Substantive green innovation or symbolic green innovation? The impact of ER on enterprise green innovation based on the dual moderating effects

Based on the existing research on environmental regulation (ER) and enterprise innovation, this paper separates green innovation ability from general technological innovation and divides it, from the perspective of motivation, into substantive green innovation (SUBGI) and symbolic green innovation (SYMGI). This paper employs panel data of China's A-share listed enterprise from 2008 to 2018 in a difference-in-difference-in-difference model to construct a quasinatural experiment on the impacts of ER and the green innovation strategy of enterprises. Government subsidies and regulatory capture are used to explore the mechanism between ER and innovation behavior. The results show that ER has a significantly positive effect on green innovation, but its impact on SYMGI and SUBGI decreases. Under the constraints of the ER policy, government subsidies incentivize the green innovation of enterprises, but they are not the main reason for the difference between the two innovation behaviors. Regulatory capture plays a negative moderating role in ER promoting enterprises’ SUBGI and has no significant impact on SYMGI, which is the key factor leading to the difference between the two innovation behaviors. The heterogeneity test suggests a pronounced promotion effect of ER on state-owned enterprises, large enterprises, and growing enterprises. This study provides momentous policy implications for making rational use of environmental policies in promoting enterprises’ green innovation capability, especially high-quality green innovation behavior aimed at promoting enterprises’ green technology progress and gaining competitive advantages

Application Research of Negative Pressure Wave Signal Denoising Method Based on VMD

The quality of pipeline leakage fault feature extractions deteriorates due to the influence of fluid pipeline running state and signal acquisition equipment. The pressure signal is characterized by high complexity, nonlinear and strong correlation. Therefore, traditional denoising methods have difficulty dealing with this kind of signal. In order to realize accurate leakage fault alarm and leak location, a denoising method based on variational mode decomposition (VMD) technology is proposed in this paper. Firstly, the intrinsic mode functions are screened out using the correlation coefficient. Secondly, information entropy is used to optimize the VMD decomposition layers k. Finally, based on the denoising signal, the inflection point of the negative pressure wave is extracted, and the position of the leakage point is calculated according to the time difference between the two inflection points. To verify the effectiveness of the algorithm, both laboratory experiments and real pipeline tests are conducted. Experimental results show that the method proposed by this paper can be used to effectively denoise the pressure signal. Furthermore, from the perspective of positioning accuracy, compared other methods, the proposed method can achieve a better positioning effect, as the positioning accuracy of the laboratory experiment reaches up to 0.9%, and that of the real pipeline test leakage point reaches up to 0.41%

Research on a Novel Denoising Method for Negative Pressure Wave Signal Based on VMD

The key to accurately locate pipeline leakage is to effectively reduce the noise in the leakage signal. However, the leakage signal has the characteristics of nonlinear and dynamic change, and the denoising effect of the traditional method is limited. In order to reduce the positioning error caused by noise, a novel denoising method based on variational mode decomposition (VMD) is proposed. First, the correlation coefficient is used to screen effective intrinsic mode function components. Then, an optimization method of VMD decomposition layers $k$ by using minimum information entropy is utilized. Thus, the optimal number of layers and noise reduction signal can be obtained. Finally, the leakage point can be obtained by the principle of negative pressure wave (NPW). Simulation results show that the SNR can effectively improve by using the method in this paper. In laboratory experiments, this method can be used to effectively denoise the pressure signal while preserving the original signal characteristics as much as possible. Furthermore, From the perspective of positioning accuracy, compared other methods, the proposed method can achieve better positioning effect, and the average relative positioning error is 2.03%