Real-time multitask scheduling method based on DSP (Digital Signal Processor) fly ash carbon content measurement

Abstract

The invention discloses a real-time multitask scheduling method based on DSP (Digital Signal Processor) fly ash carbon content measurement. The fly ash carbon content is measured on line based on a DSP by adopting a BP neural network algorithm, a non-real time task (BP neural network parameter training) and a real time task (online fly ash carbon content prediction) are simultaneously performed bya Protothread multithreading model, the 'real-time property' and 'concurrency' of multitask scheduling can be ensured, and the problems that the storage capacity in the DSP is limited and the measuring real-time property is poor because the BP neural network algorithm is complicated and the training data quantity is high are effectively solved, so that the real-time online measurement of the flyash carbon content is realized.

Description

technical field [0001] The invention belongs to the technical field of sensor detection and digital signal processing, in particular to a real-time multi-task scheduling method based on DSP fly ash carbon content measurement. Background technique [0002] In industrial thermal power generation, the carbon content of fly ash is an important indicator affecting the boiler combustion system. Real-time and online measurement of carbon content in fly ash is conducive to adjusting the ratio of primary air volume and incoming coal powder, improving combustion efficiency, and improving boiler units. The safety and economy of operation are of great significance to the prevention of environmental pollution. [0003] At present, most of the existing fly ash carbon content measurement devices use physical measurement methods, including electrostatic methods, microwave methods, optical reflection methods, etc., and their devices all have problems such as complex equipment, high cost of c...

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Problems solved by technology

[0004] The purpose of the present invention is to provide a real-time multi-task scheduling method based on DSP fly ash carbon content measurement, to solve the problems caused by complicated algorithm and large amount of parameter training data in measuring fly ash carbon content based on DSP using BP neural network algorithm The problem of limited DSP storage and poor real-time measurement, and then realize the real-time online measurement of fly ash carbon content

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