The present disclosure relates to a static cone penetration test device. The device includes a housing, an optical window and a friction cylinder coaxially connected. Light sources are mounted in the optical window and a static cone penetration assembly is disposed in the friction cylinder to detect a resistance the device suffers when the device is pressed into soil. An optical fiber sensor, a wireless transceiver, a data processing chip and a power supply are disposed in the housing. The optical fiber sensor is used to receive the reflected light of a target object and output spatial position information and spectrum information. The wireless transceiver is used to upload test data and receive a control signal. The data processing chip is used to analyze the test data. The present disclosure has the advantages of compact structure, high spectral resolution, quick imaging speed, and strong immunity to interference.

The present disclosure relates to a static cone penetration test device. The device includes a housing, an optical window and a friction cylinder coaxially connected. Light sources are mounted in the optical window and a static cone penetration assembly is disposed in the friction cylinder to detect a resistance the device suffers when the device is pressed into soil. An optical fiber sensor, a wireless transceiver, a data processing chip and a power supply are disposed in the housing. The optical fiber sensor is used to receive the reflected light of a target object and output spatial position information and spectrum information. The wireless transceiver is used to upload test data and receive a control signal. The data processing chip is used to analyze the test data. The present disclosure has the advantages of compact structure, high spectral resolution, quick imaging speed, and strong immunity to interference.

A system for locating and tracking an object is provided. The system includes a measuring device configured to determine a property of a paving-related material, a locating device configured to determine a location of the measuring device, a tracking system configured to store tracking information associated with the measuring device and one or more properties determined by the measuring device, and a communications system configured to transfer, to a remote device, the location of the measuring device and the tracking information associated with the measuring device.

A system for locating and tracking an object is provided. The system includes a measuring device configured to determine a property of a paving-related material, a locating device configured to determine a location of the measuring device, a tracking system configured to store tracking information associated with the measuring device and one or more properties determined by the measuring device, and a communications system configured to transfer, to a remote device, the location of the measuring device and the tracking information associated with the measuring device.

A system and method for monitoring an earth pressure and displacement of a miniature steel pipe pile body. Sensor installation holes are drilled at predetermined positions outside the steel pipe pile body and sensor metal protective shell with a thickness slightly lower than that of the XY-TY02A resistance-type miniature earth pressure gauge is welded on the steel pipe pile body. The XY-TY02A resistance-type miniature earth pressure gauges are stuck on the steel pipe pile body. The transmission line of the XY-TY02A resistance-type miniature earth pressure gauges passes through the sensor installation holes and are connected to data acquisition system. The reflective sheet base is welded at the preset position of the miniature steel pipe pile and the reflective sheet is attached to the reflective sheet base to realize displacement monitoring.

A system and method for monitoring an earth pressure and displacement of a miniature steel pipe pile body. Sensor installation holes are drilled at predetermined positions outside the steel pipe pile body and sensor metal protective shell with a thickness slightly lower than that of the XY-TY02A resistance-type miniature earth pressure gauge is welded on the steel pipe pile body. The XY-TY02A resistance-type miniature earth pressure gauges are stuck on the steel pipe pile body. The transmission line of the XY-TY02A resistance-type miniature earth pressure gauges passes through the sensor installation holes and are connected to data acquisition system. The reflective sheet base is welded at the preset position of the miniature steel pipe pile and the reflective sheet is attached to the reflective sheet base to realize displacement monitoring.

A system for locating and tracking an object is provided. The system includes a measuring device configured to determine a property of a paving-related material, a locating device configured to determine a location of the measuring device, a tracking system configured to store tracking information associated with the measuring device and one or more properties determined by the measuring device, and a communications system configured to transfer, to a remote device, the location of the measuring device and the tracking information associated with the measuring device.

A system for locating and tracking an object is provided. The system includes a measuring device configured to determine a property of a paving-related material, a locating device configured to determine a location of the measuring device, a tracking system configured to store tracking information associated with the measuring device and one or more properties determined by the measuring device, and a communications system configured to transfer, to a remote device, the location of the measuring device and the tracking information associated with the measuring device.

An N-value prediction apparatus according to an embodiment of the present invention includes a hypothetical learning data augmentation unit, based on an actual N-value measured at an actual location according to the Standard Penetration Test through drilling investigation, generating at least one of hypothetical N-values corresponding to a preset hypothetical point based on the actual location, an N-value prediction model learning unit learning ground characteristic data corresponding to each of the actual location and the hypothetical point by artificial intelligence, the ground characteristic data including the actual N-value and the hypothetical N-values, and an N-value prediction result calculation unit predicting an N-value at an arbitrary prediction target point by using an N-value prediction model generated by artificial intelligence learning executed in the N-value prediction model learning unit.

Disclosed is a method for assessing nitrogen leaching risk based on farmland soil pressure, including the following steps: acquiring soil drilling pressure data from a plurality of soil layers of different depths on soil to be tested using a soil drilling device, to obtain raw soil drilling pressure data; comparing a calibration curve with a raw soil drilling pressure curve; setting an interquartile range (IQR) coefficient based on a first fluctuation factor and a second fluctuation factor, and constructing a box plot of the raw soil drilling pressure data based on the IQR coefficient; and determining a peak soil drilling pressure according to the box plot of the raw soil drilling pressure data, and determining nitrogen leaching risk according to a depth interval of soil layer. The box plot is utilized to filter out abnormal values, ensuring the accuracy of assessing the nitrogen leaching risk in soil.