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Modern production systems are the carriers that advanced manufacturing technologies can be realized. Accurate health state evaluation is the basis for ensuring stable operation of the production system and developing a maintenance strategy However, the most existing health evaluation techniques of production systems are based on the single source data. The multi-source data based hidden Markov model is proposed to evaluate health state (including machine performance data, process quality data, etc.). The operational features-based health definition of the production system of production systems is proposed. The modeling process of hidden Markov model based on multi-source data is given, and the multi-performance degradation law of production system is revealed. And taking the pre-grinding gear hob production system as an example, the accuracy and superiority of this proposed approach are verified.

Tramcar will glides fast along inclined railway when it is out of control. Steel beam bumper can prevent its motion. This kind of bumper is widely used in inclined shaft of mine where tramcar is used as auxiliary transport. There exists intense impact between tramcar and steel beam bumper. The impact force is a key parameter for designing bumper. But this force is difficult to predict. Three models are established for obtaining accurately the impact force. In these models, tramcar with its buffer is simplified as a spring-mass system. Steel beam bumper is simplified as Euler-Bernoulli Beam, single-degree-of-freedom spring-mass system and a spring without mass respectively. Simulation shows that impact forces from these models are approximate, so these three models are equivalent. The maximal impact force almost increases linearly with the increasing of mass and impact speed of tramcar. The total impact time increases only with the increasing of mass, but it is not relevant to the impact speed. Single-degree-of-freedom spring-mass model is the simplest one, so it is easy and useful to simulate the impact between tramcar and steel beam bumper for actual engineering design.

Noise level is a key parameter for evaluating the quality of industry equipments and the life environment. The traditional noise test systems have all kinds of disadvantages, for example, the efficiency and precision of testing are low. A new noise test system is developed based on virtual instrument technology which comprises the testing technology, the computer technology and the network technology. In this new system, the sound card of personal computer is used as data acquired card (DAQ card) for acquiring noise signals. So the total test system is more economical. During testing, noise signals are acquired and processed simultaneity by this system. User can obtain the information of the acquired noise signals in time domain and frequency domain. It is known from the actual testing that the test efficiency and precision both are enhanced because of the use of this new system.

Pump plays a key role because it is an important device used to drain water in mine. It is very significant to keep it working normally. The flow velocity and the flux of the pump are the typical indexes that can indict its state. A measurement system that can measure these two indexes is designed to detect the state of the pump. The virtual instrument technology based on LabVIEW is used to build the software part of this measurement system. The ultrasonic sensor is also used in this system. Because of the use of this sensor, the pump can be detected without stopping working. The mathematical model of the correlation function for processing the discrete signal is built. The signal from the DAQ card is processed based on the model above. The value of the flow velocity and the flux is obtained. The precision and efficiency of the measurement are enhanced.