System for monitoring / estimating levels of airborne particles in an environment

Abstract

A system (40) for monitoring / estimating levels of airborne particles in an environment, comprises a reference sensor (25) comprising a measurement zone (16), where the reference sensor (25) is configured to detect and count airborne particles in the measurement zone (16) to provide a first particle measurement at a 5 first location (45) and a second particle measurement at a second location (45a-45e) and associate the first and second particle measurements with the location for each measurement. The system further comprises a computing device (43) and a data storage (42), where the computing device (43) is configured to receive the first and second particle measurements associated with the respective location for each 10 measurement, calculate a calibration coefficient by comparing the first and second particle measurement, and store the calculated calibration coefficient together with the location for the second particle measurement in the data storage (42). The system further comprises an optical particle sensor connected to the computing device (43), where the optical particle sensor is configured to be calibrated by using 15 the calibration coefficient stored in the data storage (42) together with the location for the second particle measurement.

Description

[0001] SYSTEM FOR MONITORING / ESTIMATING LEVELS OF AIRBORNE

[0002] PARTICLES IN AN ENVIRONMENT

[0003] TECHNICAL FIELD

[0004] The invention relates to a system for monitoring / estimating levels of airborne particles in an environment.

[0005] BACKGROUND

[0006] Exposure to elevated levels of airborne dust is intrinsically linked to an array of health challenges, encompassing conditions such as asthma, lung cancer, pneumonia, chronic obstructive pulmonary disease (COPD), and other respiratory and cardiovascular ailments. It has been estimated that a significant amount of deaths stemming from strokes, lung cancer, and respiratory diseases have connections to air pollution. Within this context, airborne dust constitutes a notable proportion. Besides its implications for human health, airborne dust critically impacts environmental integrity and sustainability.

[0007] An industrial example is air pollution in and from ferrosilicon and silicon plants. A predominant contributor to airborne dust in these environments is microsilica SiCL, a manufacturing process byproduct. These microsilica fumes consist of spherical submicron particles, predominantly composed of amorphous silica, ranging from approximately 85% to 98%.

[0008] Also other industries may have equivalent or similar pollution problems and a need for surveyal. Examples are production of manganese alloys, aluminum, industrial minerals and mining operations.

[0009] In collaboration with the Health Occupational Authorities, the process industry has introduced regulations that specify the maximum allowable concentrations of respirable and non-respirable dust in the workplace atmosphere, depending on the chemical and mineral compounds. To illustrate, the maximum concentration for respirable amorphous silica in Norway is an average of 1.5 mg / m3over 8 hours. Present methodologies to determine these concentrations predominantly rely on intermittent point-sampling using filters and consistent tests utilizing wearable filter masks.

[0010] Such dust-samplers must be sent to a laboratory to weigh the filters inside. This can be a slow and costly process. Since dust levels can vary widely from day to day, the measurements might also not be representative of the dust levels workers are exposed to.

[0011] Other methods that have been proposed for measuring dust concentrations include use of optical sensors. The harsh environment in some industrial areas, e.g., high dust concentrations and high temperatures, may, however, frequently cause malfunctions in optical sensors. These harsh conditions produce variations due to operational conditions and fluid mechanical properties, challenging calibration and accurate readings.

[0012] Also, reference sensors usually contain filters, lenses and other components that are easily clogged or damaged by the harsh environment.

[0013] There is thus a need for a real-time dust / particle monitoring system for use indoors or outdoors, which can provide real-time feedback and can also be used to discover causes to the airborne dust, thereby enabling preventive measures to be made, and also analyze the effect of mitigation strategies.

[0014] The object of the invention is to provide a system for monitoring / estimating levels of airborne particles in an indoor environment that is flexible, accurate, reliable, can provide information in real-time and can provide accurate information over a large range of particle sizes.

[0015] Such a system would facilitate the systematic recording of data, allowing for statistical analysis, routine reports on dust concentration trends, immediate alerts during unsafe spikes, and a platform to identify correlations between dust emissions, events, equipment, and specific procedures that generate high dust volumes.

[0016] The object of the invention is achieved by means of the patent claims.

[0017] SUMMARY OF THE INVENTION

[0018] A system for monitoring / estimating levels of airborne particles in an environment comprises in one configuration a reference sensor comprising a measurement zone. The reference sensor is configured to detect and count airborne particles in the measurement zone to provide a first particle measurement at a first location and a second particle measurement at a second location and associate the first and second particle measurements with the location for each measurement.

[0019] The system further comprises a computing device and a data storage, where the computing device is configured to receive the first and second particle measurements associated with the respective location for each measurement, calculate a calibration coefficient by comparing the first and second particle measurement, and store the calculated calibration coefficient together with the location for the second particle measurement in the data storage.

[0020] The system further comprises an optical particle sensor connected to the computing device, which is configured to be calibrated by using the calibration coefficient stored in the data storage together with the location for the second particle measurement.

[0021] The computing device may be configured to estimate the amount of airborne particles in any location based on the particle measurements received from the optical particle sensors. This estimating may be done by using the calibration coefficients in a prediction algorithm. The prediction algorithm may for example use extrapolation and / or interpolation routines, possibly together with other input such as experience data, thus making measurement accuracy and range exceed the physical limitation of the sensor itself.

[0022] In further configurations, the system comprises more than one optical particle sensors, for example a number n-1 optical particle sensors where n>3. The optical particle sensors are typically provided to measure particles in several points of interest, called measurement locations. For example may there be arranged one optical particle sensor in each measurement location, or there may be arranged more than one particle sensor in each measurement location.

[0023] The reference sensor can then be configured to detect and count airborne particles in the measurement zone of the reference sensor to provide a third to a nth particle measurement at a third to a nth location, ie. a particle measurement for each of the measurement locations for the optical particle sensors, and associate each of the particle measurements with the location for each measurement.

[0024] The computing device is in such a configuration configured to:

[0025] - receive each of the measurements associated with the respective location for each measurement, ie. the third to nth particle measurements,

[0026] - calculate calibration coefficients for each of the measurement locations by comparing the first particle measurement with the particle measurement of each measurement location, ie. with each of the third to nth particle measurements and

[0027] - store the calculated calibration coefficients together with the location for the third to the nth measurement in the data storage.

[0028] The optical particle sensors are connected to the computing device and all the optical particle sensors that have not been calibrated in the first configuration, ie. the n-1 optical particle sensors, are configured to be calibrated by using the respective calibration coefficient stored in the data storage together with the location for the third to nth particle measurement.

[0029] The optical particle sensor may comprise means for inducing an air flow in the measurement zone.

[0030] The optical particle sensor is for example a laser diffraction sensor, but any suitable optical sensor can be used.

[0031] The system may further comprise a flow measurement device. The flow measurement device can be an ultrasonic flow meter or any other type of flow measurement device.

[0032] The computing device and the data storage can in one configuration communicate wirelessly with each other and / or with the optical particle sensors, for example via mobile network, LoRaWAN or Wi-Fi, or they may be configured to communicate over a wired connection.

[0033] A method for monitoring / estimating levels of airborne particles in an indoor environment comprises in one configuration the following steps:

[0034] - detecting and counting airborne particles in a measurement zone in a first location to provide a first particle measurement and in a second location to provide a second particle measurement and associate the first and second particle measurements with the location for each measurement,

[0035] - calculating a calibration coefficient by comparing the first and second particle measurement,

[0036] - storing the calculated calibration coefficient together with the location for the second particle measurement in a data storage, and

[0037] - calibrating an optical particle sensor for use in the second location by using the calibration coefficient stored in the data storage together with the location for the second particle measurement.

[0038] The method may comprise a step of estimating the amount of airborne particles in any location in the vicinity of the optical particle sensor locations based on the particle measurements received from the optical particle sensor. This estimating may be done by using the calibration coefficients in a prediction algorithm . The prediction algorithm may for example use extrapolation and / or interpolation routines, possibly together with other input such as experience data.

[0039] The step of detecting and counting airborne particles in the measurement zone may further comprise to provide a third to a nth particle measurement at a third to a nth location and associate the third to the nth particle measurements with the location for each measurement, and the step of calculating a calibration coefficient may comprise the steps of

[0040] - calculating n-1 calibration coefficients by comparing the first particle measurement with each of the third to nth particle measurements,

[0041] - storing the calculated calibration coefficients together with the location for the third to the nth measurement in the data storage, and where the respective calibration coefficient stored in the data storage together with the location for the third to nth particle measurement are used to calibrate a number n-1 of optical particle sensors.

[0042] The system and method is generally suitable for measuring and monitoring airborne dust / particulate matter and may be used indoors and outdoors, in particular where the harsh environment may require a two-stage calibration to obtain reliable results. This includes, but is not limited to, particulate materials such as silica fumes, quartz, carbon and industrial minerals. The system and method described herein provides a methodology for providing accurate, affordable, robust, and interchangeable sensors.

[0043] The two-stage calibration results in coefficients for an estimation algorithm, making accurate predictions extending beyond the physical limitations of the optical sensors, i.e., estimating concentrations of particles too small or too big to measure and estimating concentrations outside the measurement range of the optical sensor.

[0044] BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The invention will now be described in more detail by means of examples and with reference to the accompanying figures.

[0046] Figure 1 illustrates a working principle of an example of an optical particle sensor.

[0047] Figure 2 illustrates an example of a signal caused by particles of different size.

[0048] Figure 3 illustrates schematically a system for calibrating optical particle sensors.

[0049] Figure 4 illustrates schematically a system for monitoring / estimating levels of airborne particles.

[0050] DETAILED DESCRIPTION

[0051] Figure 1 illustrates a working principle of an example of an optical particle sensor 10. The optical particle sensor 10 may, for example, be a laser particulate sensor or other optical sensor suitable for detecting and counting particles. The sensor comprises a light source 11, for example, a laser or other suitable light source, which transmits a light beam 12 towards a measurement zone 16, which comprises particles 15 to be detected and counted. The optical particle sensor 10 further comprises a sensor element 14 and a light trap 13.

[0052] The light beam 12 emitted from the light source 11 scatters when interacting with the particles 15 in the measurement zone 16, and after the light scattering from the particles 15, the scattered light is collected and recorded by the sensor element 14. Residue light, i.e. the light not scattered towards the sensor element 14, is captured in a light trap 13.

[0053] The sensor element 14 will output a pulse signal 30 in response to the scattered light, which can then be transformed into digital signals. The number and diameter of the detected particles can be obtained by analysis based on the correlation between the signal waveform and the particles' diameter.

[0054] Figure 2 illustrates an example of a pulse signal 30 caused by particles 15 in an optical particle sensor, exemplified by a Shinyei PPD42NS dust sensor. Using light diffraction in the optical particle sensor, the determined particle size refers to the equivalent diameter of a sphere sharing the same diffraction pattern. The optical particle sensor may comprise means for inducing an air flow in the measurement zone 16 and / or at the sensor element 14. The means for inducing an air flow can be a fan or other suitable airflow inducing device. The airflow inducing device may be selected to be able to generate high static pressure, as this can ensure consistent airflow during operation. For this purpose, a flow measuring device may also be provided - for example, a flow meter - paired with a controller. An example of such a controller can be a proportional -integral-derivative (PID) controller. A PID controller uses a control loop feedback mechanism to control process variables and is an accurate and stable controller. PID control is a well-established way of driving a system towards a target position or control parameters. Such a combination ensures a steady flow, alleviating problems with particle accumulation in the system due to agglomeration.

[0055] For immediate data accessibility, the sensor can also comprise a display that reflects current readings and is readable by an operator. An example of such may be a liquid-crystal display (LCD). It also transmits this information to the computing device for broader data analysis and storage.

[0056] The optical particle sensors should be calibrated before use to ensure that the particles are detected and counted correctly. Figure 3 illustrates schematically an example of a system 20 for calibrating optical particle sensors.

[0057] The illustrated system 20 comprises an aerosol generator 23 that produces an aerosol concentration stream, for example up to 60 mg / Nm3. The aerosol can be produced by either reference dust or dust collected at a location where the optical particle sensor is to be used. Reference dust is used to compare internal variations between sensors, while location-specific dust can be used for location calibration to increase accuracy.

[0058] The aerosol stream flows from the aerosol generator 23 into a mixing chamber 22, i.e., a contained space where the aerosol can mix with pure air. The mixing chamber 22 is connected to sampling tube 24, which is also connected to two gravimetric samplers 21a and 21b. The number of gravimetric samplers may be any suitable number, from one to several, but two is used in this example. The gravimetric sampler may be any type of gravimetric sampler, for example a low volume sampler (LVS). In an example embodiment, the gravimetric samplers 21a, 21b comprises each a compressor or suction fan and air from the mixing chamber 22 is sucked into the sampling tube 24 by means of suction from the gravimetric samplers' compressors / suction fans.

[0059] A number of optical particle sensors 10a- lOe are connected to the sampling tube 24 through isokinetic sampling nozzles to match the tube’s flow and thereby avoid biased sampling concerning particle size. Diverted flows from the sampling tube 24 to the optical particle sensors 10a- lOe are collected by the optical particle sensors lOa-lOe and can thereafter be analyzed. The system 20 further comprises a reference sensor 25 for validation. The reference sensor 25 can be of the same type as the optical particle sensors 10a- lOe to be calibrated and may have previously been calibrated in the same system. The reference sensor 25 may alternatively be a different type of optical particle sensor, for example using low volume sampling, or another type of suitable particle sensor.

[0060] The aggregated values of each sensor are then compared with the overall collected dust in the gravimetric samplers 21a, 21b to provide a basis calibration coefficient for each optical particle sensor 10a- lOe, ie. a basis calibration of the optical particle sensors lOa-lOe.

[0061] Isokinetic sampling is defined as when the flow rate of the particle counter (Vf) equals the nozzle velocity of the particle counter (Vn). Or, Vf = Vn.

[0062] After the optical particle sensors lOa-lOe are calibrated as described above, they can be used to monitor and / or estimate levels of airborne particles in a location where there is a need for such monitoring, for example, a ferrosilicon or silicon plant or other process industry plants.

[0063] Figure 4 illustrates schematically a system 40 for monitoring / estimating levels of airborne particles. The figure also illustrates how the sensors in the system 40 are calibrated for each location where monitoring is to be performed. The system comprises a reference sensor 25, and a plurality of optical particle sensors lOa-lOe. The reference sensor is configured to be used to calibrate the optical particle sensors lOa-lOe in the location where it is intended that they shall monitor / estimate the level of airborne particles. The reference sensor may be a sensor of the same type as the optical particle sensors 10a- lOe, but it is not limited to this type.

[0064] The optical particle sensors 10a- lOe may be similar to the example illustrated in figure 1 but may be any suitable optical particle sensor. The optical particle sensors lOa-lOe comprise a light source 11 and a measurement zone 16 and is configured to detect and count airborne particles that are present in the measurement zone 16. In the example in the figure, the optical particle sensors lOa-lOe is planned to provide particle measurement data for monitoring the levels of airborne particles in different locations 45a-45e, such as break room, outside a furnace, a raw material transportation installation etc., in a site 46, for example a ferrosilicon plant or other process industry plant. Many measurement locations 45a-45n may be associated with the same factory or industrial plant, ie. from one up to any number n measurement locations. The optical particle sensor 10b will provide particle measurement data for monitoring the levels of airborne particles in location 45b and so on.

[0065] In order to ensure correct measurements at the desired location, the system should be location calibrated, ie calibrated for the desired location. The reference sensor 25 is for this purpose configured to provide a first particle measurement at a first location 45a, a second particle measurement at a second location 45b, a third particle measurement at a third location 45c and so on for each location to be monitored.

[0066] In the example in figure 4, there are illustrated five measurement locations 45a-45e (ie. the highest number n is five, here denoted e). The reference sensor 25 is thus moved between each predefined location 45a-45e and the particle measurements are associated with the respective locations for each particle measurement. Additionally, measurements are performed by the optical particle sensors 10a- 10b to be able to calculate a tailored calibration coefficient for each location which can be used for the optical particle sensor 10a- lOe when they are used in the predefined locations 45a-45e.

[0067] By associating the first and second particle measurements with the location for each measurement, it will be possible to keep track of the measured particles in different locations, and such information can be used in later computations and calculations. The system further comprises a computing device 43, which is configured to receive information from the reference sensor 25, such as the first and second particle measurements and so on, associated with the location for each measurement and can also receive information and data from further optical particle sensors and possibly other information from other relevant devices.

[0068] The computing device may be an on-site computer, an off-site server, or a cloud solution.

[0069] The computing device 43 is configured to process the data received from the reference sensor and / or further optical sensors or other information received from suitable devices for different purposes. The computing device 43 is at least configured to calculate a calibration coefficient by comparing the first particle measurement received from the reference sensor 25 with the first particle measurement received from the optical particle sensor, i.e., 10a for 45a, 10b for 45b and so on.

[0070] The computing device 43 is connected to a data storage 42 that can be an internal memory in the computing device, a separate storage device accessible wirelessly or wired, or a cloud storage which can be accessed wirelessly via mobile network, LoRaWAN or Wi-Fi, or other suitable data storage means.

[0071] The computing device can send the calculated calibration coefficient together with the location for the second particle measurement to the data storage for storage and subsequent access.

[0072] More than one optical particle sensor may be employed at one measurement location 45a-45e to increase fidelity and accuracy. In figure 4 the five optical particle sensors lOa-lOe associated with the five measurement locations 45a-45e are connected to the computing device and can communicate with the computing device for sending and receiving data. The computing device or the optical particle sensors can be configured to use the calculated calibration coefficient stored in the data storage for location calibration, thus ensuring that the measurements made at the location are correct. As all the optical particle sensors are calibrated before they are put to use in the system and thereafter use the calibration coefficient for the specific location for location calibration, it is possible to replace any optical particle sensor with an optical particle sensor calibrated in the same way as the one that is replaced. The location calibration using the calibration coefficient ensures that all measurements are accurate.

[0073] The reference sensor 25 is removed once the calibration is complete and will not participate in any permanent installation. The optical particle sensors lOa-lOe will remain as the permanent installation.

Claims

CLAIMS1. System (40) for monitoring / estimating levels of airborne particles in an environment, comprising:- a reference sensor (25) comprising a measurement zone (16), where the reference sensor (25) is configured to detect and count airborne particles in the measurement zone (16) to provide a first particle measurement at a first location (45) and a second particle measurement at a second location (45a-45e) and associate the first and second particle measurements with the location for each measurement,- a computing device (43) and- a data storage (42), where the computing device (43) is configured to receive the first and second particle measurements associated with the respective location for each measurement, calculate a calibration coefficient by comparing the first and second particle measurement, and store the calculated calibration coefficient together with the location for the second particle measurement in the data storage (42), and where the system further comprises an optical particle sensor connected to the computing device (43), where the optical particle sensor is configured to be calibrated by using the calibration coefficient stored in the data storage (42) together with the location for the second particle measurement.

2. System according to claim 1 where the computing device (43) is configured to estimate the amount of airborne particles in a location based on the particle measurements received from the optical particle sensors.

3. System according to claim 1 or 2, comprising a number n-1 of optical particle sensors, where the reference sensor (25) is configured to detect and count airborne particles in the measurement zone (16) to provide a third to a / / th particle measurement at a third to a / / th location and associate the first and second particle measurements with the location for each measurement, and where the computing device (43) is configured to- receive the third to / / th particle measurements associated with the respective location for each measurement,- calculate calibration coefficients by comparing the first particle measurement with each of the third to nth particle measurements and- store the calculated calibration coefficients together with the location for the third to the / / th measurement in the data storage (42), where the n-1 optical particle sensors are connected to the computing device (43), and the n-1 optical particle sensors are configured to be calibrated by using therespective calibration coefficient stored in the data storage (42) together with the location for the third to / / th particle measurement.

4. The system according to one of the previous claims, where the optical sensor comprises means for inducing an air flow in the measurement zone (16).

5. System according to one of the previous claims, where the optical sensor is a laser diffraction sensor.

6. System according to one of the claims 3-5, comprising a flow measurement device and where the flow measurement device is an ultrasonic flow meter.

7. System according to one of the previous claims, where the computing device (43) and the data storage (42) can communicate wirelessly with each other and / or with the optical particle sensors.

8. A method for monitoring / estimating levels of airborne particles in an indoor environment, comprising the following steps:- detecting and counting airborne particles in a measurement zone (16) in a first location to provide a first particle measurement and in a second location to provide a second particle measurement and associate the first and second particle measurements with the location for each measurement,- calculating a calibration coefficient by comparing the first and second particle measurement,- storing the calculated calibration coefficient together with the location for the second particle measurement in a data storage (42), and- calibrating an optical particle sensors for use in the second location by using the calibration coefficient stored in the data storage (42) together with the location for the second particle measurement.

9. Method according to claim 8, comprising a step of estimating the amount of airborne particles in a location based on the particle measurements received from the optical particle sensor.

10. Method according to claim 8 or 9, where the step of detecting and counting airborne particles in the measurement zone (16) further comprises to provide a third to a / / th particle measurement at a third to a / / th location and associate the third to the / / th particle measurements with the location for each measurement, and the step of calculating a calibration coefficient comprises- calculating n-1 calibration coefficients by comparing the first particle measurement with each of the third to / / th particle measurements,- storing the calculated calibration coefficients together with the location for the third to the nth measurement in the data storage (42), and where the respective calibration coefficient stored in the data storage (42) together with the location for the third to nth particle measurement are used to calibrate a number n-1 of optical particle sensors.

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