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Met 163: Lecture 2 Human aspects of measurement human perception vs sensor measurements reasons for automation design, implementation, and maintenance.

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Presentation on theme: "Met 163: Lecture 2 Human aspects of measurement human perception vs sensor measurements reasons for automation design, implementation, and maintenance."— Presentation transcript:

1 Met 163: Lecture 2 Human aspects of measurement human perception vs sensor measurements reasons for automation design, implementation, and maintenance of measurement systems interpretation of sensor specifications interpretation of results human judgment Quality assurance Laboratory calibrations Field intercomparisons Data monitoring Documentation Independent review Publication of data quality assessment Instrument design and selection Performance characteristics Sources of error Standards Calibration Performance Exposure Procedural System integration instrument platforms communication systems power source Topics in Chapter 1

2 Instrument design and selection An instrument is a device containing at least a sensor, a signal conditioning device and a data-display. The instrument may contain an analog-to-digital converter, data transmission, data storage device, and microprocessor. The sensor is one of the essential elements because it interacts with the variable to be measured. The variable to be measured is called the measurand. To understand a sensor, one must explore the physics of the sensor and of sensor interaction with the measurand.

3 Performance characteristics Sensor performance can be described by reference to a standardized set of performance definitions. These characteristics are used by manufacturers to describe instruments and as purchase specifications by buyers. 1.1 Static: static characteristics are those obtained when the sensor input and output are static (not changing with time). When raw sensor output is plotted as a function of the input, the slope of this curve is called the static sensitivity.

4 Performance characteristics 1.2 Dynamic Dynamic characteristics are a way of defining a sensor response to a changing input. The most widely known dynamic performance parameter is the time constant (discussed later). 1.3 Function Model A measurement system interacts with the atmosphere and delivers data (information about the desired atmospheric variables) to the users. See Block Diagram

5 Measurand TransmitASCADCDSCSensorStorageDisplay Functional Model of a simple measurement system User XiXi Y1Y1 Y2Y2 Y3Y3 Y4Y4 Y5Y5 Y6Y6 Y7Y7 X i = is the raw input and Y 1 is the raw output. Function Model

6 There are four basic categories of errors (observed minus actual) in a meteorological system: 1. static 2. dynamic 3. drift 4. exposure Sources of Error

7 Static Static errors are measured when the input is held steady and the output becomes essentially constant. These are errors remaining after applying a calibration equation ( e.g.: x f = x r *2.5). They may be deterministic (hysteresis, sensitivity to unwanted inputs such as temperature) or random (noise). Sources of Error

8 Dynamic Dynamic errors ( to be defined in later chapters) are those due to changing inputs. By definition, dynamic errors disappear when the input is held constant long enough for the output to become constant. Thus, dynamic effects are not present during static testing. Every sensor exhibits some lag and may also produce more complex error modes. Sources of Error

9 Drift Drift is due to physical changes that occur in a sensor over time. This is a special category of error because these errors are not truly static, nor are they considered to be dynamic, because they are independent of the rate of change of the input. Drift errors are difficult to account for in most measurement systems; the most direct way to compensate for them is frequent calibration. (gas analyzers) Sensors that drift linearly with time can in principle be corrected, but this can lead to additional uncertainty in the final measurement. Sources of Error

10 Exposure Exposure is a very special category of errors. They are due to imperfect coupling between the sensor and the measurand. Ex: using a thermometer to measure air temperature. The sensor will never be at exactly the same temperature as the air because of dynamic errors. Steps can be taken to minimize the differences between the air temperature and the temperature of the sensor. By blowing air on the sensor and shielding if from radiation and conduction sources.

11 Sources of Error Exposure A temperature will respond to: radiative energy exchanges with the sun or other objects, conductive heat transfer though mechanical supports, as well as to the desired convective heat transfer to or from air moving over the sensor. The magnitude of these errors will be a function of global solar radiation, shielding, and the efficiency of convective heat transfer with the air that is strongly dependent upon the rate of air flow over the sensor. These sources of error are not present in the calibration laboratory and are not included in sensor specifications.

12 Sources of Error Exposure Therefore, statements about instrument errors from manufacturers assume no exposure error. Even with a carefully calibrated and properly maintained measurement system, exposure error can easily exceed all other error sources. Instruments report their own state, which is not necessarily the state of the atmosphere unless great care is taken to provide good exposure.

13 Sources of Error Summary Instruments report their own state, which is not necessarily the state of the atmosphere unless great care is taken to provide good exposure. A cup anemometer reports the rotation rate of its cup wheel, not the wind speed. If the bearings are in good condition and the wind speed is steady, then there is a known relationship between the rate of rotation and the wind speed, determined by the calibration. Static and dynamic errors are measured during laboratory testing and can be well documented, certainly better than drift or exposure error.

14 There are several kinds of standards that are relevant to meteorological measurement systems: calibration performance specification exposure procedural All must be considered in system design and evaluation. Standards

15 Calibration Calibration standards are maintained by standards laboratories in each country, such as the National Institute of Standards and Technology (NIST). Standards for temperature, humidity, pressure, wind speed, and many other variables are maintained. The accuracy of these standards is more than sufficient for meteorological purposes. Every organization attempting to maintain one or more measurement stations must have some facility for laboratory calibrations.

16 Calibration These include transfer standards that can be sent to a laboratory for comparison with the primary standard. A transfer standard is maintained by a primary standard, then the transfer standard can be carried or ‘transferred’ to a remote site to calibrate an instrument. This is what is meant by traceability of sensor calibration to NIST standards. The calibration can be traced back to a standard at a standards laboratory. Standards

17 Performance Performance specification standards refer to the terminology, definition of terms, and the method of testing static and dynamic sensor performance. The American Society of Testing and Materials has been active in establishing these standards. WE must agree on use of terms such as time constant, response time, sensor lag, and so on. It is essential that there be a standard method of testing sensors to determine their performance characteristics. Without these standards, vendor performance specifications would be difficult to interpret.

18 Standards Exposure Exposure standards are necessary to define what is meant by adequate exposure for certain classes of applications. At what height above ground should measurements be made? To make measurements comparable, there should be at least, a standard mounting height and some standards about the proximity of obstructions. Take wind speed and direction for example….

19 Standards Exposure: Wind Sensors The WMO (World Meteorological Organization) specifies a standard mounting height for wind instruments of: 10 m above the ground (AGL) The distance between the anemometer and an obstruction (buildings, trees, etc.) must be at least (10 x) the height of the obstruction. This precludes mounting an anemometer on the roof of a building.

20 Exposure: Temperature Sensors According to WMO recommended practice, temperature sensors should be exposed in a radiation screen, with or without forced ventilation at a height of: 1.25 m to 2.00 m AGL (above a ‘level’ ground surface) The screen must not be shielded by or close to trees, buildings or other obstructions. A measurement site must not be on a steep slope or in a depression where thermal conditions might not represent the larger scale. Standards

21 Exposure: Temperature Sensors Exposure on top of buildings is not recommended because of the vertical temperature structure in the atmosphere and the perturbation caused be the buildings. Where snow is persistent, it is acceptable to maintain the sensor at a constant height above the snow surface. Standards

22 Exposure: Precipitation Precipitation measurements are best made in clearings surrounded by brush and trees to reduce the wind effect. There is frequently a need to locate the rain gauge with the other sensors close to the data logger. To overcome this, a wind screen can be used. The screen is designed to minimize the effect of wind on the gauge catch (discuss later). In the real world, some of these requirements are exclusive and many sites fail to meet all of the exposure specifications. Therefore, it is necessary to document sites carefully with photographs to show terrain, and wind fetch.

23 Standards Procedural Procedural standards refer to the selection of data sampling and averaging periods and to simple algorithms for commonly computed quantities. These standards have been evolving slowly without much compliance so far. When data are used in only one network and for narrowly defined goals (experiment), these standards are not so important. But, if the data is from many networks, then procedural standards can become important. (NWS, RAWS stations)

24 HW #2 Due Tuesday February 16 Using the principles discussed in this lecture, write a paragraph (typed) describing any concerns you may have with regard to the SJSU weather stations.

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