In the fault diagnosis field, the fault feature signal is weak and contaminated by the noise. The lock-in amplifier is a useful tool for weak signal detection. Aiming to the amplitude error of the lock-in amplifier caused by frequency deviation between the measured signal and the reference signal, a DFT-based automatic signal frequency estimation method is studied to improve the frequency accuracy of the reference signal. Based on this frequency estimation method, a software digital lock-in amplifier method is proposed to detect the multiple frequencies signals. This proposed method can automatically measure the frequency value of the measured signal without prior frequency information. Then, the reference signals are generated through this frequency value to make the digital lock-in amplifier estimate the amplitude of the measured signal. Moreover, an iterative structure is used to implement the multiple frequencies signal measurement. The frequencies and amplitudes measurement accuracies are tested. Under different SNR conditions, the frequency relative error is less than $0.1\%$. In addition, the amplitude relative error with different signal frequencies is less than $1.7\%$ when the SNR is −1 dB. This proposed software digital lock-in amplifier method has a higher signal frequency tracking ability and amplitude measurement accuracy.

The frequency of a weak signal is used for fault diagnosis and target identification in various fields. By introducing particle swarm optimization (PSO) and spectral entropy (SE), an automated weak signal frequency estimation method based on the Duffing oscillator is proposed. The proposed method uses the differential structure to enhance the timing difference of the Duffing oscillator between the chaotic and large-scale periodic states, which is quantitatively distinguished by SE. Then, the frequency of the internal driving force is adaptively adjusted by the PSO to allow the SE to reach a minimum value where the driving frequency equals the weak signal frequency. A group of weak signals with different frequencies has been tested. The maximum relative frequency error is only 0.68%. Unlike other chaotic oscillator-based frequency estimation methods, the proposed method does not need to determine the phase state manually. A rough initial frequency search range is sufficient for automatic frequency measurement of the proposed method in this paper.

When an insulated-gate bipolar transistor (IGBT) open-circuit fault occurs, a three-phase pulse-width modulated (PWM) converter can usually keep working, which will lead to system instability and more serious secondary faults. The fault detection and diagnosis of the converter is extremely necessary to improve the reliability of the power supply system. In order to solve the problem of fault misdiagnosis caused by parameters disturbance, this paper proposes a robust accuracy weighted random forests online fault diagnosis model to accurately locate various IGBTs open-circuit faults. Firstly, the fault signal features are preprocessed by using the three-phase current signal and normalization method. Based on the test accuracy of the perturbed out-of-bag data and the multiple converters test data, a robust accuracy weighted random forests algorithm is proposed for extracting a mapping relationship between fault modes and current signal. In order to further improve the fault diagnosis performance, a parameter optimization model is built to optimize hyper-parameters of the proposed method. Finally, comparative simulation and online fault diagnosis experiments are carried out, and the results demonstrate the effectiveness and superiority of the method.

In the high-resolution analog circuit, the performance of chips is an important part. The performance of the chips needs to be determined by testing. According to the test requirements, stimulus signal with better quality and performance is necessary. The main research direction is how to generate high-resolution and high-speed analog signal when there is no suitable high-resolution and high-speed digital-to-analog converter (DAC) chip available. In this paper, we take the high-resolution analog-to-digital converter (ADC) chips test as an example; this article uses high-resolution DAC chips and multiplexers to generate high-resolution high-speed signals that can be used for testing high-resolution ADC chips based on the principle of time-alternating sampling. This article explains its method, analyzes its error and proposes a digital pre-processing method to reduce the error. Finally, the actual circuit is designed, and the method is verified on the circuit. The test results prove the effectiveness of this method for generating high-resolution ADC test signals.