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To eliminate the angle deviation of magnetic encoder, this paper aims to propose a compensation method based on permanent magnet synchronous motor (PMSM) sensorless control. The paper also describes the experiments performed to verify the validity of this proposed method.

The proposed method uses PMSM sensorless control method to get high precision virtual angle value, and then get the deviation value between virtual position and magnetic angle which is used as compensation table. Oversampling linear interpolation tabulation method has been proposed to eliminate the noise signals. Finally, a magnetic encoder with precision (repeatability) 0.09° and unidirectional motion precision 0.03 is realized. The control system with an encoder running at 14,000 and 0.01 r/min showing high motion resolution is also realized.

Higher value of current in PMSM leads to a magnetic encoder with higher precision. When using oversampling linear interpolation to tabulate the compensation table, it is understood that more oversampling does not lead to a better result. Finally, validated by experiments, using eight intervals to calculate the mean value of angle deviation leads to the best result.

The angle deviation compensation method proposed in this paper has a great practical implication and a good commercial application. The method proposed in this paper could be effectively used to self-correct the magnetic encoder using arctangent method and also correct any rotary encoder sensor.

This paper originally proposes an adaptive correction method for a rotary encoder based on PMSM sensorless control. To eliminate the noise signals in an angle compensation table, over-sampling linear interpolation tabulation method has been proposed which also guarantees the precision of the compensation table.

Most of the linear encoders are based on optics. The accuracy and reliability of these encoders are greatly reduced in polluted and noisy environments. Moreover, these encoders have a complex structure and large sensor volume and are thus not suited to small application scenarios and do not have universality. This paper aims to present a new absolute magnetic linear encoder, which has a simple structure, small size and wide application range.

The effect of swing error is analyzed for the sensor structural arrangement. A double-threshold interval algorithm is then proposed to synthesize multiple interval electrical angles into absolute angles and convert them into actual displacement distances.

The final linear encoder measurement range is 15.57 mm, and the resolution reaches ± 2 µm. The effectiveness of the algorithm is demonstrated experimentally.

The linear encoder has good robustness, and high measurement accuracy, which is suitable for industrial production. The linear encoder has been mass-produced and used in an electric power-assisted braking system.

As a type of angular displacement sensor, the Hall-effect magnetic encoder incorporates many advantages. While compared with the photoelectric encoder, the magnetic encoder nevertheless has lower precision and lower resolution. So, the purpose of this essay is to find a way to increase the precision and resolution of the magnetic encoder.

By combining a single-pole magnetic encoder and a multi-pole AlNiCo magnet, the precision and resolution of this combined magnetic encoder are increased without increasing its volume or complicating its structure. A special algorithm system is developed to ensure faithful encoding and decoding.

Tests show that the combined magnetic encoder, with a diameter of 67.12 mm (including shaft) and thickness of 6.9 mm, has a precision of ±6′, compared with a 15-bit photoelectric encoder and a static resolution of ±0.6′.

This new kind of magnetic encoder could be used in specialized fields which need high-precision servo-control systems that are small, have ultra-low-speed and high-speed ratios and are non-oil-polluting or shock-resistant.

The purpose of this paper is to develop a quantitative risk assessment method for agricultural products cold chain logistics to assess the condition of the fresh agricultural products cold chain process objectively and accurately.

A risk assessment index system of agricultural products cold chain logistics is designed on the basis of the risk identification for the process of agricultural products cold chain logistics. This paper first uses catastrophe progression method and a new maximum deviation method to build an improved catastrophe progression assessment model for agricultural products cold chain logistics. In order to verify the reliability and validity of the model, two representative enterprises are selected as the case in the study.

The results in the empirical research indicate strong support for the assessment model and coincide with the reality. The risk assessment index system can also reflect the key risk factors from agricultural products cold chain logistics scientifically. In addition, the improved catastrophe progression assessment method proposed in this paper can be scientific and reasonable to predict risk.

This paper contributes to provide a new risk assessment model for agricultural products cold chain logistics. The new model overcomes the limitation of subjective empowerment and it increases the objectivity and scientificity in the process of cold chain logistics risk assessment. This paper also shows that practitioners involved in the field of products cold chain logistics can manage the potential risk by a set of scientific methods for assessing the risk before the accident.

The paper provides a practical guideline to practitioners, especially for cold chain logistics managers, relevant management departments, and cold chain logistics management consultants. It is proved that the new risk assessment method and the risk assessment index system of agricultural products cold chain logistics can help them assess the risk scientifically and reasonably.

Although the calculation is simple, the new model can overcome the limitation of subjective empowerment scientifically and reasonably, and thus has important practical value.

The purpose of this paper is to investigate market power in the Chinese pork supply chain. The authors aim to explain why a steady rise in prices is observed in the sector, apart from existing evidence on incomplete/asymmetric cost pass-through and concerns of growing concentration and consolidation in the sector.

This study uses a new empirical industrial organization model for both oligopoly and oligopsony power to measure the degree of market power exerted on consumers and hog farmers simultaneously.

By examining annual panel data across provinces in China, the authors find that both oligopoly and oligopsony powers exist in the pork supply chain. In particular, the authors determine that a higher degree of market power is found to influence prices paid to hog farmers than prices paid by pork consumers. Estimates of key elasticities in the Chinese pork supply chain are also updated based on the structural model estimation and the latest data.

Due to the lack of data at a more granular level of geography, the authors are only able to estimate market power by three major economic regions.

The findings provide useful information for future policy analyses of Chinese food markets. First, the pork-packing industry should be of great concern in terms of market power and its influence on consumers’ and farmers’ welfare. It is essential to take into consideration market power in the pork supply chain before making any public policy regarding the pork market. Furthermore, following economic theory and experience from developed countries, large meat packers will eventually vertically control hog farmers given their stronger oligopsony power over the upstream. Vertical integration may be the next important issue in terms of food market competition. Finally, the results may also draw the government’s attention to investigating market competition in all major food markets.

The empirical evidence draws attention to the issue of food market competition in one of the largest and most important meat-packing markets in China. The authors hope to encourage further discussions on pork and hog market regulations and related public policies.

Based on the involvement and customer-delivered value theories, this paper proposes a comprehensive framework with which to examine the relationships between food traceability system, consumer perceived value and purchase intention. The study also investigates the moderating role of consumer expertise in the relationship between food traceability system and perceived value.

Survey approach is the primary data collection tool, through which a total of 238 useable responses were obtained. Structural equation modelling is employed to examine the hypothesized relationships among all variables.

The findings show that the information quality, perceived reliability and product diagnosticity of food traceability system affect consumer perceived value, and the perceived value and purchase intention are positively associated, while consumer expertise acts as a moderator on the relationship between food traceability system and consumer perceived value.

This study sheds light on how consumer perceived value of food traceability system can enhance their intention to purchase traceable food. It contributes to the theory of customer-delivered value and involvement as well as traceable product marketing strategies. From a managerial perspective, guidelines are provided for traceable food producers and marketers to implement reasonable strategies to attract consumers to purchase and promote the sustainable development of food industry.