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为了给食用油精炼加工厂的碳减排提供参考，采用排放因子法建立了食用油精炼加工过程碳排放核算模型，并以500 t/d食用油精炼为例，对食用油精炼加工厂的碳排放进行了核算，分析了食用油精炼各工段的二氧化碳排放量，并提出了碳减排措施。结果表明：每加工1 t原油二氧化碳排放总量为0.060 962 t，其中天然气燃烧产生的二氧化碳排放量、柴油燃烧产生的二氧化碳排放量、废水处理产生的二氧化碳排放当量、净购入电力产生的二氧化碳排放量分别为0.018 163、0.009 288、0.010 735、0.022 776 t；食用油精炼过程中，脱臭工段的二氧化碳排放量最高，为0.024 852 t,其次是脱胶碱炼工段，脱色工段的二氧化碳排放量最小。基于碳排放来源，可通过改进生产工艺，利用清洁能源，回收利用热能等措施减少食用油精炼加工厂碳排放。 In order to provide a reference for edible oil refinery to reduce carbon emission, the carbon emission of edible oil refinery was accounted by emission factor method with 500 t/d edible oil refining as an example, and the carbon emission of each section of edible oil refining was analyzed and carbon emission reduction measures were proposed. The results showed that the total carbon dioxide emission was 0.060 962 t per 1 t crude oil, of which the carbon dioxide emission from natural gas combustion, diesel combustion, wastewater treatment and net purchase of electricity were 0.018 163, 0.009 288, 0.010 735 t and 0.022 776 t per 1 t crude oil, respectively. In the edible oil refining process, the deodorization section has the highest carbon dioxide emission of 0.024 852 t, followed by the degumming and alkali refining section, and the bleaching section has the lowest carbon dioxide emission. Based on the sources of carbon emissions, carbon emissions of the edible oil refinery can be reduced by improving the production process, using clean energy and recycling heat.

Quadratic time-frequency distribution (TFD) is an effective method to solve the underdetermined blind source separation problems. In the proposed method, the cyclic spectrum density (CSD) is calculated using the piecewise average periodogram method ' which is used to reconstruct the Wigner-Ville distribution (WVD). The auto-term TF points are detected after computing the matrixes of TFDs, and a new three-order tensor is folded by the chosen TFD matrixes. At last, PARAFAC decomposition is applied to separate the sources directly, which does not assume that the number of active sources at any TF point is not larger than the sensor number. Simulation results demonstrate that the proposed method can suppress the noise effectively and separate the sources directly with only one step, avoiding the superposition of error of “two-step" methods, which improves the performance and efficiency of separation. [ABSTRACT FROM AUTHOR]