. This method comprises four steps: preprocessing of QAR data, identification of vertical movements, construction of a flight state characteristics model, and re-identification of flight phases. A DBSCAN-based local traversal clustering method was used to cluster the trends of pressure altitude to classify vertical movements, and a valid minimum state persistence time was set to eliminate the local flutter in the pressure altitude data. Considering aircraft-to-aircraft differences in flap position and control, fluctuations in airfield QFE, and inaccuracies in the airspeed indicator during low-speed taxiing, a flight-state characteristics model suitable for all types of aircraft and based on state parameters, such as flap switch position, landing gear position, ground speed, and vertical movements, was constructed. The model was used to divide the QAR data into flight state characteristic segments. The relationship model between each flight phase and flight state characteristics was established, and all flight state feature segments were identified as corresponding flight stages combined with landing gear air-ground logic. Three typical sample flights are used as examples, calculation results show that all the flight phases (including go-arounds) are correctly identified and divided, and are also fully consistent with the flap and landing gear states of the aircraft. The flight phase identification error in raw QAR data fields is solved effectively. The flight phases of QAR tracks of 272 268 flights are re-identified, and the success rate is 99.7%. The average durations of non-clean configuration flight phases, such as take-off, initial climb, approach, and landing, are 0.6, 1.9, 6.1 and 4.0 min, respectively, and the average altitudes from the ground are 54, 3 680, 6 030 and 2 500 ft, respectively, which are consistent with the actual flight operation behaviors. Therefore, the flight-phase re-identification method can be applied to numerous flights and provide technical support in analyzing the characteristics of civil aircraft flight phases. 5 tabs, 8 figs, 25 refs.
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图 2 样本航班1的垂直运动态势划分结果
Figure 2. Vertical movement identification result of sample flight
图 3 样本航班1的飞行状态特征划分结果
Figure 3. Flight status characteristics identification result of sample flight 1
图 4 飞行阶段与状态特征段的关系
Figure 4. Relation between flight phase and status characteristic phase
图 5 基于状态特征段的飞行阶段划分算法流程
Figure 5. Flow of flight phase identification algorithm based on status characteristic phase
图 7 QAR自带飞行阶段与重新划分后的结果对比
Figure 7. Comparison between QAR's original flight phases and re-identification results
表 1 数据字段
Table 1. Data fields
字段名 全称 描述 FID Flight Identification 航班识别码 TIME Time Stamp 时间戳 LON Longitude 经度(WGS-84大地坐标系) LAT Latitude 纬度(WGS-84大地坐标系) PA Pressure Altitude 压力高度(基准为1 013 mb) GS Ground Speed 地速 IAS Indicated Air Speed 表速 TAS True Air Speed 真空速 IVV Inertial Vertical Speed 垂直速度 MACH Mach Number 马赫数 TAT Total Air Temperature 总温 TH True Heading 真航向 FLAP Flaps Position 襟翼位置 SLAT Slats Position 缝翼位置 LDG_SELDW Gears Selection Down 起落架位置 LDG_CMPRSD Gears Compression Sensor 起落架空地逻辑 N1 Engine N1 Tachometer 发动机N1转速百分比 N2 Engine N2 Tachometer 发动机N2转速百分比 FF Fuel Flow 发动机燃油流率 GW Gross Weight 航空器质量 
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表 2 姿态与构型特征定义
Table 2. Definitions of attitudes and configuration characteristics
飞行阶段 起落架位置 起落架空地逻辑 襟翼 缝翼 垂直态势 滑出 放下 地 关/小/中/全 关/中/全 LEV 起飞 放下 地→空 小/中 中 LEV/CLM 初始爬升 收起 空 小/中 中 CLM/LEV 爬升 收起 空 关 关 CLM 巡航 收起 空 关 关 LEV 下降 收起 空 关 关 DES 进近 收起 空 小/中/全 中/全 DES/LEV/CLM 着陆 放下 空→地 中/全 中/全 DES/LEV 着陆(取消) 放下 空 中/全 中/全 DES/LEV 复飞爬升 放下 空 中/全 中/全 CLM 滑入 放下 地 关/小/中/全 关/中/全 LEV
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表 3 A320系列的襟翼和缝翼
Table 3. Flaps and slats of A320 series
档位 形态 襟翼 缝翼 使用阶段 0 0 0 0 巡航 等待 1 1 0 18 1+F 10 起飞 2 2 15 22 进近 3 3 20 22 着陆 FULL FULL 35 27
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表 4 飞行状态特征分类
Table 4. Classification of flight state characteristics
特征 起落架位置 地速 襟翼开关 垂直运动态势 1 放下 ≤ 40 kt 2 放下 > 40 kt 3 收起 ON CLM 4 收起 ON LEV 5 收起 ON DES 6 收起 OFF
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表 5 飞行阶段重新划分失败原因
Table 5. Reasons for failure to re-identify flight phases
原因描述 影响范围 航班数量 占比/% 襟翼和缝翼字段数值始终保持为0 起飞、初始爬升、进近、着陆、复飞 758 93.58 QAR航迹不完整 滑出、起飞、初始爬升、进近、着陆、复飞、滑入 48 5.93 起飞过程中先收襟翼、后收起落架 初始爬升 4 0.49
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