A computer implemented method and system for determining reliability of a machine includes receiving one of a machine data from one or more locations through an internet of things (IOT) based machine wearable sensor network. The method further includes storing the data in a distributed computer database communicatively coupled to an enterprise resource planning (ERP) system and extracting, through a computer server, one or more entity information from the data to compare against a pre-defined baseline. Further, mapping, though a big data machine learning engine, the extracted one or more entity information into a multi-classification model. The method includes indicating, through a machine learning engine coupled to a predictive analytics engine, on a user interface a set of analytical predictions for machine maintenance, repair and operation.

Internet of things based determination of machine reliability and automated maintainenace, repair and operation (mro) logs

Disclosed is an IoT-based system for overseeing process control and predictive maintenance of a machine or a network of machines by employing machine wearable sensors. The system comprises a plurality of IR temperature sensors, each of which secured to the exterior of the machine; each IR sensor capable of transmitting captured temperature data wirelessly over a communications network, an algorithm engine capable of receiving data from the IR sensors, the algorithm engine for further processing the received data to recognize real-time temperature patterns, deviations, etc., and based on the same issuing control commands pertaining to the machine, and one or more control modules disposed in operative communication with the control panel of the machine, the control module capable of receiving, over a communications network, the control commands and executing the same resulting in accomplishing process control or predictive maintenance of the machine or both.

IoT-ENABLED PROCESS CONTROL AND PREDECTIVE MAINTENANCE USING MACHINE WEARABLES

A method and system of a machine learning architecture for predictive and preventive maintenance of vacuum pumps. The method includes receiving one of a motor sensor data and a blower sensor data over a communications network. The motor sensor data is classified into one of a vacuum state sensor data and break state sensor data. The vacuum state sensor data is analyzed to detect an operating vacuum level and an alarm is raised when the vacuum state sensor data exceeds a pre-defined safety range. Vacuum break data is classified into one of a clean filter category and clogged filter category and an alarm is raised if an entry under the clogged filter category is detected. The blower sensor data in association with the motor sensor data is analyzed based on machine learning to detect one of a deficient oil level and a deficient oil structure.

Real time machine learning based predictive and preventive maintenance of vacuum pump

The invention discloses an aluminum alloy surface easy-cleaning micro-arc oxidation ceramic membrane layer and a preparation method thereof, and relates to an aluminum alloy surface ceramic membrane layer and a preparation method thereof. The invention aims at solving the problems that the existing easy-cleaning ceramic is long in preparation time, high in energy consumption, and limited in application as the existing easy-cleaning ceramic only can be applied to some products formed by sintering. The aluminum alloy surface easy-cleaning micro-arc oxidation ceramic membrane layer is prepared by micro-arc oxidation. The preparation method is as follows: by taking an aluminum alloy workpiece as an anode and a stainless plate of an electrolytic cell as a cathode, soaking the anode of the aluminum alloy workpiece in working liquid; and then, applying bipolar pulse power to the two sides of the cathode and the anode, carrying out micro-arc oxidization treatment to obtain the aluminum alloy surface easy-cleaning micro-arc oxidation ceramic membrane layer. The invention is used for the aluminum alloy surface easy-cleaning micro-arc oxidation ceramic membrane layer and the preparation method thereof.

Aluminum alloy surface easy-cleaning micro-arc oxidation ceramic membrane layer and preparation method thereof

The invention discloses a mine automated water drainage system based on an internet of things. The mine automated water drainage system based on the internet of things comprises a sensing layer, an internet layer and an application layer. A liquid level sensor, a motor current sensor, a motor winding temperature sensor, a water pump shaft temperature sensor, a water pump outlet pressure sensor, a flow sensor, a valve opening sensor and a vacuum sensor are arranged on the sensing layer, all the sensors are connected with a PLC main controller after being connected with an A/D collection module, an I/O module which is connected with the PLC main controller is respectively connected with a control button, an electromagnetic valve, an electric gate valve, an electromagnetic driver, a high-voltage electric reactor and a state indication light. The mine automated water drainage system based on the internet of things overcomes the defects that the function is single, remote real-time monitoring cannot be achieved, data administration is not standard, and large-scale networking and centralized control cannot be achieved in the prior art and conducts centralized monitoring of the type of the internet of things on key links, such as water wave information, equipment information and environmental information, of the mine water drainage system. A personal user can access a server of a centralized-control center by means of a PC through the Internet or by means of wireless terminals such as a mobile phone and a PDA so as to achieve remote control.

Mine automated water drainage system based on internet of things

The utility model provides a mine automatic drainage system based on the Internet of things The mine automatic drainage system comprises a sensing layer, a network layer and an application layer A liquid level sensor, a motor current sensor and a motor winding temperature sensor, a water pump shaft temperature sensor, a water pump outlet pressure sensor, a flow sensor, a valve open degree sensor and a vacuum sensor are arranged on the sensing layer All the sensors are connected with an A/D collection module and then are connected with a main PLC, and an I/O module connected with the main PLC is connected with a control button, an electromagnetic valve, an electric brake valve, an electromagnetic driver, a high-voltage electric reactor and state indication lamps According to the mine automatic drainage system, the defects that in the prior art, the function is singular, remote real-time monitoring can not be achieved, data management is irregular, wide-range networking and centralized controlling can not carried out are overcome, and centralized monitoring in an Internet of things type on key links like water wave information, device information and environment information of the mine automatic drainage system is achieved A user can have access to a server of an centralized control center through a PC and the Internet or through a mobile phone, a PDA and other wireless terminals

Mine automatic drainage system based on Internet of things

The invention discloses a sensor for monitoring metal abrasive particles in oil liquid on line The sensor is a mutual inductance sensor and comprises an exciting coil and an inducting coil, wherein an oil path through which the oil liquid can pass is arranged in the center of a framework made of a magnetic inert material; the exciting coil and the inducting coil are coaxially wound on the framework; the inducing coil is positioned between the exciting coil and the framework; the axial length of the inducting coil is 1/4-1/2 of that of the exciting coil; and the axial center points of the inducting coil and the exciting coil are superposed The sensor realizes zero compensation and adjustment by adopting a parallel measurement structure and is simple in structure, high in sensitivity, high in linearity and high in interference resistance The sensor applied to on-line monitoring for the metal abrasive particles in the oil liquid is convenient to operate, high in instantaneity, high in measurement precision and accurate and reliable in monitored result and can be widely applied to military and civil fields and used for monitoring the pollution degree and the abrasion to the oil liquid of lubricating systems of mechanical equipment such as various air planes, naval vessels and automobiles and monitoring and diagnosing faults of the lubricating systems of the mechanical equipment to avoid safety accidents

Sensor for monitoring metal abrasive particles in oil liquid on line and application method for sensor

The invention discloses an aluminum alloy with an army-green micro-arc oxidation ceramic membrane on the surface, and a preparation method of the aluminum alloy The aluminum alloy and the preparation method mainly solve the technical problem that most of the ceramic membranes treated by a light metal micro-arc oxidation technology existing in the prior art are off-white, white, black and the like An electrolytic solution of the aluminum alloy comprises the following solutes: sodium phosphate, sodium silicate, sodium hexametaphosphate, sodium hydroxide, ethylene diamine tetraacetic acid, potassium dichromate, sodium carbonate, lauryl sodium sulfate and hydrogen peroxide; deionized water is adopted as a solvent; and the solutes and the solvent are blended into an alkaline electrolytic solution, stirred, placed for 1-2 hours, and then subjected to micro-arc oxidation treatment, therefore, the army-green ceramic membrane is obtained The aluminum alloy has the benefits that the aluminum alloy is simple in preparation method, low in cost and small in environmental pollution The prepared army-green ceramic membrane has the advantages that the army-green ceramic membrane is high in wear resistance, good in corrosion resistance, uniform in color and luster, good in stability, and compact, and does not fade easily The army-green ceramic membrane is particularly suitable for disguise requirements of army products

Aluminum alloy with army-green micro-arc oxidation ceramic membrane on surface and preparation method of aluminum alloy

The invention discloses an embedded data acquisition system-based mechanical fault diagnosis device of a mining fan. The embedded data acquisition system-based mechanical fault diagnosis device comprises an intrinsically safe sensor, an embedded data acquisition system and a fault judgment system, wherein the intrinsically safe sensor comprises an intrinsically safe acceleration sensor, an intrinsically safe temperature sensor and an intrinsically safe rotating speed sensor; the fault judgment system comprises an online monitoring module, a fault diagnosis module, an alarming and maintaining module and a data storage module; and the intrinsically safe acceleration sensor, the intrinsically safe bearing temperature sensor and the intrinsically safe magnetoelectric rotating speed sensor are connected to the online monitoring module, the fault diagnosis module, the alarming and maintaining module and the data storage module by an input interface of the embedded data acquisition system and an output interface of the embedded data acquisition system through circuits. The embedded data acquisition system-based mechanical fault diagnosis device disclosed by the invention is used for monitoring the parameters, such as vibration quantity, temperature, rotating speed and displacement on line when the fan works, diagnosing the mechanical faults of the fan and providing corresponding solutions and is suitable for the online monitoring and mechanical fault diagnosis of various fans.

Jiang Zhansi

Papers

Mine automated water drainage system based on internet of things

Mine automatic drainage system based on Internet of things

Sensor for monitoring metal abrasive particles in oil liquid on line and application method for sensor

Aluminum alloy with army-green micro-arc oxidation ceramic membrane on surface and preparation method of aluminum alloy

Embedded data acquisition system-based mechanical fault diagnosis device of mining fan