Research On Judgment Method Of Ultrasonic Signal Onest Based On Intelligent Fitting Algorithm

Natural gas is a kind of clean energy whose calorific value is high but emission is low.The development and utilization of natural gas is of great significance for alleviating energy issues,combating climate change,and promoting sustainable development.China has successively launched grand natural gas transmission projects such as "the west-east gas pipeline project","the Sichuan-east gas pipeline project","the Russia-south gas pipeline project" and "landing gas from sea",and also built a trunk gas pipeline network with a total length of nearly 70,000 kilometers.The types of gas transmission include conventional natural gas,coal bed methane,shale gas and LNG.Because of advantages of high precision,wide range of measurement,low pressure and so on,time difference ultrasonic gas flowmeter is considered as the preferred instrument for natural gas measurement.However,in the face of such a complex pipeline environment and complex gas components,there are still some difficulties in practical applications of ultrasonic gas flowmeter,especially the difficulty in measurement of time-of-flight(TOF)of ultrasonic signal caused by signal amplitude fluctuation,waveform distortion and phase-frequency characteristics change of signal.Consequently,the measurement accuracy and reliability of flowmeter are seriously affected.Therefore,it is of great significance to improve the measurement accuracy and reliability of the time difference ultrasonic gas flowmeter in face of complex pipeline environment and complex gas source components through technology and method innovation.The accurate measurement of TOF is the fundamental guarantee of high-performance time difference ultrasonic gas flowmeter.However,the existing TOF measurement methods show disadvantages such as unreliable measurement,low accuracy and easy to be affected by transducer's characteristics due to the complicated application conditions of the time difference ultrasonic gas flowmeter.Therefore,this paper studies the TOF measurement method based on intelligent algorithms and the numerical model of the ultrasonic signal,and carries out relevant work on the reliability,accuracy and speed improvement of TOF measurement respectively,particularly in the following aspects:(1)Based on the ultrasonic exponential model,this paper estimates model parameters using artificial fish swarm algorithm(AFSA)and particle swarm optimization(PSO)jointed algorithm.Meanwhile,this paper proposes a feasible solution extraction strategy which is embedded in the jointed algorithm.The proposed strategy solves the problem that traditional ultrasonic signal onset detection algorithms are prone to fall into a local optimum and helps to avoid the problem of cycle-skip in USO detection.Subsequently,the jointed algorithm improves the USO detection reliability under noisy environment and complicated working conditions.(2)By analyzing the frequency characteristics of ultrasonic receiving signals,an improved ultrasonic signal model with time-varying frequency function is established.Subsequently,USO estimation error based on the new model is reduced to 1/3 of those based on traditional model.(3)Firstly,make sure the received signal having the similar normalized amplitude characteristics by using the coding excitation.Then,achieve the detection of a fixed zero-crossing in the received signal by comparing the similarities between continuous waveforms,which realizes fast positioning of USO and improves the speed of USO detection.Simulation results show that this method reduces the running time of algorithm to 1/3 of the original running time.In the end,the paper carries out practical application and verification of the proposed TOF measurement method.The experimental results show that the proposed method can achieve accurate and reliable USO measurement for time difference ultrasonic gas flowmeter in face of complex pipeline environment and complex gas source components.The main contents of this paper are presented as follows:1.Ultrasonic characteristic parameters determination based on artificial fish swarm algorithm and particle swarm optimization jointed algorithmAn explanation of USO detection principle based on model fitting is presented.This paper points out the shortcomings of the existing USO detection algorithms and then proposes an AFSA and PSO jointed algorithm.A feasible solution extraction strategy is also proposed through analyzing the output individual characteristics of AFSA.Based on this strategy,PSO achieves repeatedly accurate search in each USO local optimum region.These operations help to avoid the cycle-skip problem caused by a wrong abandon of global optimum region.Finally,the USO measurement reliability of the proposed algorithm is validated by both numerical and practical experiments.2.Improved ultrasonic signal model with time-varying frequencyBy the modeling and analyzing the equivalent circuits of the transmitting and receiving part of flowmeter,this paper reveals the complicated instantaneous frequency in real ultrasonic signal and points out that the constant frequency parameter cannot accurately describe the complex transient frequency is the fundamental cause for the USO detection error based on traditional model.In order to achieve accurate USO measurement,this paper proposes an improved ultrasonic signal model with time-varying frequency and obtains the instantaneous frequency by using the Teager Energy Operator(TEO).This paper conducts tests on both traditional and improved model using signals with different instantaneous frequencies.The results show that the improved model is of great significance in improving the USO detection precision.3.Fast USO positioning method based on enhanced similarity judgementThis paper points out that temperature affects normalized waveform amplitude characteristics the most by analyzing them under different working conditions.Based on this finding,this paper proposes a fast USO positioning method,which achieves reliable detection of a fixed zero-crossing of the signal by comparing the similarity between waveforms from continuous measurements and then quickly determines the time range of USO.This paper also proposes a method to control the waveform amplitude characteristics by coding excitation,which ensures the similar normalized waveform amplitude characteristics under different working conditions and enhances the fast USO positioning method.The feasibility of fast USO positioning method,coding excitation and enhanced fast USO positioning method are validated by both numerical and practical experiments.4.Application and verfification of intelligent USO detection algorithm in time differential gas ultrasonic flowmeterThe proposed USO detection algorithm is applied to the the time difference ultrasonic gas flowmeter prototype developed by our team.Various tests on experimental platform are conducted to validate the feasibility of the USO detection method based on intelligent fitting algorithm.