冷链物流外文翻译文献综述.docx

1、冷链物流外文翻译文献综述冷链物流外文翻译文献综述 (文档含中英文对照即英文原文和中文翻译) （AbstractQuality control and monitoring of perishable goods during transportation and delivery services is an increasing concern for producers, suppliers, transport decision makers and consumers. The major challenge is to ensure a continuous cold chain f

2、rom producer to consumer in order to guaranty prime condition of goods. In this framework, the suitability of ZigBee protocol for monitoring refrigerated transportation has been proposed by several authors. However, up to date there was not any experimental work performed under real conditions. Thus

3、, the main objective of our experiment was to test wireless sensor motes based in the ZigBee/IEEE 802.15.4 protocol during a real shipment. The experiment was conducted in a refrigerated truck traveling through two countries (Spain and France) which means a journey of 1,051 kilometers. The paper ill

4、ustrates the great potential of this type of motes, providing information about several parameters such as temperature, relative humidity, door openings and truck stops. Psychrometric charts have also been developed for improving the knowledge about water loss and condensation on the product during

5、shipments.1. IntroductionPerishable food products such as vegetables, fruit, meat or fish require refrigerated transportation. For all these products, Temperature (T) is the most important factor for extending shelf life, being essential to ensure that temperatures along the cold chain are adequate.

6、 However, local temperature deviations can be present in almost any transport situation. Reports from the literature indicate gradients of 5 C or more, when deviations of only a few degrees can lead to spoiled goods and thousands of Euros in damages. A recent study shows that refrigerated shipments

7、rise above the optimum temperature in 30% of trips from the supplier to the distribution centre, and in 15% of trips from the distribution centre to the stores. Roy et al. analyzed the supply of fresh tomato in Japan and quantified product losses of 5% during transportation and distribution. Thermal

8、 variations during transoceanic shipments have also been studied. The results showed that there was a significant temperature variability both spatially across the width of the container as well as temporally along the trip, and that it was out of the specification more than 30% of the time. In thos

9、e experiments monitoring was achieved by means of the installation of hundreds of wired sensors in a single container, which makes this system architecture commercially unfeasible.Transport is often done by refrigerated road vehicles and containers equipped with embedded cooling systems. In such env

10、ironments, temperatures rise very quickly if a reefer unit fails. Commercial systems are presently available for monitoring containers and trucks, but they do not give complete information about the cargo, because they typically measure only temperature and at just one point.Apart from temperature,

11、water loss is one of the main causes of deterioration that reduces the marketability of perishable food products. Transpiration is the loss of moisture from living tissues. Most weight loss of stored fruit is caused by this process. Relative humidity (RH), T of the product, T of the surrounding atmo

12、sphere, and air velocity all affect the amount of water lost in food commodities. Free water or condensation is also a problem as it encourages microbial infection and growth, and it can also reduce the strength of packaging materials.Parties involved need better quality assurance methods to satisfy

13、 customer demands and to create a competitive point of difference. Successful transport in food logistics calls for automated and efficient monitoring and control of shipments. The challenge is to ensure a continuous cold chain from producer to consumer in order to guaranty prime condition of goods

14、. The use of wireless sensors in refrigerated vehicles was proposed by Qingshan et al. as a new way of monitoring. Specialized WSN (Wireless Sensor Network) monitoring devices promise to revolutionize the shipping and handling of a wide range of perishable products giving suppliers and distributors

15、continuous and accurate readings throughout the distribution process. In this framework, ZigBee was developed as a very promising WSN protocol due to its low energy consumption and advanced network capabilities. Its potential for monitoring the cold chain has been addressed by several authors but wi

16、thout real experimentation, only theoretical approaches. For this reason, in our work real experimentation with the aim of exploring the limits of this technology was a priority.The main objective of this project is to explore the potential of wireless ZigBee/IEEE 802.15.4 motes for their applicatio

17、n in commercial refrigerated shipments by road. A secondary objective was to improve the knowledge about the conditions that affect the perishable food products during transportation, through the study of relevant parameters like temperature, relative humidity, light, shocking and psychrometric prop

18、erties.2. Materials and Methods2.1. ZigBee MotesFour ZigBee/IEEE 802.15.4 motes (transmitters) and one base station (receiver) were used. All of them were manufactured by Crossbow. The motes consist of a microcontroller board (Micaz) together with an independent transducer board (MTS400) attached by

19、 means of a 52 pin connector. The Micaz mote hosts an Atmel ATMEGA103/128L CPU running the Tiny Operating System (TinyOS) that enables it to execute programs developed using the nesC language. The Micaz has a radio device Chipcon CC2420 2.4 GHz 250 Kbps IEEE 802.15.4. Power is supplied by two AA lit

20、hium batteries.The transducer board hosts a variety of sensors: T and RH (Sensirion SHT11), T and barometric pressure (Intersema MS5534B), light intensity (TAOS TSL2550D) and a two-axis accelerometer (ADXL202JE). A laptop computer is used as the receiver, and communicates with the nodes through a Mi

21、caz mounted on the MIB520 ZigBee/USB gateway board.Each Sensirion SHT11 is individually calibrated in a precision humidity chamber. The calibration coefficients are used internally during measurements to calibrate the signals from the sensors. The accuracies for T and RH are 0.5 C (at 25 C) and 3.5%

22、 respectively.The Intersema MS5534B is a SMD-hybrid device that includes a piezoresistive pressure sensor and an ADC-Interface IC. It provides a 16 bit data word from a pressure and T (40 to +125C) dependent voltage. Additionally the module contains six readable coefficients for a highly accurate so

23、ftware calibration of the sensor.The TSL2550 is a digital-output light sensor with a two-wire, SMBus serial interface. It combines two photodiodes and an analog-to digital converter (ADC) on a single CMOS integrated circuit to provide light measurements over a 12-bit dynamic range. The ADXL202E meas

24、ures accelerations with a full-scale range of 2 g. The ADXL202E can measure both dynamic acceleration (e.g., vibration) and static acceleration (e.g., gravity).2.2. Experimental Set UpThe experiment was conducted in a refrigerated truck traveling during 23 h 41 m 21 s from Murcia (Spain) to Avignon

25、(France), a distance of 1,051 km. The truck transported approx.14,000 kg of lettuce var. Little Gem in 28 pallets of 1,000 1,200 mm . The lettuce was packed in cardboard boxes with openings for air circulation. The length of the semi-trailer was 15 m with a Carrier Vector 1800 refrigeration unit mou

26、nted to the front of the semi-trailer. For this shipment the set point was 0 C.The truck was outfitted with the wireless system, covering different heights and lengths from the cooling equipment, which was at the front of the semi-trailer. Four motes were mounted with the cargo (see Figure 1): mote

27、1 was at the bottom of the pallets in the front side of the semi-trailer, mote 2 was in the middle of the semi-trailer, mote 3 was in the rear at the top of the pallet, and mote 4 was located as shown in Figure 1, about a third of the distance between the front and the rear of the trailer. Motes 1,

28、2 and 3 were inside the boxes beside the lettuce. The program installed in the motes collects data from all the sensors at a fixed sample rate (7.2 s), with each transmission referred to as a “packet”. The RF power in the Micaz can be set from 24 dBm to 0 dBm. During the experiment, the RF power was

29、 set to the maximum, 0dBm (1mW approximately).2.3. Data AnalysisA specialized MATLAB program has been developed for assessing the percentage of lost packets (%) in transmission, by means of computing the number of multiple sending failures for a given sample rate (SR). A multiple failure of m messag

30、es occurs whenever the elapsed time between two messages lies between 1.5 m SR and 2.5 m SR. For example, with a sample rate of 11 s, a single failure (m = 1) occurs whenever the time period between consecutives packets is longer than 16.5 s (1.5 1 11) and shorter than 27.5 s (2.5 1 11). The total n

31、umber of lost packets is computed based on the frequency of each failure type. Accordingly, the total percentage of lost packets is calculated as the ratio between the total number of lost packets and the number of sent packets.The standard error (SE) associated to the ratio of lost packets is compu

32、ted based on a binomial distribution as expressed in Equation 1, where n is the total number of packets sent, and p is the ratio of lost packets in the experiment.2.4. Analysis of VarianceFactorial Analysis of Variance (ANOVA) was performed in order to evaluate the effect of the type of sensor in the registered measurements, including T (by means of Sensirion and Intersema), RH, barometric pressure, light intensity and acceleration module. ANOVA allows partitioning of the observed variance into components due to different explanatory variables. The STATISTICA software (S