FI20245323A1

FI20245323A1 - Environmental measurement procedure

Info

Publication number: FI20245323A1
Application number: FI20245323A
Authority: FI
Inventors: Tommi Kaarenoja; Atte Juvonen
Original assignee: Metso Finland Oy
Priority date: 2024-03-20
Filing date: 2024-03-20
Publication date: 2025-09-21
Also published as: WO2025196370A1

Abstract

A method for environmental monitoring of mineral material processing, comprising preparing a position measurement system (170,160b) and a dust measurement device and/or a noise measurement device; starting the position measurement system in such a way that the position measurement covers at least the area to be monitored; moving the dust measurement device and/or the noise measurement device around the area to be monitored along a desired path (180) while measuring dust level and/or noise level and while the position measurement system is operating; combining position data derived from the data provided by the position measurement system with dust level data and/or noise level data measured; and providing a dust level map and/or a noise level map of the area to be monitored.

Description

ENVIRONMENTAL MEASUREMENT METHOD

TECHNICAL FIELD

The present disclosure generally relates to an environmental measurement method. The disclosure relates particularly, though not exclusively, to environmental measurement at a mineral material processing site or plant. The disclosure relates particularly, though not exclusively, to measurement of dust and noise levels.

BACKGROUND

This section illustrates useful background information without admission of any technique described herein representative of the state of the art. — Mineral material processing causes some disturbances to the surrounding environment, such as dust creation and noise. During operation of a mineral material processing plant, the dust and noise levels need to be monitored, for example to abide by any regulations governing the operation, and each mineral material processing site or plant seeks to minimize any disturbance such as dust and noise.

For minimizing disturbances to the environment, it is important to understand any phenomena affecting for example dust and noise levels at the site.

The present disclosure aims to provide a method for environmental monitoring which will help to understand and minimize any disturbance to the environment during mineral material processing.

SUMMARY

The appended claims define the scope of protection. Any examples and technical i

S descriptions of apparatuses, products and/or methods in the description and/or drawings

A not covered by the claims are presented not as embodiments of the invention but as = background art or examples useful for understanding the invention.

N

I 25 According to a first example aspect there is provided a method for environmental monitoring > of mineral material processing, comprising

O

N

02 preparing a position measurement system and a dust measurement device and/or a +

N noise measurement device;

N starting the position measurement system in such a way that the position measurement covers at least the area to be monitored,

moving the dust measurement device and/or the noise measurement device around the area to be monitored along a desired path while measuring dust level and/or noise level and while the position measurement system is operating; combining position data derived from the data provided by the position measurement system with dust level data and/or noise level data measured; and providing a dust level map and/or a noise level map of the area to be monitored.

The position measurement system may comprise an unmanned aerial vehicle comprising imaging means, wherein the unmanned aerial vehicle comprises a drone or a balloon.

The position measurement system may comprise a radar or a lidar.

The method for environmental monitoring may further comprise processing the data provided by the position measurement system to retrieve the position data.

The method for environmental monitoring may further comprise processing the combined position data and the dust level data and/or processing the combined position data and the noise level data.

Processing the combined position and dust level data may comprise randomizing the locations of the positions at which the dust level was measured in order to spread the measurement points from the path according to normal distribution and a nominal randomization radius; spatial averaging of the measured dust level values; and interpolation of the dust level values to cover the area to be monitored.

Processing the combined position and noise level data may comprise i

S selecting expected sound power sources; 8 determining expected sound power levels for the sources by comparing measured 2 noise level data and calculated sound pressure level of the sources, and iteratively adjusting

I 25 the sound power source values until the error in the comparison converges; a @ introducing directional attenuation coefficient from each sound power source to each 02 measured noise level data position; +

N

S calculating a combined sound pressure level from all sound power sources using the directional attenuation coefficients and adjusting the coefficients until the error between calculated sound pressure level and the measured noise level converges; and calculating noise level values for the area to be monitored.

Providing a dust level map and/or a noise level map of the area to be monitored may comprise providing a heatmap with contour lines.

Operating the position measurement system and the measurement of dust level and/or noise level may be carried out for the whole path and data processing and providing results may be carried out subsequently to the operating the position measurement system and dust level and/or noise level measurement having been carried out.

The data processing and providing results may be carried out concurrently with the operating the position measurement system and dust level and/or noise level measurement. — Moving the dust measurement device and/or the noise measurement device around the area to be monitored may be carried out by a human operator or using an automated vehicle.

The desired path may be predetermined from the data provided by the position measurement system prior to moving the dust measurement device and/or the noise measurement device around the area to be monitored.

The area to be monitored may comprise a mineral material processing site or plant.

According to a second example aspect there is provided an arrangement for environmental monitoring of mineral material processing, comprising a position measurement system; a dust measurement device and/or a noise measurement device; means for moving the dust measurement device and/or the noise measurement - device around the area to be monitored along a desired path while measuring dust level

N and/or noise level; and

N

3 a processor configured to cause carrying out operating the position measurement

S 25 — system, measurement of dust level and/or noise level and data processing of the method

I of the first example aspect. a @ The position measurement system may comprise an unmanned aerial vehicle comprising 02 imaging means, wherein the unmanned aerial vehicle comprises a drone or a balloon. +

N

I The position measurement system may comprise a radar or a lidar.

According to a third example aspect there is provided a mineral material processing plant,

comprising a mineral material processing device (110); and the arrangement for environmental monitoring of the second example aspect.

Different non-binding example aspects and embodiments have been illustrated in the foregoing. The embodiments in the foregoing are used merely to explain selected aspects or steps that may be utilized in different implementations. Some embodiments may be presented only with reference to certain example aspects. It should be appreciated that corresponding embodiments may apply to other example aspects as well.

BRIEF DESCRIPTION OF THE FIGURES

Some example embodiments will be described with reference to the accompanying figures, in which:

Fig. 1A schematically shows a principle view of a mineral material processing site, or plant, in which the method according to an example embodiment is carried out;

Fig. 1B schematically shows a principle view of a mineral material processing site, or plant, — in which the method according to an example embodiment is carried out

Fig. 2 shows a flow chart of a method according to an example embodiment;

Fig. 3 shows a flow chart of a method according to an example embodiment;

Fig. 4 shows a flow chart of a method according to an example embodiment;

Fig. 5 shows a flow chart of a method according to an example embodiment; and

Fig. 6 shows an example of a noise level map according to an example embodiment.

DETAILED DESCRIPTION

In the following description, like reference signs denote like elements or steps.

Figs. 1A and 1B schematically show a principle view of a mineral material processing plant,

N or site, 100 in which the method according to an example embodiment is carried out. In an > 25 example embodiment, the mineral material processing plant comprises various machines, <Q such as a mineral material processing machines 100,140,150. oO

N r The setup of the mineral material processing site 100 differs depending on the situation, i.e. [an - on the area in use and the purpose of mineral material processing. In an example, the & processing machine 110 comprises a crushing machine with a crusher 120 and various 0 30 auxiliary devices 130 such as a motor, feeder and conveyors. The processing machine 140

N

I comprises for example a pre-crushing machine or an excavator or a wheel loader for feeding the processing machine 110. The processing machine 150 comprises for example a screening machine or a further crushing machine.

The mineral material processing site, or plant, further comprises other ongoing operations and objects, such as material waiting to be processed, piles of material having been processed and vehicles unloading and loading. Accordingly, the mineral material processing site is a source of environmental disturbances such as dust and noise from 5 various sources around the site area.

Figs 1A and 1B further show a position measurement system configured to provide position data.

Fig. 1A shows an embodiment with an unmanned aerial vehicle (UAV) 160A as the position measurement system. In an example embodiment, the unmanned aerial vehicle (UAV) 160 comprises a drone or a balloon. The unmanned aerial vehicle will hereinafter be referred to as a drone.

The drone 160a comprises imaging means 170 for imaging the mineral material processing site form air. The imaging means 170 have a field of view that allows the imaging means 170 to image the whole area of interest, for example the whole mineral material processing — site or a part thereof when flown at a suitable height. In an example embodiment, the imaging means 170 comprise a digital video camera or a digital camera configured to image subseguent still images at a large enough frame rate.

Fig. 1B shows an embodiment with a radar or lidar arrangement 160b as the position measurement system. In an example embodiment, the radar or lidar arrangement is configured to scan the area of interest as shown in Fig 1B with the concentric rings 175.

The radar or lidar arrangement 160 is configured to provide position data in form of for example a three-dimensional point cloud. In an example embodiment, the radar or lidar arrangement 160b is positioned at an elevated position, for example on a mast on top of the mineral material processing machine 110, in order for the scan to cover the whole area

S 25 of interest.

N Figs. 1A and 1B further show a path, or track 180, exemplifying a possible route along which 3 means for dust level measurement and/or means for noise level measurement are moved x in an example embodiment of the method. The path 180 starts at position 182 and ends at

E position 184. In an example embodiment, the path 180 is chosen in such a way that the e 30 measurement means can be safely moved along the track and in such a way that the path & is representative of the expected sources of noise and dust. In a further example

N embodiment, the path 180 is predetermined using image data from the imaging means 170

N of the drone 160a or from the position data from the radar or lidar arrangement 160b.

Fig. 2 shows a flow chart of a method according to an example embodiment.

At step 210, the equipment for environmental monitoring is prepared. The equipment prepared comprises in an example embodiment the drone 160a comprising imaging means and preparing a dust measurement device and/or a noise measurement device. In an example embodiment, the drone 160a comprises a multi-rotor drone, such as a quadcopter drone. In a further example embodiment, the drone 160a comprises a further type of drone or a balloon.

The equipment prepared comprises in a further example embodiment the radar or lidar arrangement 160b.

In an example embodiment, the dust measurement device comprises a movable dust measurement device configured to measure aerosol contaminants and their mass and size fractions, such as PM1, PM2.5, respirable, PM10 and PM Total. In an example embodiment, the dust measurement device comprises a Dust Trak™ Aerosol monitor.

In an example embodiment, the noise measurement device comprises a movable measuring device configured to measure sound level in dB.

At step 220, conditions for the environmental monitoring are set In an example embodiment, the conditions refer to the operation of the mineral material site. In an example embodiment, the environmental monitoring is carried out for a certain operating situation and accordingly, the operating conditions are set for the reguired situation. Such conditions comprise in an example embodiment the dust suppression used, the process devices being operated and the motor load(s).

At step 230, in an example embodiment, the drone 160a is brought to a position above the are to be monitored at such a height that the field of view of the imaging means 170 covers at least the area to be monitored. In an example embodiment, the drone is positioned directly above the center of the area to be monitored. In an example embodiment, the height

S 25 is about 50 m. In a further example embodiment, the height is chosen in accordance with

N regulations in force for drone use at the area to be monitored.

O

= At step 230, in a further example embodiment, the radar or lidar arrangement 160b is

N initialized. j n At step 240, in an example embodiment, the imaging with the imaging means is started and

N 30 the area to be monitored is imaged. In an example embodiment, the imaging comprises 3 imaging a video. At step 240, in a further example embodiment, the scanning with the radar & or lidar arrangement 160b is started and the area to be monitored is scanned

The dust level measurement and/or the noise level measurement is also started.

At step 250, the dust measurement device and/or the noise measurement device is moved around the area to be monitored along a desired path 180 while measuring dust level and/or noise level and imaging the area to be monitored with the imaging means 170 or scanning the area with with the radar or lidar arrangement 160b. In an example embodiment, the path 180 is predetermined from the imaging date or date from with the radar or lidar arrangement 160b prior to moving the measurement devices. In a further example embodiment, the path is chosen while moving the measurement devices in accordance with the conditions and the situation at the area to be monitored.

In an example embodiment, the time taken for the measurement is around 20 to 25 minutes.

In a further example embodiment, the time taken for measurement is determined based on the available flying time of the drone 160.

In an example embodiment, moving the dust measurement device and/or the noise measurement device around the area to be monitored along the path is carried out by a human operator or using an automated vehicle. In an example embodiment, the — measurement devices are moved at a certain height suitable for the measurements. In an example embodiment, the height is about 1,6 m.

In a further example embodiment, further guantities are measured along the path using suitable eguipment or before the dust and/or noise measurement is started, or before the drone is brought to its imaging position or the radar or lidar arrangement is initialized. In an example embodiment, the further quantities comprise temperature, wind speed and wind direction

At step 260 the imaging or scanning and the measurement of dust level and/or noise level is stopped.

At step 270, in an example embodiment, the imaged video, or frames, is received from the

S 25 drone and processed at step 275 in order to derive position data from the imaged data, i.e.

N in order to derive position data on the path 180 along which the dust level and/or noise level 3 measurements were carried out. At step 270, in a further example embodiment, the data x from the the radar or lidar arrangement 160b is received and processed at step 275 in order

E to derive position data therefrom. The processing is explained in further detail hereinafter e 30 with reference to Fig. 3.

N

3 At step 280 the position data derived from the data from the position measurement system

O is combined with dust level data and/or noise level data measured. At steps 285A and 285B the combined position data and dust level data and/or noise level data, respectively, are processed. The processing is explained in further detail hereinafter with reference to Figs.

4 and 5.

At step 290, the result of the environmental monitoring is provided. In an example embodiment, the result comprises a map of the area to be monitored with dust levels and/or noise levels being shown. In a further example embodiment, the result comprises a heat — map with contour lines showing the dust levels and/or noise levels. An example of the result of the environmental monitoring is shown in Fig. 6.

In an example embodiment, steps 270-290 are carried out after the whole measurement path has been completed and the measurement and imaging or scanning has been stopped. In a further example embodiment, the steps 270-290 are carried out concurrently — with the imaging or scanning and measurement.

It is to be noted that the data processing described hereinbefore and hereinafter is caused to carried by at least one processor. in an example embodiment, the processor is located locally at the area to be monitored, for example in a laptop computer or the control system of the site. In a further example embodiment, the processor is located in a different location.

Fig. 3 shows a flow chart of a method according to an example embodiment. Fig. 3 shows the processing of data from the position measurement system of step 275 of Fig. 2.

At step 310, in an example embodiment, the imaged data is received, or available, to be processed. The imaged data comprises digital video data or seguential still frames comparable to video for the purposes of the method. At step 310, in a further example embodiment, the data from the radar or lidar arrangement 160b is received, or available, to be processed. In an example embodiment, the data comprises a three-dimensional point cloud.

At step 320, in an example embodiment, coordinates of the position of the dust < measurement device and/or the noise measurement device for each frame of the digital

S 25 video data are determined, or derived. In an example the coordinates are provided in an oH x,y-coordinate system. In an example embodiment, the coordinates are determined using = a computer vision algorithm. At step 320, in a further example embodiment, coordinates of

N the position of the dust measurement device and/or the noise measurement device are = determined for each scan seguence of the data from the radar or lidar arrangement 160b. & 30 At step 330, which can also be carried out concurrently or prior to step 320, anomalous 3 parts of the imaged data or the data from the radar or lidar arrangement 160b are discarded i from being used for calculating the results. Such anomalous parts comprise situations in which there is a clearly identifiable exceptional or anomalous occurrence during the measurement, such as dust source not related to the area being monitored or the operations at the site, or an external source of noise, such as a loud vehicle near the measurement device.

At step 340, in an embodiment with imaged data, which can also be carried out concurrently — or prior to steps 320 and 330, further analysis of imaged data is carried out depending on the situation and need. In an example embodiment, visual detection of dust clouds is carried out in order to have a better overview of dust behaviour.

At step 350, the determined position data is available for further use.

Fig. 4 shows a flow chart of a method according to an example embodiment. Fig. 4 shows — the processing of dust and position data of step 285A of Fig. 2.

At step 410, the position data and the dust level data are combined. For each measured dust level value a position is provided by combining the data. In an example embodiment, prior to combining the position and dust level values, a particle type for which the dust level is to be monitored is chosen.

In an example embodiment the combined data is pre-processed. The preprocessing comprises in an example embodiment operations such as removing bad values or missing values form the data set.

At step 420, the position data is spread for the dust values. Spreading the position data comprises randomizing the locations of the positions at which the dust level was measured in order to spread the measurement points from the path 180. The spreading is in an example embodiment done according to normal distribution and a nominal randomization radius. Furthermore, a spatial averaging is carried out for the measured dust level values to remove too local variations. This is done in order to produce smoother maps providing a < better representation of average dust levels on the area being monitored.

N

N 25 At step 430, the measured, spread and averaged dust values are interpolated to cover the 3 area to be monitored. In an example embodiment with imaged data, a dust value is < interpolated for each pixel, or each group of pixels of the imaged area to be monitored.

I g At step 440, a dust map of the area to be monitored is provided. In an example embodiment, e the dust map comprises a heat map with contour lines showing the dust levels.

O

3 30 Fig. 5 shows a flow chart of a method according to an example embodiment. Fig. 5 shows

N the processing of dust and position data of step 285B of Fig. 2.

At step 510 the position data and the sound level data are combined. For each measured sound level value a position is provided by combining the data.

At step 520, expected sound power sources are selected. The selection is done by defining the locations of the sources. In an example embodiment typical sound power sources to be selected include feeder, crusher, diesel engine and the processed material falling onto a stockpile.

At step 530 sound power levels for the selected sources are determined by first calculating starting from arbitrary sound power levels a sound pressure level for each source and then comparing the measured noise level data and the calculated sound pressure level of the sources, and iteratively adjusting the sound power source values until the error in the comparison converges.

At step 540, directional attenuation coefficients are introduced from each sound power — source to each measured noise level data position.

At step 550, a combined sound pressure level from all sound power sources to each measured noise level data position using the directional attenuation coefficients and adjusting the coefficients until the error between calculated sound pressure level and the measured noise level converges. After adjustment, a noise level is calculated for the area to be monitored. In an example embodiment with imaged data, a noise value is calculated for each pixel, or each group of pixels of the imaged area to be monitored.

At step 560, a noise map of the area to be monitored is provided. In an example embodiment, the noise map comprises a heat map with contour lines showing the noise levels.

N

N 25 Fig. 6 shows an example of a noise level map 600 according to an example embodiment. 3 The map shows the noise level on the area being monitored using contour lines 610 < showing the noise levels. Fig. 6 shoes the mineral material processing machine 110 with = dashed line and it can be seen that substantial noise sources in the example are the crusher e and a conveyor. 3 30 Without in any way limiting the scope of the appended claims, some technical effects of the

N environmental monitoring method according to example embodiment are explained in the

N following.

The method according to example embodiments is configured to provide a continuous approximation of the dust and/or noise levels around the area to be monitored. The method according to example embodiments is further configured to provide information on efficacy of actions taken to minimize environmental disturbances.

The method according to example embodiments is configured to enable the mineral material processing to operate in accordance with regulations related to dust and noise levels and to provide data thereon should it be needed for regulative control.

The method according to example embodiments is configured to enable monitoring the exposure of operating personnel and equipment to dust and noise as well as the environmental exposure in the surroundings.

The method according to example embodiments is configured to enable testing and developing of equipment in view of their effect on dust and/or noise levels.

Accordingly, a technical effect of example embodiment of the invention is the provision of information on environmental disturbances. A further technical effect of the example embodiments of the invention is to provide data for more efficient dust and noise suppression. A still further technical effect of the example embodiments of the invention is to increase the environmental friendliness of the area to be monitored. A still further technical effect of the example embodiments of the invention is to improve mineral material processing.

Various embodiments have been presented. It should be appreciated that in this document, words comprise; include; and contain are each used as open-ended expressions with no intended exclusivity.

The foregoing description has provided by way of non-limiting examples of particular implementations and embodiments a full and informative description of the best mode s presently contemplated by the inventors for carrying out the invention. It is however clear to

S 25 a person skilled in the art that the invention is not restricted to details of the embodiments & presented in the foregoing, but that it can be implemented in other embodiments using o eguivalent means or in different combinations of embodiments without deviating from the

I characteristics of the invention. a

O Furthermore, some of the features of the afore-disclosed example embodiments may be & 30 used to advantage without the corresponding use of other features. As such, the foregoing

N description shall be considered as merely illustrative of the principles of the present

N invention, and not in limitation thereof. Hence, the scope of the invention is only restricted by the appended patent claims.

Claims

1. A method for environmental monitoring of mineral material processing, comprising preparing a position measurement system and a dust measurement device and/or a noise measurement device; starting the position measurement system in such a way that the position measurement covers at least the area to be monitored; moving the dust measurement device and/or the noise measurement device around the area to be monitored along a desired path while measuring dust level and/or noise level and while the position measurement system is operating; combining position data derived from the data provided by the position measurement system with dust level data and/or noise level data measured; and providing a dust level map and/or a noise level map of the area to be monitored.

2. The method for environmental monitoring of claim 1, wherein the position measurement system comprises an unmanned aerial vehicle comprising imaging means, wherein the unmanned aerial vehicle comprises a drone or a balloon.

3. The method for environmental monitoring of claim 1, wherein the position measurement system comprises a radar or a lidar.

4. The method for environmental monitoring of any preceding claim, further comprising processing the data provided by the position measurement system to retrieve — the position data.

5. The method for environmental monitoring of any preceding claim, further comprising processing the combined position data and the dust level data and/or processing the combined position data and the noise level data.

s

6. The method for environmental monitoring of claim 5, wherein processing the & 25 combined position and dust level data comprises & randomizing the locations of the positions at which the dust level was measured in o order to spread the measurement points from the path according to normal distribution and z a nominal randomization radius; * spatial averaging of the measured dust level values; and E 30 interpolation of the dust level values to cover the area to be monitored.

N

7. The method for environmental monitoring of claim 5, wherein processing the N combined position and noise level data comprises selecting expected sound power sources;

determining expected sound power levels for the sources by comparing measured noise level data and calculated sound pressure level of the sources, and iteratively adjusting the sound power source values until the error in the comparison converges; introducing directional attenuation coefficient from each sound power source to each measured noise level data position; calculating a combined sound pressure level from all sound power sources using the directional attenuation coefficients and adjusting the coefficients until the error between calculated sound pressure level and the measured noise level converges; and calculating noise level values for the area to be monitored.

8. The method for environmental monitoring of any preceding claim, wherein providing a dust level map and/or a noise level map of the area to be monitored comprises providing a heatmap with contour lines.

9. The method for environmental monitoring of any preceding claim, wherein operating the position measurement system and the measurement of dust level and/or noise level is carried out for the whole path and data processing and providing results is carried out subsequently to the operating the position measurement system and dust level and/or noise level measurement having been carried out.

10. The method for environmental monitoring of any preceding claim 1-6, wherein the data processing and providing results is carried out concurrently with the operating the position measurement system and dust level and/or noise level measurement.

11. The method for environmental monitoring of any preceding claim, wherein moving the dust measurement device and/or the noise measurement device around the area to be monitored is carried out by a human operator or using an automated vehicle. <

12. The method for environmental monitoring of any preceding claim, wherein the N 25 desired path is predetermined from the data provided by the position measurement system a prior to moving the dust measurement device and/or the noise measurement device around = the area to be monitored. N z

13. Themethod for environmental monitoring of any preceding claim, wherein the area a n to be monitored comprises a mineral material processing site or plant. 3 30

14. An arrangement for environmental monitoring of mineral material processing, O comprising a position measurement system; a dust measurement device and/or a noise measurement device;

means for moving the dust measurement device and/or the noise measurement device around the area to be monitored along a desired path while measuring dust level and/or noise level; and a processor configured to cause carrying out operating the position measurement system, measurement of dust level and/or noise level and data processing of the method of any preceding claim 1-13.

15. The arrangement for environmental monitoring of claim 14, wherein the position measurement system comprises an unmanned aerial vehicle comprising imaging means, wherein the unmanned aerial vehicle comprises a drone or a balloon.

16. The arrangement for environmental monitoring of claim 14, wherein the position measurement system comprises a radar or a lidar.

17. A mineral material processing plant, comprising a mineral material processing device (110); and the arrangement for environmental monitoring of any of the claims 14-16. i N O N O <Q oO N I [an a O N O LO + N O N