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Describes how radio telemetry can interface with process control systems such as supervisory control and data acquisition [SCADA] and distributed control systems [DCS] greatly increasing their power and efficiency. Outlines the basis of radio telemetry, the behaviour of electromagnetic waves, frequency and wavelengths. Uses the water industry as an example of the use of a large scale and sophisticated SCADA system to provide date collection and control links over a large area. Concludes that the versatility of radio telemetry coupled with its cost‐effectiveness means that this technology can help to expand and improve communications in an increasing number of industries.

The purpose of this paper is to ensure the stable operation of satellites in orbit and to assist ground personnel in continuously monitoring the satellite telemetry data and finding anomalies in advance, which can improve the reliability of satellite operation and prevent catastrophic losses.

This paper proposes a deep auto-encoder (DAE) satellite anomaly advance warning framework for satellite telemetry data. Firstly, this study performs grey correlation analysis, extracts important feature attributes to construct feature vectors and builds the variational auto-encoder with bidirectional long short-term memory generative adversarial network discriminator (VAE/BLGAN). Then, the Mahalanobis distance is used to measure the reconstruction score of input and output. According to the periodic characteristic of satellite operation, a dynamic threshold method based on periodic time window is proposed. Satellite health monitoring and advance warning are achieved using reconstruction scores and dynamic thresholds.

Experiment results indicate DAE methods can probe that satellite telemetry data appear abnormal, trigger a warning before the anomaly occurring and thus allow enough time for troubleshooting. This paper further verifies that the proposed VAE/BLGAN model has stronger data learning ability than other two auto-encoder models and is sensitive to satellite monitoring data.

This paper provides a DAE framework to apply in the field of satellite health monitoring and anomaly advance warning. To the best of the authors’ knowledge, this is the first paper to combine DAE methods with satellite anomaly detection, which can promote the application of artificial intelligence in spacecraft health monitoring.

The purpose of this paper is to develop the model of telemetry data processing flow (TDPF) for TDPF development and the TDPF run-time infrastructure to improve the spacecraft health monitoring capability.

This research tries to develop the TDPF by flow-based programming (FBP) method and the component-based telemetry data processing software.

The result from the case study is positive, thus reflecting the appropriateness of the suggested method.

Application of the proposed TDPF model and the component-based telemetry data processing software may result in improved development efficiency and less development costs.

This paper provides an effective way to develop TDPF without recompiling the software. It greatly facilitates the TDPF development that hopefully will save the TDPF development cost.

To improve the speed and precise of online monitoring and diagnosis for satellite using satellite telemetry data.Design/methodology/approach – In monitoring system, a fuzzy range which gives the probability of alarm for telemetry channels using fuzzy reasoning is outlined. A failure confidence factor is presented to modify the traditional real‐time diagnosis algorithm based on multisignal model to describe the relative failure possibility for suspected components. According to the modified real‐time diagnosis algorithm based on multisignal model, it rapidly generates the states for all the components of the system such as good, bad, suspected and unknown. Then the failure probability for suspected components is obtained by Mamdani fuzzy reasoning algorithm.Findings – The experimental results reveal that the diagnosis system can not only improve diagnosis of speed but also can improve the diagnostic precision by giving failure probability for suspected fault components which may be potential failure components.Research limitations/implications – It requires the clear fault dependency relationship between components and tests.Practical implications – A very useful method for researchers and engineers who are engaged in satellite online monitoring and diagnosis.Originality/value – This paper presents a new method combining multisignal model and fuzzy theory to give the failure probability for suspected components which improves the speed and precision for fault diagnosis.

Dynamic Logic, in cooperation with Global Cathodic protection Ltd, has applied its wide experience of telemetry techniques to the automatic monitoring of cathodic protection equipment.

An overview of radio telemetry, concentrating on low power, short‐range systems which can be operated without equipment licences. Describes transmission mechanisms, aerials and the two main types of analogue modulation: amplitude modulation [AM] and frequency modulation [FM].Outlines the developments in radio data links and modulation schemes, the benefits of networks and the various methods of encoding data. Concludes that one of the biggest problems in radio telemetry is the different regulations across Europe making it virtually impossible to design a transmitter that is acceptable in more than one country. However, in Europe the situation is slowly changing, with new common standards for defining, evaluating and testing equipment coming into effect.

TELEMETRY is the science by which a measurement of a quantity is transferred to a remote location to be recorded, displayed or used to actuate another process. It typically involves the grouping of individual data measurements in a format that can be transmitted and or stored on a single medium, retrieved from that medium and separated into the individual measurements so they are available for inspection. If there is a more complimentary role for the modern data‐recorder it would be difficult to imagine it.

The efficiency of range telemetry, as currently practiced, is somewhat limited by the available display technology. The manpower, space and accuracy problems associated with current methods are examined, and the limitations of some new approaches are discussed The concept of Real Time Digital Strip Chart Emulation (RTDSCE), as exemplified by the ES2000 System, and the benefits inherent to such a technical approach are presented and discussed in detail These benefits include reduction of manpower and space requirements by the use of the workstation concept, the elimination of D/A conversion by direct recording of digitised signals, and the facilitation of critical realtime viewing through high resolution video monitoring.

The purpose of this paper is to detect the occurrence of anomaly and fault in a spacecraft, investigate various tendencies of telemetry parameters and evaluate the operation state of the spacecraft to monitor the health of the spacecraft.

This paper proposes a data-driven method (empirical mode decomposition-sample entropy-principal component analysis [EMD-SE-PCA]) for monitoring the health of the spacecraft, where EMD is used to decompose telemetry data and obtain the trend items, SE is utilised to calculate the sample entropies of trend items and extract the characteristic data and squared prediction error and statistic contribution rate are analysed using PCA to monitor the health of the spacecraft.

Experimental results indicate that the EMD-SE-PCA method could detect characteristic parameters that appear abnormally before the anomaly or fault occurring, could provide an abnormal early warning time before anomaly or fault appearing and summarise the contribution of each parameter more accurately than other fault detection methods.

The proposed EMD-SE-PCA method has high level of accuracy and efficiency. It can be used in monitoring the health of a spacecraft, detecting the anomaly and fault, avoiding them timely and efficiently. Also, the EMD-SE-PCA method could be further applied for monitoring the health of other equipment (e.g. attitude control and orbit control system) in spacecraft and satellites.

The paper provides a data-driven method EMD-SE-PCA to be applied in the field of practical health monitoring, which could discover the occurrence of anomaly or fault timely and efficiently and is very useful for spacecraft health diagnosis.

Flight testing of modern high performance aircraft has generated an increasingly complex data handling workload and this contributes significantly to the duration and cost of flight test programmes. Automation of this critical data handling process can reduce the high cost of such a programme by reducing its duration. The effects of automation of data flow at the ground station can be enhanced by the use of immediate flight analysis of data telemetered from the aircraft.