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At present, commonly used methods of weak signal detection such as the wavelet threshold denoising method, digital filtering method, the Fourier frequency domain transformation etc. can achieve the lowest detection of signal-to-noise ratio (SNR) of -10 dB, and the bidirectional ring coupled Duffing oscillator can reach the lowest detected SNR of -20 dB. But the discharge pulse signal with a lower SNR often appears in on-site testing, so the existing detection methods are difficult to meet the practical requirements of weak signal detection. In order to effectively solve the problem, a new method for weak pulse signal detection is proposed based on an extended-Duffing oscillator. The main idea of this method is to make the Duffing oscillator model transform to an extended-Duffing oscillator model by using the general time scale transformation. This approach can effectively expand the frequency detection range for weak signal detection. In addition, because the critical amplitude of the Duffing system depends on various parameters, such as system parameters, initial values, driving signal frequency, and calculation step of Runge - Kutta method etc.. However, the Melnikov method is an approximate analytical method, which does not take into account the factors such as initial values and calculation step, therefore, the Melnikov method is not suitable for numerical simulations, and lack of practicality. For this, the critical amplitude of chaos with high accuracy is determined only through the simulation experiment. Experimental results show that the critical amplitude is equal to 0.825010 when the incentive angular frequency of the extended-Duffing oscillator equals 10000 rad/s, and the extended-Duffing oscillator changes from the critical chaotic state to the large scale cycle state for small changes (10-6) of the driving amplitude. The simulation results show that the extended-Duffing oscillator not only has a good noise immunity performance, but also can effectively detect weak partial discharge pulse signal so that the signal-to-noise ratio can be lower than -40 dB. This method further expands the detection range and application fields of weak signals.

Time delay frequently appears in many phenomena of real life and the presence of time delay in a chaotic system leads to its complexity. It is of great practical significance to study the synchronization control of fractional-order chaotic systems with time delay. This is because it is closer to the real life and its dynamical behavior is more complex. However, the chaotic system is usually uncertain or unknown, and may also be affected by external disturbances, which cannot make the ideal model accurately describe the actual system. Moreover, in most of existing researches, they are difficult to realize the synchronization control of fractional-order time delay chaotic systems with unknown terms. In this paper, for the synchronization problems of the different structural fractional-order time delay chaotic systems with completely unknown nonlinear uncertain terms and external disturbances, based on Lyapunov stability theory, an adaptive radial basis function (RBF) neural network controller, which is accompanied by integer-order adaptive laws of parameters, is established. The controller combines RBF neural network and adaptive control technology, the RBF neural network is employed to approximate the unknown nonlinear functions, and the adaptive laws are used to adjust corresponding parameters of the controller. The system stability is analyzed by constructing a quadratic Lyapunov function. This method not only avoids the fractional derivative of the quadratic Lyapunov function, but also ensures that the adaptive laws are integer-order. Based on Barbalat lemma, it is proved that the synchronization error tends to zero asymptotically. In the numerical simulation, the uncertain fractional-order Liu chaotic system with time delay is chosen as the driving system, and the uncertain fractional-order Chen chaotic system with time delay is used as the response system. The simulation results show that the controller can realize the synchronization control of the different structural fractional-order chaotic systems with time delay, and has the advantages of fast response speed, good control effect, and strong anti-interference ability. From the perspective of long-term application, the synchronization of different structures has greater research significance and more development prospect than self synchronization. Therefore, the results of this study have great theoretical significance, and have a great application value in the field of secure communication.

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