Li Hongyu, Wang Hua, Jia Lijia, et al. Data auto-collection based on sound level characteristics for weather modification operation by ground-based artillery gun shooting. J Appl Meteor Sci, 2015, 26(5): 590-599. DOI: 10.11898/1001-7313.20150508.
Citation:
Li Hongyu, Wang Hua, Jia Lijia, et al. Data auto-collection based on sound level characteristics for weather modification operation by ground-based artillery gun shooting. J Appl Meteor Sci, 2015, 26(5): 590-599. DOI: 10.11898/1001-7313.20150508.
Li Hongyu, Wang Hua, Jia Lijia, et al. Data auto-collection based on sound level characteristics for weather modification operation by ground-based artillery gun shooting. J Appl Meteor Sci, 2015, 26(5): 590-599. DOI: 10.11898/1001-7313.20150508.
Citation:
Li Hongyu, Wang Hua, Jia Lijia, et al. Data auto-collection based on sound level characteristics for weather modification operation by ground-based artillery gun shooting. J Appl Meteor Sci, 2015, 26(5): 590-599. DOI: 10.11898/1001-7313.20150508.
As an important task of weather service system, improving information technology on weather modification aircraft and ground operations and accurately collecting basic data from all kinds of operating equipment is an important element for operation management and decision making, as well as the basis for the scientific assessment of operating results. Currently, ground information management of weather modification operation generally follows earlier national rules of information collection and reporting. On one side, the collected information includes operating equipment, operating time, dosage and other basic information. A simple assessment is needed to evaluate the operation by combining comprehensive meteorological observations, making it difficult to ensure the timeliness of information reporting. On the other side, the operating information collected at ground enters the system typically by oral reports and hand typing, which limits the accuracy of the reported information. Thus it is difficult for the managing departments to know in-situ operating conditions, which directly limits operations of other services including security management. Improved data collecting methods are needed to overcome the bottleneck that data collection during weather modification operation relies on hand typing and the associated data security issues, and to improve the timeliness and accuracy of data collection. Based on mature technology, it is an effective way to collect operational data automatically through rebuilding operating instruments, and using in-situ operating sound, light or vibration features to trigger automatic responses of ground data operations. The way of using in-situ sound characteristics to trigger automatic responses to identify operating data from common-used artillery guns and rocket launchers also has a low cost and no security risk. In order to overcome the bottleneck, a new ground-level data acquisition and transmission device based on the acoustic technology are developed. Two experiments are carried out to collect sound level data of training shells and JD-07 type cloud seeding shells, respectively, which are shot from a 37 mm diameter, 65-type double-barreled artillery gun. This kind of artillery guns is widely used in weather modification throughout China. Results indicate that leading noise, sound level sharp jump and peak value yielded from the artillery gun shooting can act as a very effective index of data automatic collection during weather modification operation by artillery guns. Remarkable changes in the sound level of environmental noises inside the weather modification station can distinguish effectively the information on single or double-barreled and discontinuous or continuous gun shooting. Based on this, the shooting time and the shotted shells can be recorded automatically, accurately and in real time. The distance and position of the data acquisition and transmission device away from the artillery gun in the weather modification station have little effect on the accuracy of gun shooting data collection from sound level characteristics. As a significant mark of shell firing from the artillery gun, the leading noise recognition can be an important part of safe operation monitoring, playing an early warning role for major security incidents and their emergency treatment. Comparison of the sound level peak of each shell also helps to provide a visual reference for shell quality inspection. In addition, values of azimuth and elevation angles for each shell shooting can be calculated precisely based on the principle of time difference of arrival by arranging a sound sensing array. The accurate shooting position information can be collected automatically by integrating a GPS module.
Fig.
1
Sound level characteristics of 2 training shells from single-barreled discontinuous shooting during the total (a) and partial (b) periods of time
Fig.
6
Sound level characteristics of JD-07 type cloud seeding shells yielded from the artillery gun shooting during the total (a) and partial (b) periods of time
Table
2
Comparison of the sound level peaks collected by the 4 ground-based operation dataacquisition and transmission devices during double-barreled continuous shooting
Figure 1. Sound level characteristics of 2 training shells from single-barreled discontinuous shooting during the total (a) and partial (b) periods of time
Figure 2. The leading noise characteristics of the 1st training shell from single-barreled discontinuous shooting
Figure 3. Sound level partial characteristics of the 1st training shell from single-barreled discontinuous shooting
Figure 4. Sound level characteristics of 6 training shells from single-barreled continuous shooting during the total (a) and partial (b) periods of time
Figure 5. Sound level partial characteristics of the 2nd training shell from single-barreled continuous shooting
Figure 6. Sound level characteristics of JD-07 type cloud seeding shells yielded from the artillery gun shooting during the total (a) and partial (b) periods of time
Figure 7. Sound level characteristics of a man-made strong noise
Figure 8. Sound level partial characteristics of a man-made strong noise