In the application scenario of the actual health management for complex equipment health managements, represented by electromechanical systems, health perception and maintenance decision-making depend on the mined evolution mechanism of state of health. Both of them show an obvious coupling on their base knowledge whiling operating. The corresponding binary knowledge has the value of bi-directional fusion. Inspired by the bi-directional fusion of fault detection-maintenance binary knowledge, this article proposes a bi-directional optimization method of health perception and maintenance decision-making for electromechanical systems to regularly take advantage of the limited operation records accumulated in one period to optimize the previous health perception and maintenance decisionmaking model. Finally, the proposed bi-directional optimization method is evaluated by using the simulation experiment of the antenna leveling system in the actual electromechanical system, where the health prediction error is reduced to 0. 002% . The maintenance decision-making benefit is increased to 93. 57, which verifies the effectiveness of the proposed collaborative method of health state prediction and maintenance decision-making.